Attention to Details Everyone agreed that Parminder and her family were bighearted--generous and friendly to a fault--but they were also "bad" hearted, in one sad sense. Many of Parminder's relatives had suffered early heart attacks and strokes, and now, in her 68th year, Parminder shared that unhappy fate. In February, and then again in September, blood clots that originated in Parminder's heart found their way into the complex of arteries in her brain, cutting off blood flow to the surrounding brain tissue. The two strokes that resulted were exceptional, however, because they were exact mirror images--they damaged identical regions of the left and right parietal lobes. Parminder's unlikely lesions produced equally unlikely symptoms. A few weeks after her second stroke, Parminder had regained many of her intellectual powers--she could
converse normally and remember things. Her visual fields were apparently normal too, but her visual perception was anything but normal. Parminder had lost the ability to perceive more than one thing at a time. For example, she could see her husband's face just fine, but she couldn't judge whether he had glasses on or not. It turned out that she could see the glasses or she could see the face, but she couldn't perceive them both at the same time. When shown a drawing of several overlapping items, she could perceive and name only one at a time. Furthermore, she couldn't understand where the objects she saw were located. It was as if Parminder was lost in space, able to pay attention to only one object or detail at a time, apparently alone in a world of its own. What could explain Parminder's symptoms?
W hat is attention? William James, the great American psychologist, wrote in 1890: Everyone knows what attention is. It is the taking possession by the mind, in clear and vivid form, of one out of what seem several simultaneously possible objects or trains of thought. Focalization, concentration, of consciousness are of its essence. It implies withdrawal from some things in order to deal effectively with others, and is a condition which has a real opposite in the confused, dazed, scatterbrained state. Clearly, James understood that attention can be effortful, improves perception, and acts as a filter. This continual shifting of our focus from one interesting stimulus to the next lies at the heart of our innermost conscious experiences, our awareness of the world around us, and our place in it. So, we open this chapter by exploring the behavioral and neural dimensions of attention before turning to the more general question of our conscious experience of the world.
14.1Attention Focuses Cognitive Processing on Specific Objects
View Animation 14.2: Brain Explorer attention Also called selective attention. A state or condition of selective awareness or perceptual receptivity, by which specific stimuli are selected for enhanced processing. vigilance The global, nonselective level of alertness of an individual. overt attention Attention in which the focus coincides with sensory orientation (e.g., you're attending to the same thing you're looking at). covert attention Attention in which the focus can be directed independently of sensory orientation (e.g., you're attending to one sensory stimulus while looking at another). cocktail party effect The selective enhancement of attention in order to filter out distracters, as you might do while listening to one person talking in the midst of a noisy party.
The first part of this chapter concerns the consequences of attention processes: the ways attention filters the world and affects our processing of sensory information. At the conclusion of this section, you should be able to: 14.1.1 Provide a general definition of attention, and distinguish between overt and covert forms of attention, with examples. 14.1.2 Describe the limitations on our powers of attention, situations in which our attention may be overextended, and the behavioral manifestations of these limits on attention. 14.1.3 Speculate about the ways in which evolution may have shaped attention. 14.1.4 Distinguish between voluntary and reflexive attention, and describe general experimental designs for studying each. 14.1.5 Describe the use of focused attention to search the world for particular objects (using either a feature search or a conjunction search), and discuss the significance of the "binding problem." Despite taking delight in pretending otherwise, the average 5-year-old knows exactly what it means when an exasperated parent shouts, "Pay attention!" We all share an intuitive understanding of the term attention, but it is tricky to formally define. In general, attention (or selective attention) is the process by which we select or focus on one or more specific stimuli--either external phenomena or internal thoughts--for enhanced processing and analysis. It is the selective quality of attention that distinguishes it from the related concept of vigilance, the global level of alertness of the individual. Most of the time we direct our eyes and our attention to the same target, a process known as overt attention. For example, as you read this sentence, it is both the center of your visual gaze and (we hope) the main item that your brain has selected for attention. But if we choose to, we can also shift the focus of our visual attention covertly, keeping our eyes fixed on one location while "secretly" scrutinizing something in peripheral vision (Helmholtz, 1962; original work published in 1894). Remember that teacher who, even when looking out the window, somehow knew instantly when someone read a text? That's an example of what is known as covert attention (FIGURE 14.1). Selective attention isn't restricted to visual stimuli. Imagine yourself chatting with an old friend at a noisy party. Despite the background noise, you would probably find it relatively easy to focus on what your friend was saying, even if speaking quietly, because attention aids your sensory perception--paying close attention to a friend enhances your processing of their speech and helps filter out distracters. This phenomenon, known as the cocktail party effect,1 nicely illustrates how attention acts to focus cognitive processing resources on a particular target. If your attention drifts to a different stimulus-- for example, if you start eavesdropping on a more interesting conversation nearby--it becomes almost impossible to simultaneously follow what your friend is saying. There are limits on attention The powers of attention that help you to easily chat with a friend in a noisy room normally rely on cues in several different sensory modalities, such as where their speech sounds are coming from, the movements of their face while speaking, and what unique sounds their voice makes. But what if we restrict our attention to just one type of stimulus? In shadowing experiments, participants must focus their attention on just one out of two or more simultaneous streams of stimuli. In a classic example of this technique, 1The term cocktail party effect also sometimes describes what happens when a highly salient word (such as one's own name) captures attention in a noisy environment.
While holding our gaze steady on a central xation point, we can independently center our visual attention on a different spatial location. This selective attention has sometimes been referred to as an attentional spotlight. Location of covert spatial attention
FIGURE 14.1 Covert Attention
Cherry (1953) presented different streams of speech simultaneously to people's left and right ears via headphones--the technique is called dichotic presentation--and asked them to focus their attention on one ear or the other and report what they heard. Participants were able to accurately report what they heard in the attended ear, but they reported very little about what was said in the nonattended ear, aside from simple characteristics, such as the sex of the speaker. In fact, if a shadowing task is difficult enough, people may fail to detect even their own names in the unattended ear about two-thirds of the time (N. Wood and Cowan, 1995)! Similar restrictions of attention can be seen in other sensory modalities, such as musical notes (Zendel and Alain, 2009) and visual stimuli. Participants closely attending to one complex visual event against a background of other moving stimuli-- Wdaantscoenr/sBwreeedalvoivneg through a basketball game, for example--may show inattentional TbhlienMdnineds'ssM: aacshuinrpe rising failure to perceive nonattended stimuli. And the unperceived Foundations of Brain and Behavior 4e stimuli can be things that you might think impossible to miss, like a gorilla strolling MacMro4ses_1th4.e01scre09e/n01o/u2t0of the blue (Simons and Chabris, 1999; Simons and Jensen, 2009). Even highly trained experts can have this problem. In one study 83% of radiologists screening CT scans for lung cancer didn't notice a seemingly obvious image of a gorilla inserted into one of the scans (Drew et al., 2013) (you can see an example on the website). Inattentional blindness even occurs when the nonattended stimulus could have life-or-death consequences for the observer; for example, a significant fraction of police officers and trainees will fail to notice a gun placed in plain view during a simulated traffic stop (Simons and Schlosser, 2017). In general, divided-attention tasks--in which a person is asked to process two or more simultaneous stimuli--confirm that attention is a limited resource and that it's very difficult to attend to more than one thing at a time, particularly if the stimuli are spatially separated (Bonnel and Prinzmetal, 1998). So, our limited selective attention generally acts like an attentional spotlight (see Figure 14.1), shifting around the environment, highlighting stimuli for enhanced processing. It's an adaptation that we share with many other species because, like us, they are confronted with the problem of extracting important signals from a noisy background (Bee and Micheyl, 2008). Birds, for example, must isolate the vocalizations of specific individuals from a cacophony of calls and other noises
See Video 14.3: Inattentional Blindness shadowing A task in which the participant is asked to focus attention on one ear or the other while different stimuli are being presented to the two ears, and to repeat aloud the material presented to the attended ear. inattentional blindness The failure to perceive nonattended stimuli that seem so obvious as to be impossible to miss. divided-attention task A task in which the participant is asked to focus attention on two or more stimuli simultaneously. attentional spotlight The steerable focus of our selective attention, used to select stimuli for enhanced processing.
