Psychology Wiki

Assessment | Biopsychology | Comparative | Cognitive | Developmental | Language | Individual differences | Personality | Philosophy | Social |
Methods | Statistics | Clinical | Educational | Industrial | Professional items | World psychology |

Cognitive Psychology: Attention · Decision making · Learning · Judgement · Memory · Motivation · Perception · Reasoning · Thinking  - Cognitive processes Cognition - Outline Index

Brain animated color nevit.gif

Brain functions

Arousal Attention
Decision-makingExecutive functions
Motor coordinationPerception
PlanningProblem solving


Arthur L. BentonAntonio Damasio
Phineas GageNorman Geschwind
Donald HebbAlexander Luria
Muriel D. LezakBrenda Milner
Karl PribramOliver Sacks
Roger Sperry


Bender-Gestalt Test
Benton Visual Retention Test
Clinical Dementia Rating
Continuous Performance Task
Hayling and Brixton tests
Lexical decision task
Mini mental state examination
Stroop task
Wechsler Adult Intelligence Scale
Wisconsin card sorting task

Main article: Cognitive ability

The executive system is a theorized cognitive system in psychology that controls and manages other cognitive processes. It is also referred to as the executive function, executive functions, supervisory attentional system, or cognitive control.

The concept is used by psychologists and other neuroscientists to describe a loosely defined collection of brain processes which are responsible for planning, cognitive flexibility, abstract thinking, rule acquisition, initiating appropriate actions and inhibiting inappropriate actions, and selecting relevant sensory information.[citations needed]

Hypothesized role

The executive system is thought to be heavily involved in handling novel situations outside the domain of some of our 'automatic' psychological processes that could be explained by the reproduction of learned schemas or set behaviors. Psychologists Don Norman and Tim Shallice have outlined five types of situation where routine activation of behavior would not be sufficient for optimal performance[1]:

  1. Those that involve planning or decision making.
  2. Those that involve error correction or troubleshooting.
  3. Situations where responses are not well-learned or contain novel sequences of actions.
  4. Dangerous or technically difficult situations.
  5. Situations which require the overcoming of a strong habitual response or resisting temptation.

The executive functions are often invoked when it is necessary to override responses that may otherwise be automatically elicited by stimuli in the external environment. For example, on being presented with a potentially rewarding stimulus, such as a tasty piece of chocolate cake, the automatic response might be to take a bite. However, where this behaviour conflicts with internal plans (such as having decided not to eat chocolate cake whilst on a diet), the executive functions might be engaged to inhibit this response. The neural mechanisms by which the executive functions are implemented is a topic of ongoing debate in the field of cognitive neuroscience.

Neuropsychologist Elkhonon Goldberg, a disciple of Alexander Luria, introduced the metaphor of the prefrontal cortex as the director of an orchestra and the cortex as the front rows in order to explain the role of executive functions.

Historical perspective

Although research into the executive functions and their neural basis has increased markedly over the past 5 years, the theoretical framework in which it is situated is not new. In the 1950s, the British psychologist Donald Broadbent drew a distinction between 'automatic' and 'controlled' processes (a distinction characterized more fully by Shiffrin and Schneider in 1977),[2] and introduced the notion of selective attention, to which executive functions are closely allied. In 1975, the US psychologist Michael Posner use the term "cognitive control" in his book chapter entitled 'Attention and cognitive control'.[3]

The work of influential researchers such as Michael Posner, Joaquin Fuster, Tim Shallice, and their colleagues in the 1980s (and later Trevor Robbins, Bob Knight, Don Stuss and others) laid much of the groundwork for recent research into executive functions. For example, Posner proposed that there is separate 'executive' branch of the attentional system, which is responsible for focusing attention on selected aspects of the environment.[4] The British neuropsychologist Tim Shallice similarly suggested that attention is regulated by a 'supervisory system', which can override automatic responses in favour of scheduling behaviour on the basis of plans or intentions.[5] Throughout this period, a consensus emerged that this control system is housed in the most anterior portion of the brain, the prefrontal cortex (PFC)

Psychologist Alan Baddeley had proposed a similar system as part of his model of working memory[6] and argued that there must be a component (which he named the 'central executive') that allows information to be manipulated in short term memory (for example, when doing mental arithmetic).

