Inhaltsverzeichnis von Mind Hacks : Tips & Tricks for Using Your Brain

Inhaltsvorschau

It's never entirely true to say, "This bit of the brain is solely responsible for function X." Take the visual system [Hack #13] , for instance; it runs through many varied parts of the brain with no single area solely responsible for all of vision. Vision is made up of lots of different subfunctions, many of which will be compensated for if areas become unavailable. With some types of brain damage, it's possible to still be able to see, but not be able to figure out what's moving or maybe not be able to see what color things are.

What we can do is look at which parts of the brain are active while it is performing a particular task—anything from recognizing a face to playing the piano—and make some assertions. We can provide input and see what output we get—the black box approach to the study of mind. Or we can work from the outside in, figuring out which abilities people with certain types of damaged brains lack.

The latter, part of neuropsychology [Hack #6] , is an important tool for psychologists. Small, isolated strokes can deactivate very specific brain regions, and also (though more rarely) accidents can damage small parts of the brain. Seeing what these people can no longer do in these pathological cases, provides good clues into the functions of those regions of the brain. Animal experimentation, purposely removing pieces of the brain to see what happens, is another.

These are, however, pathology-based methods—less invasive techniques are available. Careful experimentation—measuring response types, reaction times, and response changes to certain stimuli over time—is one such alternative. That's cognitive psychology [Hack #1] , the science of making deductions about the structure of the brain through reverse engineering from the outside. It has a distinguished history. More recently we've been able to go one step further. Pairing techniques from cognitive psychology with imaging methods and stimulation techniques

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Inhaltsvorschau

It's never entirely true to say, "This bit of the brain is solely responsible for function X." Take the visual system [Hack #13] , for instance; it runs through many varied parts of the brain with no single area solely responsible for all of vision. Vision is made up of lots of different subfunctions, many of which will be compensated for if areas become unavailable. With some types of brain damage, it's possible to still be able to see, but not be able to figure out what's moving or maybe not be able to see what color things are.

What we can do is look at which parts of the brain are active while it is performing a particular task—anything from recognizing a face to playing the piano—and make some assertions. We can provide input and see what output we get—the black box approach to the study of mind. Or we can work from the outside in, figuring out which abilities people with certain types of damaged brains lack.

The latter, part of neuropsychology [Hack #6] , is an important tool for psychologists. Small, isolated strokes can deactivate very specific brain regions, and also (though more rarely) accidents can damage small parts of the brain. Seeing what these people can no longer do in these pathological cases, provides good clues into the functions of those regions of the brain. Animal experimentation, purposely removing pieces of the brain to see what happens, is another.

These are, however, pathology-based methods—less invasive techniques are available. Careful experimentation—measuring response types, reaction times, and response changes to certain stimuli over time—is one such alternative. That's cognitive psychology [Hack #1] , the science of making deductions about the structure of the brain through reverse engineering from the outside. It has a distinguished history. More recently we've been able to go one step further. Pairing techniques from cognitive psychology with imaging methods and stimulation techniques

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Inhaltsvorschau

How do you tell what's inside a black box without looking in it? This is the challenge the mind presents to cognitive psychology.

Cognitive psychology is the psychology of the basic mental processes—things like perception, attention, memory, language, decision-making. It asks the question, "What are the fundamental operations on which mind is based?"

The problem is, although you can measure what goes into someone's head (the input) and measure roughly what they do (the output), this doesn't tell you anything about what goes on in between. It's a black box, a classic reverse engineering problem.¹ How can we figure out how it works without looking at the code?

These days, of course, we can use neuroimaging (like EEG [Hack 2] , PET [Hack #3] , and fMRI [Hack #4] ) to look inside the head at the brain, or use information on anatomy and information from brain-damaged individuals [Hack #6] to inform how we think the brain runs the algorithms that make up the mind. But this kind of work hasn't always been possible, and it's never been easy or cheap. Experimental psychologists have spent more than a hundred years refining methods for getting insight into how the mind works without messing with the insides, and these days we call this cognitive psychology.

There's an example of a cognitive psychology-style solution in another book from the hacks series, Google Hacks (http://www.oreilly.com/catalog/googlehks). Google obviously doesn't give access to the algorithms that run its searches, so the authors of Google Hacks, Tara Calishain and Rael Dornfest, were forced to do a little experimentation to try and work it out. Obviously, if you put in two words, Google returns pages that feature both words. But does the order matter? Here's an experiment. Search Google for "reverse engineering" and then search for "engineering reverse." The results are different; in fact, they are sometimes different even when searching for words that aren't normally taken together as some form of phrase. So we might conclude that order does make a difference; in some way, the Google search algorithm takes into account the order. If you try to whittle a search down to the right terms, something that returned only a couple of hits, perhaps over time you could figure out more exactly how the order mattered.

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Inhaltsvorschau

EEGs give you an overall picture of the timing of brain activity but without any fine detail.

An electroencephalogram (EEG) produces a map of the electrical activity on the surface of the brain. Fortunately, the surface is often what we're interested in, as the cortex—responsible for our complex, high-level functions—is a thin sheet of cells on the brain's outer layer. Broadly, different areas contribute to different abilities, so one particular area might be associated with grammar, another with motion detection. Neurons send signals to one another using electrical impulses, so we can get a good measure of the activity of the neurons (how busy they are doing the work of processing) by measuring the electromagnetic field nearby. Electrodes outside the skull on the surface of the skin are close enough to take readings of these electromagnetic fields.

Small metal disks are evenly placed on the head, held on by a conducting gel. The range can vary from two to a hundred or so electrodes, all taking readings simultaneously. The output can be a simple graph of signals recorded at each electrode or visualised as a map of the brain with activity called out.

The EEG technique is well understood and has been in use for many decades. Patterns of electrical activity corresponding to different states are now well-known: sleep, epilepsy, or how the visual cortex responds when the eyes are in use. It is from EEG that we get the concepts of alpha, beta, and gamma waves, related to three kinds of characteristic oscillations in the signal.
Great time resolution. A reading of electrical activity can be taken every few milliseconds, so the brain's response to stimuli can be precisely plotted.
Relatively cheap. Home kits are readily available. OpenEEG (http://openeeg.sourceforge.net), EEG for the rest of us, is a project to develop low-cost EEG devices, both hardware and software.

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Inhaltsvorschau

PET is a radioactivity-based technique to build a detailed 3D model of the brain and its activity.

Positron emission tomography (PET) is more invasive than any of the other imaging techniques. It requires getting a radioactive chemical into the bloodstream (by injection) and watching for where in the brain the radioactivity ends up—the "positron emission" of the name. The level of radioactivity is not dangerous, but this technique should not be used on the same person on a regular basis.

When neurons fire to send a signal to other neurons, they metabolize more energy. A few seconds later, fresh blood carrying more oxygen and glucose is carried to the region. Using a radioactive isotope of water, the amount of blood flow to each brain location can be monitored, and the active areas of the brain that require a lot of energy and therefore blood flow can be deduced.

A PET scan will produce a 3D model of brain activity.

Scans have to take place in bulky, expensive machinery, which contain the entire body.
PET requires injecting the subject with a radioactive chemical.
Although the resolution of images has improved over the last 30 years, PET still doesn't produce as fine detail as other techniques (it can see activity about 1 cm across).
PET isn't good for looking at how brain activity changes over time. A snapshot can take minutes to be assembled.

—Myles Jones & Matt Webb

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Inhaltsvorschau

fMRI produces high-resolution animations of the brain in action.

Functional magnetic resonance imaging (fMRI) is the king of brain imaging. Magnetic resonance imaging is noninvasive and has no known side effects—except, for some, claustrophobia. Having an MRI scan requires you to lie inside a large electromagnet in order to be exposed to the high magnetic field necessary. It's a bit like being slid inside a large white coffin. It gets pretty noisy too.

The magnetic field pushes the hydrogen atoms in your brain into a state in which they all "line up" and spin at the same frequency. A radio frequency pulse is applied at this exact frequency, making the molecules "resonate" and then emit radio waves as they lose energy and return to "normal." The signal emitted depends on what type of tissue the molecule is in. By recording these signals, a 3D map of the anatomy of the brain is built up.

MRI isn't a new technology (it's been possible since the '70s), but it's been applied to psychology with BOLD functional MRI (abbreviated to fMRI) only as recently as 1992. To obtain functional images of the brain, BOLD (blood oxygen level dependent) fMRI utilizes the fact that deoxygenated blood is magnetic (because of the iron in hemoglobin) and therefore makes the MRI image darker. When neurons become active, fresh blood washes away the deoxygenated blood in the precise regions of the brain that have been more active than usual.

While structural MRI can take a long time, fMRI can take a snapshot of activity over the whole brain every couple of seconds, and the resolution is still higher than with PET [Hack #3] . It can view activity in volumes of the brain only 2 mm across and build a whole map of the brain from that. For a particular experiment, a series of fMRI snapshots will be animated over a single high-resolution MRI scan, and experimenters can see in exactly which brain areas activity is taking place.

Much of the cognitive neuroscience research done now uses fMRI. It's a method that is still developing and improving, but already producing great results.

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Inhaltsvorschau

Stimulate or suppress specific regions of the brain, then sit back and see what happens.

Transcranial magnetic stimulation (TMS) isn't an imaging technique like EEG [Hack 2] or fMRI [Hack #4] , but it can be used along with them. TMS uses a magnetic pulse or oscillating magnetic fields to temporarily induce or suppress electrical activity in the brain. It doesn't require large machines, just a small device around the head, and—so far as we know—it's harmless with no aftereffects.

Neurons communicate using electrical pulses, so being able to produce electrical activity artificially has its advantages. Selected regions can be excited or suppressed, causing hallucinations or partial blindness if some part of the visual cortex is being targeted. Both uses help discover what specific parts of the brain are for. If the subject experiences a muscle twitching, the TMS has probably stimulated some motor control neurons, and causing hallucinations at different points in the visual system can be used to discover the order of processing (it has been used to discover where vision is cut out during saccades [Hack #17] , for example).

Preventing a region from responding is also useful: if shutting down neurons in a particular area of the cortex stops the subject from recognizing motion, that's a good clue as to the function of that area. This kind of discovery was possible before only by finding people with localized brain damage; now TMS allows more structured experiments to take place.

Coupled with brain imaging techniques, it's possible to see the brain's response to a magnetic pulse ripple through connected areas, revealing its structure.

Affects neural activity directly, rather than just measuring it.

Apparently harmless, although it's still early days.

"Savant For a Day" by Lawrence Osbourne (http://www.nytimes.com/2003/06/22/magazine/22SAVANT.html or http://www.cognitiveliberty.org/neuro/TMS_NYT.html

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Neuropsychology is the study of what different parts of the brain do by studying people who no longer have those parts. As well as being the oldest technique of cognitive neuroscience, it refutes the oft-repeated myth that we only use 10% of our brains.

Of the many unscientific nuggets of wisdom about the brain that many people believe, the most common may be the "fact" that we use only 10% of our brains.

In a recent survey of people in Rio de Janeiro with at least a college education, approximately half stated that the 10% myth was true.¹ There is no reason to suppose the results of a similar survey conducted anywhere else in the world would be radically different. It's not surprising that a lot of people believe this myth, given how often it is claimed to be true. Its continued popularity has prompted one author to state that the myth has "a shelf life longer than lacquered Spam".²

Where does this rather popular belief come from?
It's hard to find out how the myth started. Some people say that something like it was said by Einstein, but there isn't any proof. The idea that we have lots of spare capacity is certainly true and fits with our aspirational culture, as well as with the Freudian notion that the mind is mostly unconscious. Indeed, the myth was being used to peddle self-help literature as early as 1929.³ The neatness and numerological potency of the 10% figure is a further factor in the endurance of the myth.
—A.B.

Neuropsychology is the study of patients who have suffered brain damage and the psychological consequences of that brain damage. As well as being a vital source of information about which bits of the brain are involved in doing which things, neuropsychology also provides a neat refutation of the 10% myth: if we use only 10% of our brains, which bits would you be happy to lose? From neuropsychology, we know that losing any bit of the brain causes you to stop being able to do something or being able to do it so well. It's all being used, not just 10% of it.

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Inhaltsvorschau

Take a brief tour around the spinal cord and brain. What's where, and what does what?

Think of the central nervous system like a mushroom with the spinal cord as the stalk and the brain as the cap. Most of the hacks in this book arise from features in the cortex, the highly interconnected cells that make a thin layer over the brain...but not all. So let's start outside the brain itself and work back in.

Senses and muscles all over the body are connected to nerves, bundles of neurons that carry signals back and forth. Neurons come in many types, but they're basically the same wherever they're found in the body; they carry electric current and can act as relays, passing on information from one neuron to the next. That's how information is carried from the sensory surface of the skin, as electric signals, and also how muscles are told to move, by information going the other way.

Nerves at this point run to the spinal cord two by two. One of each pair of nerves is for receptors (a sense of touch for instance) and one for effectors—these trigger actions in muscles and glands. At the spinal cord, there's no real intelligence yet but already some decision-making—such as the withdrawal reflex—occurs. Urgent signals, like a strong sense of heat, can trigger an effector response (such as moving a muscle) before that signal even reaches the brain.

The spinal cord acts as a conduit for nerve impulses up and down the body: sensory impulses travel up to the brain, and the motor areas of the brain send signals back down again. Inside the cord, the signals converge into 31 pairs of nerves (sensory and motor again), and eventually, at the top of the neck, these meet the brain.

At about the level of your mouth, right in the center of your head, the bundles of neurons in the spinal cord meet the brain proper. This tip of the spinal cord, called the brain stem, continues like a thick carrot up to the direct center of your brain, at about the same height as your eyes.

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The forebrain, the classic image of the brain we know from pictures, is the part of the brain that defines human uniqueness. It consists of four lobes and a thin layer on the surface called the cortex.

When you look at pictures of the human brain, the main thing you see is the rounded, wrinkled bulk of the brain. This is the cerebrum, and it caps off the rest of the brain and central nervous system [Hack #7] .

To find your way around the cerebrum, you need to know only a few things. It's divided into two hemispheres, left and right. It's also divided into four lobes (large areas demarcated by particularly deep wrinkles). The wrinkles you can see on the outside are actually folds: the cerebrum is a very large folded-up surface, which is why it's so deep. Unfolded, this surface—the cerebral cortex—would be about 1.5 m² (a square roughly 50 inches on the side), and between 2 and 4 mm deep. It's not thick, but there's a lot of it and this is where all the work takes place. The outermost part, the top of the surface, is gray matter, the actual neurons themselves. Under a few layers of these is the white matter, the fibers connecting the neurons together. The cortex is special because it's mainly where our high-level, human functions take place. It's here that information is integrated and combined from the other regions of the brain and used to modulate more basic functions elsewhere in the brain. The folds exist to allow many more neurons and connections than other animals have in a similar size area.

The four cerebral lobes generally perform certain classes of function.

You can cover the frontal lobe if you put your palms on your forehead with your fingers pointing up. It's heavily involved in planning, socializing, language, and general control and supervision of the rest of the brain.

The parietal lobe is at the top and back of your head, and if you lock your fingers together and hook your hands over the top back, that's it covered there. It deals a lot with your senses, combining information and representing your body and movements. The object recognition module for visual processing

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Inhaltsvorschau

There's a veritable electrical storm going on inside your head: 100 billion brain cells firing electrical signals at one another are responsible for your every thought and action.

A neuron, a.k.a. nerve cell or brain cell, is a specialized cell that sends an electrical impulse out along fibers connecting it, in turn, to other neurons. These guys are the wires of your very own personal circuitry.

What follows is a simplistic description of the general features of nerve cells, whether they are found sending signals from your senses to your brain, from your brain to your muscles, or to and from other nerve cells. It's this last class, the kind that people most likely mean when they say "neurons," that we are most interested in here. (All nerve cells, however, share a common basic design.)

Don't for a second think that the general structure we're describing here is the end of the story. The elegance and complexity of neuron design is staggering, a complex interplay of structure and noise; of electricity, chemistry, and biology; of spatial and dynamic interactions that result in the kind of information processing that cannot be defined using simple rules.¹ For just a glimpse at the complexity of neuron structure, you may want to start with this free chapter on nerve cells from the textbook Molecular Cell Biology by Harvey Lodish, Arnold Berk, Lawrence S. Zipursky, Paul Matsudaira, David Baltimore, and James Darnell and published by W. H. Freeman (http://www.ncbi.nlm.nih.gov/books/bv.fcgi?call=bv.View..ShowSection&rid=mcb.chapter.6074), but any advanced cell biology or neuroscience textbook will do to give you an idea of what you're missing here.

The neuron is made up of a cell body with long offshoots—these can be very long (the whole length of the neck, for some neurons in the giraffe, for example) or very short (i.e., reaching only to the neighboring cell, scant millimeters away). Signals pass only one way along a neuron. The offshoots receiving incoming transmissions are called

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Inhaltsvorschau

When you think really hard, your heart rate noticeably increases.

The brain requires approximately 20% of the oxygen in the body, even during times of rest. Like the other organs in our body, our brain needs more glucose, oxygen, and other essential nutrients as it takes on more work. Many of the scanning technologies that aim to measure aspects of brain function take advantage of this. Functional magnetic resonance imaging (fMRI) [Hack #4] benefits from the fact that oxygenated blood produces slightly different electromagnetic signals when exposed to strong magnetic fields than deoxygenated blood and that oxygenated blood is more concentrated in active brain areas. Positron emission tomography (PET) [Hack #3] involves being injected with weakly radioactive glucose and reading the subsequent signals from the most active, glucose-hungry areas of the brain.

A technology called transcranial Doppler sonography takes a different approach and measures blood flow through veins and arteries. It takes advantage of the fact that the pitch of reflected ultrasound will be altered in proportion to the rate of flow and has been used to measure moment-to-moment changes in blood supply to the brain. It has been found to be particularly useful in making comparisons between different mental tasks. However, even without transcranial Doppler sonography, you can measure the effect of increased brain activity on blood flow by measuring the pulse.

For this exercise you will need to get someone to measure your carotid pulse, taken from either side of the front of the neck, just below the angle of the jaw. It is important that only very light pressure be used—a couple of fingertips pressed lightly to the neck, next to the windpipe, should enable your friend to feel your pulse with little trouble.

First you need to take a measure of a resting pulse. Sit down and relax for a few minutes. When you are calm, ask your friend to count your pulse for 60 seconds. During this time, close your eyes and try to empty your mind.

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More intense signals cause faster reaction times, but there are diminishing returns: as a stimulus grows in intensity, eventually the reaction speed can't get any better. The formula that relates intensity and reaction speed is Pieron's Law.

It's a common illusion that if you are in a hurry for the elevator you can make it come quicker by pressing the button harder. Or more often. Or all the buttons at once. It somehow feels as if it ought to work, although of course we know it doesn't. Either the elevator has heard you, or it hasn't. How loud you call doesn't make any difference to how long it'll take to arrive.

But then elevators aren't like people. People do respond quicker to more stimulation, even on the most fundamental level. We press the brake quicker for brighter stoplights, jump higher at louder bangs. And it's because we all do this that we all fall so easily into thinking that things, including elevators, should behave the same way.

Give someone this simple task: she must sit in front of a screen and press a button as quickly as she can as soon as she sees a light flash on. If people were like elevators, the time it takes to press the button wouldn't be affected by the brightness of the light or the number of lights.

But people aren't like elevators and we respond quicker to brighter lights; in fact, the relationship between the physical intensity of the light and the average speed of response follows a precise mathematical form. This form is captured by an equation called Pieron's Law. Pieron's Law says that the time to respond to a stimulus is related to the stimulus intensity by the formula:

Reaction Time 

 R₀ + kI^-β

Reaction Time is the time between the stimulus appearing and you responding. I is the physical intensity of the signal. R ₀ is the minimum time for any response, the asymptotic value representing all the components of the reaction time that don't vary, such as the time for light to reach your eye.

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All abilities are skills; practice something and your brain will devote more resources to it.

The sensory homunculus looks like a person, but swollen and out of all proportion. It has hands as big as its head; huge eyes, lips, ears, and nose; and skinny arms and legs. What kind of person is it? It's you, the person in your head. Have a look at the sensory homunculus first, then make your own.

You can play around with Jaakko Hakulinen's homunculus applet (http://www.cs.uta.fi/~jh/homunculus.html; Java) to see where different bits of the body are represented in the sensory and motor cortex. There's a screenshot of it in Figure 1-3.

Figure 1-3: The figure shown is scaled according to the relative sizes of the body parts in the motor and sensory cortex areas; motor is shown on the left, sensory on the right

This is the person inside your head. Each part of the body has been scaled according to how much of your sensory cortex is devoted to it. The area of cortex responsible for processing touch sensations is the somatosensory cortex. It lives in the parietal lobe, further toward the back of the head than the motor cortex, running alongside it from the top of the head down each side of the brain. Areas for processing neighboring body parts are generally next to each other in the cortex, although this isn't always possible because of the constraints of mapping the 3D surface of your skin to a 2D map. The area representing your feet is next to the area representing your genitals, for example (the genital representation is at the very top of the somatosensory cortex, inside the groove between the two hemispheres).

The applet lets you compare the motor and sensory maps. The motor map is how body parts are represented for movement, rather than sensation. Although there are some differences, they're pretty similar. Using the applet, when you click on a part of the little man, the corresponding part of the brain above lights up. The half of the man on the left is scaled according to the representation of the body in the primary motor cortex, and the half on the right is scaled to represent the somatosensory cortex. If you click on a brain section or body part, you can toggle shading and the display of the percentage of sensory or motor representation commanded by that body part. The picture of the man is scaled, too, according to how much cortex each part corresponds to. That's why the hands are so much larger than the torso.

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The puzzle that is vision lies in the chasm between the raw sensation gathered by the eye—light landing on our retinas—and our rich perception of color, objects, motion, shape, entire 3D scenes. In this chapter, we'll fiddle about with some of the ways the brain makes this possible.

We'll start with an overview of the visual system [Hack #13] , the limits of your vision [Hack #14] , and the active nature of visual perception [Hack #15] .

There are constraints in vision we usually don't notice, like the blind spot [Hack #16] and the 90 minutes of blindness we experience every day as vision deactivates while our pupils jump around [Hack #17] . We'll have a look at both these and also at some of the shortcuts and tricks visual processing uses to make our lives easier: assuming the sun is overhead [Hack #20] and [Hack #21] , jumping out of the way of rapidly expanding dark shapes [Hack #32] (a handy shortcut for faster processing if you need to dodge quickly), and tricks like the use of noisy neurons [Hack #33] to extract signal out of visual noise.

Along the way, we'll take in how we perceive depth [Hack #22] and [Hack #24] , and motion [Hack #25] and [Hack #29] . (That's both the correct and false perception of motion, by the way.) We'll finish off with a little optical illusion called the Rotating Snakes Illusion [Hack #30] that has all of us fooled. After all, sometimes it's fun to be duped.

The visual system is a complex network of modules and pathways, all specializing in different tasks to contribute to our eventual impression of the world.

When we talk about "visual processing," the natural mode of thinking is of a fairly self-contained process. In this model, the eye would be like a video camera, capturing a sequence of photographs of whatever the head happens to be looking at at the time and sending these to the brain to be processed. After "processing" (whatever that might be), the brain would add the photographs to the rest of the intelligence it has gathered about the world around it and decide where to turn the head next. And so the routine would begin again. If the brain were a computer, this neat encapsulation would be how the visual subsystem would probably work.