From D. J. Simons and C. F. Chabris, 1999. Perception 28: 1059
Gorillas in the Midst Who could miss the gorilla in the video from which this still is taken? Most people do, if they are concentrating on some other task, such as counting the number of times people in white shirts touch a ball that is being passed around. attentional bottleneck A filter created by the limits intrinsic to our attentional processes, whose effect is that only the most important stimuli are selected for special processing. perceptual load The immediate processing demands presented by a stimulus. sustained-attention task A task in which a single stimulus source or location must be held in the attentional spotlight for a protracted period. voluntary attention Also called endogenous attention. The voluntary direction of attention toward specific aspects of the environment, in accordance with our interests and goals.
in the environment--an avian version of the cocktail party problem (Benney and Braaten, 2000). Having a single attentional spotlight helps us focus cognitive resources and behavioral responses toward the most important things in the environment at any given moment (the smell of smoke, the voice of a potential mate, a glimpse of a big spotted cat), while ignoring extraneous information. In general, by acting as a filter, attention narrows our focus and directs our cognitive resources toward only the most important stimuli around us, thereby protecting the brain from being overwhelmed by the world. But the details of this attentional bottleneck have been elusive. Initial research gave evidence of an early-selection model of attention, in which unattended information is filtered out right away, at the level of the initial sensory input, as in the shadowing experiments we just described (Broadbent, 1958). But other researchers noted that important but unattended stimuli (such as your name) may undergo substantial unconscious processing, right up to the level of semantic meaning and awareness, before suddenly capturing attention (N. Wood and Cowan, 1995), thus illustrating a late-selection model of attention. Many contemporary models of attention now combine both early- and late-selection mechanisms (e.g., Wolfe, 1994), and debate continues over their relative importance (for a classic demonstration, see A STEP FURTHER 14.1, on the website). A possible resolution to this debate involves the concept of perceptual load--the immediate processing demands presented by a stimulus. According to this view, when we focus on a very complex stimulus, the load on our perceptual processing resources is so great that there is nothing left over. We are thus unable to process competing unattended items, so those extra stimuli are excluded right from the outset: an early-selection process (N. Lavie et al., 2004; S. Murphy et al., 2017). But when we focus on stimuli that are easier to process, we may have enough perceptual resources left over to simultaneously process additional stimuli, all the way up to the level of semantic meaning and awareness. In this case the result is a late selection of stimuli to attend to (N. Lavie et al., 2009). In other words, if we view attention as a limited resource, then we only have enough of it to do one complex task at a time, or a few very simple ones. This research thus suggests that attention is continually rebalanced between early and late selection, depending on the difficulty of the task at hand. These more modern perspectives on attention are central to the development of computational models of attention in visual and auditory "scenes"; one hope is that mathematical descriptions of attentional processes will aid in the development of machine versions of vision and audition (Shic and Scassellati, 2007; Kaya and Elhilali, 2017). Attention is deployed in several different ways We've now seen that through an act of willpower we can direct our attention to specific stimuli without moving our eyes or otherwise reorienting. Early experiments on this phenomenon employed sustained-attention tasks, like the one depicted in Figure 14.1, where a single stimulus location must be held in the attentional spotlight for an extended period. Although these tasks are useful for studying basic phenomena, several key questions about attention require another approach. For example, how do we shift our attention around? How does attention enhance the processing of stimuli, and which brain regions are involved? To answer these questions, researchers devised clever tasks that employ stimulus cuing to control attention, which revealed two general categories of attention, as we'll discuss next. The kind of attention that we have been discussing thus far in the chapter is what researchers call voluntary attention (or endogenous attention). As the name implies,
In three types of cuing trials, participants xating on a central point are shown a symbol that gives an accurate clue to the location in which a subsequent stimulus item will brie y appear (A), a bogus cue that indicates an incorrect location (B), or a symbol that doesn't cue any particular location (C).
FIGURE 14.2 Measuring the Effects of Voluntary Shifts of Attention (After M. I. Posner, 1980. Q. J. Exp. Psychol. 32: 3.)
Reaction times for valid cues are signi cantly faster than for invalid cues, and neutral cues fall somewhere in between. This pattern of results shows that voluntary shifts of attention enhance stimulus processing independently of visual gaze.
200 Invalid Neutral Valid Type of cue provided
voluntary shifts of attention come from within; they are the conscious, top-down directing of our attention toward specific aspects of the environment, according to our interests and goals. FIGURE 14.2 features the symbolic cuing task (or spatial cuing task), developed by Michael Posner and used extensively to study voluntary attention. Studies using cuing tasks have confirmed that consciously directing your attention to the correct location or stimulus improves processing speed and accuracy. Conversely, directing your attention to an incorrect location or stimulus impairs processing efficiency. How much does it help to shift your attention to a location before a stimulus occurs there? Posner's (1980) symbolic cuing task allows us to quantify how voluntary attention benefits processing. In a symbolic cuing task, participants stare at a point in the center of a computer screen and must press a key as soon as a specific target (the stimulus) appears on the screen; this technique thus measures reaction time. The stimulus is preceded by a cue that briefly flashes on the screen, hinting where the stimulus will appear. Most of the time, as in FIGURE 14.2A, the participant is provided with a valid cue; for example, a rightward arrow flashes on the screen moments before the stimulus appears on the right side Wofatthsoens/cBrreeeednl.oIvne a few trials, like the one in FIGURE 14.2B, the arrow points the wrong TwhaeyMainndd'sthMuaschpirnoevides an invalid cue. And in "neutral" control trials (FIGURE 14.2C), the Foundations of Brain and Behavior 4e cue doesn't provide any hint at all. Both the cue and the stimulus are on the screen so MbrMie4fely_1t4h.0a2t pa0r7t/i1c4ip/2a0nts don't have time to shift their gaze (and in any case, they have been told to stare at the fixation point). Averaged over many trials, the reaction-time data (FIGURE 14.2D) clearly show that people swiftly learn to use cues to predict stimulus location, shifting their attention without shifting their gaze. Compared with neutral trials, processing is significantly faster for validly cued trials, and participants pay a price for misdirecting their attention on those few trials in which the cue is invalid, pointing to the wrong side of the display. Many variants of the symbolic cuing paradigm have been developed-- varying the timing of the stimuli, altering their complexity, requiring a choice between different responses--all of which can affect reaction time, which we discuss next.
symbolic cuing Also called spatial cuing. A technique for testing voluntary attention in which a visual stimulus is presented and participants are asked to respond as soon as the stimulus appears on a screen. Each trial is preceded by a meaningful symbol used as a cue to hint at where the stimulus will appear. reaction time The delay between the presentation of a stimulus and a participant's response to that stimulus, measured in milliseconds.
Reaction times reflect brain processing, from input to output
Reaction-time measures are a mainstay of cognitive neuroscience research. In tests of simple reaction time, participants make a single response--for example, pressing a button--in response to an experimental stimulus (the appearance of a target, the solution to a problem, a tone, or whatever the experiment is testing). In tests of choice reaction time, the situation is slightly more complicated: a person is presented with alternatives and has to choose among them (e.g., correct versus incorrect, same versus different) by pressing one of two or more buttons. Reaction times in an uncomplicated choice reaction time test, in which the participant indicates whether two stimuli are the same or different, average about 300-350 milliseconds (ms). The delay between stimulus and response varies depending on the amount of neural processing required between input and output. The neural systems involved in this sort of task, and the timing of events in the response circuit, are illustrated in FIGURE 14.3. Brain activity proceeds from the primary visual cortex (V1) through a ventral visual object identification pathway (see Chapter 7) to prefrontal cortex, and then through premotor and primary motor cortex, down to the spinal motor neurons and out to the finger muscles. In the sequence shown in the figure-- proceeding from the presentation of visual stimuli to a discrimination response--notice that it takes about 110 ms for the sensory system to recognize the stimulus (somewhere in the inferior temporal lobe), about 35 ms more for that information to reach the prefrontal cortex, and then about 30 ms more to determine which button to push. After that, it takes another 75 ms or so for the movement to be executed (i.e., 75 ms of time elapses between the moment the signal from the prefrontal cortex arrives in premotor cortex and the moment the
finger pushes the button). It is fascinating to think that something like this sequence of neural events happens over and over
in more-complicated behaviors, such as recognizing a long-lost friend or composing an opera.
Question Does the length of time required to respond to a stimulus increase with stimulus complexity? Test Compare the time taken to press a button after the appearance of a simple stimulus (such as a light turning on), versus time to react to more complex stimuli (for example, a green light but not an orange light).
Arrows indicate the sequence and timing of brain events that determine reaction time.
Premotor cortex Primary (175 ms) motor cortex (210 ms)
Spinal cord (225 ms) Finger muscle (250 ms) Result The more complex the stimulus processing that is required, the longer the reaction time. Conclusion Complex stimuli require the participation of more brain pathways, slowing down reaction time proportionately.
FIGURE 14.3 A Reaction-Time Circuit in the Brain LGN, lateral geniculate nucleus; V1, primary visual cortex; V2 and V4, extrastriate visual areas. (Timings based on S. J. Thorpe and M. Fabre Thorpe, 2001. Science 291: 260.)
Some types of stimuli just grab our attention There is a second way in which we pay attention to the world, involving more than just consciously steering our attentional spotlight around. Flashes, bangs, sudden movements--any striking or important change--can instantly snatch our attention away from whatever we're doing, unless we are very focused. Drop your glass in a restaurant, and every conversation stops, every head in the place swivels, seeking the source of the sound (you, embarrassingly). This sort of involuntary reorientation toward a sudden or important event is an example of reflexive attention (or exogenous attention). It is considered to be a bottom-up process, because attention is being seized by sensory inputs from lower levels of the nervous system, rather than being directed by voluntary, conscious top-down processes of the forebrain. Researchers study reflexive attention using a different kind of cuing task, called peripheral spatial cuing. In this task, instead of a meaningful symbol like an arrow, the cue that is presented is a simple sensory stimulus, such as a flash of light, occurring in the location to which attention is to be drawn. Research with this type of simple cuing confirmed that valid reflexive cues enhance the processing of subsequent stimuli at the same location, but only when the target stimulus closely follows the cue. At longer intervals between the cue and target, starting at about 200 ms, a curious phenomenon is observed: detection of stimuli at the location where the valid cue occurred is actually impaired (Satel et al., 2019). It's as though attention has moved on from where the cue occurred and is reluctant to return to that location. This inhibition of return probably evolved because it prevented reflexive attention from settling on unimportant stimuli for more than an instant, an effective strategy in animals foraging for food or scanning the world for threats. Normally, reflexive and voluntary attention work together to direct cognitive activities (FIGURE 14.4), probably relying on somewhat overlapping neural mechanisms. Anyone who has watched a squirrel at work has seen that twitchy interplay. When it comes to single-mindedly searching for tasty morsels (an example of voluntary attention), a squirrel has few rivals. But even slight noises and movements (cues that reflexively capture attention) cause the squirrel to stop and scan its surroundings--a sensible precaution if, like a squirrel, you are yourself a tasty morsel. So, it's no surprise that emotional cues--a sudden gasp from a companion, for example--can likewise reflexively capture attention and augment sensory processing (Carretié, 2014). And effective cues for reflexive attention may involve multiple sensory modalities: a sudden sound coming from a particular location, for example, can improve the visual processing of a stimulus that appears there (McDonald et al., 2000; Feng et al., 2017).
