Brain regions active during different economic decisions.

The editor's choice section of science magazine spotlights an interesting paper in J. Neurosci:

When we make economic decisions, for example the purchase of a good or a service, our brain has to perform at least three computations. First, it has to assess the goal value of the good: in economic terms, our maximal willingness to pay. Second, it has to assess the decision value of the good: the goal value minus the unavoidable costs. Third, there is a prediction error, which indicates the deviation from one's expectations of reward; the prediction error is positive when something better than expected happens and negative when the opposite occurs. Unfortunately, these three related quantities are intermingled and are often highly correlated, making it challenging to isolate the neural regions performing these computations.

Hare et al. have attempted to measure goal value, decision value, and prediction error in a single neuroimaging task so that they could dissociate these parameters. They found that ventral striatum activation reflected prediction error and not goal or decision value. However, activity in the medial orbitofrontal cortex and the central orbitofrontal cortex correlated with goal value and decision value, respectively.

Here is a summary figure from the paper:

Figure - Combined activation maps for goal values (GVs), decision values (DVs), and prediction errors (PEs). Activity correlated with GVs in the mOFC is shown in red, activity correlated with DVs in the cOFC is shown in yellow, and activity correlated with PEs in the ventral striatum is shown in green.

ScienceHack - monkey brain moving robotic arm

I stumbled across this site with interesting science videos from a number of areas (biology, psychology, robotics, etc.). They are mainly at a superficial 'gee whiz' level, but quite engaging. Here is the Monkey moving a robotic arm. This is work from the Pittsburgh group, described in Nature, which promises to lead to effective therapy for human patients paralyzed by strokes, spinal-cord injuries and degenerative neuromuscular disease.

Retaliation for unfairness - depends on serotonin

Nature highlights an article by Crockett et al. showing that serotonin modulates our reaction to unfairness. The experimenters:

...temporarily lowered serotonin (5-HT) levels in 20 volunteers and had them play the part of responder in the 'ultimatum game'. The responder can either accept the division of a sum of money offered by the game's proposer, in which case they both get their share, or reject it and deprive both players of the amounts proposed.

Although mood, fairness judgments, basic reward processing, or response inhibition, remained unchanged when players' serotonin levels were lowered, they were more likely to reject unfair and very unfair offers, defined as 30% and 20% of the stake, respectively.

A new perspective on culture-specific behavior

Yamagishi et al. demonstrate that the East Asian "preference" for conformity is actually a default strategy to avoid accrual of negative reputation. When the possibility for negative evaluations in a given situation was clearly defined, cultural differences in the tendency for uniqueness disappeared. The framework for analyzing the motivations for choices made by Japanese and Americans in a simple task is described in a summary in Science.

When offered a single colored pen from a group of five pens as a token payment for filling out a survey, Hokkaido students were less likely than Wolverines (Michigan students) to take a particular pen if it were the only one of that color available--that is, they would avoid reducing the scope of choice for subsequent people and thus, by incurring the cost of passing up the uniquely colored pen, not run the risk of making a negative impression on others. In contrast, a cultural psychological assessment would explain this outcome as revealing the preference (higher valuation) that East Asians place on conformity as opposed to the affinity of Westerners for individualism. When the choice task was expanded to include situations where the student was told explicitly that he was the first or the last of the five students to receive pens, the East-West difference disappeared; both Japanese and Americans were less likely to take the uniquely colored if they were the first and more likely (equally so) if they were the last to choose.

Yamagishi et al. suggest that:

... while cultural psychological perspectives are commendable for bringing culture into the mainstream of psychology, they have tended to be oversimplistic in attributing the cause of culture-specific behaviors to internalized cultural norms and values.

Their approach to the issue of the culturally grounded nature of human behavior is:

... from a game-theoretic perspective, and proposes an institutional approach as an alternative to the cultural psychology approach. The institutional approach to cultural differences views culture-specific behavior as strategies adapted to a set of collectively created social incentives. In this framework, no psychological concepts such as self-construals are required to interpret cultural differences, and thus the institutional approach can provide a more parsimonious explanation of cultural differences that can extend toward social science disciplines outside of psychology.

Obama and Neuroeconomics

In the New York Review of Books John Cassidy offers an interesting review of Nudge: Improving Decisions About Health, Wealth, and Happiness by Richard H. Thaler and Cass R. Sunstein.