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The puzzle that is vision lies in the chasm between the raw sensation gathered by the eye—light landing on our retinas—and our rich perception of color, objects, motion, shape, entire 3D scenes. In this chapter, we'll fiddle about with some of the ways the brain makes this possible.

We'll start with an overview of the visual system [Hack #13] , the limits of your vision [Hack #14] , and the active nature of visual perception [Hack #15] .

There are constraints in vision we usually don't notice, like the blind spot [Hack #16] and the 90 minutes of blindness we experience every day as vision deactivates while our pupils jump around [Hack #17] . We'll have a look at both these and also at some of the shortcuts and tricks visual processing uses to make our lives easier: assuming the sun is overhead [Hack #20] and [Hack #21] , jumping out of the way of rapidly expanding dark shapes [Hack #32] (a handy shortcut for faster processing if you need to dodge quickly), and tricks like the use of noisy neurons [Hack #33] to extract signal out of visual noise.

Along the way, we'll take in how we perceive depth [Hack #22] and [Hack #24] , and motion [Hack #25] and [Hack #29] . (That's both the correct and false perception of motion, by the way.) We'll finish off with a little optical illusion called the Rotating Snakes Illusion [Hack #30] that has all of us fooled. After all, sometimes it's fun to be duped.

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The visual system is a complex network of modules and pathways, all specializing in different tasks to contribute to our eventual impression of the world.

When we talk about "visual processing," the natural mode of thinking is of a fairly self-contained process. In this model, the eye would be like a video camera, capturing a sequence of photographs of whatever the head happens to be looking at at the time and sending these to the brain to be processed. After "processing" (whatever that might be), the brain would add the photographs to the rest of the intelligence it has gathered about the world around it and decide where to turn the head next. And so the routine would begin again. If the brain were a computer, this neat encapsulation would be how the visual subsystem would probably work.

With that (admittedly, straw man) example in mind, we'll take a tour of vision that shows just how nonsequential it all really is.

And one need go no further than the very idea of the eyes as passive receptors of photograph-like images to find the first fault in the straw man. Vision starts with the entire body: we walk around, and move our eyes and head, to capture depth information [Hack #22] like parallax and more. Some of these decisions about how to move are made early in visual processing, often before any object recognition or conscious understanding has come into play.

This pattern of vision as an interactive process, including many feedback loops before processing has reached conscious perception, is a common one. It's true there's a progression from raw to processed visual signal, but it's a mixed-up, messy kind of progression. Processing takes time, and there's a definite incentive for the brain to make use of information as soon as it's been extracted; there's no time to wait for processing to "complete" before using the extracted information. All it takes is a rapidly growing dark patch in our visual field to make us flinch involuntarily

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The high-resolution portion of your vision is only the size of your thumbnail at arm's length. The rest of your visual input is low res and mostly colorless, although you seldom realize it.

Your vision isn't of uniform resolution. What we generally think of as our visual ability, the sharpness with which we see the world, is really only the very center of vision, where resolution is at its highest. From this high-resolution center, the lower-resolution periphery, and using continual movements of our head and eyes [Hack #15] , we construct a seamless—and uniformly sharp—picture of the universe. But how much are we compensating? What is the resolution of vision?

The eye's resolution is determined by the density of light-sensitive cells on the retina, which is a layer of these cells on the back of the eye (and also includes several layers of cells to process and aggregate the visual signals to send on to the rest of the brain). If the cells were spread evenly, we would see as well out of the corners of our eyes as directly ahead, but they're not. Instead, the cells are most heavily packed right in the center of the retina, a small region called the fovea, so the highest-resolution part of the vision is in the middle of your visual field. The area corresponding to this is small; if you look up at the night sky, out of everything you see, your fovea just about covers the full moon. Away from this, in your peripheral vision, resolution is much coarser.

Color also falls off in peripheral vision. The light-sensitive cells, called photoreceptors, come in different types according to what kinds of light they convert into neural signals. Almost all the photoreceptors that can discriminate colors of light are in the fovea. Outside of this central area you can still make out color, but it's harder; the oter type of cell, more sensitive but able to recognize only brightness, is more abundant.

Figure 2-1 is a variant of the usual eye chart you will have encountered at the optometrist, constructed by Stuart Anstis. Hold it in front of you, and rest your gaze on the central dot. The letters in the chart are smallest in the middle and largest at the outer edge; they scale up at a rate to exactly compensate for your eyes' decrease in resolution from the central fovea to the periphery.

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Think of perception as a behavior, as something active, rather than as something passive. Perception exists to guide action, and being able to act is key to the construction of the high-resolution illusion of the world we experience.

The other hacks in this chapter could give the impression that seeing is just a matter of your brain passively processing the information that comes in through the eyes. But perception is far more of an active process. The impression we have of the world is made up by sampling across times, as well as just by sampling across the senses. The sensation we receive at any moment prompts us to change our head position, our attention, maybe to act to affect something out in the world, and this gives us different sensations in the next moment to update our impression of the world.

It's easier for your brain to take multiple readings and then interpolate the answers than it is to spend a long time processing a single scene. Equally important, if you know what you want to do, maybe you don't need to completely interpret a scene; you may need to process it just enough to let you decide what to do next and in acting give yourself a different set of sensations that make the scene more obvious.

This school of thought is an "ecological" approach to perception and is associated with the psychologist J. J. Gibson.¹ He emphasized that perception is a cognitive process and, like other cognitive processes, depends on interacting with the world. The situations used by vision scientists in which people look at things without moving or reaching out to touch them are extremely unnatural, as large as the difference between a movie at the theater directed by someone else and the freewill experience of regular real life.

If you want people to see something clearly, give them the chance to move it around and see how it interacts with other objects. Don't be fooled into thinking that perception is passive.

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Find out how big your visual blind spot is and how your brain fills the hole so you don't notice it.

Coating the back of each eye are photoreceptors that catch light and convert it to nerve impulses to send to the brain. This surface, the retina, isn't evenly spread with receptors—they're densest at the center and sparse in peripheral vision [Hack #14] . There's also a patch that is completely devoid of receptors; light that falls here isn't converted into nerve signals at all, leaving a blind spot in your field of view—or actually two blind spots, one for each eye.

First, here's how to notice your blind spot (later we'll draw a map to see how big it is). Close your left eye and look straight at the cross in Figure 2-6. Now hold the book flat about 10 inches from your face and slowly move it towards you. At about 6 inches, the black circle on the right of the cross will disappear, and where it was will just appear grey, the same color as the page around it.

Figure 2-6: A typical blind spot pattern

You may need to move the book back and forth a little. Try to notice when the black circle reappears as you increase the distance, then move the book closer again to hide the circle totally. It's important you keep your right eye fixed on the cross, as the blind spot is at a fixed position from the center of vision and you need to keep it still to find it.

Now that you've found your blind spot, use Jeffrey Oristaglio and Paul Grobstein's Java applet at the web site Serendip (http://serendip.brynmawr.edu/bb/blindspot; Java) to plot its size.

The applet shows a cross and circle, so, as before, close your left eye, fix your gaze on the cross, and move your head so that the circle disappears in your blind spot. Then click the Start button (at the bottom of the applet) and move your cursor around within the blind spot. While it's in there, you won't be able to see it, but when you can (only just), click, and a dot will appear. Do this a few times, moving the cursor in different directions starting from the circle each time.

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Our eyes constantly dart around in extremely quick movements called saccades. During each movement, vision cuts out.

Despite the fact that the eye has a blind spot, an uneven distribution of color perception, and can make out maximal detail in only a tiny area at the center of vision, we still manage to see the world as an uninterrupted panorama. The eye jumps about from point to point, snapshotting high-resolution views, and the brain assembles them into a stunningly stable and remarkably detailed picture.

These rapid jumps with the eyes are called saccades, and we make up to five every second. The problem is that while the eyes move in saccade all visual input is blurred. It's difficult enough for the brain to process stable visual images without having to deal with motion blur from the eye moving too. So, during saccades, it just doesn't bother. Essentially, while your eyes move, you can't see.

Put your face about 6 inches from a mirror and look from eye to eye. You'll notice that while you're obviously switching your gaze from eye to eye, you can't see your own eyes actually moving—only the end result when they come to rest on the new point of focus. Now get someone else to watch you doing so in the mirror. They can clearly see your eyes shifting, while to you it's quite invisible.

With longer saccades, you can consciously perceive the effect, but only just.

Hold your arms out straight so your two index fingers are at opposite edges of your vision. Flick your eyes between them while keeping your head still. You can just about notice the momentary blackness as all visual input from the eyes is cut off. Saccades of this length take around 200 ms (a fifth of a second), which lies just on the threshold of conscious perception.

What if something happens during a saccade? Well, unless it's really bright, you'll simply not see it. That's what's so odd about saccades. We're doing it constantly, but it doesn't look as if the universe is being blanked out a hundred thousand times a day for around a tenth of a second every time.

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Our sense of time lends a seamless coherence to our conscious experience of the world. We are able to effortlessly distinguish between the past, present, and future. Yet, subtle illusions show that our mental clock can make mistakes.

You only have to enjoy the synchrony achieved by your local orchestra to realize that humans must be remarkably skilled at judging short intervals of time. However, our mental clock does make mistakes. These anomalies tend to occur when the brain is attempting to compensate for gaps or ambiguities in available sensory information.

Such gaps can be caused by self-generated movement. For example, our knowledge about how long an object has been in its current position is compromised by the suppression of visual information [Hack #17] that occurs when we move our eyes toward that object—we can have no idea what that object was actually doing for the time our eyes were in motion. This uncertainty of position, and the subsequent guess the brain makes, can be felt in action by saccading the eyes toward a moving object.

Sometimes you'll glance at a clock and the second hand appears to hang, remaining stationary for longer than it ought to. For what seems like a very long moment, you think the clock may have stopped. Normally you keep looking to check and see that shortly afterward the second hand starts to move again as normal—unless, that is, it truly has stopped.

This phenomenon has been dubbed the stopped clock illusion. You can demonstrate it to yourself by getting a silently moving clock and placing it off to one side. It doesn't need to be an analog clock with a traditional second hand; it can be a digital clock or watch, just so long as it shows seconds. Position the clock so that you aren't looking at it at first but can bring the second hand or digits into view just by moving your eyes. Now, flick your eyes over to the clock (i.e., make a saccade

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It takes longer to shift your attention to a new object if the old object is still there.

Shifting attention often means shifting your eyes. But we're never fully in control of what our eyes want to look at. If they're latched on to something, they're rather stubborn about moving elsewhere. It's faster for you to look at something new if you don't have to tear your eyes away—if what you were originally looking at disappears and then there's a short gap, it's as if your eyes become unlocked, and your reaction time improves. This is called the gap effect.

The gap effect can be spotted if you're asked to stare at some shape on a screen, then switch your gaze to a new shape that will appear somewhere else on the screen. Usually, switching to the new shape takes about a fifth of a second. But if the old shape vanishes shortly before the new shape flashes up, moving your gaze takes less time, about 20% less.

It has to be said: the effect—on the order of just hundredths of a second—is tiny in the grand scheme of things. You're not going to notice it easily around the home. It's a feature of our low-level cognitive control: voluntarily switching attention takes a little longer under certain circumstances. In other words, voluntary behavior isn't as voluntary as we'd like to think.

We take in the world piecemeal, focusing on a tiny part of it with the high-resolution center of our vision for a fraction of a second, then our eyes move on to focus on another part. Each of these mostly automatic moves is called a saccade [Hack #15] .

We make saccades continuously—up to about five every second—but that's not to say they're fluid or all the same. While you're taking in a scene, your eyes are locked in. They're resistant to moving away, just for a short time. So what happens when another object comes along and you want to move your eyes toward it? You have to overcome that inhibition, and that takes a short amount of time.

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How do you figure out the three-dimensional shape of objects, just by looking? At first glance, it's using shadows.

Looking at shadows is one of many tricks we use to figure out the shape of objects. As a trick, it's easy to fool—shading alone is enough for the brain to assume what it's seeing is a real shadow. This illusion is so powerful and so deeply ingrained, in fact, that we can actually feel depth in a picture despite knowing it's just a flat image.

Have a look at the shaded circles in Figure 2-8, following a similar illustration in Kleffner and Ramachandran's "On the Perception of Shape from Shading."¹

Figure 2-8: Shaded figures give the illusion of three-dimensionality

I put together this particular diagram myself, and there's nothing to it: just a collection of circles on a medium gray background. All the circles are gradient-filled black and white, some with white at the top and some with white at the bottom. Despite the simplicity of the image, there's already a sense of depth.

The shading seems to make the circles with white at the top bend out of the page, as though they're bumps. The circles with white at the bottom look more like depressions or even holes.

To see just how strong the sense of depth is, compare the shaded circles to the much simpler diagram in Figure 2-9, also following Kleffner and Ramachandran's paper.

Figure 2-9: Binary black-and-white "shading" doesn't provide a sense of depth

The only difference is that, instead of being shaded, the circles are divided into solid black and white halves. Yet the depth completely disappears.

Shadows are identified early in visual processing in order to get a quick first impression of the shape of a scene. We can tell it's early because the mechanism it uses to resolve light source ambiguities is rather hackish.

Ambiguities occur all the time. For instance, take one of the white-at-top circles from Figure 2-8. Looking at it, you could be seeing one of two shapes depending on whether you imagine the shape was lit from the top or the bottom of the page. If light's coming from above, you can deduce it's a bump because it's black underneath where the shadows are. On the other hand, if the light's coming from the bottom of the page, only a dent produces the same shading pattern. Bump or dent: two different shapes can make the same shadow pattern lit from opposite angles.

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Moving shadows make us see moving objects rather than assume moving light sources.

Shadows get processed early when trying to make sense of objects, and they're one of the first things our visual system uses when trying to work out shape. [Hack #20] further showed that our visual system makes the hardwired assumption that light comes from above. Another way shadows are used is to infer movement, and with this, our visual system makes the further assumption that a moving shadow is the result of a moving object, rather than being due to a moving light source. In theory, of course, the movement of a shadow could be due to either cause, but we've evolved to ignore one of those possibilities—rapidly moving objects are much more likely than rapidly moving lights, not to mention more dangerous.

Observe how your brain uses shadows to construct the 3D model of a scene. Watch the ball-in-a-box movie at:

http://gandalf.psych.umn.edu/~kersten/kersten-lab/images/ball-in-a-box.mov (small version)
http://gandalf.psych.umn.edu/~kersten/kersten-lab/demos/BallInaBox.mov (large version, 4 MB)

If you're currently without Internet access, see Figure 2-12 for movie stills.

The movie is a simple piece of animation involving a ball moving back and forth twice across a 3D box. Both times, the ball moves diagonally across the floor plane. The first time, it appears to move along the floor of the box with a drop shadow directly beneath and touching the bottom of the ball. The second time the ball appears to move horizontally and float up off the floor, the shadow following along on the floor. The ball actually takes the same path both times; it's just the path of the shadow that changes (from diagonal along with the ball to horizontal). And it's that change that alters your perception of the ball's movement. (Figure 2-12 shows stills of the first (left) and second (right) times the ball crosses the box.)

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Our perception of a 3D world draws on multiple depth cues as diverse as atmospheric haze and preconceptions of object size. We use all together in vision and individually in visual design and real life.

Our ability to see depth is an amazing feature of our vision. Not only does depth make what we see more interesting, it also plays a crucial, functional role. We use it to navigate our 3D world and can employ it in the practice of visual communication design to help organize what we see through depth's ability to clarify through separation¹.

Psychologists call a visual trigger that gives us a sense of depth a depth cue. Vision science suggests that our sense of depth originates from at least 19 identifiable cues in our environment. We rarely see depth cues individually, since they mostly appear and operate in concert to provide depth information, but we can loosely organize them together into several related groups:

Binocular cues (stereoscopic depth, eye convergence): With binocular (two-eye) vision, the brain sees depth by comparing angle differences in the images from each eye. This type of vision is very important to daily life (just try catching a ball with one eye closed), but there are also many monocular (single-eye) depth cues. Monocular cues have the advantage that they are easier to employ for depth in images on flat surfaces (e.g., in print and on computer screens).
Perspective-based cues (size gradient, texture gradient, linear perspective): The shape of a visual scene gives cues to the depth of objects within it. Perspective lines converging/diverging or a change in the image size of patterns that we know to be at a constant scale (such as floor tile squares) can be used to inform our sense of depth.
Occlusion-based cues (object overlap, cast shadow, surface shadow): The presence of one object partially blocking the form of another and the cast shadows they create are strong cues to depth. See

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A powerful illusion of brightness shows how our brain takes scene structure and implied lighting into account when calculating the shade of things.

A major challenge for our vision is the reconstruction of a three-dimensional visual world from a two-dimensional retinal picture. The projection from three to two dimensions irrevocably loses information, which somehow needs to be reconstructed by the vision centers in our brain. True, we have two eyes, which helps a bit in the horizontal plane, but the vivid self-experience of seeing a 3D world clearly persists after covering one eye [Hack #22] .

In the process of reconstructing 3D from 2D, our brain cleverly relies on previous experience and assumptions on the physics of the real world. Since information is thus fabricated, the process is prone to error, especially in appropriately manipulated pictures, which gives rise to various large classes of optical illusions. We will concentrate here on a fairly recent example, Ted Adelson's checker shadow illusion.¹

Take a look at Adelson's checker shadow illusion in Figure 2-19.

Figure 2-19: Adelson's checker shadow—which is brighter, A or B?

We would all agree that one sees a checkerboard with a pillar standing in one corner. Illumination obviously comes from the top-right corner, as the shadow on the checkerboard tells us immediately (and we know how important shadows are for informing what we see [Hack #20] ). All of this is perceived at one rapid glance, much faster than this sentence can be read (lest written!).

Now let's ask the following question: which square is brighter, A or B? The obvious answer is B, and I agree. But now change the context by looking at Figure 2-20. The unmasked grays are from the two squares A and B, and unquestioningly the two shades of gray are identical (in fact, the entire figure was constructed just so).

Figure 2-20: This checkerboard is the same as the first, except for the added bars—now does A look brighter than B?

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We can use a little-known illusion called the Pulfrich Effect to hack the brain's computation of motion, depth, and brightness—all it takes is a pair of shades and a pendulum.

This is a journey into the code the visual system uses to work out how far away things are and how fast they are moving. Both of the variables—depth and velocity—can be calculated by comparing measurements of object position over time. Rather than have separate neural modules to figure out each variable, performing the same fundamental processing, the brain combines the two pieces of work and uses some of the same cells in calculating both measures. Because depth and motion are jointly encoded in these cells, it's possible (under the right circumstances) to convert changes in one into changes in another. An example is the Pulfrich Effect, in which a moving pendulum and some sunglasses create an illusion of the pendulum swinging in ellipses rather than in straight lines. It works because the sunglasses create an erroneous velocity perception, which gets converted into a depth change by the time it reaches your perception. It's what we'll be trying out here.

Make a pendulum out of a piece of string and something heavy to use as a weight, like a bunch of keys. You'll also need a pair of sunglasses or any shaded material.

Ask a friend to swing the pendulum in front of you in a perpendicular plane, and make sure it's going exactly in a straight line, left to right. Now, cover one of your eyes with the shades (this is easiest if you have old shades and can poke one of the lenses out). Keep both eyes open! You'll see that the pendulum now seems to be swinging back and forth as well as side to side, so that it appears to move in an ellipse. The two of you will look something like Figure 2-21.

Figure 2-21: Matt and Tom use sunglasses and a pendulum made out of a bootlace to test the Pulfrich Effect

Show your friend swinging the pendulum how you see the ellipse, and ask her to swing the pendulum in the opposite manner to counteract the illusion. Now the pendulum appears to swing in a straight line, and the thing that seems odd is not the distance from you, but the velocity of the pendulum. Because it really is swinging in an elliptical pattern, it covers perceived distance at an inconsistent rate. This makes it seem as if the pendulum is making weird accelerations and decelerations.

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Aftereffect illusions are caused by how cells represent motion in the brain.

Why, when the train stops, does the platform you are looking at out the window appear to creep backward? The answer tells us something important about the architecture of the visual system and about how, in general, information is represented in the brain.

The phenomenon is the motion aftereffect. Just as when you go from very bright sunlight to the indoors, everything looks dark, or if you are in a very quiet environment, loud noises seem even louder, so continuous motion in a certain direction leaves us with a bias in the other—an aftereffect.

Watch the video of a waterfall (http://www.biols.susx.ac.uk/home/George_Mather/Motion/MAE.HTML; QuickTime) for a minute or so, staring at the same position, then hit pause. You'll have the illusion of the water flowing upward. It works best with a real waterfall, if you can find one, although pausing at the end is harder, so look at something that isn't moving instead, like the cliff next to the waterfall.

The effect doesn't work for just continuous downward motion. Any continuous motion will create an opposite aftereffect; that includes spiral motion, such as in the Flash demo at http://www.at-bristol.org.uk/Optical/AfterEffects_main.htm.

The effect works only if just part of your visual field is moving (like the world seen through the window of a train). It doesn't occur if everything is moving, which is why, along with the fact that your motion is rarely continuous in a car, you don't suffer an aftereffect after driving.

Part of what makes this effect so weird is the experience of motion without any experience of things actually changing location. Not only does this feel pretty funny, but it suggests that motion and location are computed differently within the architecture of the brain.

Brain imaging confirms this. In some areas of the visual cortex, cells respond to movement, with different cells responding to different types of movement. In other areas of the visual cortex, cells respond to the location of objects in different parts of the visual field. Because the modules responsible for the computation of motion and the computation of location are separate, it is possible to experience motion without anything actually moving.

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We get used to things because our brain finds consistency boring and adjusts to filter it out.

My limbs feel weightless. I can't feel my clothes on my body. The humming of my laptop has disappeared. The flicker of the overhead light has faded out of my consciousness. I know it all must still be happening—I just don't notice it anymore.

In other words, it's just another normal day in the world with my brain.

Our brains let us ignore any constant input. A good thing too; otherwise, we'd spend all our time thinking about how heavy our hands are, how exactly our T-shirts feel on our backs, or at precisely what pitch our computers are humming, instead of concentrating on the task at hand.

The general term for this process of adjusting for constant input is called adaptation. Combined with relative representation of input, adaptation gives us aftereffects. The motion aftereffect is a good example of a complex adaptation process, so we'll walk through a detailed story about that here in a moment.

Both relative representation and the motion aftereffect are described in [Hack #25] . Simply put, how much "movement up" we perceive depends on the activation of up-sensitive neurons compared against the activation of down-sensitive neurons, not just the absolute level of activity.

Adaptation is a feature of all the sensory systems. You'll notice it (or, on the contrary, most likely not notice it) for sound, touch, and smells particularly. It affects vision [Hack #25] , too. If you stop to consider it for a moment, you'll appreciate just how little of the world you actually notice most of the time.

Adaptation is a general term for number of processes. Some of these processes are very basic, are of short term, and occur at the level of the individual sense receptor cells. An example is neuronal fatigue, which means just what it sounds as if it means. Without a break, individual neurons stop responding as vigorously to the same input. They get tired. Strictly speaking, ion channels in the membrane that regulate electrical changes in the cell become inactivated, but "tired" is a close enough approximation.

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Find out why static pictures can make up a moving image on your TV screen.