View Animation 14.4: From Input to Output reflexive attention Also called exogenous attention. The involuntary reorienting of attention toward a specific stimulus source, cued by an unexpected object or event. peripheral spatial cuing A technique for testing reflexive attention in which a visual stimulus is preceded by a simple task-irrelevant sensory stimulus either in the location where the stimulus will appear or in an incorrect location. inhibition of return The phenomenon, observed in peripheral spatial cuing tasks when the interval between cue and target stimulus is 200 milliseconds or more, in which the detection of stimuli at the former location of the cue is increasingly impaired.
Voluntary attention is slower but can be maintained longer, and is coordinated with re exive attention to study important stimuli. Re exive attention rapidly orients to interesting stimuli, but it fades quickly unless the stimulus is important (dashed line).
FIGURE 14.4 Voluntary and Reflexive Attention
442CHAPTER14 feature search A search for an item in which the target pops out right away, no matter how many distracters are present, because it possesses a unique attribute. conjunction search A search for an item that is based on two or more features (e.g., size and color) that together distinguish the target from distracters that may share some of the same attributes. binding problem The question of how the brain understands which individual attributes blend together into a single object, when these different features are processed by different regions in the brain.
Attention helps us to search for specific objects in a cluttered world Another familiar way that we use attention is in visual search: systematically scanning the world to locate a specific object among many--your car in a parking lot, for example, or your friend's face in a crowd. If the sought-after item varies in just one key attribute, the task can be pretty easy--searching for your red car among a bunch of silver and black ones, for example. In a simple feature search like this (FIGURE 14.5A), the sought-after item "pops out" immediately, no matter how many distracters are present (Joseph et al., 1997). Effortful voluntary attention isn't needed. More commonly, however, we must use a conjunction search--searching for an item on the basis of a combination of two or more features, such as size and color (FIGURE 14.5B and C). This can become very difficult when, for example, you must simultaneously consider the hair, nose, eyes, and smile of your friend's face in a crowd--and the bigger the crowd grows, the harder the task becomes (unless your friend waves, thereby reflexively grabbing your attention--phew!). Experimental results (FIGURE 14.5D) confirm what you probably already know intuitively: conjunction searches can be relatively slow and laborious, involving a large cognitive effort. That's because your brain has to deal with what is known as the binding problem (A. M. Treisman, 1996), which is this: How do we know which
(B) Conjunction search, target present Find a green circle
(C) Conjunction search, target absent Find a yellow square
In these two feature search arrays, targets "pop out" because they differ from all other stimuli on one key feature, such as color or shape.
In conjunction searches, nding the target, or determining that it is absent, takes longer because several target features must be considered simultaneously.
FIGURE 14.5 Visual Search (After A. M. Treisman and G. Gelade, 1980. Cog. Psych. 12: 97.)
Added distractions slow down reaction time in a conjunction search, especially if target is absent.
Conjunction search, target absent Conjunction search, target present Feature search
When the target "pops out," it is quickly found and additional distractors have little or no effect.
From Where's Waldo? © Martin Handford 2005
attention to enhance the processing of Where's Waldo? Puzzles like the "Where's Waldo?" series are classic examples of
stimuli. So, in these studies, the ques- conjunction searches: you can find Waldo only if you search for the right combination of
tion is, What are the targets of attention? Second, we can try to uncover the mechanisms of attention, the brain regions that produce and control at-
striped sweater, hat, glasses, and slightly goofy expression. Imagine how much easier it would be to find Waldo if everyone else on the beach were wearing green! In that case, finding Waldo would be a feature search (the only person not wearing green) and he would "pop out" in the picture ... but that wouldn't be any fun.
Here, the question is, What are the sources of attention? In selecting experimental
techniques to address these different objectives, researchers must juggle the need
for good temporal resolution--the ability to track changes in the brain that occur
very quickly--with the need for excellent spatial resolution, the ability to observe the detailed structure of the brain. In general, electrophysiological approaches offer the speed (temporal resolution) necessary to distinguish the consequences of atten-
temporal resolution The ability to track changes in the brain that occur very quickly.
tion from the mechanisms that direct it, while brain-imaging techniques like fMRI offer the anatomical detail (spatial resolution) to figure out where these neural ac-
spatial resolution The ability to observe the detailed structure of
tions are taking place. This speed-versus-accuracy trade-off permeates the research the brain.
that we discuss in the following section.
1. How do you define attention? Distinguish between overt and covert attention, giving examples of each. What is the attentional spotlight? 2. What is inattentional blindness, and under what circumstances might it occur? 3. How do early-selection effects of attention differ from late-selection effects? What single aspect of a stimulus may determine whether early or late selection occurs? 4. Summarize Posner's symbolic cuing task. What did this task reveal? 5. Compare and contrast voluntary attention and reflexive attention, and identify the principal ways in which they differ. What is inhibition of return, and does it relate to voluntary attention or to reflexive attention? 6. While conducting a visual search for something, we sometimes experience "popout." What is it? Is pop-out more closely associated with feature search or with conjunction search, and how do those differ? 7. Distinguish between temporal resolution and spatial resolution as they apply to brain-imaging techniques. How are they related?
444CHAPTER14 event-related potential (ERP) Also called evoked potential. Averaged EEG recordings measuring brain responses to repeated presentations of a stimulus. Components of the ERP tend to be reliable because the background noise of the cortex has been averaged out. auditory N1 effect A negative deflection of the event-related potential, occurring about 100 milliseconds after stimulus presentation, that is enhanced for selectively attended auditory input compared with ignored input.
14.2Targets of Attention: Attention Alters the Functioning of Many Brain Regions The next section turns to the impact of attention on brain processes. Once you have finished studying this section, you should be able to: 14.2.1 Describe how and why scientists use the electrical activity of the brain to study attention. 14.2.2 Name and describe the main components seen in event-related potentials (ERPs) as they relate to auditory versus visual attention, and particularly compare the auditory N1 effect and the visual P1 effect. 14.2.3 Describe the electrophysiological phenomena associated with visual search tasks. 14.2.4 Describe experimental evidence that selective attention to stimuli enhances neural activity in the brain regions processing the attended stimuli. Recording electrical activity directly from the neurons of people's brains would be a way to obtain excellent temporal and excellent spatial resolution, but of course we can't just stick recording electrodes directly into the brains of healthy participants. Instead, we must find noninvasive ways to assess brain activity. When many cortical neurons work together on a specific task, their activity becomes synchronized to some degree. You might think this would be easy to see in a standard EEG recording (i.e., an electroencephalogram, where the brain's electrical activity is recorded from the scalp, as we described in Chapter 3), but it isn't. Because of variation in the firing of the neurons, not to mention regional differences in the timing of brain activity, a real-time EEG recorded during an attention task looks surprisingly random. So instead, researchers record participants doing a task (FIGURE 14.6A) over and over again, and they average all the EEGs recorded during those repeated trials (FIGURE 14.6B). Over enough trials, the random variation averages out, and what's left is the overall electrical activity specifically associated with task performance (FIGURE 14.6C). This averaged activity, called the event-related potential (ERP) (Luck, 2005; Helfrich and Knight, 2019), tracks regional changes in brain activity much faster than brain-imaging techniques like fMRI do. For this reason, ERP has become the favorite tool of neuroscientists studying moment-to-moment consequences of attention in the brain. Distinctive patterns of brain electrical activity mark shifts of attention Consciously directing your attention to a particular auditory stimulus--for example, shadowing one ear, as we described earlier--has a predictable effect on the ERP. Between about 100 and 150 ms after the onset of a sound stimulus, two large waves are seen in the ERP from the auditory cortex: an initial positive-going wave called P1, immediately followed by a larger negative-going wave called N1 (see Figure 14.6C). The N1 wave reflects an important aspect of auditory attention: it is much larger following a stimulus that is being attended to than it is for the very same stimulus presented at the same ear but not attended to (Hillyard et al., 1973). Because the only thing that changes between conditions is the participants' attention to the stimuli, this auditory N1 effect must be a result of selective attention somehow acting on neural mechanisms to enhance processing of that particular sound. Auditory attention may also affect much later ERP components, such as the wave called P3 (or auditory P300) (see Figure 14.6C). Changes in late-occurring components like P3 are tricky to interpret, because they can be associated with multiple different cognitive operations, ranging from memory access to reactions to unexpected events (Wessel and Aron, 2017). Nevertheless, some researchers believe that P3 is
Over multiple trials, the EEGs recorded each time look quite different, because of random variation...
Scalp electrodes record EEG activity during a task.