If Obama isn't an old-school Keynesian, what is he? One answer is that he is a behavioralist—the term economists use to describe those who subscribe to the tenets of behavioral economics, an increasingly popular discipline that seeks to marry the insights of psychology to the rigor of economics...One of the reasons this approach has proved so popular is that it appears to provide a center ground between the Friedmanites and the Keynesians, whose intellectual jousting dominated economics for most of the twentieth century...Thaler and Sunstein lay out a number of principles that can be used to encourage better choice-making, and they apply them to various topical issues, including retirement saving, health care, and the environment. In a number of cases, the measures that Thaler and Sunstein recommend are mirrored by proposals in Obama's voluminous policy papers, which can be downloaded from his Web site.

The neural circuits of free choice

We often face alternatives that we are free to choose between. Planning movements to select an alternative involves several areas in frontal and parietal cortex. Pesaran et al. have looked at activity of single brain neurons in these areas when monkeys are free to choose which movement among several alternatives to make versus when they are following instructions. Correlations between simultaneously recorded spikes and local field potentials in dorsal premotor and parietal reach regions (which are anatomically connected into long-range circuits) increase during the free choice condition. They propose that a decision circuit featuring a sub-population of cells in frontal and parietal cortex may exchange information to coordinate activity between these areas, with cells participating in this decision circuit influencing movement choices by providing a common bias to the selection of movement goals.

Models of cognitive control in prefrontal cortex.

In the May issue of Trends in Cognitive Sciences David Badre reviews different models of the cognitive controls in our prefrontal cortex that support flexible behavior by selecting actions that are consistent with our goals and appropriate for our environment. I thought I would pass on two nice graphics from the papers, showing the structures and models involved. They do make the point that we have a long way to go before figuring out how the system works.

Figure (click to enlarge). Schematic of major anatomical sub-divisions in the frontal lobes. Boundaries and Brodmann areas (BA) are only approximate. Arrows indicate anatomical directions of anterior/rostral (front) versus posterior/caudal (back) and dorsal (up) versus ventral (down). From caudal to rostral, labeled areas include motor cortex, dorsal (PMd) and ventral premotor cortex, dorsal (pre-PMd) and ventral aspects of anterior premotor cortex, ventro- (VLPFC) and dorsolateral PFC (DLPFC), and lateral frontal polar cortex (FPC).


Figure: (Click to enlarge) Theoretical accounts of the rostro–caudal gradient in the PFC. (a) From a working memory perspective, rostral and caudal PFC can be distinguished on the basis of processing domain general versus specific representations. Hierarchical versions of this perspective propose that domain-specific posterior frontal regions can be modulated by the maintenance domain general rules in anterior DLPFC and FPC. (b) Relational complexity proposes a gradient in the PFC with respect to evaluation of simple stimulus properties, first-order relationships among the properties, and second-order relationships among relationships. (c) The cascade model proposes four levels of control that are distinguished by temporally disparate control signals, either sensory, context, episodic or branching. (d) Abstract representational hierarchy proposes that regions of the PFC are distinguished by the level of abstraction at which representations compete in a hierarchy of action representations.

Our brains can choose our actions 10 sec before awareness

Here is an elegant update from Soon et al. of the continuing story that started with Libet's original observation that supplementary motor area (SMA) becomes active before our subjective sense of consciously willing an action. This work ignited a a long controversy as to whether subjectively 'free' decisions are determined by brain activity ahead of time. These new results go substantially further than those of previous studies by showing that the earliest predictive information is encoded in specific regions of frontopolar and parietal cortex, up to 10 seconds before it enters awareness (and not in SMA), presumably reflecting the operation of a network of high-level control areas that begin to prepare an upcoming decision. This preparatory time period in high-level control regions is considerably longer than that reported previously for motor-related brain regions.