The motion aftereffect [Hack #25] shows that motion is computed in your brain separately from location. For instance, becoming accustomed to the moving surface of a waterfall causes you to see stationary surfaces as moving the other way, although they're quite still. In theory, motion can be calculated from position and time information, but that's not how your brain does it—there's a specialized brain region for detecting motion directly. Since location and motion are perceived separately, this can lead to some odd illusions, the motion aftereffect chief among them: you get the illusion of motion without anything actually changing position.

The motion aftereffect relies on an initial moving scene to set it up, but we can go one better and get an impression of movement when there's been no actual thing present, moving or otherwise. The effect is apparent motion, and even if you haven't heard of it, you'll have experienced it.

Look at two pictures one after the other, very rapidly, showing objects in slightly different positions. Get the timing right, and your brain fills in the gap: You get an illusion of the objects in the first picture moving smoothly to their position in the second. There's no single, moving object out there in the world, but your brain's filling in of the assumed path of movement gives you that impression.

Sound familiar? It should; it's the effect that all television and cinema is based on, of course.

The easiest way to experience this effect is, of course, to turn on your television or go to the cinema. Movie projectors show 24 frames (pictures) a second, and that's good enough for everyone to perceive continuous motion in the change from one frame to the next.

In the old days of cinema, the film had 16 frames a second, which were projected using a three-bladed shutter to increase the flicker frequency above the rate necessary for flicker fusion. Despite seeing the same frame three times, your brain would fill in the gaps between the images, whether they were the same or different, so that you'd get the impression of continuous motion.

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If there's a flash of light on a moving object, the flash appears to hang a little behind.

How quickly we can act is slow compared to how quickly things can happen to us—especially when you figure that by the time you've decided to respond to something that is moving it will already be in a new position. How do you coordinate your slow reactions to deal with moving objects? One way is to calibrate your muscles to deal with the way you expect things to be, so your legs are prepared for a moving escalator [Hack #62] , for example, before you step on it, to avoid the round-trip time of noticing the group is moving, deciding what to do, adjusting your movements, and so on. Expectations are built into your perceptual system as well as your motor system, and they deal with the time delay from sense data coming in to the actual perception being formed. You can see this coping strategy with an illusion called the flash-lag effect.¹

Watch Michael Bach's Flash Lag demo at http://www.michaelbach.de/ot/mot_flashlag1 (Flash). A still from it is shown in Figure 2-23. In it, a blue-filled circle orbits a cross—hold your eyes on the cross so you're not looking directly at the moving circle. This is to make sure the circle is moving across your field of view.

Figure 2-23: In the movie, the circle orbits the cross and flashes from time to time

Occasionally the inside of the ring flashes yellow, but it looks as if the yellow flash happens slightly behind the circle and occupies only part of the ring. This is the flash-lag illusion. You can confirm what's happening by clicking the Slow button (top right). The circle moves slower and the flash lasts longer, and it's now clear that the entire center of the circle turns yellow and the lag is indeed only an illusion.

The basic difficulty here is that visual perception takes time; almost a tenth of a second passes between light hitting your retina to the signal being processed and reaching your cortex (most of this is due to how long it takes the receptors in the eye to respond). The circle in Bach's demo moves a quarter of an inch in that time, and it's not even going that fast. Imagine perpetually interacting with a world that had already moved on by the time you'd seen it.

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Motion detection uses contrast information first, not color.

The moral of this story is that if you want people to see moving objects, make them brighter or darker than the background, not just a different color.

Motion is important stuff for the brain. Information about movement gets routed from the eye to the visual cortex—the final destination for all visual information—along its own pathway (you can take a tour round the visual system [Hack #13] ), the magnocellular pathway. (Like a lot of things in neuroscience, this sounds more technical than it is; magnocellular means "with large cells.")

Color and form information travels along the parvocellular pathway (yup, "small cells") to the visual cortex, which means any motion has to be processed without access to that information. This functional division makes sense for a brain that wants to know immediately if there's a movement, and only secondly what exactly that moving something looks like. Problems arise only when movement processing is trying to figure out what sort of motion is occurring but the clues it needs are encoded in color and so not available.

Stuart Anstis has constructed just such a problematic situation, and it leads to the nifty stepping feet illusion¹ (http://psy.ucsd.edu/~sanstis/Foot.html; Shockwave). Blue and yellow blocks move smoothly in tandem from side to side. Click the Background button to bring up the striped background, and look again. It should look like Figure 2-24.

Figure 2-24: The stepping feet illusion, with the striped background

Even though they're still moving in the same direction, the blocks now appear to be alternately jerking forward, like little stepping feet. Like a lot of illusions, the effect is stronger in your peripheral vision; fix the center of your gaze at the cross off to the side and the stepping feet will be even clearer.

The easiest way to see why the stepping feet occur is to look at the same pattern, but without any color—the yellow becomes white and the blue becomes black. Michael Bach's animation of stepping feet (

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Shading in pictures combined with the continuous random jiggling our eyes make can generate compelling movement illusions.

We've all seen optical illusions in which parts of a completely static picture appear to drift and swirl. One of the most famous examples is Professor Akiyoshi Kitaoka's rotating snake illusion (Figure 2-25), commonly passed around via email, but, sadly, rarely with explanation.

This is really a story about why you don't see everything moving all the time rather than about why you see movement sometimes when it isn't there. Your eyes constantly move in your head [Hack #15] , your head moves on your body, and your body moves about space. Your brain has to work hard to disentangle those movements in incoming visual information that are due to your movement and those due to real movement in the world.

One way your brain cuts down on confusion is shutting down visual input during rapid eye movements [Hack #17] .

Another mechanism is used to cancel out visual blur that results from head movements. Signals from how your head is moving are fed to the eyes to produce opposite eye movements that keep the visual image still.

Try this experiment. Hold the book in one hand and shake your head from side to side. You can still read the book. Now shake the book from side to side at the same speed at which you shook your head. You can't read a word, even though the words are moving past your head in the same way, and at the same speed, as when you were shaking your head. The vestibular-ocular reflex feeds a signal from your inner ear [Hack #47] to your eyes in such a way that they move in the opposite direction and at the correct rate to correct the visual displacement produced by the movement of your head.

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If you imagine an inner space, the movements you make in it take up time according to how large they are. Reducing the imaginary distances involved makes manipulating mental objects easier and quicker.

Mental imagery requires the same brain regions that are used to represent real sensations. If you ask someone to imagine hearing the first lines to the song "Purple Haze" by Jimi Hendrix, the activity in her auditory cortex increases. If you ask someone to imagine what the inside of a teapot looks like, his visual cortex works harder. If you put a schizophrenic who is hearing voices into a brain scanner, when she hears voices, the parts of the brain that represent language sounds really are active—she's not lying; she really is hearing voices.

Any of us can hear voices or see imaginary objects at will; it's only when we lose the ability to suppress the imaginings that we think of it as a problem.

When we imagine objects and places, this imagining creates mental space that is constrained in many of the ways real space is constrained. Although you can imagine impossible movements like your feet lifting up and your body rotating until your head floats inches above the floor, these movements take time to imagine and the amount of time is affected by how large they are.

Is the left shape in Figure 2-28 the same as the right shape?

Figure 2-28: Is the left shape the same as the right shape?

How about the left shape in Figure 2-29—is it the same as the right shape?

Figure 2-29: Is the left shape the same as the right shape?

And is the left shape in Figure 2-30 the same as the one on the right?

Figure 2-30: Is the left shape the same as the right shape?

To answer these questions, you've had to mentally rotate one of each pair of the shapes. The first one isn't too hard—the right shape is the same as the left but rotated 50°. The second pair is not the same; the right shape is the mirror inverse of the left and again rotated by 50°. The third pair is identical, but this time the right shape has been rotated by 150°. To match the right shape in the third example to the left shape, you have to mentally rotate 100° further than to match the first two examples. It should have taken you extra seconds to do this. If you'd like try an online version, see the demonstration at

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We have special routines that detect things that loom and make us flinch in response.

Typically, the more important something is, the deeper in the brain you find it, the earlier in evolution it arose, and the quicker it can happen.

Avoiding collisions is pretty important, as is closing your eyes or tensing if you can't avoid the collision. What's more, you need to do these things to a deadline. It's no use dodging after you've been hit.

Given this, it's not surprising that we have some specialized neural mechanisms for detecting collisions and that they are plugged directly into motor systems for dodging and defensive behavior.

The startle reaction is pretty familiar to all of us—you blink, you flinch, maybe your arms or legs twitch as if beginning a motion to protect your vulnerable areas. We've all jumped at a loud noise or thrown up our arms as something expands toward us. It's automatic. I'm not going to suggest any try-it-at-home demonstrations for this hack. Everyone knows the effect, and I don't want y'all firing things at each other to see whether your defense reactions work.

Humans can show response to a collision-course stimulus within 80 ms.¹ This is far too quick for any sophisticated processing. In fact, it's even too quick for any processing that combines information across both eyes.

It's done, instead, using a classic hack—a way of getting good-enough 3D direction and speed information from crude 2D input. It works like this: symmetrical expansion of darker-than-background areas triggers the startle response.

"Darker-than-background" because this is a rough-and-ready way of deciding what to count as an object rather than just part of the background. "Symmetrical expansion" because this kind of change in visual input is characteristic of objects that are coming right at you. If it's not expanding, it's probably just moving, and if it's not expanding symmetrically, it's either changing shape or not moving on a collision course.

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Neural signals are innately noisy, which might just be a good thing.

Neural signals are always noisy: the timings of when they fire, or even whether they fire at all, is subject to random variation. We make generalizations at the psychological level, such as saying that the speed of response is related to intensity by a certain formula—Pieron's Law [Hack #11] . And we also say that cells in the visual cortex respond to different specific motions [Hack #25] . But both of these are true only on average. For any single cell, or any single test of reaction time, there is variation each time it is measured. Not all the cells in the motion-sensitive parts of the visual cortex will respond to motion, and those that do won't do it exactly the same each time we experience a particular movement.

In the real world, we take averages to make sense of noisy data, and somehow the brain must be doing this too. We know that the brain is pretty accurate, despite the noisiness of our neural signals. A prime mechanism for compensating for neural noise is the use of lots of neurons so that the average response can be taken, canceling out the noise.

But it may also be the case that noise has some useful functions in the nervous system. Noise could be a feature, rather than just an inconvenient bug.

To see how noise can be useful, visit Visual Perception of Stochastic Resonance (http://neurodyn.umsl.edu/~simon/sr.html; Java) designed by Enrico Simonotto,¹ which includes a Java applet.

A grayscale picture has noise added and the result filtered through a threshold. The process is repeated and results played like a video. Compare the picture with various levels of noise included. With a small amount of noise, you see some of the gross features of the picture—these are the parts with high light values so they always cross the threshold, whatever the noise, and produce white pixels—but the details don't show up often enough for you to make them out. With lots of noise, most of the pixels of the picture are frequently active and it's hard to make out any distinction between true parts of the picture and pixels randomly activated by noise.

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It's a busy world out there, and we take in a lot of input, continuously. Raw sense data floods in through our eyes, ears, skin, and more, supplemented by memories and associations both simple and complex. This makes for quite a barrage of information; we simply haven't the ability to consider all of it at once.

How, then, do we decide what to attend to and what else to ignore (at least for now)?

Attention is what it feels like to give more resources over to some perception or set of perceptions than to others. When we talk about attention here, we don't mean the kind of concentration you give to a difficult book or at school. It's the momentary extra importance you give to whatever's just caught your eye, so to speak. Look around the room briefly. What did you see? Whatever you recall seeing—a picture, a friend, the radio, a bird landing on the windowsill—you just allocated attention to it, however briefly.

Or perhaps attention isn't a way of allocating the brain's scarce processing resources. Perhaps the limiting factor isn't our computational capacity at all, but, instead, a physical limit on action. As much as we can perceive simultaneously, we're able to act in only any one way at any one time. Attention may be a way of throwing away information, of narrowing down all the possibilities, to leave us with a single conscious experience to respond to, instead of millions.

It's hard to come up with a precise definition of attention. Psychologist William James,¹ in his 1890 The Principles of Psychology, wrote: "Everyone knows what attention is." Some would say that a more accurate and useful definition has yet to been found.

That said, we can throw a little light on attention to see how it operates and feels. The hacks in this chapter look at how you can voluntarily focus your visual attention [Hack #34] , what it feels like when you do (and when you remove it again) [Hack #36] , and what is capable of overriding your voluntary behavior and grabbing attention

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It's a busy world out there, and we take in a lot of input, continuously. Raw sense data floods in through our eyes, ears, skin, and more, supplemented by memories and associations both simple and complex. This makes for quite a barrage of information; we simply haven't the ability to consider all of it at once.

How, then, do we decide what to attend to and what else to ignore (at least for now)?

Attention is what it feels like to give more resources over to some perception or set of perceptions than to others. When we talk about attention here, we don't mean the kind of concentration you give to a difficult book or at school. It's the momentary extra importance you give to whatever's just caught your eye, so to speak. Look around the room briefly. What did you see? Whatever you recall seeing—a picture, a friend, the radio, a bird landing on the windowsill—you just allocated attention to it, however briefly.

Or perhaps attention isn't a way of allocating the brain's scarce processing resources. Perhaps the limiting factor isn't our computational capacity at all, but, instead, a physical limit on action. As much as we can perceive simultaneously, we're able to act in only any one way at any one time. Attention may be a way of throwing away information, of narrowing down all the possibilities, to leave us with a single conscious experience to respond to, instead of millions.

It's hard to come up with a precise definition of attention. Psychologist William James,¹ in his 1890 The Principles of Psychology, wrote: "Everyone knows what attention is." Some would say that a more accurate and useful definition has yet to been found.

That said, we can throw a little light on attention to see how it operates and feels. The hacks in this chapter look at how you can voluntarily focus your visual attention [Hack #34] , what it feels like when you do (and when you remove it again) [Hack #36] , and what is capable of overriding your voluntary behavior and grabbing attention

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Focusing on detail is limited by both the construction of the eye and the attention systems of the brain.

What's the finest detail you can see? If you're looking at a computer screen from about 3 meters away, 2 pixels have to be separated by about a millimeter or more for them not to blur into one. That's the highest your eye's resolution goes.

But making out detail in real life isn't just a matter of discerning the difference between 1 and 2 pixels. It's a matter of being able to focus on fine-grain detail among enormously crowded patterns, and that's more to do with the limits of the brain's visual processing than what the eye can do. What you're able to see and what you're able to look at aren't the same.

Figure 3-1 shows two sets of bars. One set of bars is within the resolution of attention, allowing you to make out details. The other obscures your ability to differentiate particularly well by crowding .¹

Figure 3-1: One set of bars is within the resolution of attention (right), the other is too detailed (left)¹

Hold this book up and fix your gaze on the cross in the middle of Figure 3-1. To notice the difference, you have to be able to move your focus around without moving your eyes—it does come naturally, but it can feel odd doing it deliberately for the first time. Be sure not to shift your eyes at all, and notice that you can count how many bars are on the righthand side easily. Practice moving your attention from bar to bar while keeping your eyes fixed on the cross in the center. It's easy to focus your attention on, for example, the middle bar in that set.

Now, again without removing your gaze from the cross, shift your attention to the bars on the lefthand side. You can easily tell that there are a number of bars there—the basic resolution of your eyes is more than good enough to tell them apart. But can you count them or selectively move your attention from the third to the fourth bar from the left? Most likely not; they're just too crowded.

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You don't need counting if a group is small enough; subitizing will do the job, and it's almost instant.

The brain has two methods for counting, and only one is officially called counting. That's the regular way—when you look at a set of items and check them off, one by one. You have some system of remembering which have already been counted—you count from the top, perhaps—and then increment: 7, 8, 9...

The other way is faster, up to five times faster per item. It's called subitizing. The catch: subitizing works for only really small numbers, up to about 4. But it's fast! So fast that until recently it was believed to be instantaneous.

See how many stars there are in the two sets in Figure 3-3. You can tell how many are in set A just by looking (there are three), whereas it takes a little longer to see there are six in set B.

Figure 3-3: The set of stars on the left can be subitized; the one on the right cannot

I know this feels obvious, that it takes longer to see how many stars there are in the larger set. After it, there are more of them. But that's exactly the point. If you can tell, and it feels like immediately, how many stars there are when there are three of them, why not when there are six? Why not when there are 100?

Subitizing and counting do seem like different processes. If you look at studies of how long it takes for a person to look at some shapes on the screen and report how many there are, the time grows at 40-80 ms per item up to four, then increases at 250-350 milliseconds beyond that.¹ Or to put it another way, assessing the first four items takes only a quarter of a second. It takes another second for every four items after that. That's a big jump.

The difference between the two is borne out by the subjective experience. Counting feels to be a very deliberate act. You must direct your attention to each item. Your eyes move from star to star. Subitizing, on the other hand, feels preattentive. Your eyes don't need to move from star to star at all. There's no deliberate act required; you just know that there are four coffee mugs on the table or three people in the lobby, without having to check. You just look. It's this that leads some researchers to believe that subitizing isn't an act in itself, but rather a side effect of visual processing.

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Following seemingly identical objects around with your eyes isn't an easy job. Concentrating, it's possible, and the brain can even track objects when they momentarily pass behind things and disappear, but only in certain circumstances.

The problem with attention as a mechanism is that we use it continuously—it's an intrinsic part of perception—and consequently it's very hard to spot what it actually does or what giving attention to something actually feels like.

This hack has a go at showing you what allocating attention actually feels like, by getting you to voluntarily give attention to some fairly generic objects—in this case, you'll be tracking small, colored shapes as they move around. And you'll be able to feel what happens to these shapes when you take attention away. These are humble beginnings—attention allocation to moving shapes—but we use these mechanisms for following any thing as it moves around: tennis balls, dogs, ants, and cursors.

Watch the sequence of multiple object tracking (MOT) demonstrations at Dr. Zenon Pylyshyn's Visual Attention Lab (http://ruccs.rutgers.edu/finstlab/demos.htm).¹ Multiple object tracking is a class of experiment based around trying to keep track of many objects (small circles in the first demonstration) simultaneously, as they jiggle about. It tests the limits of your attention and specialized tracking skills.

Just in case you're not online at the moment, Figures Figure 3-4 through Figure 3-6 provide screenshots of the experiments for your convenience.

Figure 3-4: You have to track four of these circles as they move around the screen

Start with the General MOT experiment (http://ruccs.rutgers.edu/finstlab/mot.mov; QuickTime; Figure 3-4). In this demo, you're required to track four of the eight circles as they move around; you're told which four as they flash briefly at the beginning of the movie.

The point of this demonstration is simply to point out that you can indeed attend to more than one object at a time. It's not a trivial matter to follow all four circles around simultaneously, but you'll find that you can gaze at the center of the screen and track your four chosen circles fairly easily, without even having to stare directly at each in turn.

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Sudden movement or light can grab your attention, thanks to a second region for visual processing.

What are you paying attention to? These words? In a minute it could switch to a friend or to making coffee or to the person on the bus who just stood up and you noticed out of the corner of your eye. We don't pay attention to everything we see or experience. Following two conversations at the same time is hard, even though we hear both perfectly well, and, likewise, it's simply not possible to read every word on the page of a book simultaneously, although they're all in plain view.

While your senses work overtime to provide as much input as possible, there's a bottleneck in the brain's limited capacity for attention. So we consciously decide which line of text to focus on and read across and down the page, line by line. And this happens at the expense of all the other stimuli we could have attended to, such as the color of the walls or the traffic noise from the road outside.

Choosing what to give attention to is voluntary...mostly. But attention can also be captured.

Stand so that you're facing a crowded scene. Watching a crowded theater settle down is ideal. A busy street corner is a good choice, too. A TV screen or video game will do as well, as long as there's a lot going on in the frame.

Don't try to direct your attention; just let it wander and feast your eyes on the full field of view.

Notice that when a person waves, or stands up, your attention is grabbed and snaps to focus on the person's position. It's not so much that you notice the waving or standing up itself; the event simply captures your attention and you properly focus on that place a fraction of a second afterward.

Since you're relaxed, your attention soon drifts away, until someone else moves and captures it again. Your attention scintillates across your whole field of view, darting from point to point.

After visual information leaves the eye, it doesn't just go to one place for processing; the signal divides. Our conscious appreciation of visual information is provided by processing done in the visual cortex. It sits at the back of the brain in the area called the

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Your visual attention contains a basic function that puts the dampers on second glances.

There are layers and layers of functions and processing in the brain. One—attention—is a collaborative exercise between voluntary application of attention and automatic mechanisms to snap attention to where it's needed [Hack #37] . Even the voluntary application of attention is a negotiation with what evolution has taught the brain is most sensible. In particular, the brain doesn't like to return attention to a place or object it has just left. This phenomenon is called inhibition of return.

Like negative priming [Hack #42] , which is how contextual features are suppressed from attention, inhibition of return is such a low-level effect that it's hard to show without precision timing equipment. Again, just like those other effects, it turns up in all kinds of cases because attention is so widely employed.

Imagine you're taking part in an experiment in which an icon flashes up on a screen and you have to touch that position. It'll take you longer to move and touch the icon if some other icon had previously, and recently, been in that position.

Inhibition doesn't kick in immediately. Let's say you're playing Whack-A-Mole,¹ in which moles emerge from holes and you have to hit them with a hammer. A hole could light up momentarily before the mole appears. This would be a prime candidate for the inhibition-of-return effect. If the brightening occurs very shortly before the mole appears, only a fifth of a second or so, it serves to draw your attention to that place and you'll actually respond to the mole faster.

If, on the other hand, the brightening occurs and then there's a longer pause—more than a fifth of a second and up to 3 or 4 seconds—that's enough time for your attention to be dragged to the brightness change then shift away again. Inhibition of return kicks in, and when the mole appears in that same spot, you have to overcome the inhibition. It'll take longer for you to react to the mole (although it's not likely you'll miss it. Reaction time increases only on the order of a twentieth of a second or so—enough to make a difference in some circumstances, but hard to spot.) One caveat: if the brightening happens before the mole pops up every single time, you're going to learn that pattern and end up being better at whacking the mole every time instead.

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Our ability to notice things suffers in the half-second after we've just spotted something else.

A good way to think about attention is as the brain's way of paring down the sheer volume of sensory input into something more manageable. You can then concentrate your resources on what's important (or at least perceived to be so on first blush) and ignore the rest. If processing capacity weren't limited, perhaps we wouldn't need attention at all-we'd be able to give the same amount of concentration to everything in our immediate environment, simultaneously.

Another reason we continually pare down perception, using attention as a final limiting stage before reaching conscious awareness, could be that perception causes action. Maybe processing capacity doesn't intrinsically need to be limited, but our ability to act definitely is: we can do only one major task at a time. Attention might just be a natural part of conflict resolution over what to do next.
—M.W.

Attention isn't the end of the chain, however. There's conscious awareness too. The difference between the two is subtle but important. Think of walking down a street and idly looking at the faces going by. Each face as it passes has a moment of your attention, but if you were asked how many brown-haired people you'd seen, you wouldn't have the slightest idea.

Say somebody you recognize passes. Suddenly this semiautomatic, mostly backgrounded looking-at-faces routine jumps to the foreground and pushes the face into conscious awareness. This is the act of noticing.

It turns out the act of noticing takes up resources in the brain too, just as paying attention does. Once you've noticed a face in the crowd, there's a gap where your ability to consciously notice another face is severely reduced. It's a big gap too—about half a second. This phenomenon has been dubbed the attentional blink, drawing a parallel with the physical eye blink associated with visual surprise.