...but averaging across many trials cancels out the random variation, leaving only the unchanging task-related components shown here. (By convention, negative voltages [N1, N2, etc.] are charted above the zero line, and positive voltages [P1, P2, etc.] are charted below the zero line. Yes, it's kind of weird.) (C) Averaged ERP waveform - N1 N2
FIGURE 14.6 Event-Related Potentials
especially sensitive to higher-order cognitive processing of the stimulus (Herrmann
and Knight, 2001)--qualities like the underlying meaning of the stimulus, identi-
ty of the speaker, and so on--in which case the P3 effect provides an example of a
late-selection effect of attention. Researchers are debating whether P3 therefore is
(Dehaene and Changeux, 2011) or is not (Pitts et al., 2014) an electrophysiological
What about effects of attention on ERPs from visual stimuli? Because the neural
systems involved in visual perception are different from those involved in audition,
voluntary visual attention causes its own distinctive changes in the ERP. We can study
these visual effects by collecting ERP data over occipital cortex--the primary visual
area of the brain--while a participant performs a symbolic cuing task. FIGURE 14.7
depicts this sort of experiment. On valid trials (remember, this is when the target ap-
pears as expected, in the location indicated by the cue, as in Figure 14.7A), electrodes
over occipital cortex show a substantial enhancement of the ERP component P1, the
positive wave that occurs about 70-100 ms after stimulus onset, often carrying over
into an enhancement of the N1 component immediately afterward (FIGURE 14.7C). A
similar effect on P1 is evident when attention is instead oriented reflexively to a flash
or sound (Hopfinger and Mangun, 1998; McDonald et al., 2005), but only when the
tThhee MP1inedf'sfeMcatcmhinaey actually be reduced as an electrophysiological manifestation of the
iFnouhnidbaittiioonns ooffBreaitnuarnnd (BMehcavDioorn4ae ld et al., 1999) we discussed earlier. And for invalid trials
(FIGURE 14.7B), where MM4e_14.06 06/23/20
evident at all, even though the visual stimulus is identical and in the same location
as in the validly cued trials. Interestingly, the P1 effect is evident only in visual tasks
involving manipulations of spatial attention (where is the target?)--not other features,
like color, orientation, or more complex properties that would be characteristic of
P3 effect A positive deflection of the event-related potential, occurring about 300 milliseconds after stimulus presentation, that is associated with higher-order auditory stimulus processing and late attentional selection. visual P1 effect A positive deflection of the event-related potential, occurring 70-100 milliseconds after stimulus presentation, that is enhanced for selectively attended visual input compared with ignored input.
The individual xates on the red point and covertly orients attention (dashed circle) in the direction indicated by a prior symbolic cue (such as an arrow), pressing a key when the stimulus (blue rectangle) appears.
...but sometimes it misdirects attention to another location.
Correct direction of attention enhances neural processing, resulting in larger P1 and N1 components in the corresponding ERP. Note that neither the stimulus nor the individual's gaze differs between conditions; the change in attention is solely responsible for the ERP effect.
Attention enhances contralateral occipital activity.
FIGURE 14.7 ERP Changes in Voluntary Visual Attention
Watson/Breedlove The Mind's Machine Foundations of Brain and Behavior 4e MM4e_14.07 08/24/20
What happens to ERPs during visual search tasks, where we are directing attention so as to find a particular target in an array and ignore distracters? Under these conditions, a subcomponent of N2 (see Figure 14.6), called N2pc, is triggered at occipitotemporal sites contralateral to the visual target (Luck and Hillyard, 1994; Hickey et al., 2009). The neural mechanisms of visual attention may be quite plastic. For example, extensive experience with action video games, which heavily rely on visual attention, is associated with neural changes (S. Tanaka et al., 2013; West et al., 2015) and corresponding enhancements of longer-latency ERP components (Mishra et al., 2011; Palaus et al., 2017). Possible trade-offs for all this gaming, however, may include impaired social and emotional function (no, we're not kidding: K. Bailey and West, 2013). And of course, some people could be drawn to gaming simply because they are already good at visuospatial processing (Boot et al., 2008). Attention affects the activity of neurons PET and fMRI operate too slowly to track the rapid changes in brain activity that occur in reaction-time tests. Instead, researchers have used "sustained-attention tasks" to confirm that attention enhances activity in brain regions that process key aspects of the target stimulus. In these experiments, participants are asked to pay close and lasting attention to one particular aspect of a complex stimulus--just the faces in a complex scene, or changes in the pattern of selected dots within an array, for example. Concurrent fMRI generally confirms that attention somehow acts directly on neurons, boosting the activity of those brain regions that process whichever stimulus characteristic has been targeted. So, in these particular examples, enhancement is seen in the cortical fusiform face area during attention to faces (O'Craven et al., 1999), or in the subcortical superior colliculus and lateral geniculate (important for spatial processing of visual stimuli) during attention to spatial arrays (Schneider and Kastner, 2009). In
Attention and Higher Cognition 447 general, it seems that directed attention reduces variability and improves the signalto-noise ratio in neural systems, perhaps by adjusting the influence of individual synapses (Briggs et al., 2013; Sprague et al., 2015). In Chapter 7 we discussed the distinctive receptive fields of visual neurons and how stimuli falling within these fields can excite or inhibit the neurons, causing them to produce more or fewer action potentials. In an important early study, Moran and Desimone (1985) recorded the activity of individual neurons in visual cortex while attention was shifted within each cell's receptive field. Using a system of rewards, the researchers trained monkeys to covertly attend to one spatial location or another while recordings were made from single neurons in visual cortex. A display was presented that included the cell's most preferred stimulus, as well as an ineffective stimulus (one that, by itself, did not affect the cell's firing) a short distance away but still within the cell's receptive field. As long as attention was covertly directed at the preferred stimulus, the cell responded by producing many action potentials (FIGURE 14.8). But when the monkey's attention was shifted elsewhere within the cell's receptive field, even though the animal's gaze had not shifted, that same stimulus provoked far fewer action potentials from the neuron. Only the shift in attention could account for this sort of modulation of the cell's excitability. Subsequent work has confirmed that attention can also remold the receptive fields of neurons in a variety of ways (Womelsdorf et al., 2008; Speed et al., 2020).
Here, a monkey has been trained to maintain central xation while directing covert attention. Within the receptive eld for the particular cortical neuron being recorded, the area being attended to is shown as a dashed circle.
In the rst condition the monkey's attention is directed to the area where the effective stimulus (yellow bar) will appear, not where the distracter (green bar) will appear.
The only difference in the second condition is that the attentional spotlight is directed away from where the yellow bar will appear.
Effective sensory stimulus for neuron Ineffective sensory stimulus for neuron
The yellow bar is less effective at ring the cell in the second condition. Because (1) the stimuli are identical in both conditions, (2) the xation point hasn't changed, and (3) the same cell is being recorded in both conditions, attentional mechanisms must have directly altered the individual neuron's responsiveness.
FIGURE 14.8 Effect of Selective Attention on the Activity of Single Visual Neurons (After J. Moran and R. Desimone, 1985. Science 229: 782.)
1. Define EEG and ERP, and explain how ERPs are measured. Why is the ERP a favored technique in cognitive neuroscience? 2. Match each of the following ERP phenomena--N1, P1, P3, N2pc--with one of these terms: pop-out, early selection, auditory attention, late selection, visual attention, distractors. 3. Describe an experimental procedure that can demonstrate the effects of selective attention on the activity of an individual neuron.
14.3Sources of Attention: A Network of Brain Sites Creates and Directs Attention
View Activity 14.1: Subcortical Sites Implicated in Visual Attention
In the section that follows, we turn our attention to the anatomy of attention: the network of cortical and subcortical sites that govern voluntary and reflexive attention. After studying this material, you should be able to: 14.3.1 Discuss the functions of the principal subcortical sites--the superior colliculus and the pulvinar--that are associated with shifts of visual attention. 14.3.2 Summarize the dorsal frontoparietal network that is believed to govern voluntary attention, illustrating this action with examples of research. 14.3.3 Summarize the right temporoparietal network associated with reflexive shifts of attention, and again provide relevant research examples. 14.4.4 Describe some of the most striking forms of attentional disorders and some medical approaches to treat them.
superior colliculus A gray matter structure of the dorsal midbrain that processes visual information and is involved in direction of visual gaze and visual attention to intended stimuli.
Whether attention comes reflexively, from the bottom up, or is controlled voluntarily, from the top down, it strongly affects neural processing in the brain, thereby augmenting electrophysiological activity. That doesn't mean that the sources of the different forms of attention are identical, however, or even that they are similar--just that their consequences are somewhat comparable. So let's turn to some of the details of the brain mechanisms that are the source of attention.
Superior colliculus Reticular activating system
FIGURE 14.9 Subcortical Sites Implicated in Visual Attention
Two subcortical systems guide shifts of attention Subcortical structures can be difficult to study because, deep in the center of the brain and skull, their activity is harder to measure with EEG/ERP and other noninvasive techniques. Our knowledge of their roles in attention thus comes mostly from work with animals. Single-cell recordings from individual neurons have implicated the superior colliculus, a midbrain structure (FIGURE 14.9), in controlling the movement of the eyes toward objects of attention, especially in overt forms of attention (Wurtz et al., 1982; Zhaoping, 2016). When the same eye movements are made but attention is directed elsewhere, a lower rate of firing by the collicular neurons is recorded. And in people with lesions in one superior colliculus, inhibition of return was reduced for visual stimuli on the affected side (Sapir et al., 1999). So it seems that the superior colliculus helps direct our gaze to attended objects, and it ensures that we don't return to them too soon after our gaze has moved on. The superior colliculus may also help direct the covert attentional spotlight: for example, monkeys in which the superior colliculus has been temporarily inactivated lose the ability to use selective attention cues (arrows, flashes, etc.) until the inactivation ends (Krauzlis et al., 2013).
The pulvinar, making up the posterior quarter of the human thalamus (see Fig-
ure 14.9), is heavily involved in visual processing, with widespread interconnections
between lower visual pathways, the superior colliculus, and many cortical areas.