Figure (click to enlarge) Color-coded brain areas show regions where the specific outcome of a motor decision could be decoded before (bottom, green) and after (top, red) it had been made. The graphs separately depict for each time point the accuracy with which the subject's free choice to press the left or right button could be decoded from the spatial pattern of brain activity in that region (solid line, left axis; filled symbols, significant at P < 0.05; open symbols, not significant; error bars, s.e.m.; chance level is 50%). As might be expected, the decoding accuracy was higher in cortical areas involved in the motor execution of the response than in areas shaping the upcoming decision before it reaches awareness (note the difference in scale). The vertical red line shows the earliest time at which the subjects became aware of their choices. The dashed (right) vertical line in each graph shows the onset of the next trial. The inset in the bottom left shows the representative spatial pattern of preference of the most discriminative searchlight position in frontopolar cortex for one subject (ant, anterior; sup, superior)

Fairness activates brain reward circuitry.

Some interesting observations from Tabibnia et al. They:

...examined self-reported happiness and neural responses to fair and unfair offers while controlling for monetary payoff. Compared with unfair offers of equal monetary value, fair offers led to higher happiness ratings and activation in several reward regions of the brain. Furthermore, the tendency to accept unfair proposals was associated with increased activity in right ventrolateral prefrontal cortex, a region involved in emotion regulation, and with decreased activity in the anterior insula, which has been implicated in negative affect. This work provides evidence that fairness is hedonically valued and that tolerating unfair treatment for material gain involves a pattern of activation resembling suppression of negative affect.

Figure legend - Ventromedial prefrontal cortex (VMPFC), ventral striatum, and amygdala activation associated with fairness preference. The illustration (a) shows the location of clusters with significantly greater activation in response to fair compared with unfair offers.



Figure legend - Brain activation associated with the tendency to accept unfair offers. The illustrations show the location of areas in (a) left anterior insula and (c) right ventrolateral prefrontal cortex (right VLPFC) whose activation predicted this tendency.

Brain imaging can predict the mistakes you are about to make.

From Fountain's review of work by Eichele et al.:

...brain patterns start to change about 30 seconds before an error is committed... changes were seen in two brain networks. One, called the default mode region, is normally active when a person is relaxed and at rest. When a person is doing something, like playing the game, this region becomes deactivated...researchers found that in the time leading up to an error, the region became active again — the subject was heading toward a relaxed state...Another network in the right frontal lobe gradually became less active, the researchers found. This is an area in the brain thought to be related to cognitive control, Dr. Eichele said, to keeping “on task.”

...it might be possible someday to develop a warning system — perhaps by monitoring the brain’s electrical activity, which is more practical — that could be used by people doing monotonous or repetitive tasks. Such a system would alert users when they are heading for a harmful or costly, not to mention mindless, mistake.

8-month-old infants use intuitive statistics..

Here is a fascinating result from Xu and Garcia, a demonstration that our brains begin to employ statistics at a very young age. Here are some (slightly edited) clips from their paper:

One hallmark of human learning is that human learners are able to make inductive inferences given a small amount of data. Our hunter–gatherer ancestors may have tasted a few berries on a tree and then decided that all berries from the same kind of tree are edible. They may have encountered a few friendly people from a neighboring tribe and made the inference that people in that tribe are likely to be friendly in general. Once such generalizations are made, the inferences may go in the other direction as well. This type of statistical inference (going from samples to populations, and from populations to samples) is present in virtually every domain of learning, be it foraging, social interaction, visual perception, word learning, or causal reasoning . Inductive learning in general requires some understanding of intuitive statistics, perhaps a simpler version of what scientists do in laboratory experiments or field studies.

Xu and Garcia performed six experiments investigating whether 8-month-old infants are "intuitive statisticians." Their results show that, given a sample, the infants are able to make inferences about the population from which the sample had been drawn. Conversely, given information about the entire population of relatively small size, the infants are able to make predictions about the sample...This ability to make inferences based on samples or information about the population develops early and in the absence of schooling or explicit teaching. Human infants may be rational learners from very early in development.