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We don't memorize every detail of a visual scene. Instead, we use the world as its own best representation—continually revisiting any bits we want to think about. This saves the brain time and resources, but can make us blind to changes.

Both our vision [Hack 14] and attention [Hack #34] have far coarser resolutions than we'd have thought. What's more, there are gaps in our vision across time [Hack #17] and in space [Hack #16] , but our brains compensate for these gaps and knit together a rather seamless impression of the world.

And this gapless impression is utterly convincing. Most of the time we don't even realize that there are holes in the information we're getting. And so we believe we experience more of the world than we actually do. There are two possibilities as to what's going on here. The first is that we build a model inside our heads of the world we can see. You can test to see whether this is the case.

Imagine you are looking at a picture. There's a flicker as the picture disappears and appears again. What's different? If we made and kept a full internal representation of the visual world inside our heads, it would be easy to spot the difference. In theory—before memory decay set in—it should be as easy as comparing two pictures (before and after) side by side on a page. But it isn't.

So that puts paid to the first possibility. The other is that you don't build a full internal model of what you're seeing at all—you just think you do. The illusion is maintained by constant sampling as you move your eyes around, a part of what is called active vision [Hack #15] . After all, why bother to store information about the world in your head when the information is freely available right in front of your very eyes?

The proof of the pudding for active vision is testing the consequence that, if true, you should find it very difficult to spot changes between two scenes, even with just a short flicker in between. Since most of the two separated images aren't stored in memory, there's no way to compare them. And, true enough, spotting any difference is very difficult—so hard, in fact, that the phenomenon's been labeled

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What you pay attention to determines what you see, so much so that you can miss things that are immensely obvious to others—like dancing gorillas, for instance.

Attention acts as a kind of filter, directing all resources to certain tasks and away from others. Nowhere is the impact of attention on what you actually see more evident than in the various experiments on inattention blindness.

Inattention blindness comes up when you're focusing as much attention as you can on a particular task and trying really hard to ignore distractions. It's the name given to the phenomenon of not noticing those distractions, however blatant and bizarre they become. In the most famous experiment on this subject, subjects had to watch a video of a crowd playing basketball. Concentrating on a spurious task, a good number of them were completely blind to the gorilla that walked into view halfway through the game.

You can watch the basketball video used in the gorilla experiment by Daniel Simons and Christopher Chabris.¹ Find it from the University of Illinois Visual Cognition Lab's page at http://viscog.beckman.uiuc.edu/media/mindhacks.html.²

OK, because you know what's going to happen, this isn't going to work for you, but here's the procedure anyway. Watch the basketball game, and count the number of passes made by the team in white shirts only. Find a friend and set her on the task.

If you were a subject in this experiment for real, counting those passes, what happens next would be completely unexpected: a woman in a gorilla suit walks through the group playing the game and stands in the middle of the screen before walking off again. About half the observers tested in Simons and Chabris's experiment missed the gorilla.

Following the passes in the game and counting only some of them is a difficult task. There are two balls and six players, everyone's moving around, and the balls are often obscured. It's all your brain can do to keep up.

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The act of focusing on just one object goes hand in hand with actively suppressing everything you have to ignore. This suppression persists across time, in a phenomenon called negative priming.

In the story "The Boy Who Cried Wolf," the young shepherd repeatedly claims a wolf has come to attack his flock. There's no wolf there. The boy just enjoys seeing all the villagers run up the hill, coming to save him and the sheep. The villagers, naturally, get a bit annoyed at getting panicked and trying to scare off the nonexistent wolf, so when they hear the boy cry, "Wolf!" again in the middle of the night, they don't bother getting up. But this time there is a wolf. Oh dear. I could say the boy learns his lesson, but he doesn't: he gets eaten. Morality tale, very sad, etc.

Negative priming is the tiniest psychological root of "The Boy Who Cried Wolf." A stimulus, such as a color, a word, a picture, or a sound acts like the cry of "Wolf!" The brain acts as the villagers did, and it has an inhibition to responding to meaningless cries, and this kicks in after only one cry. But nobody gets eaten.

Negative priming can be picked up only in experiments with careful timing and many trials—it's a small-scale effect, but it's been demonstrated in many situations.

Look at the flash card in Figure 3-9, and say what the gray picture is as fast as you can. Speak it out loud.

Figure 3-9: An example negative priming flash card

Now look at Figure 3-10, and do the same: name the gray picture, out loud, as quickly as possible.

Figure 3-10: The next flash card in the sequence

You may find the picture in the second flash card slightly harder to make out, although really you need a controlled situation to pick up the reaction time difference. Both cards have a gray drawing to pick out and a black drawing to ignore, and you suppress both the black ink and the black image in order to ignore it. If, as is the case here, the image you have to identify in the second flash card is the same as the one you had to ignore in the first, you'll take a little longer about it. Your brain is acting like the second time the villagers hear the boy shouting "Wolf!"—they still get out of bed, but it takes slightly longer to pull their clothes on.

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Some of the constraints on how fast we can task-switch or observe simultaneously aren't fixed. They can be trained by playing first-person action video games.

Our visual processing abilities are by no means hardwired and fixed from birth. There are limits, but the brain's nothing if not plastic. With practice, the attentional mechanisms that sort and edit visual information can be improved. One activity that requires you to practice lots of the skills involved in visual attention is playing video games.

So, what effect does playing lots of video games have? Shawn Green and Daphne Bavelier from the University of Rochester, New York, have researched precisely this question; their results were published in the paper "Action Video Game Modifies Visual Attention,"¹ available online at http://www.bcs.rochester.edu/people/daphne/visual.html#video.

Two of the effects they looked at we've talked about elsewhere in this book. The attentional blink [Hack #39] is that half-second recovery time required to spot a second target in a rapid-fire sequence. And subitizing is that alternative to counting for very low numbers (4 and below), the almost instantaneous mechanism we have for telling how many items we can see [Hack #35] . Training can both increase the subitization limit and shorten the attentional blink, meaning we're able to simultaneously spot more of what we want to spot, and do it faster too.

Comparing the attentional blink of people who have played video games for 4 days a week over 6 months against people who have barely played games at all finds that the games players have a shorter attentional blink.

The attentional blink comes about in trying to spot important items in a fast-changing sequence of random items. Essentially, it's a recovery time. Let's pretend there's a video game in which, when someone pops up, you have to figure out whether it's a good guy or a bad guy and respond appropriately. Most of the characters that pop up are good guys, it's happening as fast as you can manage, and you're responding almost automatically—then suddenly a bad one comes up. From working automatically, suddenly the bad guy has to be lifted to conscious awareness so you can dispatch him. What the attentional blink says is that the action of raising to awareness creates a half-second gap during which you're less likely to notice another bad guy coming along.

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Your ears are not simply "eyes for sound." Sound contains quite different information about the world than does light. Light tends to be ongoing, whereas sound occurs when things change: when they vibrate, collide, move, break, explode! Audition is the sense of events rather than scenes. The auditory system thus processes auditory information quite differently from how the visual system processes visual information: whereas the dominant role of sight is telling where things are, the dominant role of hearing is telling when things happen [Hack #44] .

Hearing is the first sense we develop in the womb. The regions of the brain that deal with hearing are the first to finish the developmental process called myelination, in which the connecting "wires" of neurons are finished off with fatty sheaths that insulate the neurons, speeding up their electrical signals. In contrast, the visual system doesn't complete this last step of myelination until a few months after birth.

Hearing is the last sense to go as we lose consciousness (when you're dropping off to sleep, your other senses drop away and sounds seem to swell up) and the first to return when we make it back to consciousness.

We're visual creatures, but we constantly use sound to keep a 360° check on the world around us. It's a sense that supplements our visual experience—a movie without a music score is strangely dull, but we hardly notice the sound track normally. We'll look at how we hear some features of that sound track, stereo sound [Hack #45] , and pitch [Hack #46] .

And of course, audition is the sense of language. Hacks in this chapter show how we don't just hear a physical sound but can hear the meanings they convey [Hack #49] , even on the threshold of perception [Hack #48] . Just as with vision, what we experience isn't quite what is physically there. Instead, we experience a useful aural construction put together by our brains.

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Your ears are not simply "eyes for sound." Sound contains quite different information about the world than does light. Light tends to be ongoing, whereas sound occurs when things change: when they vibrate, collide, move, break, explode! Audition is the sense of events rather than scenes. The auditory system thus processes auditory information quite differently from how the visual system processes visual information: whereas the dominant role of sight is telling where things are, the dominant role of hearing is telling when things happen [Hack #44] .

Hearing is the first sense we develop in the womb. The regions of the brain that deal with hearing are the first to finish the developmental process called myelination, in which the connecting "wires" of neurons are finished off with fatty sheaths that insulate the neurons, speeding up their electrical signals. In contrast, the visual system doesn't complete this last step of myelination until a few months after birth.

Hearing is the last sense to go as we lose consciousness (when you're dropping off to sleep, your other senses drop away and sounds seem to swell up) and the first to return when we make it back to consciousness.

We're visual creatures, but we constantly use sound to keep a 360° check on the world around us. It's a sense that supplements our visual experience—a movie without a music score is strangely dull, but we hardly notice the sound track normally. We'll look at how we hear some features of that sound track, stereo sound [Hack #45] , and pitch [Hack #46] .

And of course, audition is the sense of language. Hacks in this chapter show how we don't just hear a physical sound but can hear the meanings they convey [Hack #49] , even on the threshold of perception [Hack #48] . Just as with vision, what we experience isn't quite what is physically there. Instead, we experience a useful aural construction put together by our brains.

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Audition is a specialized sense for gathering information from the fourth dimension.

If vision lets you see where something is, hearing tells you when it is. The time resolution of audition is way above that of vision. A cinema screen of 24 images a second looks like a constant display, rather than 24 brief images. A selection of 24 clicks a second sounds like a bunch of clicks—they don't blur into a constant tone.

Listen to these three sound files:

24 clicks per second, for 3 seconds (http://www.mindhacks.com/book/44/24Hz.mp3; MP3)
48 clicks per second, for 3 seconds (http://www.mindhacks.com/book/44/48Hz.mp3; MP3)
96 clicks per second, for 3 seconds (http://www.mindhacks.com//book/44/96Hz.mp3; MP3)

At a frequency of 24 frames per second, film blurs into a continuous image. At 24 clicks per second, you perceive the sound as separate clicks. At four times that rate, you still hear the sound as discontinuous. You may not be able to count the clicks, but you know that the sound is made up of lots of little clicks, not one continuous hum. Auditory "flicker" persists up to higher frequencies than visual flicker before it is integrated to a continuous percept.

Specialization for timing is evident in many parts of the auditory system. However, it is the design of the sound receptor device (the ears) that is most crucial. In the eye, light is converted to neural impulses by a slow chemical process in the receptor cells. However, in the ear, sound is converted to neural impulses by a fast mechanical system.

Sound vibrations travel down the ear canal and are transmitted by the tiny ear bones (ossicles) to the snail-shaped cochlea, a piece of precision engineering in the inner ear. The cochlea performs a frequency analysis of incoming sound, not with neural circuitry, but mechanically. It contains a curled wedge, called the basilar membrane, which, due to its tapering thickness, vibrates to different frequencies at different points along its length. It is here, at the basilar membrane, that sound information is converted into neural signals, and even that is done mechanistically rather than chemically. Along the basilar membrane are receptors, called hair cells. These are covered in tiny hairs, which are in turn linked by tiny filaments. When the hairs are pushed by a motion of the basilar membrane, the tiny filaments are stretched, and like ropes pulling open doors, the filaments open many minute channels on the hairs. Charged atoms in the surrounding fluid rush into the hair cells, and thus sound becomes electricity, the native language of the brain. Even movements as small as those on the atomic scale are enough to trigger a response. And for low frequency sounds (up to 1500 cycles per second), each cycle of the sound can trigger a separate group of electrical pulses. For higher frequencies, individual cycles are not coded, just the average intensity of the cycles. The cells that receive auditory timing input in the brain can fire at a faster rate than any other neurons, up to 500 times a second.

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Our ears let us know approximately which direction sounds are coming from. Some sounds, like echoes, are not always informative, and there is a mechanism for filtering them out.

A major purpose of audition is telling where things are. There's an analogy used by auditory neuroscientists that gives a good impression of just how hard a job this is. The information bottleneck for the visual system is the ganglion cells that connect the eyes to the brain [Hack #13] . There are about a million in each eye, so, in your vision, there are about two million channels of information available to determine where something is. In contrast, the bottleneck in hearing involves just two channels: one eardrum in each ear. Trying to locate sounds using the vibrations reaching the ears is like trying to say how many boats are out on a lake and where they are, just by looking at the ripples in two channels cut out from the edge of the lake. It's pretty difficult stuff.

Your brain uses a number of cues to solve this problem. A sound will reach the near ear before the far ear, the time difference depending on the position of the sound's source. This cue is known as the interaural (between the ears) time difference. A sound will also be more intense at the near ear than the far ear. This cue is known as the interaural level difference. Both these cues are used to locate sounds on the horizontal plane: the time difference (delay) for low-frequency sounds and the level difference (intensity) for high-frequency sounds (this is known as the Duplex Theory of sound localization). To locate sounds on the vertical plane, other cues in the spectrum of the sound (spectral cues) are used. The direction a sound comes from affects the way it is reflected by the outer ear (the ears we all see and think of as ears, but which auditory neuroscientists call pinnae). Depending on the sound's direction, different frequencies in the sound are amplified or attenuated. Spectral cues are further enhanced by the fact that our ears are slightly different shapes, thus differently distort the sound vibrations.

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Why we perceive pitch at all is a story in itself. Pitch exists for sounds because our brains calculate it, and to do that, they must have a reason.

All sounds are vibrations in air. Different amplitudes create different sound intensities; different frequencies of vibration create different pitches. Natural sounds are usually made up of overlaid vibrations that are occurring at a number of different frequencies. Our experience of pitch is based on the overall pattern of the vibrations. The pitch isn't, however, always a quality that is directly available in the sound information. It has to be calculated. Our brains have to go to some effort to let us perceive pitch, but it isn't entirely obvious why we do this at all. One theory for why we hear pitch at all is because it relates to object size: big things generally have a lower basic frequency than small things.

The pitch we perceive a sound having is based on what is called the fundamental of the sound wave. This is the basic rate at which the vibration repeats. Normally you make a sound by making something vibrate (say, by hitting it). Depending on how and what you hit (this includes hitting your vocal cords with air), you will establish a main vibration—this is the fundamental—which will be accompanied by secondary vibrations at higher frequencies, called harmonics. These harmonics vibrate at frequencies that are integer multiples of the fundamental frequency (so for a fundamental at 4 Hz, a harmonic might be at 8 Hz or 12 Hz, but not 10 Hz). The pitch of the sound we hear is based on the frequency of the fundamental alone; it doesn't matter how many harmonics there are, the pitch stays the same.

Amazingly, even if the fundamental frequency isn't actually part of the sound we hear; we still hear pitch based on what it should be. So for a sound that repeats four times a second but that is made up of component frequencies at 8 Hz, 12 Hz, and 16 Hz, the fundamental is 4 Hz, and it is based upon this that we experience pitch.

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The ear isn't just for hearing; it helps you keep your balance.

Audition isn't the only function of the inner ear. We have semicircular channels of fluid, two in the horizontal plane, two in the vertical plane, that measure acceleration of the head. This, our vestibular system, is used to maintain our balance.

Note that this system can detect only acceleration and deceleration, not motion. This explains why we can be fooled into thinking we're moving if a large part of our visual field moves in the same direction—for example, when we're sitting on a train and the train next to ours moves off, we get the impression that we've started moving. For slow-starting movement, the acceleration information is too weak to convince us we've moved.

It's a good thing the system detects only acceleration, not absolute motion, otherwise we might be able to tell that we are moving at 70,000 mph through space round the sun. Or, worse, have direct experience of relativity—then things would get really confusing.
—T.S.

You can try and use this blind spot for motion next time you're on a train. Close your eyes and focus on the rocking of the train side to side. Although you can feel the change in motion side to side, without visual information—and if your train isn't slowing down or speeding up—you don't have any information except memory to tell you in which direction you are traveling. Imagine the world outside moving in a different way. See if you can hallucinate for a second that you are traveling very rapidly in the opposite direction. Obviously this works best with a smooth train, so readers in Japan will have more luck.

Any change in our velocity causes the fluid in the channels of the vestibular system to move, bending hair cells that line the surface of the channels (these hair cells work the same as the hair cells that detect sound waves in the cochlea, except they detect distortion in fluid, not air). Signals are then sent along the vestibular nerve into the brain where they are used to adjust our balance and warn of changes in motion.

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Can you sort the signal from the noise? Patterns and regularity are often deeply hidden, but we're surprisingly adept at finding them.

Our perceptual abilities and sensory acumen differ from one individual to another, making our threshold for detecting faint or ambiguous stimuli vary considerably. The brain is particularly good at making sense of messy data and can often pick out meaning in the noisiest of environments, filtering out the chaotic background information to pick out the faintest signals.

A sample of Bing Crosby's "White Christmas" has been hidden in the sound file on our book web site (http://www.mindhacks.com/book/48/whitechristmas.mp3;MP3). The sound file is 30 seconds long and is mostly noise, so you will have to listen carefully to detect when the song starts. The song will start either in the first, second, or third 10 seconds and will be very faint, so pay close attention.

You'll get more out of this hack if you listen to the sound file before knowing how the music has been hidden, so you're strongly recommended not to read ahead to the next section until you've done so.

If you managed to hear the strains of Bing Crosby in the noisy background of the sound file, you may be in for a surprise. The sound file is pure noise, and despite what we promised earlier, "White Christmas" is not hidden in there at all (if you read ahead without trying it out for yourself, try it out on someone else). Not everyone is likely to detect meaningful sounds in the background noise, but it's been shown to work on a certain subset of the population. An experiment conducted by Merckelbach and van de Ven¹ reported that almost a third of students reported hearing "White Christmas" when played a similar noisy sound track.

There's been a lot of debate about why this might happen and what sort of attributes might be associated with the tendency to detect meaning in random patterns. In the study mentioned earlier, the authors found that this ability was particularly linked to measures of fantasy proneness—a measure of richness and frequency of imagination and fantasy—and hallucination proneness—a measure of vividness of imagery and unusual perceptual experiences. If you, or someone you tested, heard "White Christmas" amid the noise and are now worried, there's no need to be. The tendencies measured by Merckelbach and van de Ven's study were very mild and certainly not a marker of anything abnormal (after all, it worked in a third of people!), and we all hallucinate to some degree (not seeing the eye's blind spot

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Once your brain has decided to classify a sound as speech, it brings online a raft of tricks to extract from it the maximum amount of information.

Speech isn't just another set of noises. The brain treats it very differently from ordinary sounds. Speech is predominantly processed on the left side of the brain, while normal sounds are mostly processed on the right.

This division is less pronounced in women, which is why they tend to recover better from strokes affecting their left-sided language areas.

Knowing you're about to hear language prepares your brain to make lots of assumptions specially tailored to extract useful information from the sound. It's this special way of processing language-classified sounds that allows our brains to make sense of speech that is coming at us at a rate of up to 50 phonemes a second—a rate that can actually be produced only using an artificially sped-up recording.

To hear just how much the expectation of speech influences the sounds you hear, listen to the degraded sound demos created by Bob Shannon et al. at the House Ear Institute (http://www.hei.org/research/depts/aip/audiodemos.htm).

In particular, listen to the MP3 demo that starts with a voice that has been degraded beyond recognition and then repeated six times, each time increasing the quality (http://www.hei.org/research/depts/aip/increase_channels.mp3).

You won't be able to tell what the voice is saying until the third or fourth repetition. Listen to the MP3 again. This time your brain knows what to hear, so the words are clearer much earlier. However hard you try, you can't go back to hearing static.

Sentences are broken into words having meaning and organized by grammar, the system by which we can build up an infinite number of complex sentences and subtle meanings from only a finite pool of words.

Words can be broken down too, into morphemes, the smallest units of meaning. "-ing" is a morpheme and makes the word "run" become "running." It imparts meaning. There are further rules at this level, about how to combine words into large words.

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The sounds of words carry meaning too, as big words for big movements demonstrate.

Steven Pinker, in his popular book on the nature of language, The Language Instinct ¹, encounters the frob-twiddle-tweak continuum as a way of talking about adjusting settings on computers or stereo equipment. The Jargon File, longtime glossary for hacker language, has the following under frobnicate (http://www.catb.org/~esr/jargon/html/F/frobnicate.html):

Usage: frob, twiddle, and tweak sometimes connote points along a continuum. `Frob' connotes aimless manipulation; twiddle connotes gross manipulation, often a coarse search for a proper setting; tweak connotes fine-tuning. If someone is turning a knob on an oscilloscope, then if he's carefully adjusting it, he is probably tweaking it; if he is just turning it but looking at the screen, he is probably twiddling it; but if he's just doing it because turning a knob is fun, he's frobbing it.²

Why frob first? Frobbing is a coarse action, so it has to go with a big lump of a word. Twiddle is smaller, more delicate. And tweak, the finest adjustment of all, feels like a tiny word. It's as if the actual sound of the word, as it's spoken, carries meaning too.

The two shapes in Figure 4-3 are a maluma and a takete. Take a look. Which is which?

Don't spoil the experiment for yourself by reading the next paragraph! When you try this out on others, you may want to cover up all but the figure itself.

Figure 4-3: One of these is a "maluma," the other a "takete"—which is which?

If you're like most people who have looked at shapes like these since the late 1920s, when Wolfgang Köhler devised the experiment, you said that the shape on the left is a "takete," and the one on the right is a "maluma." Just like "frob" and "tweak," in which the words relate to the movements, "takete" has a spiky character and "maluma" feels round.

Words are multilayered in meaning, not just indices to some kind of meaning dictionary in our brains. Given the speed of speech, we need as many clues to meaning as we can get, to make understanding faster. Words that are just arbitrary noises would be wasteful. Clues to the meaning of speech can be packed into the intonation of a word, what other words are nearby, and the sound itself.

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The length of a sentence isn't what makes it hard to understand— it's how long you have to wait for a phrase to be completed.

When you're reading a sentence, you don't understand it word by word, but rather phrase by phrase. Phrases are groups of words that can be bundled together, and they're related by the rules of grammar. A noun phrase will include nouns and adjectives, and a verb phrase will include a verb and a noun, for example. These phrases are the building blocks of language, and we naturally chunk sentences into phrase blocks just as we chunk visual images into objects.

What this means is that we don't treat every word individually as we hear it; we treat words as parts of phrases and have a buffer (a very short-term memory) that stores the words as they come in, until they can be allocated to a phrase. Sentences become cumbersome not if they're long, but if they overrun the buffer required to parse them, and that depends on how long the individual phrases are.

Read the following sentence to yourself:

While Bob ate an apple was in the basket.

Did you have to read it a couple of times to get the meaning? It's grammatically correct, but the commas have been left out to emphasize the problem with the sentence.

As you read about Bob, you add the words to an internal buffer to make up a phrase. On first reading, it looks as if the whole first half of the sentence is going to be your first self-contained phrase (in the case of the first, that's "While Bob ate an apple")—but you're being led down the garden path. The sentence is constructed to dupe you. After the first phrase, you mentally add a comma and read the rest of the sentence...only to find out it makes no sense. Then you have to think about where the phrase boundary falls (aha, the comma is after "ate," not "apple"!) and read the sentence again to reparse it. Note that you have to read again to break it into different phrases; you can't just juggle the words around in your head.