The pulvinar is important for the orienting and shifting of attention. Monkeys
whose pulvinars are inactivated with drugs, and humans with strokes affecting the
pulvinar, may have great difficulty orienting covert attention toward visual targets
(D. L. Robinson and Petersen, 1992; Kraft et al., 2015). The pulvinar is also needed
to filter out and ignore distracting stimuli while we're engaged in covert attention
tasks, and in general it coordinates activity in larger-scale cortical networks accord-
ing to attentional demands (Saalman et al., 2012; Green et al., 2017). In humans,
attention tasks with larger numbers of distracters induce greater activation of the
pulvinar (M. S. Buchsbaum et al., 2006), indicating that this nucleus is also import- pulvinar In humans, the posterior
Several cortical areas are crucial for generating
The extensive connections between subcortical mechanisms of attention and the parietal lobes, along with observations from clinical cases that we will discuss shortly, point to a special role of the parietal lobes for attention control. Two integrated
A region in the monkey parietal lobe, homologous to the human intraparietal sulcus, that is especially involved in voluntary, top-down control of attention.
networks--dorsal frontoparietal and right temporoparietal--work together to continually select and shift between objects of interest, in coordination with subcortical
intraparietal sulcus (IPS) A region in the human parietal lobe, homologous to
the monkey lateral intraparietal area, that
is especially involved in voluntary, top-
A DORSAL FRONTOPARIETAL NETWORK FOR VOLUNTARY (TOP-DOWN) CONTROL
OF ATTENTION In monkeys, recordings from single cells show that a region called the lateral intraparietal area, or just LIP, is crucial for voluntary attention. LIP neurons increase their firing rate when attention--not gaze--is directed to particular locations, and it doesn't matter whether the voluntary attention is being directed
frontal eye field (FEF) An area in the frontal lobe of the brain that contains neurons important for establishing gaze in accordance with cognitive goals (top-down processes) rather than with any character-
toward visual or auditory targets (Bisley and Goldberg, 2003; Gottlieb, 2007). So it's
the top-down steering of the attentional spotlight that is
important to LIP neurons, not the sensory characteristics
The human equivalent of this system is a region
around the intraparietal sulcus (IPS) (FIGURE 14.10) that behaves much like the monkey LIP. For example, on tasks designed so that covert attention can be sustained long enough to make fMRI images, IPS activity is enhanced while participants are actively steering their attention
Dorsal frontoparietal system: Cognitive control of voluntary attention
(Corbetta and Shulman, 1998). And when researchers
used transcranial magnetic stimulation (see Chapter 2)
to temporarily inhibit the functioning of the IPS, the re-
search participants found it difficult to voluntarily shift
People with damage to a frontal lobe region called the
frontal eye field (FEF) (see Figure 14.10) struggle to pre-
vent their gaze from being drawn away toward peripheral
distracters while they're performing a voluntary attention task (Paus et al., 1991). Neurons of the FEF appear to be
crucial for ensuring that our gaze is directed among stimuli according to cognitive goals rather than eye-catching
Right temporoparietal system: Re exive capture of attention
characteristics of the stimuli. In effect, the FEF ensures that
cognitively controlled top-down attention gets priority. It's
no surprise, then, that the FEF is closely connected to the
superior colliculus, which, as we discussed earlier, is im-
FIGURE 14.10 Cortical Regions Implicated
Dorsolateral frontal, FEF vicinity During conscious shifts of covert attention, ER-fMRI shows activation of the frontal eye eld and the intraparietal sulcus (along with some activation of the temporal lobe). Superior temporal
FIGURE 14.11 The Frontoparietal Attention
A modified form of fMRI that links rapid behavioral events to changes in activity of selected brain regions (called, unsur-
prisingly, event-related fMRI, or ER-fMRI) reveals network ac-
tivities during top-down attentional processing (Hopfinger
From J. B. Hopfinger et al., 2000. Nat. Neurosci. 2: 284
et al., 2000, 2010). FIGURE 14.11 shows patterns of activation
while voluntary attention is shifting in response to a symbolic
cue. Enhanced activity is evident in the vicinity of the frontal
eye fields (dorsolateral frontal cortex) and, simultaneously, in
the IPS. Electrophysiological studies of the timing of activity
in the network indicate that the attentional control-related ac-
tivity is first seen in the frontal and parietal components, fol-
lowed by anticipatory activation of visual cortex (if the expected
stimulus is visual) or auditory cortex (if the stimulus is a sound)
(McDonald and Green, 2008; Green et al., 2011). Taken togeth-
er, these studies support the view that a dorsal frontoparietal network provides top-
A RIGHT TEMPOROPARIETAL NETWORK FOR REFLEXIVE (BOTTOM-UP) SHIFTS
OF ATTENTION A second attention system, located at the border of the temporal
and parietal lobes of the right hemisphere--and named, a little unimaginatively, the
temporoparietal junction (TPJ) (see Figure 14.10)--is involved in reflexive steering
of attention toward novel or unexpected stimuli (flashes, color changes, and so on).
ER-fMRI studies (FIGURE 14.12) confirm that there's a spike in right-hemisphere TPJ
activity if a relevant stimulus suddenly appears in an unexpected location (Corbet-
ta and Shulman, 2002; Igelström and Graziano, 2017). Interestingly, the TPJ system
receives direct input from the visual cortex, presumably providing direct access for
information about visual stimuli. The TPJ also has strong connections with the ventral
frontal cortex, a region that is involved in working memory (see Chapter 13). Because
working memory tracks sensory inputs over short time frames, this system may spe-
cialize in analyzing novelty by comparing present stimuli with those of the recent past.
Overall, the ventral TPJ system seems to act as an alerting signal, or "circuit breaker,"
overriding our current attentional priority if something new and unexpected happens.
temporoparietal junction (TPJ) The point in the brain where the temporal and parietal lobes meet. It plays a role in shifting attention to a new location after
Ultimately, the dorsal and ventral attention-control networks need to interact extensively and function as a single interactive system. According to one influential model (Corbetta and Shulman, 2002), the more dorsal stream of processing is responsible for voluntary attention, enhancing neural processing of stimuli and interacting with the
pulvinar and superior colliculus to steer the attentional spotlight around. At the same
time, the right-sided temporoparietal system scans the envi-
The Mind's Machine FoundationLs eofftBrain and BehaRviiogrh4te
ronment for novel salient stimuli (which then draw reflexive attention), rapidly reassigning attention as interesting stimuli pop
up. This basic model seems to apply across sensory modalities,
including both visual and auditory stimuli (Brunetti et al., 2008;
Temporoparietal junction (TPJ) When attention is captured by the sudden appearance of stimuli (exogenous attention), activity is evident in this righthemisphere system.
Brain disorders can cause specific impairments of attention One way to learn about attention systems in the brain is to carefully analyze the behavioral consequences of damage to specific regions of the brain. Research on people with attentional disorders shows that damage of cortical or subcortical attention mechanisms can dramatically alter our ability to understand and interact with the environment.
FIGURE 14.12 The Right Temporoparietal System for Reflexive Attention
RIGHT-HEMISPHERE LESIONS We've discussed ev idence that the right hemisphere normally plays a special role in attention (see Figure 14.12). Unfortunately, it is not
From M. Corbetta et al., 2000. Nat. Neurosci. 3: 292
uncommon for people to suffer strokes or other types of brain damage that particularly affect this part of the brain. The result--hemispatial neglect--is an extraordinary attention syndrome in which the person tends to completely disregard the left side of the world. People and objects to the left of the person's midline may be completely ignored, as if unseen, even though the person's vision is otherwise normal (Rafal, 1994). Someone with neglect may fail to dress the left side of their body, will not notice visitors if they approach from the left, and may fail to eat the food on the left side of their dinner plate. If touched lightly on both hands at the same moment, the person may notice only the right-hand touch--a symptom called simultaneous extinction. They may even deny ownership of their left arm or leg--"My sister must've left that arm in my bed; wasn't that an awful thing to do?!"--despite normal sensory function and otherwise intact intellectual capabilities. It is as if the normally balanced competition for attention between the two sides has become skewed and now the input from the right side of the world overrules or extinguishes the input from the left. Lesions in people with hemispatial neglect (FIGURE 14.13A) neatly overlap the frontoparietal attention network that we discussed earlier (shown again in FIGURE 14.13B). This overlap suggests that hemispatial neglect is a disorder of attention itself, and not a problem with processing spatial relationships, as was once thought (Mesulam, 1985; Bartolomeo, 2007). With time, hemispatial neglect can significantly improve (although simultaneous extinction often persists), and targeted therapies may help. For example, researchers are experimenting with the use of special prism glasses to shift vision to the right during intense physical therapy, in order to recalibrate the visual attention system (Barrett et al., 2012; O'Shea et al., 2017). BILATERAL LESIONS Parminder, whom we met at the beginning of the chapter, had bilateral lesions of the parietal lobe regions that are implicated in the attention network. While rare, biparietal damage can result in a dramatic disorder called Balint's syndrome, made up of three principal symptoms. First, people with Balint's syndrome have great difficulty steering their visual gaze appropriately (a symptom called oculomotor apraxia). Second, they are unable to accurately reach for objects using visual guidance (optic ataxia). And third--the most striking symptom--people with Balint's syndrome show a profound restriction of attention, to the point that only one object or feature can be consciously observed at any moment. This problem, called simultagnosia, can be likened to an extreme narrowing of the attentional spotlight, to the point that it can't encompass more than one object at a time. Hold up a comb or a pencil, and Parminder has no trouble identifying the object. But hold up both the comb and the pencil, and she can identify only one or the other. It's as though she is simply unable to consciously
(A) Critical areas damaged in hemispatial neglect
(B) Model of cortical attention control network
Diagnostic Test for Hemispatial Neglect When asked to duplicate drawings of common symmetrical objects, people with hemispatial neglect ignore the left side of the model that they're copying. (After V. W. Mark. 2003. Front. Biosci. 8: e172.) hemispatial neglect Failure to pay any attention to objects presented to one side of the body. Balint's syndrome A disorder, caused by damage to both parietal lobes, that is characterized by difficulty in steering visual gaze (oculomotor apraxia), in accurately reaching for objects using visual guidance (optic ataxia), and in directing attention to more than one object or feature at a time (simultagnosia). simultagnosia A profound restriction of attention, often limited to a single item or feature. Watson/Breedlove The Mind's Machine Foundations of Brain and Behavior 4e MM4e_UN14.03 08/26/20
This brain map is an average of the lesions of several people with hemispatial neglect.