Here is one of the experiments, which asked whether 8-month-old infants could use the information in a sample to make inferences about a larger population:

...8-month-old infants watched some events unfold on a puppet stage. Each infant was first given a set of six ping-pong balls in a small container to play with for a few seconds; half of the ping-pong balls were red, half were white. Then the infant was shown four familiarization trials. On each trial, a large box was brought onto the stage. The experimenter opened the front panel of the box and drew the infant's attention to the box. The box contained either mostly red ping-pong balls and a few white ping-pong balls or mostly white ping-pong balls and a few red ping-pong balls. The experimenter showed the infants these two displays alternately; thus the infants were equally familiarized with each display. Then the test trials began (see Fig. 1 for a schematic representation of the test events). On each test trial, the same box was brought onto the stage, its content not known to the infants. The experimenter shook the box for a few seconds, closed her eyes, reached into the top opening, and pulled out a ping-pong ball. She then placed it into a transparent sample display container next to the large box. A total of five ping-pong balls were drawn from the box, one at a time. In half of the test trials, a sample of four red and one white ping-pong balls were drawn. In the other half of the test trials, a sample of one red and four white ping-pong balls were drawn. After the five ping-pong balls were placed in the sample display container, the experimenter opened the front panel of the box to reveal its content. The infant's looking time was recorded. The experimenter then cleared the stage and started the next test trial until a total of eight test trials were completed. Only one outcome display was shown for each infant, either the mostly white or the mostly red one. On alternate test trials, the infants were shown the two samples (four red and one white or one red and four white). For an infant who saw the mostly red outcome display when the box was opened, the four red and one white sample was more probable and therefore expected, whereas the four white and one red ball sample was much less probable and therefore unexpected,{dagger} assuming each set was a random sample from the box. For an infant who saw the mostly white outcome display, the converse was true.


Figure - Schematic representation of the test events (Images 1, 3, and 5) The experimenter shook the box for a few seconds, closed her eyes, reached into the top opening, and pulled out a ping-pong ball. (Images 2, 4, and 6) She then placed the ball into a transparent sample display container next to the large box. Test outcomes are shown at the bottom.

The infants looked reliably longer at the unexpected outcome (M = 9.9s) than the expected outcome (M = 7.5 s). It appears that infants were able to predict the content of the box from which the samples had been drawn.

Rationalization of our choices - statistics rather than psychology?

Tierny has done it again - a really really kewl article on what appears to be an error in some classical psychological experiments on cognitive dissonance and rationalization. He provides online exercises you can do. Those early experiments suggested choice rationalization: Once we reject something, we tell ourselves we never liked it anyway (and thereby spare ourselves the painfully dissonant thought that we made the wrong choice). It turns out that in the free-choice paradigm used to test our tendency to rationalize decisions, any bias or slight preference for one of the initial choices can lead to results on subsequent choices that are explained by simple statistics rather than a psychological explanation. The article is worth a careful read...

The 'size' of an odor can influence our reaching to grasp an object.

An nice example from Tubaldi et al. of multisensory integration. They find that olfactory information contains highly detailed information able to elicit the planning for a reach-to-grasp movement suited to interact with the evoked object. From their paper:

The size of the object evoked by the odour has the potential to modulate hand shaping. Importantly, the fact that ‘size’ olfactory information modulates the hand at the level of individual digits (and not only the thumb-index distance as previously reported) leads to two important considerations in terms of sensorimotor transformation. First, from a perceptual perspective, the representation evoked by the odour seems to contain highly detailed information about the object (i.e., volumetric features rather than a linear dimension such as the thumb-index distance). If olfaction had provided a blurred and holistic object's representation (i.e., a low spatial-resolution of the object's image), then the odour would have not affected the hand in its entirety. Second, from a motor perspective, the olfactory representation seems to be mapped into the action vocabulary with a certain degree of reliability. The elicited motor plan embodies specific and selective commands for handling the ‘smelled’ object, and it is fully manageable by the motor system. Therefore, it is not an incomplete primal sketch which only provides a preliminary descriptive in the terms of motor execution.

Some of the details:

When the odour was ‘large’ and the visual target was small, only one finger joint (i.e., the mcp joint of the ring finger) was affected by the olfactory stimulus. In contrast, the influence of the ‘small’ odour on the kinematics of a reach-to-grasp movement towards a large target was much more evident and a greater number of joints were mobilized. This seems to suggest that planning for a reach-to-grasp movement on the basis of a ‘small’ odour when the target is large poses more constraints than when the odour is ‘large’ and the movement is directed towards a small target. Our proposal is that the motor plan elicited by the odour has to be modified according to the visual target. However such reorganization could be more easily managed without compromising object grasp when the odour is ‘large’ and the visual target is small than vice versa.