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Neural networks process in parallel rather than serially. This means that as processing of different aspects proceeds, previously processed aspects can be used quickly to disambiguate the processing of others.

Neural networks are massively parallel computers. Compare this to your PC, which is a serial computer. Yeah, sure, it can emulate a parallel processor, but only because it is really quick. However quick it does things, though, it does them only one at a time.

Neural processing is glacial by comparison. A neuron in the visual cortex is unlikely to fire more than every 5 milliseconds even at its maximum activation. Auditory cells have higher firing rates, but even they have an absolute minimum gap of 2 ms between sending signals. This means that for actions that take 0.5 to 1 second—such as noticing a ball coming toward you and catching it (and many of the things cognitive psychologists test)—there are a maximum of 100 consecutive computations the brain can do in this time. This is the so-called 100 step rule.¹

The reason your brain doesn't run like a PC with a 0.0001 MHz processor is because the average neuron connects onto between 1000 and 10,000 other neurons. Information is routed, and routed back, between multiple interconnected neural modules, all in parallel. This allows the slow speed of each neuron to be overcome, and also makes it natural, and necessary, that all aspects of a computational job be processed simultaneously, rather than in stages.

Any decision you make or perception you have (because what your brain decides to provide you with as a coherent experience is a kind of decision too) is made up of the contributions of many processing modules, all running simultaneously. There's no time for them to run sequentially, so they all have to be able to run with raw data and whatever else they can get hold of at the time, rather than waiting for the output of other modules.

A good example of simultaneous processing is in understanding language. As you hear or read, you use the context of what is being said, the possible meaning of the individual words, the syntax of the sentences, and how the sounds of each word—or the letters of each word—look to figure out what is being said.

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This chapter looks at how we integrate our perceptions—images ( Chapter 2), sounds (Chapter 4), our own mechanisms of attention (Chapter 3), and our other senses [Hack #12] —into a unified perceptual experience.

For instance, how do we use our eyes and ears together? (We prefer to use our ears for timing and eyes for determining location [Hack #53] .) And what are the benefits of doing so? (We feel experiences that happen in two senses simultaneously as more intense [Hack #57] and [Hack #58] .)

Sometimes, we overintegrate. The Stroop Effect [Hack #55] , a classic experiment, shows that if we try to respond linguistically, irrelevant linguistic input interferes. In its eagerness to assimilate as much associated information, as much context, as possible, the brain makes it very hard to ignore even what we consciously know is unimportant.

We'll also look at one side effect and one curious limitation of the way we integrate sense information. The first goes to show that even the brain's errors can be useful and that we can actually use a mistaken conclusion about a sound's origin to better listen to it [Hack #60] . The second answers the question: do we really need language to perform what should be a basic task, of making a simple deduction from color and geometry? In some cases, it would appear so [Hack #61] .

The timing of an event will be dominated by the sound it makes, the location by where it looks as if it is happening—this is precisely why ventriloquism works.

Hearing is good for timing [Hack #44] but not so good for locating things in space. On the flip side, vision has two million channels for detecting location in space but isn't as fast as hearing.

What happens when you combine the two? What you'd expect from a well-designed bit of kit: vision dominates for determining location, audition dominates for determining timing. The senses have specialized for detecting different kinds of information, and when they merge, that is taken into account.

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This chapter looks at how we integrate our perceptions—images ( Chapter 2), sounds (Chapter 4), our own mechanisms of attention (Chapter 3), and our other senses [Hack #12] —into a unified perceptual experience.

For instance, how do we use our eyes and ears together? (We prefer to use our ears for timing and eyes for determining location [Hack #53] .) And what are the benefits of doing so? (We feel experiences that happen in two senses simultaneously as more intense [Hack #57] and [Hack #58] .)

Sometimes, we overintegrate. The Stroop Effect [Hack #55] , a classic experiment, shows that if we try to respond linguistically, irrelevant linguistic input interferes. In its eagerness to assimilate as much associated information, as much context, as possible, the brain makes it very hard to ignore even what we consciously know is unimportant.

We'll also look at one side effect and one curious limitation of the way we integrate sense information. The first goes to show that even the brain's errors can be useful and that we can actually use a mistaken conclusion about a sound's origin to better listen to it [Hack #60] . The second answers the question: do we really need language to perform what should be a basic task, of making a simple deduction from color and geometry? In some cases, it would appear so [Hack #61] .

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The timing of an event will be dominated by the sound it makes, the location by where it looks as if it is happening—this is precisely why ventriloquism works.

Hearing is good for timing [Hack #44] but not so good for locating things in space. On the flip side, vision has two million channels for detecting location in space but isn't as fast as hearing.

What happens when you combine the two? What you'd expect from a well-designed bit of kit: vision dominates for determining location, audition dominates for determining timing. The senses have specialized for detecting different kinds of information, and when they merge, that is taken into account.

You can see each of the two senses take control in the location and timing domains. In the first part, what you see overrules the conflicting location information in what you hear; in the second part, it's the other way around.

Section 5.2.1.1: Vision dominates for localization

Go to the theater, watch a film, or play a movie on your PC, listening to it on headphones. You see people talking and the sound matches their lip movement [Hack #59] . It feels as if the sound is coming from the same direction as the images you are watching. It's not, of course; instead, it's coming at you from the sides, from the cinema speakers, or through your headphones.

The effect is strongest at public lectures. You watch the lecturer on stage talking and don't notice that the sound is coming at you from a completely different direction, through speakers at the sides or even back of the hall. Only if you close your eyes can you hear that the sounds aren't coming from the stage. The visual correspondence with the sounds you are hearing causes your brain to absorb the sound information into the same event as the image, taking on the location of the image. This is yet another example (for another, see [Hack #58] ) of how our most important sense, vision, dominates the other senses.

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Attention isn't separate for different senses. Where you place your attention in visual space affects what you hear in auditory space. Attention exists as a central, spatially allocated resource.

Where you direct attention is not independent across the senses. Where you pay attention to in space with one sense affects the other senses.¹ If you want people to pay attention to information across two modalities (a modality is a sense mode, like vision or audition), they will find this easiest if the information comes from the same place in space. Alternatively, if you want people to ignore something, don't make it come from the same place as something they are attending to. These are lessons drawn from work by Dr. Charles Spence of the Oxford University crossmodal research group (http://www.psych.ox.ac.uk/xmodal/default.htm). One experiment that everyone will be able to empathize with involves listening to speech while driving a car.²

Listening to a radio or mobile phone on a speaker from the back of a car makes it harder to spot things happening in front of you.

Obviously showing this in real life is difficult. It's a complex situation with lots of variables, and one of these is whether you crash your car—not the sort of data psychologists want to be responsible for creating. So Dr. Spence created the next best thing in his lab—an advanced driving simulator, which he sat people in and gave them the job of simultaneously negotiating the traffic and bends while repeating sets of words played over a speaker (a task called shadowing). The speakers were placed either on the dashboard in front or to the side.

Drivers who listened to sounds coming from the sides made more errors in the shadowing task, drove slower, and took longer to decide what to do at junctions.

You can see coping strategy in action if you sit with a driver. Notice how he's happy to talk while driving on easy and known roads, but falls quiet and pops the radio off when having to make difficult navigation decisions.

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When you're speaking, written words can distract you. If you're thinking nonlinguistically, they can't.

The Stroop Effect is a classic of experimental psychology. In fact, it's more than a classic, it's an industry. J. Ridley Stroop first did his famous experiment in 1935, and it's been replicated thousands of times since then. The task is this: you are shown some words and asked to name the ink color the words appear in. Unfortunately, the words themselves can be the names of colors. You are slower, and make more errors, when trying to name the ink color of a word that spells the name of a different color. This, in a nutshell, is the Stroop Effect. You can read the original paper online at http://psychclassics.yorku.ca/Stroop.

To try out the Stroop Effect yourself, use the interactive experiment available at http://faculty.washington.edu/chudler/java/ready.html ¹ (you don't need Java in your web browser to give this a go).

Start the experiment by clicking the "Go to the first test" link; the first page will look like Figure 5-1, only (obviously) in color.

Figure 5-1: In the Stroop experiment, the color of the ink isn't necessarily the same as the color the word declares

As fast as you're able, read out loud the color of each word—not what it spells, but the actual color in which it appears. Then click the Finish button and note the time it tells you. Continue the experiment and do the same on the next screen. Compare the times.

The difference between the two tests is that whereas the ink colors and the words correspond on the first screen, on the second they conflict for each word. It takes you longer to name the colors on the second screen.

Although you attempt to ignore the word itself, you are unable to do so and it still breaks through, affecting your performance. It slows your response to the actual ink color and can even make you give an incorrect answer. You can get this effect with most people nearly all of the time, which is one reason why psychologists love it.

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You're drawn to reach in the same direction as something you're reacting to, even if the direction is completely unimportant.

So much of what we do in everyday life is responding to something that we've seen or heard—choosing and clicking a button on a dialog box on a computer or leaping to turn the heat off when a pan boils over. Unfortunately, we're not very good at reacting only to the relevant information. The form in which we receive it leaks over into our response.

For instance, if you're reacting to something that appears on your left, it's faster to respond with your left hand, and it takes a little longer to respond with your right. And this is true even when location isn't important at all. In general, the distracting effect of location responses is called the Simon Effect,¹ named after J. Richard Simon, who first published on it in 1968 and is now Professor Emeritus at the University of Iowa.2

The Simon Effect isn't the only example of the notionally irrelevant elements of a stimulus leaking into our response. Similar is the Stroop Effect [Hack #55] , in which naming an ink color nets a slower response if the ink spells out the name of a different color. And, although it's brought about by a different mechanism, brighter lights triggering better reaction times [Hack #11] is similar in that irrelevant stimulus information modifies your response (this one is because a stronger signal evokes a faster neural response).

A typical Simon task goes something like this: you fix your gaze at the center of a computer screen and at intervals a light flashes up, randomly on the left or the right—which side is unimportant. If it is a red light, your task is to hit a button on your left. If it is a green light, you are to hit a button on your right. How long it takes you is affected by which side the light appears on, even though you are supposed to be basing which button you press entirely on the color of the light. The light on the left causes quicker reactions to the red button and slower reactions to the green button (good if the light is red, bad if the light is green). Lights appearing on the right naturally have the opposite effect. Even though you're supposed to disregard the location entirely, it still interferes with your response. The reaction times being measured are usually a half-second or less for this sort of experiment, and the location confusion results in an extension of roughly 5%.

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Events that affect more than one sense feel more intense in both of them.

The vision and audition chapters (Chapter 2 and Chapter 4, respectively) of this book look at the senses individually, just as a lot of psychologists have over the years. But interesting things begin to happen when you look at the senses as they interact with one another.¹

Multisensory information is the norm in the real world, after all. Tigers smell strong and rustle as they creep through the undergrowth toward you. Fire shines and crackles as it burns. Your child says your name as she shakes your shoulder to wake you up.

These examples all suggest that the most basic kind of interaction between two senses should be the enhanced response to an event that generates two kinds of stimulation rather than just one. Information from one sense is more likely to be coincidence; simultaneous information on two senses is a good clue that you have detected a real event.

We can see the interaction of information hitting two senses at once in all sorts of situations. People sound clearer when we can see their lips [Hack #59] . Movies feel more impressive when they have a sound track. If someone gets a tap on one hand as they simultaneously see two flashes of light, one on each side, the light on the same side as the hand tap will appear brighter.

Helge Gillmeister and Martin Eimer of Birkbeck College, University of London, have found that people experience sounds as louder if a small vibration is applied to their index finger at the same time.² Although the vibration didn't convey any extra information, subjects rated sounds as up to twice as loud when they occurred at the same time as a finger vibration. The effect was biggest for quieter sounds.

Recent research on such situations shows that the combination of information is wired into the early stages of sensory processing in the cortex. Areas of the cortex traditionally thought to respond to only a single sense (e.g., parts of the visual cortex) do actually respond to stimulation of the other senses too. This makes sense of the fact that many of these effects occur preconsciously, without any sense of effort or decision-making. They are preconscious because they are occurring in the parts of the brain responsible for initial representation and processing of sensation—another example (as in

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Looking at your skin makes it more sensitive, even if you can't see what it is you're feeling. Look through a magnifying glass and it becomes even more sensitive.

The skin is the shortest-range interface we have with the world. It is the only sense that doesn't provide any information about distant objects. If you can feel something on your skin, it is next to you right now.

Body parts exist as inward-facing objects—they provide touch information—but they also exist as external objects—we can feel them with other body parts, see them, and (if you're lucky) feel and see those of other people. [Hack #64] and [Hack #93] explore how we use vision to update our internal model of our body parts. But the integration of the two senses goes deeper, so much so that looking at a body part enhances the sensitivity of that body part, even if you aren't getting any useful visual information to illuminate what's happening on your skin.

Kennett et al.¹ tested how sensitive people were to touch on their forearms. In controlled conditions, people were asked to judge if they were feeling two tiny rods pressed against their skin or just one. The subjects made these judgments in three conditions. The first two are the most important, providing the basic comparison. Subjects were either in the dark or in the light and looking at their arm—but with a brief moment of darkness so they couldn't actually see their arm as the pins touched it. Subjects allowed to look at their arms were significantly more accurate, indicating that looking at the arm, even though it didn't provide any useful information, improved tactile sensitivity.

The third condition is the most interesting and shows exactly how pervasive the effect can be. Subjects were shown their forearm through a magnifying glass (still with darkness at the actual instant of the pinprick). In this condition, their sensitivity was nearly twice as precise as their sensitivity in the dark!

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Listen with your eyes closed and you'll hear one sound; listen and watch the speaker at the same time and you'll hear another.

If there were ever a way of showing that your senses combine to completely change your ultimate experience, it's the McGurk Effect. This classic illusion, invented by Harry McGurk (and originally published in 1976¹, makes you hear different sounds being spoken depending on whether or not you can see the speaker's lips. Knowing what's going to happen doesn't help: the effect just isn't as strong.

Watch Arnt Maas's McGurk Effect video (http://www.media.uio.no/personer/arntm/McGurk_english.html; QuickTime with sound). You can see a freeze frame of the video in Figure 5-3.

Figure 5-3: Arnt Maas's McGurk Effect video

When you play it with your eyes closed, the voice says "ba ba." Play the video again, and watch the mouth: the voice says "da da." Try to hear "ba ba" while you watch the lips move. It can't be done.

The illusion itself can't happen in real life. McGurk made it by splicing the sound of someone saying "ba ba" over a video of him making a different sound, "ga ga." When you're not watching the video, you hear what's actually being spoken. But when you see the speaker too, the two bits of information clash. The position of the lips is key in telling what sound someone's making, especially for distinguishing between speech sounds (called phonemes) like "ba," "ga," "pa," and "da" (those which you make by popping air out).

Visual information is really important for listening to people speak. It's a cliché, but I know I can't understand people as well when I don't have my glasses on.
—M.W.

We use both visual and auditory information when figuring out what sound a person is making and they usually reinforce each other, but when the two conflict, the brain has to find a resolution. In the world the brain's used to, objects don't usually look as if they're doing one thing but sound as if they're doing another.

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Sounds from the same spatial location are harder to separate, but not if you use vision to fool your brain into "placing" one of the sounds somewhere else.

Sense information is mixed together in the brain and sorted by location [Hack #54] , and we use this organization in choosing what to pay attention to (and therefore tune into). If you're listening to two different conversations simultaneously, it's pretty easy if they're taking place on either side of your head—you can voluntarily tune in to whichever one you want. But let's say those conversations were occurring in the same place, on the radio: it's suddenly much harder to make out just one.

Which is why we can talk over each other in a bar and still understand what's being said, but not on the radio. On the radio, we don't have any other information to disambiguate who says what and the sounds get confused with each other.
—T.S.

Hang on...how do we decide on the spatial location of a sense like hearing? For sound alone, we use clues implicit in what we hear, but if we can see where the sound originates, this visual information dominates [Hack #53] .

Even if it's incorrect.

Jon Driver from University College London¹ took advantage of our experience with syncing language sounds with lip movements to do a little hacking. He showed people a television screen showing a person talking, but instead of the speech coming from the television, it was played through a separate amplifier and combined with a distracting, and completely separate, voice speaking. The television screen was alternately right next to the amplifier or some distance away. The subject was asked to repeat the words corresponding to the talking head on the television.

If they watched the talking head on screen nearby the amplifier, they made more errors than if they watched the talking head on the screen kept distant from the sound. Even though both audio streams were heard from the single amplifier in the two cases, moving the video image considerably changed the listener's ability to tune into one voice.

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Language isn't just for talking to other people; it may play a vital role in helping your brain combine information from different modules.

Language might be an astoundingly efficient way of getting information into your head from the outside [Hack #49] , but that's not its only job. It also helps you think. Far from being a sign of madness, talking to yourself is something at the essence of being human.

Rather than dwell on the evolution of language and its role in rewiring the brain into its modern form,¹ let's look at one way language may be used by our brains to do cognitive work. Specifically we're talking about the ability of language to combine information in ordered structures—in a word: syntax.

Peter Carruthers, at the University of Maryland,² has proposed that language syntax is used to combine, simultaneously, information from different cognitive modules. By "modules," he means specialized processes into which we have no insight,3 such as color perception or instant number judgments [Hack #35] . You don't know how you know that something is red or that there are two coffee cups, you just know. Without language syntax, the claim is, we can't combine this information.

The theory seems pretty bold—or maybe even wrong—but we'll go through the evidence Carruthers uses and the details of what exactly he means and you can make up your own mind. If he's right, the implications are profound, and it clarifies exactly how deeply language is entwined with thought. At the very least, we hope to convince you that something interesting is going on in these experiments.

The experiment described here was done in the lab of Elizabeth Spelke.⁴You could potentially do it in your own home, but be prepared to build some large props and to get dizzy.

Imagine a room like the one in Figure 5-4. The room is made up of four curtains, used to create four walls in a rectangle, defined by two types of information: geometric (two short walls and two long walls) and color information (one red wall).

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The story of the brain is a story of embodiment, of how much the brain takes for granted the world we're in and the body that carries it about.

For instance, we assume a certain level of stability in the world. We make assumptions about how our body is able to move within the environment, and if the environment has changed [Hack #62] , we get confused.

As we assume stability in the world, so too do we assume stability from our body. Why should the brain bother remembering the shape of our own body when it's simply there to consult? But when our body's shape doesn't remain stable, the brain can get confused. You start by getting your fingers mixed up when you cross your hands [Hack #63] ; you end up convincing your brain that you're receiving touch sensations from the nearby table [Hack #64] .

This is also a story of how we interact with the world. Our brains continually assess and anticipate the movements we need to grasp objects, judging correctly even when our eyes are fooled [Hack #66] . We're built for activity, our brains perceiving the uses of an object, its affordances [Hack #67] , as soon as we look at it—as soon as we see something, we ready ourselves to use it.

We'll finish on what we use for manipulation: our hands. What makes us right- or left-handed [Hack #68] ? And, while we're on the topic, what does all that left-brain, right-brain stuff really mean [Hack #69] ?

Your conscious experience of the world and control over your body both feel instantaneous—but they're not.

Lengthy delays in sensory feedback and in the commands that are sent to your muscles mean that what you see now happened a few moments ago and what you're doing now you planned back then. To get around the problem caused by these delays in neural transmission, your brain is active and constructive in its interactions with the outside world, endlessly anticipating what's going to happen next and planning movements to respond appropriately.

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The story of the brain is a story of embodiment, of how much the brain takes for granted the world we're in and the body that carries it about.

For instance, we assume a certain level of stability in the world. We make assumptions about how our body is able to move within the environment, and if the environment has changed [Hack #62] , we get confused.

As we assume stability in the world, so too do we assume stability from our body. Why should the brain bother remembering the shape of our own body when it's simply there to consult? But when our body's shape doesn't remain stable, the brain can get confused. You start by getting your fingers mixed up when you cross your hands [Hack #63] ; you end up convincing your brain that you're receiving touch sensations from the nearby table [Hack #64] .

This is also a story of how we interact with the world. Our brains continually assess and anticipate the movements we need to grasp objects, judging correctly even when our eyes are fooled [Hack #66] . We're built for activity, our brains perceiving the uses of an object, its affordances [Hack #67] , as soon as we look at it—as soon as we see something, we ready ourselves to use it.

We'll finish on what we use for manipulation: our hands. What makes us right- or left-handed [Hack #68] ? And, while we're on the topic, what does all that left-brain, right-brain stuff really mean [Hack #69] ?

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Your conscious experience of the world and control over your body both feel instantaneous—but they're not.

Lengthy delays in sensory feedback and in the commands that are sent to your muscles mean that what you see now happened a few moments ago and what you're doing now you planned back then. To get around the problem caused by these delays in neural transmission, your brain is active and constructive in its interactions with the outside world, endlessly anticipating what's going to happen next and planning movements to respond appropriately.

Most of the time this works well, but sometimes your brain can anticipate inappropriately, and the mismatch between what your brain thought was going to happen and what it actually encounters can lead to some strange sensations.

One such sensation can be felt when you walk onto a broken escalator. You know it's broken but your brain's autopilot takes over regardless, inappropriately adjusting your posture and gait as if the escalator were moving. This has been dubbed the broken escalator phenomenon.1 Normally, the sensory consequences of these postural adjustments are canceled out by the escalator's motion, but when it's broken, they lead to some self-induced sensations that your brain simply wasn't expecting. Your brain normally cancels out the sensory consequences of its own actions [Hack #65] , so it feels really weird when that doesn't happen.

To try it out yourself, the best place to look is somewhere like the London Underground (where you're sure to find plenty of broken escalators) or your favorite run-down mall. You need an escalator that is broken and not moving but that you're still allowed to walk up. You could also use the moving walkways they have at airports; again, you need one that's stationary but that you're still permitted to walk onto. Now, try not to think about it too much and just go ahead and walk on up the escalator. You should find that you experience an odd sensation as you take your first step or two onto the escalator. People often report feeling as though they've been "sucked" onto the escalator. You might even lose your balance for a moment. If you keep trying it, the effect usually diminishes quite quickly.

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How do we keep the sensations on our skin up to date as we move our bodies around in space?

When an insect lands on your skin, receptors in that area of skin fire and a signal travels up to your brain. The identity of the receptor indicates which part of your skin has been touched. But how do you know exactly where that bit of your body is so you can swat the fly? As we move our bodies around in space we have to remap and take account of our changes in posture to understand the sensations arriving at our skin; very different movements are required to scratch your knee depending on whether you're sitting down or standing up. This might seem like a trivial problem, but it is more complex than it seems at first. We have to integrate information from our joints and muscles about the current position of our body—proprioceptive information—as well as touch and vision, for example, to gauge that the sight of a fly landing and the sensation of it contacting your finger are coming from the same place.

Try closing your eyes and feeling an object on a table in front of you with the fingers of both hands. Now, cross your hands and return your fingers to the object. Despite swapping the point of contact between your two hands, you do not feel that the object has flipped around. The next two illusions attempt to make this remapping fail.

First, try crossing your index finger and middle finger and run the gap between them along the ridge and around the tip of your nose (make sure you do this quite slowly). You will probably feel as if you have two noses. This is because your brain has failed to take account of the fact that you have crossed your fingers. Notice that you are unable to overcome this illusion even if you consciously try to do so. This is sometimes called Aristotle's Illusion, as he was apparently the first person to record it.