The Development of the Executive System

Genetic influences on Executive Function

A spate of recent studies has explored genetic and environmental influences on the development of the executive system. On one hand, some researchers have claimed that 99% of the variance in executive function is caused by genes, whilst other researchers have isolated environmental correlates of executive function and claimed that these are important to its development. One should note that, whilst estimates of hereditary are not perfect and often misinterpreted [7], environmental correlates of executive function (e.g. parenting style) may not be causational.

In 2008, Naomi Friedman and colleagues produced an astonishing claim that 99% of variance in one's executive function ability can be explained by genes, leaving little room for environmental influences [8] . The researchers used a composite measure of executive functioning which isolates a latent executive function factor across a battery of executive tests (see factor analysis). Previous studies have suggested that only 20-70% of variance in individual tasks of executive function can be attributed to genes, however the measure employed here can be seen as superior since it extracts only the variance common to all the tests used in the executive function battery, which is used as a purer measure of executive function. As part of the "unity and diversity" model of executive functions, the researchers used factor-analytic techniques to separate genetic influences on the common executive system and on its separate components (inhibition, updating and shifting). Interestingly, the three inhibition tasks which made up the "inhibiting" executive function component shared 100% of its genetic influence with the common EF factor, thus having no unique heritability from the common executive function factor. On the other hand, the updating and shifting components were 66% & 67% uniquely heritable. Environmental factors accounted for 13% of the variance in the shifting component, and close to zero for the other two. 

Environmental Influences on Executive Function

On the other hand, researchers have also shown that executive ability correlates with various environmental factors. Researchers have looked at various aspects of parenting style which may affect the executive function of their children. In addition, various intervention studies have shown that executive function can be improved by environmental factors, suggesting a role for the environment.

The effect of various parenting factors on child executive function has been studied, including: sensitivity, "maternal autonomy support", parental use of words, family chaos and inconsistent parenting. "Maternal autonomy support" is a composite measure of scaffolding, supportive verbal behavior and flexibility of a parent to a child during a problem-solving task, and has been shown to have good inter-rater reliability. Annie Bernier and colleagues found some small correlations between maternal sensitivity (r=.26) and maternal autonomy support (r=.32) on executive tasks measuring conflict [9]. The effect of general cognitive development was partialled out of the correlation estimates, ruling out this as a possible explanatory factor, however the effect of social class could remain a viable mediating factor between better test performance and parenting style. A separate study showed that parental education and parental income did not mediate the effect of maternal autonomy support, however the child's vocabulary completely mediated the effect of maternal autonomy support on executive function [10].

Claire Hughes and Rosie Ensor have also showed that family chaos (r=-.2), inconsistent parenting (r=-.2) and parental scaffolding (r=.3) also correlated with improved executive function at age 4 compared to age 2, and with the effect of verbal ability at age 4 partialled out [11]. The first two variables were measured as self-reports from a parent, whereas as with other studies scaffolding was measured through behavioural ratings of a parent during a task with their child. The effect size of most of these factors is rather small (r<.40 normally), however most of these studies do not take into account the attenuating effect of measurement error on effect sizes, so it is difficult to compare to the proposed effect of genes on executive function.