When a preceding odour elicits a motor plan which is congruent with the motor plan subsequently established for the visual target, the kinematic patterning is magnified. Therefore, the grasp plan triggered by the olfactory stimulus primed the grasp plan established for the visual target. This effect was evident at the very beginning of the movement, fading away during the second phase of the movement. For both the incongruent conditions the conflict between the ‘olfactory’ and the ‘visual’ grasp plans lasted for the entire movement duration. Importantly, and again in contrast with what reported for the incongruent conditions, an odour of a similar ‘size’ than the visual target, does not alter hand synergies with respect to when no-odour is presented. This indicates that when the ‘size’ of the odour and the size of the visual target match, the integration of the two modalities reinforces the grasp plan, the established synergic pattern is more ‘protected’ and it does not change. Having two sources carrying similar information leads to a more stable and coherent action.

Emonomics

Berreby offers an entertaining review of Ariely's new book "Predictably Irrational," which deals with behavioral economics - the experimental study of what people actually do when they buy, sell, change jobs, marry and make other real-life decisions. The book is a concise summary of why today’s social science increasingly treats the markets-know-best model as a fairy tale.

To see how arousal alters sexual attitudes, for example, Ariely and his colleagues asked young men to answer a questionnaire — then asked them to answer it again, only this time while indulging in Internet pornography on a laptop wrapped in Saran Wrap. (In that state, their answers to questions about sexual tastes,, violence and condom use were far less respectable.) To study the power of suggestion, Ariely’s team zapped volunteers with a little painful electricity, then offered fake pain pills costing either 10 cents or $2.50 (all reduced the pain, but the more expensive ones had a far greater effect). To see how social situations affect honesty, they created tests that made it easy to cheat, then looked at what happened if they reminded people right before the test of a moral rule. (It turned out that being reminded of any moral code — the Ten Commandments, the non-existent “M.I.T. honor system” — caused cheating to plummet.)

Our motor adaptation as a process of reoptimization.

Because I'm a classical pianist and am continually trying to optimize the motor performance involved, I'm fascinated by articles like this one by Izawa et al. They oppose the common assumption that the goal of motor adaptation is to compensate for some perturbation by returning to a previous baseline condition assumed to be optimal. Here is their abstract:

Adaptation is sometimes viewed as a process in which the nervous system learns to predict and cancel effects of a novel environment, returning movements to near baseline (unperturbed) conditions. An alternate view is that cancellation is not the goal of adaptation. Rather, the goal is to maximize performance in that environment. If performance criteria are well defined, theory allows one to predict the reoptimized trajectory. For example, if velocity-dependent forces perturb the hand perpendicular to the direction of a reaching movement, the best reach plan is not a straight line but a curved path that appears to overcompensate for the forces. If this environment is stochastic (changing from trial to trial), the reoptimized plan should take into account this uncertainty, removing the overcompensation. If the stochastic environment is zero-mean, peak velocities should increase to allow for more time to approach the target. Finally, if one is reaching through a via-point, the optimum plan in a zero-mean deterministic environment is a smooth movement but in a zero-mean stochastic environment is a segmented movement. We observed all of these tendencies in how people adapt to novel environments. Therefore, motor control in a novel environment is not a process of perturbation cancellation. Rather, the process resembles reoptimization: through practice in the novel environment, we learn internal models that predict sensory consequences of motor commands. Through reward-based optimization, we use the internal model to search for a better movement plan to minimize implicit motor costs and maximize rewards.

Watching yourself during a brain stroke...

This widely circulating video has some fascinating insights into the experience of having a stroke. Jill Bolte Taylor gives an very simplified description of left versus right hemisphere function and then describes the consequences of a hemmorage in her left hemisphere that formed a large clot pressing against the language area. She watched a flickering back and forth between having a self with thoughts and a la-la land or nirvana of pure awareness as she gradually lost motor and sensory control :

More on Brain Enhancement

Have a look at Benedict Carey's article, "Brain Enhancement Is Wrong, Right?," in the NY Times Week in Review of 3/9/08. It continues the topic of using performance enhancing drugs, following up on a Nature article that I mentioned in my Feb. 1 post on the same subject. By the way, I have been meaning to point you to Chris Chatham's excellent post on how to use caffeine properly, obtaining effects on cognitive performance equivalent to those of modifanil. Here are some clips from the Carey article:

...two Cambridge University researchers reported that about a dozen of their colleagues had admitted to regular use of prescription drugs like Adderall, a stimulant, and Provigil, which promotes wakefulness, to improve their academic performance. The former is approved to treat attention deficit disorder, the latter narcolepsy, and both are considered more effective, and more widely available, than the drugs circulating in dorms a generation ago.