Temporoparietal junction Note how the hemispatial-neglect lesions overlap with the proposed attentional networks discussed in the text and shown here.
FIGURE 14.13 Brain Damage in Hemispatial Neglect
experience more than one external feature at a time, despite having little or no loss of vision. Balint's syndrome thus illustrates the coordination of attention and awareness with mechanisms that orient us within our environment.
Difficulty with Sustained Attention Can Sometimes Be Relieved with Stimulants
At least 5% of all children are diagnosed with attention deficit hyperactivity disorder (ADHD), characterized as difficulty with directing sustained attention to a task or activity, along with a higher degree of impulsivity than in other children of the same age. About three-fourths of those diagnosed are male. Estimating the prevalence of ADHD (FIGURE 14.14) is complicated and very controversial; for example, there is significant variation in ADHD diagnosis and medication between different (sometimes neighboring) states within the USA, raising questions about the reliability of current diagnostic practices (Fulton et al., 2009). Nevertheless, researchers have identified several neurological changes associated with this disorder. Affected children tend to have slightly reduced overall brain volumes (about 3-4% smaller than in unaffected children), with reductions especially evident in the cerebellum and the frontal lobes (Arnsten, 2006). As we discuss elsewhere in the chapter, frontal lobe function is important for myriad complex cognitive processes, including the inhibition of impulsive behavior, as we will discuss below. (But remember, correlational studies like these are mute with regard to causation; we don't know whether the brain differences cause, or are caused by, the behavior.) In addition to structural changes, ADHD has been associated with abnormalities in connectivity between brain regions, such as within the default mode network, a neural system implicated in conscious reflection that we will discuss shortly (Cao et al., 2014). In fact, individual differences in the ability to sustain attention can be predicted with high accuracy from the strength of sets of brain connections (Rosenberg et al., 2016, 2017), even in the resting state, when the individual is not working on any particular task. Children with ADHD may have abnormal activity levels in some specific brain systems, such as the system that signals the rewarding aspects of activities (Furukawa et al., 2014). Based on a model of ADHD that implicates impairments in dopamine and norepinephrine neurotransmission, some researchers advocate treating these children with stimulant drugs like methylphenidate (Ritalin), which inhibits the synaptic reuptake of dopamine and norepinephrine, or with selective norepinephrine reuptake inhibitors
Percentage 5.0 5.1-7.0 7.1-9.0 9.1-11.0 11.1 The rate of diagnosis for ADHD varies by state. Is ADHD really more common in the Southeast, or is the behavior more likely to be regarded as a problem?
FIGURE 14.14 Prevalence of ADHD in the United States (After S. N. Visser et al., 2014. J. Am. Acad. Child Adolesc. Psychiatry 53: 34.)
like atomexetine (Strattera) (Schwartz and Correll, 2014). Stimulant treatment often improves the focus and performance of children with ADHD within traditional school settings, but this treatment remains controversial because of the significant risk of side effects. Furthermore, stimulants improve focus in everybody, not just people with ADHD, which raises doubts about the orthodox view that impaired neurotransmission is the sole cause of ADHD (del Campo et al., 2013). An emerging alternative view is that what is diagnosed as ADHD may simply be an extreme on a continuum of normal behavior. Allowing kids diagnosed with ADHD to fidget and engage in more intense physical activity effectively reduces their symptoms and improves task performance (Hartanto et al., 2016; Den Heijer et al., 2017). You can read more about ADHD Wanadtsaonn/oBthreeerddleovveelopmental disorder--autism spectrum disorder-- TinhAe MStienpd'Fs uMrtahcehrin1e3.4, on the website. Foundations of Brain and Behavior 4e
attention deficit hyperactivity disorder (ADHD) A syndrome characterized by distractibility, impulsiveness, and hyperactivity that, in children, interferes with school performance.
MM4e_14.14 06/25/20 1. Identify two subcortical structures that are implicated in the control of attention. What functions do they perform? 2. What is the general name for the cortical system responsible for conscious shifts of attention? What are its components, and what happens when those components are damaged? 3. Name the cortical system implicated in reflexive shifts of attention. Which specific regions are part of this system, and what happens if they are damaged?
Attention and Higher Cognition 453 14.4Consciousness, Thought, and Decision Making Are Mysterious Products of the Brain
The final part of the chapter looks at the most enigmatic, top-level product of the brain--consciousness--and its relationships with attention, reflection, and the executive processes that direct thoughts and feelings. After reading this section, you should be able to: 14.4.1 Provide a reasonable definition of consciousness, and name the neural networks and structures that, when activated, may play a special role in coordinating conscious states. 14.4.2 Discuss the relationship between consciousness as experienced by healthy people and the diminished levels of consciousness experienced by people in comas and minimally conscious states. 14.4.3 Discuss the impediments to the scientific study of consciousness, distinguishing between the "easy" and "hard" problems of consciousness, and how free will relates to the study of consciousness. 14.4.4 Provide an overview of the organization and function of the frontal lobes, and especially prefrontal cortex, as they relate to high-level cognition and executive functions. There can be no denying the close relationship between attention and consciousness; indeed, attention is the foundation on which consciousness is built. Whenever we are conscious, we're attending to something, be it internal or external. William James (1890) tried to capture the relationship between attention and consciousness when he wrote, "My experience is what I agree to attend to. Only those items which I notice shape my mind--without selective interest, experience is an utter chaos." We all experience consciousness, so we know what it is, but that experience is so personal, so subjective, that it's difficult to come up with an objective definition. Perhaps a reasonable attempt is to say that consciousness is the state of being aware that we are conscious and that we can perceive what's going on in our minds and all around us. However, "what's going on in our minds and all around us" covers an awful lot of ground. It includes our perception of time passing, our sense of being aware, our recollection of events that happened in the past, and our imaginings about what might happen in the future. Add to that our belief that we employ free will to direct our attention and make decisions, and we have a concept of immense scope. Which brain regions are active when we are conscious? Despite definitional complexities, consciousness is an active area of neuroscience research. So far, there are numerous competing theoretical models of consciousness, and a growing body of neuroscientific data. One approach is to look for patterns of synchronized activity in neural networks as people engage in conscious, inwardly focused thought. Using fMRI, researchers have identified a large circuit of brain regions--collectively called the default mode network, consisting of parts of the frontal, temporal, and parietal lobes--that seems to be selectively activated when we are at our most introspective and reflective, and relatively deactivated during behavior directed toward external goals (Raichle, 2015). In some ways you could think of it as a daydream network (and thereby also engage in metacognition: see Table 14.1). It has been proposed that dysfunction within the default mode network contributes to the symptoms of various cognitive problems, such as ADHD, autism spectrum disorder, schizophrenia, and dementia, in both adults and children (Whitfield-Gabrieli and Ford, 2012; Sato et al., 2015). Monkeys and lab rats have circuits that resemble the human default mode network on structural and functional grounds, raising the possibility that some nonhuman species may likewise engage in self-reflection or other introspective mental activity (Mantini et al., 2011; Sierakowiak et al., 2015). Some of the basic elements of human consciousness that researchers agree on are identified in TABLE 14.1, which also lists other species that may have comparable capacities and experiences.
consciousness The state of awareness of one's own existence, thoughts, emotions, and experiences. default mode network A circuit of brain regions that is active during quiet introspective thought.
TABLE 14.1 Elements of Consciousness in Humans and Other Animals
Theory of mind Mirror recognition Imitation Empathy and emotion Tool use Language Metacognition
Insight into the mental lives of others; understanding that other individuals act on their own unique beliefs, knowledge, and desires Ability to recognize the self as depicted in a mirror Ability to copy the actions of others; thought to be a stepping-stone to awareness and empathy Possession of complex emotions and the ability to imagine the feelings of other individuals Ability to employ found objects to achieve intermediate and/or ultimate goals Use of a system of arbitrary symbols, with specific meanings and strict grammar, to convey concrete or abstract information to any other individual that has learned the same language "Thinking about thinking": the ability to consider the contents of one's own thoughts and cognitions
Only chimpanzees, so far All great apes; dolphins; magpies; some elephants Many species, including cephalopods like the octopus Most mammals, ranging from primates and dolphins, to hippos and rodents; most vertebrates able to experience pleasure (and other basic emotions) Chimps and other primates; other mammals such as elephants, otters, and dolphins; birds such as crows and gulls Generally considered to be an exclusively human ability, with controversy over the extent to which the great apes can acquire language skills Nonhuman primates; dolphins
A practical alternative approach has been to study consciousness by focusing on people who lack it--people in comas or other states of reduced consciousness. Maps of brain activity in such people--or more precisely, maps of deactivated areas (Tsuchiya and Adolphs, 2007)--suggest that consciousness depends on a specific frontoparietal network (FIGURE 14.15) that includes much of the cortical attention network we've
These fMRI studies range from the temporary unconsciousness we all experience (sleep) to the profound and long-lasting unconsciousness of a persistent vegetative state. They share reduced activity of a frontoparietal network that includes dorsolateral prefrontal cortex (F), medial frontal cortex (MF), posterior parietal cortex (P), and posterior cingulate (Pr).