Miller & Cohen's (2001) model

More recently, in 2001, Earl Miller and Jonathan Cohen published an influential article entitled 'An integrative theory of prefrontal cortex function' in which they argue that cognitive control is the primary function of the PFC, and that control is implemented by increasing the gain of sensory or motor neurons that are engaged by task- or goal-relevant elements of the external environment.[12] In a key paragraph, they argue:

'We assume that the PFC serves a specific function in cognitive control: the active maintenance of patterns of activity that represent goals and the means to achieve them. They provide bias signals throughout much of the rest of the brain, affecting not only visual processes but also other sensory modalities, as well as systems responsible for response execution, memory retrieval, emotional evaluation, etc. The aggregate effect of these bias signals is to guide the flow of neural activity along pathways that establish the proper mappings between inputs, internal states, and outputs needed to perform a given task.'

Miller and Cohen draw explicitly upon an earlier theory of visual attention which conceptualises perception of a visual scene in terms of competition among multiple representations - such as colors, individuals, or objects.[13] Selective visual attention acts to 'bias' this competition in favour of certain selected features or representations. For example, imagine that you are waiting at a busy train station for a friend who is wearing a red coat. You are able to selectively narrow the focus of your attention to search for red objects, in the hope of identifying your friend. Desimone and Duncan argue that the brain achieves this by selectively increasing the gain of neurons responsive to the color red, such that output from these neurons is more likely to reach a downstream processing stage, and consequently to guide behaviour. According to Miller and Cohen, this selective attention mechanism is in fact just a special case of cognitive control - one in which the biasing occurs in the sensory domain. According to Miller and Cohen's model, the PFC can exert control over input (sensory) or output (response) neurons, as well as over assemblies involved in memory, or emotion. Cognitive control is mediated by reciprocal connectivity between the PFC and both sensory, limbic, and motor cortices. Within their approach, thus, the term 'cognitive control' is applied to any situation where a biasing signal is used to promote task-appropriate responding, and control thus becomes a crucial component of a wide range of psychological constructs such as selective attention, error monitoring, decision-making, memory inhibition and response inhibition.

Psychometric Models of Executive Function

Psychometric analyses of Executive function have had two inter-related aims: improving the measurement of executive function, and outlining models of executive function.

Measurement of Executive Function

Executive function tests typically have poor psychometric (measurement) qualities. In most executive function studies, inter-correlations between tasks which aim to measure executive function are typically low (r<.40 in nearly all cases). [14] Such low correlations are put down to the so-called problem of "task impurity"[15]; that even when tests are designed to assess specific executive functioning abilties, it is inescapable that cognitive factors other than those intended to be measured affect performance. For example, the archetypal executive function "planning" task, the "Tower of Hanoi", requires individuals to match a current configuration of disks on four pegs to an ending configuration shown on a piece of paper- however various rules about how the disks can be moved and the maximum number of moves increases demands on planning ability. One can imagine that factors other than planning affect task performance, such as spatial working memory. Other problems include the low test-retest reliability of tasks, however it is sometimes assumed that a re-presentation of a task will never measure the same amount of "controlled" executive behavior as our responses become more automatic. [16]Finally, executive functions are hypothesised to have a low process-behaviour correspondense; in other words the executive is a very domain general entity which manifests itself in lots of different behaviors. One can compare this to facial recognition cognition, which manifests itself in narrow situations, and is more easily measured.

The "Unity and Divesity" Model

This model was formally proposed in Akira Miyake, Naomi Friedman and colleageues in an influential 2000 paper. [17] The research tried to address the somewhat vague notions of executive system that existed, with some researchers defining executive tasks as being purely "frontal lobe", and others defining executive function as being everything from "controlled" behavior to planning and working memory. [18] Even before this line research, most researchers did not see the executive system a single entity (probably because of the large number of processes it has been implicated in), but something multi-dimensionsal with "relatively independant subfunctions"[19].