Francis Fukuyama raises the broader issue of performance enhancement: “The original purpose of medicine is to heal the sick, not turn healthy people into gods.” He and others point out that increased use of such drugs could raise the standard of what is considered “normal” performance and widen the gap between those who have access to the medications and those who don’t — and even erode the relationship between struggle and the building of character.

People already use legal performance enhancers, he said, from high-octane cafe Americanos to the beta-blockers taken by musicians to ease stage fright, to antidepressants to improve mood. “So the question with all of these things is, Is this enhancement, or a matter of removing the cloud over our better selves?”.

“You can imagine a scenario in the future, when you’re applying for a job, and the employer says, ‘Sure, you’ve got the talent for this, but we require you to take Adderall.’ Now, maybe you do start to care about the ethical implications.”

Watching musical improvisation in the brain

Limb and Braun have done a fascinating functional MRI study of brain activity changes distinctively associated with improvisation in professional jazz pianists (compared to production of learned musical sequences). They suggest that a pattern of focal activation of the medial prefrontal (frontal polar) cortex, along with extensive deactivation of dorsolateral prefrontal and lateral orbital regions, may reflect a combination of psychological processes required for spontaneous improvisation, in which internally motivated, stimulus-independent behaviors unfold in the absence of central processes that typically mediate self-monitoring and conscious volitional control of ongoing performance.

The patterns they observe suggest cognitive dissociations that may be intrinsic to the creative process: the innovative, internally motivated production of novel material (at once rule based and highly structured) that can apparently occur outside of conscious awareness and beyond volitional control.

You can check out the experimental paradigms used and also listen to audio samples of the musical excerpts provided in supporting information.

Three-dimensional surface projection of activations and deactivations associated with improvisation during the Jazz paradigm. Medial prefrontal cortex activation, dorsolateral prefrontal cortex deactivation, and sensorimotor activation can be seen. The scale bar shows the range of t-scores; the axes demonstrate anatomic orientation. Abbreviations: a, anterior; p, posterior; d, dorsal; v, ventral; R, right; L, left.

The Advantages of Closing a Few Doors

John Tierney has a fascinating short article with the title of this post in the NY Times - noting studies that show most of us insist on keeping options open even when doing this is irrational and against our best interests. The article focuses on the work of Dan Ariely at M.I.T. and relates an interesting experiment which I suspect you will be able to relate to your own behavior:

They played a computer game that paid real cash to look for money behind three doors on the screen. (You can play it yourself, without pay, at tierneylab.blogs.nytimes.com.) After they opened a door by clicking on it, each subsequent click earned a little money, with the sum varying each time...As each player went through the 100 allotted clicks, he could switch rooms to search for higher payoffs, but each switch used up a click to open the new door. The best strategy was to quickly check out the three rooms and settle in the one with the highest rewards.

Even after students got the hang of the game by practicing it, they were flummoxed when a new visual feature was introduced. If they stayed out of any room, its door would start shrinking and eventually disappear...They should have ignored those disappearing doors, but the students couldn’t. They wasted so many clicks rushing back to reopen doors that their earnings dropped 15 percent. Even when the penalties for switching grew stiffer — besides losing a click, the players had to pay a cash fee — the students kept losing money by frantically keeping all their doors open.

Why were they so attached to those doors? The players...would probably say they were just trying to keep future options open. But that’s not the real reason, according to Dr. Ariely and his collaborator in the experiments, Jiwoong Shin, an economist who is now at Yale.

They plumbed the players’ motivations by introducing yet another twist. This time, even if a door vanished from the screen, players could make it reappear whenever they wanted. But even when they knew it would not cost anything to make the door reappear, they still kept frantically trying to prevent doors from vanishing...Apparently they did not care so much about maintaining flexibility in the future. What really motivated them was the desire to avoid the immediate pain of watching a door close.

“Closing a door on an option is experienced as a loss, and people are willing to pay a price to avoid the emotion of loss,” Dr. Ariely says. In the experiment, the price was easy to measure in lost cash. In life, the costs are less obvious — wasted time, missed opportunities. If you are afraid to drop any project at the office, you pay for it at home.