FIGURE 14.15 The Unconscious Brain
F P Pr MF From B. J. Baars et al., 2003. Trends Neurosci. 26: 671
been discussing, along with regions of medial frontal and cingulate cortices. Some researchers suspect that the claustrum (FIGURE 14.16)--a slender sheet of
neurons buried within the white matter of the forebrain lateral to the basal ganglia--plays a critical role in generating the experience of being conscious (Crick
One woman's consciousness could be instantly switched off when her claustrum--a mysterious gray matter region
and Koch, 2005; S. P. Brown et al., 2017), by virtue of its remarkable reciprocal connections with virtually every area of cortex, and especially prefrontal cortex. In
buried within the white matter of the brain--was electrically stimulated via an electrode. Consciousness
one case, a woman with a stimulating electrode in the claustrum experienced a "switching off" of conscious
returned immediately on cessation of stimulation.
awareness whenever a strong stimulation pulse was de-
livered through the electrode (Koubeissi et al., 2014); in
another case, consciousness was interrupted by bilateral electrical stimulation in lateral frontal cortex (Qurai-
shi et al., 2017), perhaps as a result of disrupting activity
in complex networks associated with consciousness. But is clinical unconsciousness really the inverse of consciousness? Perhaps it's not that simple. For one thing,
FIGURE 14.16 Consciousness Controller? (After M. Z. Koubeissi et al., 2014. Epilepsy Behav. 37: 32.)
some people in a persistent vegetative state (a very deep coma)
can be instructed to use two different forms of mental imagery to create distinct "yes"
and "no" patterns of activity on fMRI and then to use this mental activity to answer
questions (FIGURE 14.17) (Monti et al., 2010; Fernández-Espejo and Owen, 2013).
Functional MRI shows the brain activity of a healthy control participant asked to use two different mental images (playing tennis versus navigating) to signal "yes" or "no" answers to questions.
Watson/Breedlove The Mind's Machine Foundations of Brain and Behavior 4e MM4e_14.16 09/01/20
The strikingly similar brain activity of a person in a persistent vegetative state raises questions about the de nition of unconsciousness. The person was able to correctly answer a variety of questions using this technique, despite being in a state of apparently deep unconsciousness due to profound brain damage (as evident in the grossly abnormal MRI scan) and lacking behavioral responses.
FIGURE 14.17 Communication in "Unconscious" People (After M. M. Monti et al., 2010. NEJM 362: 579.)
456CHAPTER14 See Video 14.5: Reconstructing Brain Activity cognitively impenetrable Referring to basic neural processing operations that cannot be experienced through introspection--in other words, that are unconscious. easy problem of consciousness Understanding how particular patterns of neural activity create specific conscious experiences by reading brain activity directly from people's brains as they're having particular experiences. hard problem of consciousness Understanding the brain processes that produce people's subjective experiences of their conscious perceptions--that is, their qualia. quale A purely subjective experience of perception. free will The feeling that our conscious self is the author of our actions and decisions.
Most people in a vegetative state don't respond to questions and outside stimulation, but others in minimally conscious states may have considerable cognitive activity and awareness with little or no overt behavior (Gosseries et al., 2014). So, it's increasingly clear that we can't simply view a coma as an exact inverse of what we experience as consciousness. In any case, there seems to be more to consciousness than just being awake, aware, and attending. How can we identify and study the additional dimensions of consciousness? Some aspects of consciousness are easier to study than others Most of the activity of the central nervous system is unconscious. Scientists call unconscious brain functions cognitively impenetrable: they involve basic neural processing operations that cannot be experienced through introspection. For example, we see whole objects and hear whole words and can't really imagine what the primitive sensory precursors of those perceptions would feel like. Sweet food tastes sweet, and we can't mentally break it down any further. But those simpler mechanisms, operating below the surface of awareness, are the foundation that conscious experiences are built on. In principle, then, we might someday develop technology that would let us directly reconstruct people's conscious experience--read their minds--by decoding the primitive neural activity and assembling identifiable patterns from it. This is sometimes called the easy problem of consciousness: understanding how particular patterns of neural activity create specific conscious experiences. Of course, it's almost a joke to call this problem "easy," but at least we can fairly say that, someday, the necessary technology and knowledge may be available to accomplish the task of eavesdropping on large networks of neurons, in real time. Present-day technology offers a glimpse of that possible future. For example, if participants are repeatedly scanned while viewing several distinctive scenes, a computer can eventually learn to identify which of the scenes the participant is viewing on each trial, solely on the basis of the pattern of brain activation (FIGURE 14.18A) (Kay et al., 2008). Of course, this outcome relies on having the participants repeatedly view the same static images--hardly a normal state of consciousness. A much more complex problem is to reconstruct conscious experience from neural activity during a person's first exposure to a stimulus. So far, this has been accomplished for only relatively simple visual stimuli (FIGURE 14.18B) (Miyawaki et al., 2008) or brief video reconstructions (Nishimoto and Gallant, 2011). But it's a good start, and rapid progress seems likely as technological problems are solved. Alas, there is also the hard problem of consciousness, and it may prove impossible to crack. How can we understand the brain processes that produce people's subjective experiences of their conscious perceptions? To use a simple example, everyone with normal vision will agree that a ripe tomato is "red." That's the label that children all learn to apply to the particular pattern of information, entering consciousness from the color-processing areas of visual cortex, that is provoked by looking at something like a tomato. But that doesn't mean that your friend's internal personal experience of "red" is the same as yours. These purely subjective experiences of perceptions are referred to as qualia (singular quale). Because they are subjective and impossible to communicate to others--how can your friend know if "redness" feels the same in your mind as it does in hers?--qualia may prove impossible to study (FIGURE 14.18C). At this point, anyway, we are unable to even conceive of a technology that would make it possible. Our subjective experience of consciousness is closely tied up with the notion of free will: the belief that our conscious self is unconstrained in deciding our actions and decisions and that for any given moment, given exactly the same circumstances, we could have chosen to engage in a different behavior. After centuries of argument, there's still no agreement on whether we actually have free will, but most people behave as though there are always options, and in any event, there must be a neural substrate for the universal feeling of having free will. When participants intend to act (push a
(A) Pattern identi cation (B) Visual reconstruction + + (C) Subjective experience Both people instantly identify the color as red, but what differs is the way red feels in their minds. Actual color "Red" Watson/Breedlove The Mind's Machine
FIGURE 14.18 Easy and Hard Problems of Consciousness (Part A after K. N. Kay et al., 2008. Nature 452: 352; B after Y. Miyawaki et al., 2008. Neuron 60: 915.)
For a person in a brain scanner, repeatedly viewing the same image causes the same pattern of brain activity to occur each time. Over enough trials, researchers can develop computer models that identify which of about 20 images the participant is looking at.
"In the past, that pattern of brain activity only appeared when he was looking at the rabbit."
Scientists also know enough about how different parts of the brain are activated by light striking the retina that they can even predict what type of simple shapes a person is viewing.
"It looks like a `plus' sign." The "hard" problem is to go beyond predicting what a person is seeing to knowing what that person's subjective experience is like. Here, the participant and the researcher would both immediately identify the color being viewed as "red" but, as suggested by their respective thought bubbles, the participant's personal, internal, subjective experience may be quite different from that of the researcher. It is dif cult to see how we could ever be sure that we share any subjective experiences of consciousness. "I could tell he was looking at a red screen."
button, say), there is selective activation
screen ashing a sequence of random letters.
screen when I decided to press the button."
gions including dorsal prefrontal cortex (Lau et al., 2004), suggesting that these regions are important for our feelings
2 Whenever they choose, participants press a button with either their left hand or right hand.
which letter was on the screen when they decided to press a button.
the conscious experience of intention may come relatively late in the process of deciding what to do. Early research (Libet, 1985), using EEG and a precise
Our brains may decide what we'll do long before we are conscious of the decision. In this experiment, participants decided for themselves
Researchers found that they could use fMRI scans to predict when participants would "decide" to press the button. By 10 seconds before the conscious "decision," decision-making regions of the brain became active,
signaling movement preparation was evident 200 ms before participants consciously decided to move. Although
when to press a button, and whether to press with the right hand or the left.
and by 5 seconds the motor cortex associated with left- or right-hand button press became active.
controversy initially surrounded this work, later confirmatory research using
found, astonishingly, that brain activity
preted as meaning we have no free will, if our brain decides to push a button be-
At this point the participant has the conscious experience of making a choice.
that your brain has decided to push the left button, it was still your brain that made that decision, not someone else's brain. The conscious you may
FIGURE 14.19 Reading the Future (After C. S. Soon et al., 2008. Nat. Neurosci. 11: 543.)
be a Johnny-come-lately in the decision-making process, but that doesn't tell us whether your brain was truly free to choose the left button rather than the right, or to take the blue pill or the red.
In any event, the earliest indications of the decision-making process are found in
prefrontal cortex. Such involvement of prefrontal systems in most aspects of attention
and consciousness, regardless of sensory modality or emotional tone, suggests that the
prefrontal cortex is the main source of goal-driven behaviors (E. K. Miller and Cohen,
2001; Badre and Nee, 2018), as we discuss next.