Miyake & Friedman's analysis of 9 different executive function tests allowed the researchers to test the fit of three different models onto the data, namely; can the test performances be best explained by variation in 1, 2 or 3 different abilities? A three-factor model was the best fit of the data, and thus three different "latent factors" were proposed as subcomponents of executive functioning, which included: "shifting" (the ability to change between mental sets or tasks), "updating" (updating or monitoring working memory) and "inhibition" (ability to inhibit an automatic response). The "factor loadings" describe to what extent variance in these tasks is explainable by the subcomponents of executive function, and these varied from 11% to 40%. One should be reminded that the outcome of any factor analysis is clearly tied to the number and nature of the tasks included in the analysis, and the subcomponents found in this study are not meant to be conclusive. Indeed, when analysing 9 tests that are meant to analyse just inhibition, researchers found that inhibition could be described by three further subdivisions. [20] However, the analysis of the three aforementioned components has been dominant in the literature. 

The "Unity" aspect of the model comes from the finding that subcomponents of executive function) tend to correlate with each other. For example, in Miyake's original study[21], the components of executive function correlated with each other quite strongly (.42 < r < .63). Miyake suggested that a common executive system or task requirement such as "the maintenance of goal and context infomation in working memory" [22]could explain this correlation. However, the researchers do not even contemplate the possibility that general intelligence (or "g") explains the "unity" in the analyses. This is especially strange, since the only concrete definition of "g" is that it is the phenomena of "positive manifold" (poitive correlations) between cognitive tests [23] . Later analyses have suggested that general intelligence may indeed be a factor influencing the "unity" of executive functions. [24]

Some obvious limitations of this line of research is that one-word entities such as "updating" are nearly equally vague and amorphous as concepts such as "executive function". In addition, correlations between tasks does not necessarily entail functional relationships. For example, one would expect a correlation between top speed of a car and the price of interior fittings, however this relationship is not directly causal. However, the top speed of the car, its miles per gallon, the expense of its seperate components, we would all expect to correlate to a factor which represents how "premium" it is, which can also be thought of as a relatively amorphous property (like "updating" ability). In conclusion, psychometric models gives the field more conceptual clarity, and the use of factor-analytic techniques allows for better measuement.

Experimental evidence

The executive system has been traditionally quite hard to define, mainly due to what psychologist Paul W. Burgess calls a lack of "process-behaviour correspondence"[25]. That is, there is no single behavior which can in itself be tied to executive function, or indeed executive dysfunction. For example, it is quite obvious what reading impaired patients cannot do, but it is not so obvious as to exactly what executive impaired patients might be incapable of.

This is largely due to the nature of the executive system itself. It is mainly concerned with the dynamic, 'online' co-ordination of cognitive resources and hence its effect can only be observed by measuring other cognitive processes. Similarly, it does not always fully engage outside of real-world situations. As neurologist Antonio Damasio has reported, a patient with severe day-to-day executive problems may still pass paper-and-pencil or lab-based tests of executive function[26].

Theories of the executive system were largely driven by observations of patients who had suffered frontal lobe damage. They exhibited disorganized actions and strategies for everyday tasks (a group of behaviors now known as dysexecutive syndrome) although they seemed to perform normally when clinical or lab based tests were used to assess more fundamental cognitive functions such as memory, learning, language and reasoning. It was hypothesized that, to explain this unusual behaviour, there must be an overarching system that co-ordinates other cognitive resources.

Much of the experimental evidence for the neural structures involved in executive functions comes from laboratory tasks such as the Stroop task or the Wisconsin Card Sorting Task (WCST). In the Stroop task, for example, human subjects are asked to name the color that color words are printed in when the ink color and word meaning often conflict (for example, the word 'RED' in green ink). Executive functions are needed to perform this task, as the relatively overlearned and automatic behaviour (word reading) has to be inhibited in favour of a less practiced task - naming the ink color. Recent functional neuroimaging studies have shown that two parts of the PFC, the anterior cingulate cortex (ACC) and the dorsolateral prefrontal cortex (DLPFC), are thought to be particularly important for performing this task. However, functional neuroimaging studies alone cannot prove that a given (activated) brain region is critical for task performance - that requires neuropsychology, e.g. [27] as well as other loss-of-function studies using Transcranial Magnetic Stimulation, e.g. [28]