Now, try out the crossed hands illusion. You'll need a friend to help. Cross your hands over in front of your chest, at arm's length. Then turn your palms inward, so your thumbs point downward and clasp your hands together, so your fingers are interleaved. Next, rotate your hands up toward your chest, until your thumbs are pointing away from you, as shown in Figure 6-1. Now, if a friend points to one of your fingers and asks you to move it, you will probably fail to move the correct finger and instead move the same finger but on the opposite hand. Again, you have failed to take account of your unusual posture; you assume that the finger you see corresponds to the finger that would be in that position if you had simply clasped your hands, without crossing them over. You may find that you are able to overcome the illusion if your friend indicates which finger he wants you to move by touching it. This can help you to remap and take your posture into account.

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Your body image is mutable within only a few minutes of judicious—and misleading—visual feedback.

Our brains are constantly updated with information about the position of our bodies. Rather than relying entirely on one form of sensory feedback, our bodies use both visual and tactile feedback in concert to allow us to work out where our limbs are likely to be at any one moment. Proprioception—generated by sensory receptors located in our joints and muscles that feed back information on muscle stretch and joint position—is another sense that is specifically concerned with body position.

The brain combines all this information to provide a unified impression of body position and shape known as the body schema. Nevertheless, by supplying conflicting sensory feedback during movement, we can confuse our body schema and break apart the unified impression.

Find a mirror big enough so you can stand it on its edge, perpendicular to your body, with the mirrored side facing left. Put your arms at your sides (you'll probably need a friend to hold the mirror). This whole setup is shown in Figure 6-2. Look sideways into the mirror so you can see both your left hand and its reflection in the mirror, so that it appears at first blush to be your hidden right hand. While keeping your wrists still and looking into the mirror, waggle your fingers and move both your hands in synchrony for about 30 seconds. After 30 seconds, keep your left hand moving but stop your right. You should sense a momentary feeling of "strangeness," as if disconnected from your right hand. It looks as if it is moving yet feels as if it has stopped.

Figure 6-2: Matt confuses his body schema using a mirror and curtain rail (being in dire need of a haircut isn't essential for the experiment)

One easy way of moving your hands together is to run a curtain rail under the mirror, if you have one handy, and place each hand on a curtain ring (this is what I'm doing in Figure 6-2). Move your hands toward and away from the mirror for 30 seconds, until your brain has confused your right hand and your reflected left hand in the mirror—then release the curtain ring from your right hand. You can feel the ring has gone, but in the mirror it looks as though you're still holding it. To me, the disconnect felt like pins and needles, all through my right hand.

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Experiments with tickling provide hints as to how the brain registers self-generated and externally generated sensations.

Most of us can identify a ticklish area on our body that, when touched by someone else, makes us laugh. Even chimpanzees, when tickled under their arms, respond with a sound equivalent to laughter; rats, too, squeal with pleasure when tickled. Tickling is a curious phenomenon, a sensation we surrender to almost like a reflex. Francis Bacon in 1677 commented that "[when tickled] men even in a grieved state of mind . . . cannot sometimes forebear laughing." It can generate both pleasure and pain: a person being tickled might simultaneously laugh hysterically and writhe in agony. Indeed, in Roman times, continuous tickling of the feet was used as a method of torture. Charles Darwin, however, theorized that tickling is an important part of social and sexual bonding. He also noted that for tickling to be effective in making us laugh, the person doing the tickling should be someone we are familiar with, but that there should also be an element of unpredictability.

As psychoanalyst Adam Phillips commented, tickling "cannot be reproduced in the absence of another." So, for tickling to induce its effect, there needs to be both a tickler and a ticklee. Here are a couple of experiments to try in the privacy of your own home—you'll need a friend, however, to play along.

First, you can look at why there's a difference between being tickled by yourself and by someone else.

Section 6.5.1.1: In action

Try tickling yourself on the palm of your hand and notice how it feels. It might feel a little ticklish. Now, ask a friend to tickle you in the same place and note the difference. This time, it tickles much more.

Section 6.5.1.2: How it works

When you experience a sensation or generate an action, how do you know whether it was you or someone else who caused it? After all, there is no special signal from the skin receptors to tell you that it was generated by you or by something in the environment. The sensors in your arm cannot tell who's stimulating them. The brain solves this problem using a prediction system called a

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When it comes to visual processing in the brain, it's all about job delegation. We've got one pathway for consciously perceiving the world—recognizing what's what—and another for getting involved—using our bodies to interact with the world out there.

The most basic aspects of the visual world are processed altogether at the back of your brain. After that, however, the same visual information is used for different purposes by two separate pathways. One pathway flows forward from the back of your brain to the inferior temporal cortex near your ears, where memories are stored about what things are. The other pathway flows forward and upward toward the crown of your head, to the posterior parietal cortex, where your mental models of the outside world reside. Crudely speaking, the first pathway (the "ventral" pathway) is for recognizing things and consciously perceiving them, whereas the second (the "dorsal" pathway) is for interacting with them. (Well, that's according to the dual-stream theory of visual processing [Hack #13] .)

The idea was developed by David Milner and Melvyn Goodale in the 1990s, inspired in part by observation of neurological patients with damage to one pathway but not the other. Patients with damage to the temporal lobe often have difficulty recognizing things—a toothbrush, say—but when asked to interact with the brush they have no problems. In contrast, patients with damage to the parietal lobe show the opposite pattern; they often have no trouble recognizing an object but are unable to reach out and grasp it appropriately.

Since then, psychologists have found behavioral evidence for this separation of function in people without neurological problems, using visual illusions.

In the mid-'90s, Salvatore Aglioti1 and colleagues showed that when people are presented with the Ebbinghaus illusion (see Figure 6-6) they find the disk surrounded by smaller circles seems larger than an identically sized disk surrounded by larger circles, and yet, when they reach for the central disks, they use the same, appropriate, finger-thumb grip shape for both disks. The brain's conscious perceptual system (the ventral pathway) appears to have been tricked by the visual illusion, whereas the brain's visuomotor (hand-eye) system (the dorsal pathway) appears immune.

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When we see objects, they automatically trigger the movements we'd make to use them.

How do we understand and act upon objects around us? We might perceive the shape and colors of a cup of coffee, recognize what it is, and then decide that the most appropriate movement would be to lift it by the handle toward our mouth. However, there seems to be something rather more direct and automatic going on. In the 1960s, James Gibson developed the idea of object affordances. Objects appear to be associated with (or afford) a particular action or actions, and the mere sight of such an object is sufficient to trigger that movement in our mind. There are obvious advantages to such a system: it could allow us to respond quickly and appropriately to objects around us, without having to go to the bother of consciously recognizing (or thinking about) them. In other words, there is a direct link between perceiving an object and acting upon it. I don't just see my cup of coffee; it also demands to be picked up and drunk.

You may not believe me yet, but I'm sure you can think of a time when your movements appeared to be automatically captured by something in your environment. Have you ever seen a door handle with a "Push" sign clearly displayed above it, yet found yourself automatically pulling the door toward you? The shape of the pullable handle suggests that you should pull it, despite the contradictory instruction to push it. I go through such a door several times a week and still find myself making that same mistake!

Try finding such a door near where you live or work. Sit down and watch how people interact with it. What happens if you cover up the "Push" sign with a blank piece of paper? Or cover it with a piece of paper labeled "Pull"; does this appear to affect how often people pull rather than push, or is the shape of the handle all they're really paying attention to?

Perhaps you've found yourself picking up a cup or glass from the table in front of you, even though you didn't mean to (or even knowing that it belonged to someone else)?

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We all have a hand preference when undertaking manual tasks. But why is this so? And do you always prefer the same hand, or does it vary with what you are doing? Does the way people vary their hand preference differ between right- and left-handers?

The world is a right-handed one, as will be obvious to left-handers. Most tools are made for right-handed people. Implements such as scissors, knives, coffee pots, and so on are all constructed for the right-handed majority. In consequence, the accident rate for left-handers is higher than for right—and not just in tool use; the rate of traffic fatalities among left-handers is also greater than for right.¹

The word "sinister," which now means "ill-omened," originally meant "left-handed." The corresponding word for "right-handed" is "dexter," from which we get the word "dexterous."
—T.S.

Nine out of 10 people are right-handed.² The proportion appears to have been stable over thousands of years and across all cultures in which handedness has been examined. Anthropologists have been able to determine the incidence of handedness in ancient cultures by examining artifacts, such as the shape of flint axes. Based on evidence like this and other evidence such as writing about handedness in antiquity, our species appears always to have been a predominantly right-handed one.

But even right-handers vary in just how right-handed they are, and this variation may have a link to how you use the different sides of your brain [Hack #69] .

Have a go at the following tests to determine which is your dominant hand and just how dominant it is. Do each test twice—once with each hand—and record your score, in seconds, both times. You don't have to do all of them; just see which you can do given the equipment you have on hand.

Darts: Throw three darts at a dartboard. (Be very careful when doing this with your off-hand!) Add up the distances from the bull's-eye.

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The logical left brain and intuitive right brain metaphor is popular, but the real story of the difference between the two halves of your brain is more complex and more interesting.

There's a grain of truth in all the best myths, and this is true for the left-brain/right-brain myth. Our cortex is divided into left and right hemispheres, and they do seem to process information differently, but exactly how they do this isn't like the story normally told by management gurus and the self-help literature. As with many scientific myths, the real story is less intuitive but more interesting.

Our brains follow the general pattern of the rest of our bodies: two of everything down the sides and one of everything down the middle. With the brain, the two halves are joined directly in the subcortex, but in the cortex the two halves, called hemispheres, have a gap between them. They are connected by a tight bunch of some 250 million nerve fibers, called the corpus callosum, which runs between the two hemispheres (it's not the only way for information to cross the hemispheres, but it's the most important).

Each hemisphere is wired up to sense and act on the opposite side of the body. So information from your right goes to the left side of the visual cortex, and signals from your left motor cortex control your right hand. For higher functions, in which information from both senses is combined, the two hemispheres seem to have different strengths and weaknesses, so that for certain tasks one hemisphere or the other will be dominant.

The origins of the popular myth were studies of patients who had their corpus callosum severed as part of a radical surgical intervention for epilepsy. These "split-brain" patients could function seemingly normally on many tasks, but displayed some quirks when asked to respond to the same material with different hands or when speaking (left brain) rather than pointing with their left hand (right brain).

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We consider ourselves pretty rational animals, and we can indeed be pretty logical when we put our minds to it. But you only have to scratch the surface to find out how easily we're misled by numbers [Hack #70] , and it's well-known that statistics are really hard to understand [Hack #71] . So how good are we at being rational? It depends: our logic skills aren't too hot, for instance, until we need to catch people who might be cheating on us [Hack #72] instead of just logically solving sums. And that's the point. We have a very pragmatic kind of rationality, solving complex problems as long as they're real-life situations.

Pure rationality is overrated anyway. Figuring out logic is slow going when we can have gut feelings instead, and that's a strategy that works. Well, the placebo effect [Hack #73] works at least—belief is indeed a powerful thing. And we have a strong bias toward keeping the status quo [Hack #74] too. It's not rational, that's for sure, but don't worry; the "If it ain't broke, don't fix it" policy is a pragmatic one, at least.

Our brains haven't evolved to think about numbers. Funny things happen to them as they go into our heads.

Although we can instantly appreciate how many items comprise small groups (small meaning four or fewer [Hack #35] ), reasoning about bigger numbers requires counting, and counting requires training. Some cultures get by with no specific numbers higher than 3, and even numerate cultures took a while to invent something as fundamental as zero.¹

So we don't have a natural faculty to deal with numbers explicitly; that's a cultural invention that's hitched onto natural faculties we do have. The difficulty we have when thinking about numbers is most apparent when you ask people to deal with very large numbers, with very small numbers, or with probabilities [Hack #71] .

This hack shows where some specific difficulties with numbers come from and gives you some tests you can try on yourself or your friends to demonstrate them.

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Inhaltsvorschau

We consider ourselves pretty rational animals, and we can indeed be pretty logical when we put our minds to it. But you only have to scratch the surface to find out how easily we're misled by numbers [Hack #70] , and it's well-known that statistics are really hard to understand [Hack #71] . So how good are we at being rational? It depends: our logic skills aren't too hot, for instance, until we need to catch people who might be cheating on us [Hack #72] instead of just logically solving sums. And that's the point. We have a very pragmatic kind of rationality, solving complex problems as long as they're real-life situations.

Pure rationality is overrated anyway. Figuring out logic is slow going when we can have gut feelings instead, and that's a strategy that works. Well, the placebo effect [Hack #73] works at least—belief is indeed a powerful thing. And we have a strong bias toward keeping the status quo [Hack #74] too. It's not rational, that's for sure, but don't worry; the "If it ain't broke, don't fix it" policy is a pragmatic one, at least.

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Inhaltsvorschau

Our brains haven't evolved to think about numbers. Funny things happen to them as they go into our heads.

Although we can instantly appreciate how many items comprise small groups (small meaning four or fewer [Hack #35] ), reasoning about bigger numbers requires counting, and counting requires training. Some cultures get by with no specific numbers higher than 3, and even numerate cultures took a while to invent something as fundamental as zero.¹

So we don't have a natural faculty to deal with numbers explicitly; that's a cultural invention that's hitched onto natural faculties we do have. The difficulty we have when thinking about numbers is most apparent when you ask people to deal with very large numbers, with very small numbers, or with probabilities [Hack #71] .

This hack shows where some specific difficulties with numbers come from and gives you some tests you can try on yourself or your friends to demonstrate them.

The biases discussed here and, in some of the other hacks in this chapter, don't affect everyone all the time. Think of them as forces, like gravity or tides. All things being equal, they will tend to push and pull your judgments, especially if you aren't giving your full attention to what you are thinking about.

How big is:

9 x 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1

How about:

1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 x 9

Since you've got both in front of you, you can easily see that they are equivalent and so must therefore equal the same number. But try this: ask someone the first version. Tell her to estimate, not to calculate—have her give her answer within 5 seconds. Now find another person and ask him to estimate the answer for the second version. Even if he sees the pattern and thinks to himself "ah, 9 factorial," unless he has the answer stored in his head, he will be influenced by the way the sum is presented.

Probably the second person you asked gave a smaller answer, and both people gave figures well below the real answer (which is a surprisingly large 362,880).

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Probability statistics are particularly hard to think about correctly. Fortunately you can make it easier by presenting the same information in a way that meshes with our evolved capacity to reason about how often things happen.

Mark Twain once said, "People commonly use statistics like a drunk uses a lamppost: for support rather than for illumination."¹ Things haven't changed. It's strange, really, given how little people trust them, that statistics get used so much.

Our ability to think about probabilities evolved to keep us safe from rare events that would be pretty serious if they did happen (like getting eaten) and to help us learn to make near-correct estimates about things that aren't quite so dire and at which we get multiple attempts (like estimating the chances of finding food in a particular part of the valley for example). So it's not surprising that, when it comes to formal reasoning about single-case probabilities, our evolved ability to estimate likelihood tends to fail us.

One example is that we overestimate low-frequency events that are easily noticed. Just ask someone if he gets more scared traveling in a car or by airplane. Flying is about the safest form of transport there is, whether you calculate it by miles flown or trips made. Driving is pretty risky in comparison, but most people would say that flying feels like the more dangerous of the two.

Another thing we have a hard time doing is accounting for the basic frequency at which an event occurs, quite aside from the specific circumstances of its occurrence on the current occasion. Let me give an example of this in action . . .

This is a famous demonstration of how hard we find it to work out probabilities. When it was published in Parade magazine in 1990, the magazine got around 10,000 letters in response—92% of which said that their columnist, Marilyn vos Savant, had reached the wrong conclusion.² Despite the weight of correspondence, vos Savant

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Our sense of logic is much better when applied to social situations than used in abstract scenarios.

Despite the old saying that we're ruled by our emotions, it's tempting to believe that we have at least some intuitive sense of logic. The various forms of logic such as syllogisms and deductive and inductive reasoning¹ seem so simple and fundamental that you might expect that the rules are hardwired into our brains. After all, since we're constantly told that our neurons are the equivalent of computer processors, shouldn't our brains be able to handle a little bit of logic?

See how you do on these logical puzzles.

Each of the cards in Figure 7-1 has a letter on one side and a number on the reverse. If I told you there was a rule stating that a card with a vowel on one side must have an even number on the reverse, which of these cards would you need to turn over to prove or disprove this rule?

Figure 7-1: Each card has a letter on one side and a number on the reverse

Give it a whirl before reading on.

Many people turn over A and 2—but that's not quite right. While turning over A will tell you whether "one side" of the rule is true (if vowel, then even number), turning over 2 won't tell you any more. It doesn't matter whether 2 has a K or an A on its reverse—the rules doesn't specify either being true. Along with A, the other card you need to turn over is 7. If 7 has an A on its reverse, then the rule is disproved no matter what the A has on its reverse. You need to turn over A and 7.

Very few people solve this riddle on the first try. It shows that humans do not possess an innate set of abstract logic rules. Yet somehow we manage to get by without those rules. Try this similar puzzle, in Figure 7-2.

Figure 7-2: Four people sit at a bar drinking beer or cola, the cards show age on one side and beverage on the other—who's breaking the rules?

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Many of the unpleasant phenomena associated with injury and infection are in fact produced by the brain to protect the body. Medical assistance shifts the burden of protection from self to other, which allows the brain to reduce its self-imposed unpleasantness.

Injury or infection triggers a coordinated suite of physiological responses involving the brain, hormones, and immune system. The brain generates pain and fever, stress hormones mobilize energy from fat, and immune cells cause local swelling and redness. These processes are collectively known as the acute phase response because they occur rapidly and tend to subside after a few days. Medical assistance can help these unpleasant signs and symptoms to subside more quickly, even when that assistance is completely bogus—such as a witch doctor waving a rattle at you or a quack prescribing a sugar pill. This is known as the placebo effect.

It's hard to invent a placebo and try it on yourself, because the effect relies crucially on the sincerely held belief that it will work. Several experiments have shown that pure placebos such as fake ultrasound produce no pain relief when they are self-administered. So unless you can fool yourself that other people are caring for you when they are not, your experiments with placebos will have to involve other people.

Moreover, you will also probably have to lie. The placebo effect depends not just on other people, but also on the belief that those people are providing bona fide medical assistance. If you don't believe that the assistance provided by those around you is going to help you recover, you won't experience a placebo effect.

Sometimes a placebo effect seems to be triggered despite the absence of other people and the absence of deception. If you have ever felt better after taking a homeopathic remedy, for example, or after applying dock leaves to the pain caused by a stinging nettle, that was almost certainly a placebo effect, because it has been scientifically proven that such treatments are completely bogus. The essential factor, however, must still be present—a belief that this kind of treatment will help. Once you discover the truth about such bogus treatments, therefore, they cease to be capable of producing placebo effects.

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People don't like change. If you really want people to try something new, you should just coerce them into giving it a go and chuck the idea of persuading them straight off.

By default, people side with what already is and what happened last time. We're curious, as animals go, but even humans are innately conservative. Like the Dice Man, who delegates all decisions to chance in Luke Rhinehart's classic 1970s novel of the same name, was told: "It's the way a man chooses to limit himself that determines his character. A man without habits, consistency, redundancy—and hence boredom—is not human. He's insane."¹

In this hack we're going to look at our preference for the way things are and where this tendency comes from. I'm not claiming that people don't change—obviously this happens all the time and is the most interesting part of life—but, in general, people are consistent and tend toward consistency. Statistically, if you want to predict what people will do in a familiar situation, the most useful thing you can measure is what they did last time. Past action correlates more strongly with their behavior than every other variable psychologists have tried to measure.² If you're interested in predicting who people will vote for, what they will buy, what kind of person they will sleep with, anything at all really, finding out what tendencies they've exhibited or what habits they've formed before is the most useful information at your disposal. You're not after what they say they will do—not what party, brand, or sexual allegiance they tick on a form—nor the choice they think they're feeling pressured into making. Check out what they actually did last time and base your prediction on that. You won't always be right, but you will be right more often by basing your guess upon habit than upon any other single variable.

This bias is the result of a number of factors, not least the fact that people's previous choice is often the best one or the one that best reflects their character. But also we have mental biases,3 like the mental biases we have about numbers

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What makes "this" a word, rather than being simply the adjacently written letters t, h, i, s? Or, to ask a similar question, why should we see a single dog running across a field rather than a collection of legs, ears, hair, and a wet nose flying over the grass? And why, when the dog knocks us over, do we know to blame the dog?

To put these questions another way: how do we group sensations into whole objects, and how do we decide that a certain set of perceptions constitutes cause and effect?

It's not a terribly easy problem to solve. The nature of causality isn't transmitted in an easy-to-sense form like color is in light. Rather than sense it directly, we have to gues. We have built-in heuristics to do just that, and these heuristics are based on various forms of togetherness. The word "this" hangs together well because the letters are in a straight line, for example, and they're closer to one another than the letters in the surrounding words. Those are both principles by which the brain performs grouping. To take the second question, we see the parts of the dog as a single animal because they move together. That's another heuristic.

This recognition acuity lets us see human forms from the tiniest of clues, but it also—as we'll see in [Hack #77] —is not perfect and can be duped. We'll see how we can perceive animacy—the aliveness shown by living creatures—where none exists and how we can ignore the cause in cause and effect. Sometimes that's the best way to find out what our assumptions really are, to see when they don't quite match what's happening in the real world.

We group our visual perceptions together according to the gestalt grouping principles. Knowing these can help your visual information design to sit well with people's expectations.

It's a given that we see the world not as isolated parts, but as groups and single objects. Instead of seeing fingers and a palm, we see a hand. We see a wall as a unit rather than seeing the individual bricks. We naturally group things together, trying to make a coherent picture out of all the individual parts. A few fundamental grouping principles can be used to do most of the work, and knowing them will help you design well-organized, visual information yourself.

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Inhaltsvorschau

What makes "this" a word, rather than being simply the adjacently written letters t, h, i, s? Or, to ask a similar question, why should we see a single dog running across a field rather than a collection of legs, ears, hair, and a wet nose flying over the grass? And why, when the dog knocks us over, do we know to blame the dog?

To put these questions another way: how do we group sensations into whole objects, and how do we decide that a certain set of perceptions constitutes cause and effect?

It's not a terribly easy problem to solve. The nature of causality isn't transmitted in an easy-to-sense form like color is in light. Rather than sense it directly, we have to gues. We have built-in heuristics to do just that, and these heuristics are based on various forms of togetherness. The word "this" hangs together well because the letters are in a straight line, for example, and they're closer to one another than the letters in the surrounding words. Those are both principles by which the brain performs grouping. To take the second question, we see the parts of the dog as a single animal because they move together. That's another heuristic.

This recognition acuity lets us see human forms from the tiniest of clues, but it also—as we'll see in [Hack #77] —is not perfect and can be duped. We'll see how we can perceive animacy—the aliveness shown by living creatures—where none exists and how we can ignore the cause in cause and effect. Sometimes that's the best way to find out what our assumptions really are, to see when they don't quite match what's happening in the real world.

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Inhaltsvorschau

We group our visual perceptions together according to the gestalt grouping principles. Knowing these can help your visual information design to sit well with people's expectations.