Watson/Breedlove The Mind's Machine Foundations of Brain and Behavior 4e MM4e_14.19 06/23/20 executive function A neural and cognitive system that helps develop plans of action and organizes the activities of other high-level processing systems. prefrontal cortex The most anterior region of the frontal lobe.
A flexible frontal system plans and monitors our behavior How do we translate our inner thoughts into behavior? Careful analysis of impairments in people with localized brain damage, along with functional imaging studies in healthy people, shows that a network of anterior forebrain sites dominated by the frontal lobes--but including several other cortical and subcortical sites--is crucial for executive function, the suite of high-level cognitive processes that control and organize lower-level cognitive functions in line with our thoughts and feelings (Alvarez and Emory, 2006; Yuan and Raz, 2014). Some scientists liken executive function to a "supervisory system" that analyzes important stimuli, weighs competing ideas and hypotheses, and governs the creation of suitable "plans" for future action by drawing on cognitive processes like working memory, attention, feedback utilization, and so on. Executive function involves at least three interrelated processes: (1) smooth task switching between different cognitive operations, (2) continual updating of the
TABLE 14.2 Tests of Executive Functions
Wisconsin Card Sorting Test (WCST) (Weigl, 1941; Heaton et al., 1993) Controlled Oral Word Association Test (COWAT) (Benton and Hamsher, 1976) Stroop Test of Color-Word Interference (Stroop, 1935; MacLeod, 1991)
Sort cards into piles on the basis of the number, color, or shape of symbols on card face. Every 10 cards, discover and shift to a new sorting rule (see Figure 14.21). Say as many words as possible that start with a specific letter (F, A, or S), in 60 seconds. Read aloud as quickly as possible color names that are printed in the congruent color (e.g., BLUE) or incongruent color (e.g., BLUE).
Scoring Errors in sorting; perseveration in old sorting rule after rule change Total number of unique words uttered for all three starting letters Time and total errors
Functions sampled Task switching and abstract reasoning Verbal fluency, updating, working memory Response inhibition
cognitive plan based on new information and the contents of working memory, and (3) timely inhibition of responses that would compromise the plan (A. Diamond, 2013). A closely related account proposes that the crucial function of the frontal network is hierarchical cognitive control: the ability to direct shorter-term actions while simultaneously keeping longer-term goals in mind (Koechlin et al., 2003; Badre and Nee, 2018). Accordingly, a person with executive dysfunction due to frontal lesions who is given a simple set of errands may be unable to complete them without numerous false starts, backtracking, and confusion (Shallice and Burgess, 1991; Rabinovici et al., 2019). Several of the most widely studied tests of executive functions are described in TABLE 14.2. We have touched on some frontal lobe functions in earlier chapters--things like movement control, memory, language, psychopathology--but this mass of cortex also underlies other, more mysterious intellectual characteristics. Perhaps it reflects a bit of vanity about our species, but the large size of our frontal lobes-- about one-third of the entire cortical surface (FIGURE 14.20A)--also led to the long-standing view that the frontal cortex is the seat of intelligence and abstract thinking. The remarkable story of Phineas Gage, one of the most famous case studies in the history of neurology, underscores the subtlety and complexity of behaviors governed by the frontal lobes. Like Gage, people with discrete prefrontal lesions express various unusual emotional, motor, and cognitive changes. Widespread frontal damage may be associated with a persistent strange apathy, broken by bouts of euphoria (an exalted sense of well-being). Ordinary social conventions are readily cast aside by impulsive behavior. Concern for the past or the future may be absent (Petrides and Milner, 1982; Duffy and Campbell, 1994). Forgetfulness is shown in many tasks requiring sustained attention. In fact, some people with frontal damage even forget their own warnings to "remember." However, standard IQ test performance often shows only slight changes after prefrontal injury or stroke. On the basis of both structure and function, researchers distinguish between several major divisions of the human frontal lobes. The posterior portion of the frontal cortex includes motor and premotor regions (see Chapter 5). The anterior portion, usually referred to as prefrontal cortex, is immensely interconnected with the rest of the brain (Fuster, 1990; Mega and Cummings, 1994). It was prefrontal cortex that was surgically disrupted in frontal lobotomy--the notorious, now-discredited treatment for psychiatric disorders that we discussed in Chapter 12. Prefrontal cortex is further subdivided into dorsolateral and orbitofrontal regions (FIGURE 14.20B). Dorsolateral prefrontal cortex is closely associated with executive control, as it is crucial for working memory (holding information in mind while using it to solve problems) and task switching. People with lesions that include the
The human prefrontal cortex can be subdivided into a dorsolateral region (blue) and an orbitofrontal region (green). Lesions in these different areas of prefrontal cortex have different effects on behavior. (A) (B)
FIGURE 14.20 The Prefrontal Cortex
Images courtesy of S. Mark Williams and Dale Purves
Left from the collection of Jack and Beverly Wilgus; right after J. D. Van Horn et al., 2012. PLOS ONE 7: e37454, courtesy of Warren Anatomical Museum, Harvard Medical School
Phineas Gage Phineas P. Gage was a sober, polite, and capable member of a rail-laying crew, responsible for placing the charges used to blast rock from new rail beds. That's Gage on the left, holding a meter-long steel tamping rod. Perhaps the images on the right can help you guess why there appears to be something wrong with the left side of his face. In a horrific accident in 1848, a premature detonation blew that rod right through Gage's skull, on the trajectory shown in red, severely damaging both frontal lobes, especially in the orbitofrontal regions. Amazingly, Gage could speak shortly after the accident, and he walked up the stairs to a doctor's office, although no one expected him to live (Macmillan, 2000). In fact, Gage survived another 12 years, but he was definitely a changed man, so rude and aimless, and his powers of attention so badly impaired, "that his friends and acquaintances said that he was `no longer Gage.'" The historical account of Gage's case, now a neuroscience classic, was eventually found to closely agree with the symptoms in modern cases of people with frontal lobe damage (H. Damasio et al., 1994; Wallis, 2007).
perseverate Continue any activity beyond a reasonable degree.
dorsolateral prefrontal cortex may thus struggle with top-down conscious switching from one task to a new one, as in the Wisconsin Card Sorting Task (FIGURE 14.21), and tend to perseverate (continue beyond a reasonable degree) in any activity (B. Milner, 1963; Alvarez and Emory, 2006). Similarly, frontal lobe lesions may cause motor perseveration, repeating a simple movement over and over. However, the overall level of ordinary spontaneous motor activity is often quite diminished in people with frontal lesions. Along with movement of the head and eyes, facial expression of emotions may be greatly reduced. People with prefrontal lesions often have an inability to plan future acts and use foresight, as in the famous case of Phineas Gage. Their social skills may decline, especially the ability to inhibit inappropriate behaviors, and they may be unable to stay focused on any but short-term projects. They may agonize over even simple decisions. Some of the clinical features of damage to the subdivisions of prefrontal cortex are summarized in TABLE 14.3.
Watson/Breedlove The Mind's Machine Foundations of Brain and Behavior 4e MM4e_UN14.04 06/23/20
The participant starts sorting cards into piles on the basis of the number, color, or shape of the symbols, receiving only "correct" or "incorrect" feedback from the examiner to guide the sorting. The rule changes every 10 cards, so the participant must shift their sorting behavior until they discover the new rule. Here, the card should be added to pile 1 if the rule is "color," pile 2 if the rule is "number," or pile 4 if the rule is "shape."
FIGURE 14.21 The Wisconsin Card Sorting Task (WCST)
TABLE 14.3 Regional Prefrontal Syndromes
Prefrontal damage type Syndrome type Characteristics
Diminished judgment, planning, insight, and temporal organization; reduced cognitive focus; motor-programming deficits (possibly including aphasia and apraxia); diminished self-care Stimulus-driven behavior; diminished social insight; distractibility; emotional lability Diminished spontaneity; diminished verbal output; diminished motor behavior; urinary incontinence; lowerextremity weakness and sensory loss; diminished spontaneous prosody; increased response latency
A network that includes the orbitofrontal cortex appears to be crucial for goal-directed behaviors. For example, monkeys that must make decisions that could lead to rewards show increased orbitofrontal activation (Matsumoto et al., 2003); in general, orbitofrontal cortex seems to link pleasant experiences (e.g., eating a delicious meal) with reward signals generated elsewhere in the brain (Kringelbach, 2005). In fact, some researchers believe that orbitofrontal cortex is actually more important for anticipating outcomes than for learning (Schoenbaum et al., 2009), but either way the prospect of reward plays an important role. In humans performing tasks in which some stimuli have more reward value than others, the level of activation in prefrontal cortex correlates with how rewarding the stimulus is (Gottfried et al., 2003). This relationship seems to be a significant factor in gambling behavior and, more generally, is important for our decision-making processes, as we discuss next. We make decisions using a frontal network that weighs risk and benefit The waiter has brought over the dessert trolley, and it's decision time: do you go with the certain delight of the chocolate cake, or do you succumb to the glistening allure of the sticky toffee pudding? Or, do you allow yourself only a cup of black coffee, for the sake of your waistline? What happens in the brain when we make everyday decisions? In the lab, researchers usually evaluate decision making by using monetary rewards (instead of desserts, darn it) because money is convenient: you can vary how much money is at stake, how great a reward is offered, and so on, to accurately gauge how we really make economic decisions. These studies show that most of us are very averse to loss and risk: we are more sensitive to losing a certain amount of money than we are to gaining that amount. In other words, losing