A primer on executive function in the prefrontal cortex

Gilbert and Burgess offer a brief review of our prefrontal brain cortex structures that enable our flexible responses to situations with alternative choices. I think it provides a good look-up reference, and so I want to excerpt a few of the summary figures and text here:

At the heart of most (but not all) theories of executive function is a distinction, or gradation, between routine (or ‘automatic’) and non-routine (or ‘controlled’) processing. Routine processing refers to mental operations that are well rehearsed or overlearned, for example reading out a word. By contrast, non-routine processing most commonly refers to mental operations that are used in situations when there is not a well-established stimulus-response association, or where a behavioural impasse has occurred (for example one notices an error, or realises that one is behaving in a sub-optimal fashion). The term ‘executive functions’ has become synonymous with those behaviours and abilities.

Determining the relative contributions of different frontal subregions to different executive functions is a highly complex matter, both theoretically and methodologically. On current evidence, however, one can make some preliminary suggestions. The figure illustrates some of the major subdivisions of the human PFC, which may be divided into lateral and medial surfaces. On the lateral surface, the PFC may be further subdivided into ventrolateral, dorsolateral, and rostral regions. Although the medial PFC is depicted as a single area in the figure, there is now strong evidence that this part of PFC can also be subdivided both on cytoarchitectonic and functional grounds. The figure shows the lateral surface split into a ventrolateral region (VLPFC), dorsolateral region (DLPFC) and rostral region (RPFC). The medial surface (MPFC) is illustrated as a single region, but recent studies indicate considerable anatomical and functional variation within this region as well. (Click to enlarge)


Ventrolateral PFC (VLPFC) is thought to be involved in comparatively simple tasks, such as short-term maintenance of information that cannot currently be perceived in ‘working memory’ (for example, memorising a phone number you have just been told, before keying the numbers into a telephone). It has also been proposed — although this is controversial — that different parts of the VLPFC are used to store different types of information (for example, the sound of a word versus its meaning). By contrast, dorsolateral PFC (DLPFC) has been most commonly implicated not so much in maintaining information that is no longer available in our environment, but in manipulating that information. For example, although DLPFC is probably not involved in processes such as remembering a telephone number, it does seem to play a role in more difficult tasks, such as dialling the number in reverse order (rearranging the digits that we have just been told). DLPFC has also been suggested to be involved in complex functions such as making plans for the future.

A brain region with strong projections to and from the DLPFC is the anterior cingulate cortex (ACC), part of the medial PFC. One influential theory proposes that this brain region detects the need for control, for example where there is competition between two or more ways of behaving in a certain situation, both of which may be triggered by events in our environment, requiring top-down input to resolve the conflict. It is suggested that the ACC does not itself provide higher-level modulation of lower-level processes, but instead signals to DLPFC when such higher-level modulation is required.

The largest, but most mysterious, sub-region of prefrontal cortex is the rostral PFC (RPFC). As a proportion of whole-brain volume, some have estimated the human RPFC to be twice as large as the corresponding region in the chimpanzee brain. Yet curiously, patients with damage restricted to the RPFC often perform well on standard neuropsychological tests, including ‘classical’ tests of executive function such as the Wisconsin card sorting test. Instead, patients with damage to this region seem to have particular difficulty in real-world ‘multitasking’ situations, such as organising a shopping trip when there are few strict constraints — participants are relatively free to organise their behaviour however they like — but there are also multiple instructions to be remembered, rules to be followed, and potential distractions in the environment. Recent accounts have focused on the role of RPFC in the most high-level human abilities, such as combining two distinct cognitive operations in order to perform a single task, trying to work out what other people are thinking (‘mentalising’), and reflecting on information we retrieve from long-term memory (‘source memory’, for example trying to work out when we last saw a person familiar to us). We recently put forward the unifying hypothesis that this brain region serves as a ‘gateway’ between cognitive processes directed towards current incoming perceptual information, versus information that we generate ourselves. We have also shown (see following figure) by a meta-analysis of functional neuroimaging results that there are distinct functions associated with different parts of the RPFC, with segregation especially between lateral versus medial regions, and between rostral versus caudal regions. (Click to enlarge)