It's a given that we see the world not as isolated parts, but as groups and single objects. Instead of seeing fingers and a palm, we see a hand. We see a wall as a unit rather than seeing the individual bricks. We naturally group things together, trying to make a coherent picture out of all the individual parts. A few fundamental grouping principles can be used to do most of the work, and knowing them will help you design well-organized, visual information yourself.

Automatic grouping is such second nature that we really notice only its absence. When the arrangement of parts doesn't sit well with the grouping principles the brain uses, cracks can be seen. Figure 8-1 shows some of these organizational rules coming into play.¹

Figure 8-1: Two groups of triangles that point different ways and a middle triangle that can appear to point either way, depending on which group you see it being part of²

You don't see 17 triangles. Instead, you see two groups of eight and one triangle in the middle. Your similarity drive has formed the arrangement into rows and columns of the shapes and put them into two groups: one group points to the bottom left, the other points off to the right.

Each group belongs together partly because the triangles are arranged into a pattern (two long rows pointing in a direction) and partly because of proximity (shapes that are closer together are more likely to form a group). The triangle in the middle is a long way from both groups and doesn't fall into the same pattern as either. It's left alone by the brain's grouping principles.

You can, however, voluntarily group the lone triangle. By mentally putting it with the left-hand set, it appears to point down and left along with the other triangles. You can make it point right by choosing to see it with the other set.

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We tend to group together things that happen at the same time or move in the same way. It's poor logic but a great hack for spotting patterns.

It's a confusing, noisy world out there. It's easier to understand the world if we perceive a set of objects rather than just a raw mass of sensations, and one way to do this is to group together perceptions that appear to have the same cause. The underlying assumptions involved manifest as the gestalt grouping principles, a set of heuristics used by the brain to lump things together (see [Hack #75] for the simplest of these, used for vision).

Perhaps the most powerful of these assumptions is termed common fate. We group together events that occur at the same time, change in the same way, or move in the same direction. Imagine if you saw, from far off, two points of light that looked a bit like eyes in the dark. You might think they were eyes or you could just put it down to a coincidence of two unrelated lights. But if the points of light moved at the same time, in the same direction, bounced with the characteristic bounce of a person walking, you'd know they were eyes. Using behavior over time allows you to stringently test spatial data for possible common cause. If the bouncing lights pass the common fate test, they're almost certainly a single object. Visual system tags this certainty by providing you with a correspondingly strong perceptual experience; if some things move together, it is almost impossible to see them as separate items instead of a coherent whole.

"Illusion—Motion Capture—Grouping" (http://psy.ucsd.edu/chip/illu_mot_capt_grpng.html; a Real video requiring Real Player) demonstrates just how completely your perception of a single item is altered by global context and common fate. Watch the video for at least 30 seconds. At first you see just a dot blinking on and off next to a square. But then other dots are added in the surrounding area, and as the first dot blinks off, they all shift right. Now your unavoidable impression is of the first dot moving behind the square. The appearance of the other dots, and their behavior, gives your visual system correlations that are just too strong to ignore. The single dot is still blinking on and off—you just can't see it like that any more.

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Lights on the joints of a walking person are enough to give a vivid impression of the person, carrying information on mood, gender, and other details—but only while the person keeps moving.

Visual perception has special routines for grouping things that move along together into single objects [Hack #76] . That's why we see cars as cars and not a collection of wheels, glass, and side-view mirrors just happening to travel along in the same direction. That's all well and good, but humans live not just in a world of objects like trees and cars, but a world full of people. Given how social we are, and how tricky other people can be, it's not surprising we also have specialized routines for grouping things that move like people together into single objects too. Looking at only a constellation of moving points of light attached to knees, elbows, and other parts of the body, we a get vivid perception of a person, a perception that doesn't exist at all when the points of light are still.

Open up your browser and point it at http://www.lifesci.sussex.ac.uk/home/George_Mather/Motion/BM.HTML ¹ or http://www.at-bristol.org.uk/Optical/DancingLights_main.htm (both are QuickTime movies). What do you see?

Both are just points of light moving in two dimensions. Yet the first is clearly a person walking, and the second obviously two people dancing, fighting, and otherwise performing.

As with the common fate demos [Hack #76] of how we group objects by their behavior over time, you can remove the effect by pausing the movies. This information only makes sense when it is moving (shame we can't have animations in the book, really), which is why Figure 8-4 (a frame of the first movie) looks more like a random star constellation than a human figure.

Figure 8-4: If this were moving, it'd look like a person walking

The vivid impression of a walking human shows that we are able to integrate the correlations of the light points and match them to some kind of template we have developed for moving humans. It is orientation-specific, by the way. Watch the video upside down (it's easier if you have a laptop), and you won't see anything resembling human motion at all.

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Add a few tweaks to the way a thing moves, and you can make objects seem as if they have a life of their own.

Sometimes, when there isn't evidence of causation, your perceptual system detects self-causation and delivers up an impression of animacy—that quality of having active purpose that makes objects seem alive.

Animacy is simultaneously easy to see but hard to think about, and both for the same reason. We have evolved to live in a world of animals and objects. But living things are more difficult and more dangerous than objects, so our minds are biased in lots of ways to detect agency—things happening because someone or something wanted them to happen for a purpose (better to assume something happened for a reason than to ignore it completely, right?). This specialization for making sense of agency means we're disposed to detect it even if it isn't strictly there—it is natural for us to use the language of intentions to describe events when there are no intentions. If you say that water "wants" to find the quickest way down the mountain, people understand you far easier than if you start talking about energy minimization, even though the water doesn't strictly "want" anything. It's natural to feel as if your computer hates you, just as it is natural to feel that people are deliberately making things hard for you,¹ when the sad fact is that most people probably aren't spending too much time thinking about you at all, and your computer certainly isn't thinking about you.

We can take advantage of our disposition to detect agency in objects, making them appear to be alive by adding just a few simple characteristics to the way they move.

One way of showing that something is pretty psychologically fundamental is to show that children do it. As soon as children can see, they expect to find animate objects in their environment and prefer to watch them than simple moving objects.² So we'll show how fundamental it is to perceive animate objects by showing some movement to a young kid and seeing how he interprets it.

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By following a couple of simple rules, you can show a clear pattern of cause and effect, and ensure your viewer is able to make the connection between separate things happening at the same time.

Research suggests that just as the visual system works to recover the physical structure of the world by inferring properties such as 3-D shape, so too does it work to recover the causal and social structure of the world by inferring properties such as causality and animacy.¹

Perception is finding structure in sensations. Finding a structure to things lets you hold them in mind and store them in a memory-efficient way. If the structure corresponds to reality, it can also be used to provide predictions about the thing you're representing. So it's easier to think of several sections of cable on your desk as all being part of the same mouse lead, and once you've assumed that it's easy to find the mouse, you just follow the cable away from the stack.

We've already seen that the brain looks for structure in space [Hack #75] and structure in time [Hack #76] to organize perceptions. These principles apply to the basic perception of physical objects, as well as helping us understand how we make sense of our body images [Hack #64] and the bodies of other people [Hack #77] .

But our visual system doesn't look for just static physical structures—it can also pick up on causal relationships between things. You don't see two things happening but rather one event: you don't stop to wonder why the plate smashed just at the same moment that it hit the floor.

This ability to detect causation and animacy [Hack #78] is a perceptual phenomenon, different from our slow deliberate reasoning about what causes what ("Hmm...why does my computer crash only after I have written at least 2000 words without saving?" is a different kind of nonperceptual, causal reasoning).

When our visual perception picks up on causes it does so quickly and without any conscious effort on our part. Like with many visual illusions, it happens without your consent and without any ability on your part to stop it, even if you wanted to and know that it is illusion.

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How do we experience our actions as self-caused? It's not automatic; in fact, the feeling of consciousness may indeed have been added to our perception of our actions after our brains had already made the decision to act.

Place your hand on the table. Look at it as an object, not unlike just about anything else on the table. Now, raise one of your fingers. Why did you raise that one? Can you say? Was it a free choice? Or was the decision made somewhere else, somewhere in your brain you don't have access to? You experienced your finger being raised by you, but what was it in you that caused it?

If you record EEG readings [Hack #2] from the scalps of people just about to decide to raise their fingers and at the same time make them watch a timer and remember at what time they experienced deciding to raise their finger, they're found to report that the experience of deciding to raise their finger comes around 400 ms after the EEG shows that their brain began to prepare to raise their finger.1 Stimulating particular parts of the brain using transcranial magnetic stimulation [Hack #5] , you can influence which finger people choose to move,² yet they still experience their choice as somehow willed by them, somehow "theirs."

This is an example of how an action we feel we own may be influenced by things outside of our conscious deliberation. The feeling of conscious will isn't always a good indication that we consciously willed something. And the reverse can also be true. We can disown actions we are responsible for, doing things we don't feel are caused by our own will.

Draw a cross on a piece of paper. Next, make a pendulum out of something light: a button and a length of string is ideal. Now hold the pendulum over the cross and ask a question ("Is the button on this pendulum blue?" or "Is it lunchtime yet?" perhaps). Know that to indicate "yes" the pendulum will swing clockwise, and to answer "no" the pendulum will swing counterclockwise. Don't rest your arm or elbow on anything as it holds the pendulum. Just watch the pendulum as it begins to swing to answer to your question.

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The idea of priming comes up more than once in this book. Given a single concept being activated in the brain, other associated concepts are quietly activated too, ready to impinge on consciousness or experience. Automatic associations lie behind the Stroop Effect [Hack #55] , and the measurement of a type of priming is how we know that we unconsciously ready ourselves to make use of an object, just by laying eyes on it [Hack #67] .

We dive into priming [Hack #81] in the first hack of this chapter, and from there, we'll see it manifested as subliminal perception [Hack #82] and implicated in the creation of false memory. For memory is the main topic here. We'll look at how false memories and familiarity come about [Hack#83] , [Hack#84] and [Hack #85] , by using priming to activate concepts that have not been directly experienced.

We'll also look at how to build strong, true memories too, in the form of learning. Learning implicitly involves context, the situation you're in while you're doing the learning (that's another appearance of the associative nature of the mind). Exploiting this feature can help you learn better to begin with [Hack #86] and improve your recall skills in the future [Hack #87] . There's even a nifty trick on how to improve your memory using your built-in navigational skills too [Hack #89] .

Along the way, we'll take in a grab bag of hacks on the reality of imagination. Such as how thinking about your muscles can make them stronger [Hack #88] , or at least improve your control of them. Such as why you live your life from behind your eyes, but often remember it like a movie, in the third person [Hack #90] . And why you should fall asleep on the train to let your imagination run riot [Hack #91] .

Last, but—particularly in the hacker crowd—certainly not least: caffeine. Why do people get so upset if you make their coffee the wrong way, and what's that got to do with learning anyway? Understand this, and make the caffeine habit taste good

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The idea of priming comes up more than once in this book. Given a single concept being activated in the brain, other associated concepts are quietly activated too, ready to impinge on consciousness or experience. Automatic associations lie behind the Stroop Effect [Hack #55] , and the measurement of a type of priming is how we know that we unconsciously ready ourselves to make use of an object, just by laying eyes on it [Hack #67] .

We dive into priming [Hack #81] in the first hack of this chapter, and from there, we'll see it manifested as subliminal perception [Hack #82] and implicated in the creation of false memory. For memory is the main topic here. We'll look at how false memories and familiarity come about [Hack#83] , [Hack#84] and [Hack #85] , by using priming to activate concepts that have not been directly experienced.

We'll also look at how to build strong, true memories too, in the form of learning. Learning implicitly involves context, the situation you're in while you're doing the learning (that's another appearance of the associative nature of the mind). Exploiting this feature can help you learn better to begin with [Hack #86] and improve your recall skills in the future [Hack #87] . There's even a nifty trick on how to improve your memory using your built-in navigational skills too [Hack #89] .

Along the way, we'll take in a grab bag of hacks on the reality of imagination. Such as how thinking about your muscles can make them stronger [Hack #88] , or at least improve your control of them. Such as why you live your life from behind your eyes, but often remember it like a movie, in the third person [Hack #90] . And why you should fall asleep on the train to let your imagination run riot [Hack #91] .

Last, but—particularly in the hacker crowd—certainly not least: caffeine. Why do people get so upset if you make their coffee the wrong way, and what's that got to do with learning anyway? Understand this, and make the caffeine habit taste good

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Just because you're not thinking of something doesn't mean it isn't there just waiting to pop into your mind. How recently you last thought of it, and whether you've thought of anything related to it, affects how close to the surface an idea is.

Things aren't just in your thoughts or out of them. It seems as if some things are nearer the surface while others are completely in the dark, tucked deep down in your mind.

The things near the surface jump out into the light without much prompting; they connect to other things you're thinking about, volunteer themselves for active duty in your cognitive processes, so to speak. This isn't always a good thing, as anyone who has tried to put an upcoming exam or interview out of mind will attest.

So what affects how deeply submerged mental items are? It probably wouldn't surprise you to hear that how recently something was last used is one of the key variables. Association is another factor: activating a mental item brings related items closer to the surface. Not always right to the surface, into conscious awareness, but closer at least, so that if you later reach for the general concept of the related item, the specific one will be more easily at hand. Psychologists use measures of the pre-preparedness of mental items to get a handle on the limitations of perception and on the associations between different concepts that your mind has absorbed.

We found this amusing when we were at school, so maybe you'll get the best results if you pick one of your more childish friends to try it out. For dramatic effect, claim beforehand—as we used to—that you can read your friend's mind. Then, ask her the following questions in quick succession:

What is 5 + 1?
What is 3 + 3?
What is 2 + 4?
What is 1 + 5?
What is 4 + 2?
What is the first vegetable you can think of?

Most people, most of the time, say "carrot."¹

Here's something similar. Like the carrot game, it works best if you can get the person answering the question to hurry.

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Subliminal perception sneaks underneath the level of consciousness and can influence your preferences—but only a little.

Being exposed to a photograph for two-hundredth of a second can't really be called seeing, because you won't even be consciously aware of it. But having a photo flashed at you like this works it into your subliminal perception and means that next time you see it you'll—very slightly, mind—prefer it to one you've never been exposed to before.

Proving that mere exposure can change your preferences isn't easy to do at home, so it's best to look at the experiments. Robert Bornstein and Paul D'Agostino exposed a group of volunteers to images, either photographs or unfamiliar shapes, and then asked each person to rate the images according to how much he or she liked them.¹

If you were one of those volunteers, you'd have spent 5-10 minutes at the beginning of the experiment being exposed to images for only 5 milliseconds each. That's a tiny amount of time for vision, only as long as a quarter of one frame of television. Exposed to a picture for that long, you're not even aware you've seen it. As a volunteer, you could be shown the picture later to look at, and it's as if you're seeing it for the first time.

When you're asked which images you prefer out of a larger selection, you'll rate images you were exposed to but can't recall seeing higher.

The rating exercise is a little like the game Hot or Not (http://www.hotornot.com) but with some of the photos flashed up at you faster than you can make them out beforehand. In Hot or Not, you see a photo of a person and rate it: 10 being Hot and 1 being Not. The web page then immediately reloads with another photo for you to rate, and you can also see how your score on the previous photo compared to what everyone else said.

All else being equal—all the photos being equally attractive—let's pretend you're rating all the photos 5 on average.

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Hack memory to make people feel they've seen something before.

The memory system is chockablock with hacks. The information that our environment constantly provides exceeds any viable storage capacity, so memory employs a variety of methods that allow it to be choosy. One memory experience we all know is the feeling of familiarity for previously seen things or people. The process beneath it is quick and feels automatic, with an almost perceptual flavor. As we will see, that is not too far from the truth. However, there are hidden layers that contribute to this process, and these can be revealed by the use of a memory illusion.

Try this teasing task, using stimuli from Whittlesea and Williams' 1998 study.1 Or better yet find a volunteer to tax instead. Look at the words in Table 9-1, one at a time (around 2-3 seconds a word), in both columns. Then take a breather for a minute or two.

Table 9-1: Study each word for 2 to 3 seconds each
MACHINE	ISOLATE
DAISY	FRAMBLE
FISSEL	SUBBEN
PNAFTED	STOFWUS
FAMILIAR	VASSIL
COELEPT	DETAIL
HADTACE	GERTPRIS
STATION	MEUNSTAH
PLENDON	HENSION

Now turn to the second list of words, Table 9-6, at the very end of this chapter. Go through the second list and check/tick with a pencil those that feel familiar (if you like, you can put a cross by those you definitely didn't see).

What did you experience? Most people find that while the real words were easy to identify one way or another, certain of the nonwords had a creeping feeling of familiarity. Possibly you checked/ticked some that, in fact, you hadn't seen. If so, your recognition memory has just been royally messed with.

This test is a good way to bring out the heuristic, fast-and-loose nature of recognition memory. When we encounter something we have experienced before, familiarity can hit us extremely rapidly. This feeling need not be accompanied by extensive memory information, which shows it isn't due to deep memory retrieval. Instead, recognition memory seems to be piggybacking on the rapid incoming sensory information to flood us with this sense of "having seen." What qualities of perception might be useful? Well, as seen before, items that have been seen recently are processed faster and more easily

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When memory serves up information upon request, it seems to come packaged with its origin and sender. But these details are often produced ad hoc and may not fully match the true source.

Every memory has a source—or at least it ought to. That said, memories can often float loose from their moorings, making it some achievement that we manage to anchor mnemonic detail to their origins.

This test involves word stems, the idea being to complete the beginning of each stem in Table 9-2 with a word of your choice. So ple___ (complete it with any number of letters) could be "please," or equally "pledge," "pleat," and so on. Complete the odd-numbered stems (the ones on the left) out loud; for the even-numbered ones (on the right), merely imagine saying the words. Use a different word for each stem (i.e., don't use "please" twice if you run across the ple___ stem twice).

Table 9-2: Stem completion task. Think of a word to complete each stem. Speak the ones on the left out loud, but the ones on the right just in your head.
Complete out loud	Imagine completing out loud
1. BRE___
	2. MON___
3. FLA___
	4. TAR___
5. SAL___
	6. FAL___
7. SPE___
	8. BRE___
9. TAR___
	10. SPE___
11. MON___
	12. SAL___

Take a break! This is a memory test, so you need to pause for 1 or 2 minutes before reading on.

Now see if you remember your two fla__words (it should be fairly easy) and whether they were spoken or imagined. You've got a fair chance of being right, although you'd likely make a few slips across the whole list. Try the whole list if you like, giving both items and whether you said them out loud or in your head: bre__, spe__, sal__, tar__, mon__, and spe__. It's probable that you can remember what you said for most words, and usually whether it was spoken or imagined. But while this is not an impossible task, you are in no way guaranteed to get the source of a recalled item correct.

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Here is one way of creating memories of things that you haven't actually experienced.

We've seen how memory's way of orienting us to our surroundings has all the ingredients for a hack [Hack #83] —a fast-and-loose process that is expressed through gut sensation. Here we will see that even more measured and absolute experiences, like recalling an event or information, can also be fooled. The processes that sit behind familiarity, or word recall (in this example), use a whatever-works principle. They're ad hoc, not carefully designed filing systems that pack away memories and bring them out later for comparison or regurgitation. By seeing where these processes break down, here by constructing very simple false memories, we can shed light on how memory works.

Let's show false memory construction with a couple of word lists. First wrap your eyes around the words in Table 9-3, read them out loud once, then close the book and try to list all the words you saw.

Table 9-3: Read these words aloud straight off, and then close the book and write down all you can remember
THREAD	POINT	HURT
PIN	PRICK	INJECTION
EYE	THIMBLE	SYRINGE
SEWING	HAYSTACK	CLOTH
SHARP	THORN	KNITTING

Do the same with the next set listed in Table 9-4: read the words aloud, then close the book and make a list.

Table 9-4: As before, read these words aloud, and then write down all you can remember
BED	WAKE	SNORE
REST	SNOOZE	NAP
AWAKE	BLANKET	PEACE
TIRED	DOZE	YAWN
DREAM	SLUMBER	DROWSY

Make your lists before reading ahead to get the most out of this hack.

Don't worry about the words you didn't get. But did your lists include either "needle" or "sleep"? If so, you should know that those two words were phantoms in your mind: They're not in either list! This is the Deese/Roediger/McDermott paradigm, or DRM,¹ and highlights how the fallibility of memory is not limited to the absence of information but includes outright fabrications. Experts believe that this doesn't represent glitches in the system but an outcome of the healthy memory system—built as well as needs be.

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When you learn something, you tend to store context as well. Sometimes this is a good thing, but it can mean your memories don't lend themselves to being recalled in different circumstances.

This situation should sound familiar to almost all of you: you're trying to remember the name of the guy who wrote that book you read at some point in the not-too-distant past. You can't remember his name, but you can remember that he's a Canadian who moved to the United States and also writes about politics and has affairs with minor celebrities. You had a copy of the book about 5 years ago, the cover was reddish, and you packed it into a box when you moved and haven't seen it since then. You remember reading the book in the old café that they've since turned into a video rental store. You remember an amazing amount about the book and loads of information associated with it...just not the name of the guy who wrote it. What gives?

Often, you don't know in advance what details you need to remember for later recall. There aren't any clean boundaries between relevant and not relevant, and there are no tags reading "You will be tested on this later." So instead of remembering only what you choose to learn or are sure to need later, your brain files away many intricate details of context.

To you, this is just the context, but in your memory, it isn't necessarily sharply defined as such. Your memory is a set of interlinked and interleaved representations [Hack #87] , so that in a fundamental sense the context can be part of the memory as much as the thing intended to be learned is part of the memory.

One consequence of this is that reinstating the original context helps you recall what you originally learned in that context. Another is that any consistent context associated with the learned item will become part of the memory for that item. Sometimes this can be a good thing, as is the case when you're trying to recall details you didn't know were going to be useful at the time or when you are trying to reproduce a skilled behavior in exactly the same circumstances in which you learned it. Other times it can hinder your recall of the memory in isolation—when you're out of that context.

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Your memories aren't stored discretely like objects in a filing cabinet; rather, they are interleaved with other things in memory. This explains why you're good with faces but not with names, why you should go back to your hometown to better remember your school days, and maybe even why you dream, too.

Human memory is not organized like a filing cabinet or a hard disk drive. In these storage systems, each memory is neatly indexed and stored so that it doesn't affect any other memory. The items in a computer memory don't affect processing unless they are explicitly retrieved, and to retrieve them, you have to consult an index to work out where they are. If you don't know where they are or if you don't have the right tag by which to access the files, you're out of luck—you're stuck with a brute force look through each file, one by one. The same holds for finding related items—you do it through some form of indexing system or again resort to a brute-force search. The system is content-blind.

But human memory is even further unlike any filing cabinet or computer memory system. This is the fundamental difference: human memories are stored as changes in the connections between neurons, the self-same neurons that actually do the processing.

So there are no passive storage locations: the processing-storage distinction fundamental to conventional computer architecture1 doesn't hold. Instead, memories about things are stored by the same units that are responsible for processing them. As you look at a face, your brain doesn't need to send away for information on whether you've seen the face before, and it doesn't need to store or index that face so that it can be recognized later. The ease with which that face was processed by your neural units provides a signature that can be used to calculate familiarity [Hack #83] . If you see the face once, it makes it easier for the neurons that respond to that particular combination of features to respond together, effectively acting as a key for recognizing it later.

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You can train your strength and skill with imagination alone, showing that there's a lot more to limb control than mere muscle size.

How your brain controls your muscles is something you don't notice until it goes wrong. When you drop a plate for no good reason, when disease or age rob you of the ability to will your muscles to move just like that, when you can't stop your legs trembling (even though that is possibly the least useful thing they could be doing in your situation), then you notice the gap between what you want to happen and what your muscles do. Normally the coordination of body movement happens so smoothly and (seemingly) instantaneously that it's hard to really believe there are any gaps in these processes. Hold your finger up in front of your face. Watch it carefully. And . . . ready . . . curl it. Magic. How did that happen? It's impossible to truly introspect about the control system involved: our bodies appear to be the ultimate pieces of invisible technology.

But that doesn't mean there isn't a very complex system of control in place. It needs to be complex for the range of jobs done, at the speeds they're done. The standard visuomotor feedback loop (the delay between acting and getting visual information to update or correct that action) is 100-200 milliseconds,¹ so much of this control has to happen without the aid of direct guidance from the senses. Movement must be controlled, at least in part, by processes that do not require immediate sensory feedback.

There's that number again: 100-200 ms! It occurs all over this book, and I think this may be the root of it; the commonly found window for conscious experience [Hack #27] may be this size because of the uncertainty introduced by the delay between our senses and reactions. So this is the range over which our brain has developed the ability to predict, by simulation, the outcome of our actions.
—T.S.

The thing is, movements are often so quick it doesn't feel as if feedback loops are intimately responsible. Rather, it often

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A 2,500-year-old memory trick shows how our memory for events may be based on our ability to remember routes to get to places.

Remembering where you are and what is currently happening are (as you might expect) both rather important. It turns out that orienting yourself in space may rely on some of the same brain areas as are used for remembering what has happened to you—areas that originally evolved to help animals find their way around, but now allow us to retain the episodes that make up our personal narratives.

The demonstration we'll use is a famous memory trick used to remember a list of arbitrary things, with the added bonus that the things are remembered in order. It's called the method of loci and involves remembering things according to where they are positioned along a route. Simply take your list of things to remember and place them along a familiar route, imagining each item (or something that will remind you of it) at key points on the route.

How many words do you think you could remember if given an arbitrary list and around 10 seconds per word in which to learn them? Knowing that my memory isn't all that good, I thought perhaps I could remember around 10. So I decided to use the method of loci to remember 20 words, twice that number. I didn't want to come up with my own list, because it would be easier for me to remember, so I used the 20 most common words appearing in the lyrics of the songwriter Tom Waits, as kindly provided by the excellent Tom Waits Supplement (http://www.keeslau.com/TomWaitsSupplement/Lyrics/common.htm) and shown in Table 9-5.

Table 9-5: Imagine an item for each word at points along a route that is familiar to you. Rehearse for 4 minutes and then test yourself
1. NIGHT	8. HOME	15. DRINK
2. TIME	9. RAIN	16. STREET
3. LOVE	10. HEART	17. BLOOD
4. DAY	11. DEATH	18. RED
5. EYE	12. DOG	19. HAIR
6. DREAM	13. BLUE	20. GIRL
7. MOON

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Our regular experience of the world is first person, but in some situations, we see ourselves from an external perspective. These out-of-body experiences may even have a neurological basis.

We are used to experiencing the world from a first-person perspective, looking out through our eyes with our bodies at the center of our consciousness. This is sometimes known as the Cartesian theater.

Some people, however, claim to have out-of-body experiences, in which their consciousness seems separated from their body, sometimes to the extent that people feel as if they are looking down on themselves from a third-person perspective, rather than looking out from the inside. These claims are not common, but most people can experience similar out-of-body phenomena, in the form of memories of past events. Furthermore, research has identified certain specific brain areas that may be involved in producing the egocentric, "looking out of our eyes" perspective and found that out-of-body experiences can be induced by unusual activity there.

Remember back to when you were last lying down reading something: perhaps it was on holiday at the beach, in a local park, or just on the couch at home. Try and fix that image in your mind.

Now, notice where your "mind's eye" is. Are you looking at yourself from an external point of view—much like someone wandering by might have seen you—or are you remembering yourself looking out through your own eyes as you are while reading this book right now?

The majority of people remember a scene like this from a seemingly disembodied third-person perspective, despite originally having experienced it from a first-person point of view.

The first study to explore this effect in detail was published in 1983 by Nigro and Neisser.¹ They made the link between the likelihood of recalling a memory as either a first-person or third-person image and emotions and discovered that asking someone to focus on their feelings at the time of the event was more likely to result in a first-person memory. The example in the preceding "In Action" section focused on a situation and was probably a fairly neutral emotional experience, so is likely to produce a third-person memory in most people.

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On the edge of sleep, you may enter hypnagogia, a state of freewheeling thoughts and sometimes hallucinations.

Hypnagogia, or the hypnagogic state, is a brief period of altered consciousness that occurs between wakefulness and sleep, typically as people "doze off" on their way to normal sleep. During this period, thoughts can become loosely associated, whimsical, and even bizarre. Hallucinations are very common and may take the form of flashes of lights or colors, sounds, voices (hearing your own name being called is quite common), faces, or fully formed pictures. Mental imagery may become particularly vivid and fantastical, and some people may experience synaesthesia, in which experiences in one sense are experienced in another—sounds, for example, may be experienced as visual phenomena.

It is a normal stage of sleep and most people experience it to some degree, although it may go unnoticed or be very brief or quite subdued in some people. It is possible, however, to be more aware of the hypnagogic state as it occurs and to experience the effects of the brain's transition into sleep more fully.

Although there is no guaranteed technique to extend or intensify the hypnagogic state, sometimes it can be enough to simply make a conscious effort to be aware of any changes in consciousness as you relax and drop off, if practiced regularly. Trying to visualize or imagine moving objects and scenes, or passively noting any visual phenomena during this period might allow you to notice any changes that take place. Extended periods of light sleep seem more likely to produce noticeable hypnagogia, so being very tired may mean you enter deep sleep too quickly. For this reason, afternoon dozing works well for some.

Some experimenters have tried to extend or induce hypnagogia by using light arousal techniques to prevent a quick transition into deep sleep. A microphone and speaker were used in one study to feed the sound of breathing back to the sleeper. Another method is the use of "repeat alarm clocks" (like the snooze function on many modern alarm clocks)—on entering sleep, subjects are required to try and maintain enough awareness to press a key every 5 minutes; otherwise, a soft alarm sounds and rouses them.

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Caffeine chemically hacks the brain's reward system, boosting the value we give not only to the morning cuppa, but also to everything associated with it.

I couldn't even begin to write this for you until I'd made myself a coffee. Some days I drink tea, but coffee is my normal stimulant of choice, and a cup of that ol' "creative lighter fluid" is just what I need to get started on my morning writing.

After you've drunk a cup of tea or coffee, the caffeine diffuses around your body, taking less than 20 minutes to reach every cell, every fluid (yes, every fluid¹) of which you're made. Pretty soon the neurotransmitter messenger systems of the brain are affected too. We know for certain that caffeine's primary route of action is to increase the influence of the neurotransmitter dopamine, although exactly how it does this is less clear.² Upshifting the dopaminergic system is something caffeine has in common with the less socially acceptable stimulants cocaine and amphetamine, although it does so in a different way.³

Neurons [Hack #9] use neurotransmitters to chemically send their signals from one neuron to the next, across the synapse (the gap between two neurons). There are many different neurotransmitters, and they tend to be used by neurons together in systems that cross the brain. The neurons that contain dopamine, the dopaminergic system, are found in systems dealing with memory, movement, attention, and motivation. The latter two are what concern us here.

Via the dopaminergic system, caffeine stimulates a region of the subcortex (the brain beneath the cerebral cortex [Hack #8] ) called the nucleus accumbens, a part of the brain known to be heavily involved in feelings of pleasure and reward. Sex, food, all addictive drugs, and even jokes cause an increased neural response in this area of the brain. What happens with addictive drugs is that they chemically hack the brain's evolved circuitry for finding things rewarding—the ability to recognize the good things in life and learn to do more of them.

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We don't live in a lifeless world—we live in a world of other people. It's other people, not rocks or trees, that have minds of their own, minds just as capable as ours. It's other people with whom we gang together to fight off threats, build knowledge, build cities, and sustain life. It's other people we need to fit in with.

A good deal of this book has been about the patterns of the world as they're reflected in our minds, as assumptions and expectations. Assumptions like the direction of sunlight, as comes through in our specialized routines for processing shadows on objects [Hack #20] . And, to pick another example, our observation and subsequent assumption that cause and effect tend to sit together in both time and space [Hack #79] , which we use as a heuristic to make sense out of the universe. These are good assumptions to make. It's their very robustness that has lodged them in the functioning of the brain itself.

So how do our assumptions about other people, as constituents of our universe, manifest themselves in the deep operations of the mind? We'll look at how we have a dedicated module for processing faces [Hack #93] and how eye gaze tugs at our reaching response [Hack #97] just like any physical location Simon Effect task [Hack #56] .

We'll look at how we signal emotion, how emotion is induced, and how we use it to develop common feeling in a group [Hack #94] and [Hack #95] .

And, speaking of fitting in, we'll finish by seeing how exposure to photographs of faces and the written word triggers our drive to imitate [Hack #98] , [Hack #99] , and [Hack #100] , from mirroring gestures to automatic mimicry of social stereotypes.

We have dedicated neural machinery for recognizing faces from just a few basic features arranged in the right configuration.

It's an important evolutionary skill to be able to quickly and efficiently recognize faces that are important to us. This allowed our ancestors to conform to the social hierarchies of the groups in which they lived, to keep checks on who was stronger and who was weaker than they were, and to track potential mates.

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We don't live in a lifeless world—we live in a world of other people. It's other people, not rocks or trees, that have minds of their own, minds just as capable as ours. It's other people with whom we gang together to fight off threats, build knowledge, build cities, and sustain life. It's other people we need to fit in with.

A good deal of this book has been about the patterns of the world as they're reflected in our minds, as assumptions and expectations. Assumptions like the direction of sunlight, as comes through in our specialized routines for processing shadows on objects [Hack #20] . And, to pick another example, our observation and subsequent assumption that cause and effect tend to sit together in both time and space [Hack #79] , which we use as a heuristic to make sense out of the universe. These are good assumptions to make. It's their very robustness that has lodged them in the functioning of the brain itself.

So how do our assumptions about other people, as constituents of our universe, manifest themselves in the deep operations of the mind? We'll look at how we have a dedicated module for processing faces [Hack #93] and how eye gaze tugs at our reaching response [Hack #97] just like any physical location Simon Effect task [Hack #56] .

We'll look at how we signal emotion, how emotion is induced, and how we use it to develop common feeling in a group [Hack #94] and [Hack #95] .

And, speaking of fitting in, we'll finish by seeing how exposure to photographs of faces and the written word triggers our drive to imitate [Hack #98] , [Hack #99] , and [Hack #100] , from mirroring gestures to automatic mimicry of social stereotypes.

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We have dedicated neural machinery for recognizing faces from just a few basic features arranged in the right configuration.

It's an important evolutionary skill to be able to quickly and efficiently recognize faces that are important to us. This allowed our ancestors to conform to the social hierarchies of the groups in which they lived, to keep checks on who was stronger and who was weaker than they were, and to track potential mates.

While faces are very important things to recognize, they are also all remarkably similar. Eyes, noses, and mouths—and it is these features that we rely on most when we discriminate between faces—all look pretty much alike, and the ratios of the spacing between them do not leave too much scope for differing widely either. Nevertheless, it is remarkably easy for us to distinguish between faces.

Take a look at the two pictures in Figure 10-1.

Figure 10-1: Two upside-down faces, but you should have no problem recognizing who it is¹

While you might detect some sort of difference between them, the odds are that both will look like pretty normal upside-down pictures of a face (and you might well be able to identify who it is, too). Now turn the book upside down. The face on the right is a grotesque: its eyes and mouth have been inverted. But you probably didn't notice this (and it certainly is not as striking as when the faces are the right way up). This is a neat demonstration of the fact that faces are normally processed holistically. When they are the right way up, we "understand" faces as a whole based on their internal components; turning them upside down disrupts this ability. We then have to rely on componential encoding instead and judge the face simply in terms of the individual items that make it up. This makes it much harder to detect that something is "wrong" than when we are able to use holistic processing. While, of course, we rely on differences in hairstyle and color and other factors when identifying people in the real world, experiments have shown that we rely most on the central features of faces.

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Emotions are powerful on the inside but often displayed in subtle ways on the outside. Are these displays culturally dependent or universal?

We find our emotional lives impossible to untangle from ourselves and examine critically. They're a core part of who we are. If you could imagine it, a life without feelings would be far more alien than any Mr. Spock. Emotions prepare us for situations both physiologically and cognitively too, and emerge from multiple dedicated systems that interact below the level of consciousness. Advances in psychology and neuroscience unveil these systems, and reveal how we signal our emotional states to others and decode even subtle emotional expressions.

Take a stroll down an imaginary lane in a distant, foreign land. You've no knowledge of the language spoken and no idea of the local customs and practices. Before you is a fork in the road with no clear sign of which direction leads to where. Thankfully, you spy a local working the land. Hungry for information to guide you, you point to the first path. His mouth broadens until his teeth are visible. After taking this in, you point to the second. His brow furrows as his mouth becomes small and tight. Lo and behold, despite any language and cultural barriers, you most likely have enough information to know that the first is probably a better bet.

Try it yourself. Consider the photo in Figure 10-3.

Figure 10-3: What emotion is this face signaling?¹

I'm sure there is no doubt in your mind what is being expressed here. At the very least, it's a very different face from that shown in Figure 10-4.

Figure 10-4: What emotion is this second face signaling?²

It's clear that the first face is happy and the second is in a less than positive mood.

Obvious, you say?

It might feel so, but before you dismiss this disambiguation out of hand, you should know that many of the cues are fairly subtle and there's a lot more going on behind the scenes than you might realize. In fact, these cues can slip by brain-damaged patients entirely, even those whose perception is otherwise fairly good. Let's dig a little deeper.

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Turn on your affective system by tweaking your face muscles—or getting an eyeful of someone else doing the same.

Find yourself a pen, preferably a nontoxic, nonleaky one. We're going to use this little item to improve your quality of life and give you a little pleasure.

Put the pen between your teeth, in far enough so that it's stretching the edges of your mouth back without being uncomfortable. Feeling weird? Just hold it there for a little, and appraise your level of mood. You should find that you end up feeling just a little happier.

If you want to go for the reverse effect, remove the pen (maybe give it a wipe), then trap it between your upper lip and nose like a mustache. If you're feeling anything, it's likely to be a touch of gloom, particularly in contrast to when you had the pen in your mouth.

Alternatively, if you're pen-averse, refer to the pictures in [Hack #94] and scrutinize the smiling face for a while. You should find yourself perked up—while the unhappy photo will likely send you downhill if you stare at it a little.

Emotional expressions are much more than just by-products of our affective system, the system that deals with emotions. Expressions serve as agents that transmit emotions to other individuals and are crucial in creating and maintaining our own emotional experience. And while aspects of this may be conscious and deliberate—my girlfriend may throw me a grin to let me know she's not mad that I've been glued to the computer all evening, and that reassurance will make me happy—there is a deeply automatic component. This is termed primitive contagion and is characterized as a three-stage process: it begins with perception, which triggers mimicry, which itself produces emotion. [Hack #94] deals with how we perceive emotions, so here we`ll unpack the other two stages: mimicry and resulting emotion.

Section 10.4.2.1: Mimicry

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Find the fire that's cooking your memory systems.

Our emotional system contributes not just to how we respond to the world at a given moment, but how we store representations of what has happened in the past. The makeup of our memories is not decided dispassionately by an impartial documentary reel in our brain, but by passionate, loaded mechanisms that draw out the aspects with the most juice.

Read the following two tales.¹ There will be a quiz at the end of class.

Section 10.5.1.1: Tale 1

"A mother and her son are leaving home in the morning. She is taking him to visit his father's workplace. The father is a laboratory technician at Victory Memorial Hospital. While walking along, the boy sees some wrecked cars in a junkyard, which he finds interesting.

"At the hospital, the staff are preparing for a practice disaster drill, which the boy will watch. Makeup artists were able to create realistic-looking injuries on actors for the drill.

"After the drill, while the father watched the boy, the mother left to phone her other child's preschool. Running a little late, she phones the preschool to tell them she will soon pick up her child. Heading to pick up her child, she hails a taxi at the number 9 bus stop."

Section 10.5.1.2: Tale 2

"A mother and her son are leaving home in the morning. She is taking him to visit his father's workplace. The father is a laboratory technician at Victory Memorial Hospital.

"While crossing the road, the boy is caught in a terrible accident, which critically injures him. At the hospital, the staff prepares the emergency room, to which the boy is rushed. Specialized surgeons were able to reattach the boy's severed feet.

"After the surgery, while the father stayed with the boy, the mother left to phone her other child's preschool. Feeling distraught, she phones the preschool to tell them she will soon pick up her child. Heading to pick up her child, she hails a taxi at the number 9 bus stop."

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We are innately programmed to follow other people's eye gaze to see what they are looking at. It's so deeply ingrained that even cartoon eyes can interfere with our mental processing of direction.

Eyes are special. They're part of a two-way sense. Wherever I look, you can tell what I'm looking at. You can tell if I'm paying attention to you or not, as well as hazarding a good guess as to what I'm really thinking about. Following gaze isn't a learned behavior. As far as the brain's concerned, gaze direction is a first-class citizen of the real world, as important as location. In the case of location, the Simon Effect [Hack #56] demonstrates that we have a tendency to react to a prompt in the same direction as that stimulus. This hack shows that we interpret gaze direction in much the same way as location: a cartoon pair of eyes looking in one direction has the same effect.

A team at the University of Padua in Italy constructed an experiment to see the effect of gaze.1 They drew a pair of cartoon eyes—just two ovals with a colored oval (the iris) within each, as shown in Figure 10-5. The irises were colored either blue or green, and the cartoon could be looking either straight ahead or to one of the sides.

Figure 10-5: Cartoon eyes similar to the ones used in the experiment: show this page to someone and watch what her eyes do—see if you can catch her just flicking off to the right as the cartoon eyes trigger her automatic gaze-following routine

People taking part in the experiment had to report the color of the irises, hitting a button on the left for blue and on the right for green. The apparent gaze direction wasn't important at all. Despite that, it was faster to hit the button for green on the right when the eyes were looking the same way (to the right) and slower when they were looking the other way. The same held true for blue and the eyes looking left.

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We mimic accents, gestures, and mannerisms without even noticing, and it seems it's the mere act of perception that triggers it.

We're born imitators, even without knowing we're doing it. I have a British accent, but whenever I spend a couple of weeks in North America, I start to pick up the local pronunciation. It's the same with hanging around certain groups of friends and ending up using words common in that group without realizing I'm picking them up.

Imitation doesn't require immersion in a culture. You can start mirroring people's movements without realizing it in moments.

I find a lot of psychology experiments a little mean, because they often involve telling the participants the experiment is about one thing, when actually it's about something else entirely. Tanya Chartrand and John Bargh's experiments on what they dub the Chameleon Effect fall into this category of keeping the participants in the dark (but are harmless enough not to be mean).¹

Chartrand and Bargh had volunteers take part in a dummy task of describing photographs while sitting in pairs, taking turns looking at each photo and speaking outloud their free associations. What the volunteers didn't know was that describing the photographs wasn't the point of the experiment and that their partner wasn't a volunteer but a confederate in league with the experiment organizers. The confederate exhibited some subtle behavior, either rubbing his face or shaking his foot for the 10-minute duration of the experiment.

What the experimenters were actually watching was how often a subject would rub her own face or shake her own foot—ultimately, how much a person could have her behavior influenced by the confederate, a person she hadn't met before and had no requirement to be friends with. The answer: behavior is influenced a lot.

Sitting with a face-rubbing confederate, a volunteer would rub her own face once every 100 seconds, on average. Normally, away from exposure to face-rubbing, she'd have about 30 seconds longer between touches.

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Have you ever found yourself in a confrontational mood for no reason? It could come down to what you've been reading.

We know our moods are affected by the world around us. It's easy to come home from a day at work when everything's gone wrong and stay grumpy for the rest of the evening. Then there are days when your mood is good or bad for no apparent reason at all. I've had miserable-mood days because I've finished a really great, but sad, novel in the morning and not even connected my mood with the book until that night. Thinking about mood like this, the regular way, makes us consider moods as long-timescale phenomena that we just have to live with, like the weather. Like the weather, moods in this frame seem impenetrable to understanding. Instead, it's good to take a different approach: how do moods begin? What's the smallest thing we can do that has an effect on our mood?

That's what this hack is about, showing that the words we encounter can make us ruder people in a matter of minutes—and not words that are meant to elicit a strong emotional response or ones that are taken to heart, but ones in the context of an innocuous word puzzle.

Puzzles are an excellent way to get people to keep words in mind for a substantial time. One such puzzle is the scrambled sentence test. Given a scrambled sentence of five words, such as "he it hides finds instantly," you have to make as many four-word sentences as you can, as fast as you can.

John Bargh, Mark Chen, and Lara Burrows used this test style¹ and incorporated 15 words to do with impolite behavior: "aggressively," "intrude," "brazen," and so on. They also had polite and neutral versions of the test. The subjects were unaware there were different forms of the test at this time and also unaware of the real point of the experiment.

Each subject spent about 5 minutes doing the puzzle, but that (of course) wasn't the point of the experiment. The critical point came when a subject stepped out of the room to say he'd finished, only to see the person running the experiment engaged in conversation. The question was: would he interrupt? Only just over 15% of those who'd been puzzling over polite words interrupted within 10 minutes, while of those who'd been using words like "obnoxious," more than 60%—

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Thinking about how certain stereotypes behave can make you walk slower or get a higher score in a general knowledge quiz.

The concept of priming [Hack #93] runs all the way through explanations of how perception influences behavior. Subliminal perception of photographs can prime you to prefer those photos in the future [Hack #82] , and simply spending time with someone who is, say, rubbing his face can infect you with his mannerism [Hack #98] . It's not necessary to consciously perceive the photographs or the gestures for them to automatically alter our behavior.

Nowhere is this truer than in exemplar activation: being exposed to ideas of stereotypes of people (the exemplars), not even the people themselves, will prime the characteristic traits of those people, and you'll begin to act in that way. It's very odd, and very cool.

Here's what John Bargh, Mark Chen, and Lara Burrows did¹: they gave 30 psychology undergraduates word puzzles to do (undergraduates are the raw material for most psychology studies). In half of the experiments, the puzzles included words associated with the elderly, like "careful," "wise," "ancient," and "retired." In the other half, all the puzzle words were neutral and not deliberately associated with any single concept. Immediately after individual students had completed the puzzle, they were free to go.

Bargh and team timed, using a hidden stopwatch, how long it took each undergraduate to walk down the corridor to the elevator. Students who had been given the puzzle featuring elderly related words took, on average, a whole second longer to make the walk—an increase from 7.3 to 8.3 seconds. They had picked up one of the perceived traits of the elderly: slower walking speed.

The specifics of how exemplar activation works is still an open question, but the basic mechanism is the same as how we pick up mannerisms [Hack #98] . It's a feature of the brain that perceiving something requires activating some kind of physical representation of the thing being perceived: simply making that representation primes that behavior, making us more likely to do what we see. Exemplar activation takes this a little further than we're used to, because it's the reading of words—in an apparently unrelated task to walking along the corridor—that primes the concept of "the elderly," which then goes on to influence behavior. But the principle is the same.

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