Context-sensitivity of PFC neurons

Other evidence for the involvement of the PFC in executive functions comes from single-cell electrophysiology studies in non-human primates, such as the macaque monkey, which have shown that (in contrast to cells in the posterior brain) many PFC neurons are sensitive to a conjunction of a stimulus and a context. For example, PFC cells might respond to a green cue in a condition where that cue signals that a leftwards saccade should be made, but not to a green cue in another experimental context. This is important, because the optimal deployment of executive functions is invariably context-dependent. To quote an example offered by Miller and Cohen, a US resident might have an overlearned response to look left when crossing the road. However, when the 'context' indicates that he or she is in the UK, this response would have to be suppressed in favour of a different stimulus-response pairing (look right when crossing the road). This behavioural repertoire clearly requires a neural system which is able to integrate the stimulus (the road) with a context (US, UK) to cue a behaviour (look left, look right). Current evidence suggests that neurons in the PFC appear to represent precisely this sort of information. Other evidence from single-cell electrophysiology in monkeys implicates ventrolateral PFC (inferior prefrontal convexity) in the control of motor responses. For example, cells have been identified which increase their firing rate to NoGo signals[29] as well as a signal that says "don't look there!"[30]

Evidence for attentional biasing in sensory regions

Electrophysiology and functional neuroimaging studies involving human subjects have been used to describe the neural mechanisms underlying attentional biasing. Most studies have looked for activation at the 'sites' of biasing, such as in the visual or auditory cortices. Early studies employed event-related potentials to reveal that electrical brain responses recorded over left and right visual cortex are enhanced when the subject is instructed to attend to the appropriate (contralateral) side of space.[31] The advent of bloodflow-based neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) has more recently permitted the demonstration that neural activity in a number of sensory regions, including color-, motion-, and face-responsive regions of visual cortex, is enhanced when subjects are directed to attend to that dimension of a stimulus, suggestive of gain control in sensory neocortex. For example, in a typical study, Liu and coworkers[32] presented subjects with arrays of dots moving to the left or right, presented in either red or green. Preceding each stimulus, an instruction cue indicated whether subjects should respond on the basis of the colour or the direction of the dots. Even though colour and motion were present in all stimulus arrays, fMRI activity in colour-sensitive regions (V4) was enhanced when subjects were instructed to attend to the colour, and activity in motion-sensitive regions was increased when subjects were cued to attend to the direction of motion. Several studies have also reported evidence for the biasing signal prior to stimulus onset, with the observation that regions of the frontal cortex tend to come active prior to the onset of an expected stimulus.[33]

Connectivity between the PFC and sensory regions when executive functions are used

Despite the growing currency of the 'biasing' model of executive functions, direct evidence for functional connectivity between the PFC and sensory regions when executive functions are used, is to date rather sparse.[34] Indeed, the only direct evidence comes from studies in which a portion of frontal cortex is damaged, and a corresponding effect is observed far from the lesion site, in the responses of sensory neurons.[35][36] However, few studies have explored whether this effect is specific to situations where executive functions are required. Other methods for measuring connectivity between distant brain regions, such as correlation in the fMRI response, have yielded indirect evidence that the frontal cortex and sensory regions communicate during a variety of processes thought to engage executive functions, such as working memory,[37] but more research is required to establish how information flows between the PFC and the rest of the brain when executive functions are used.

Top down inhibitory control

Aside from facilitatory or amplificatory mechanisms of control, many authors have argued for inhibitory mechanisms in the domain of response control,[38] memory,[39] selective attention,[40], theory of mind[41], [42], emotion regulation [43], as well as social emotions such as empathy.[44] A recent review was written on this topic, arguing that active inhibition is a valid concept in some domains of psychology/cognitive control. [45]

More recent contributions

Other important evidence for executive functions processes in the prefrontal cortex have been described. One widely-cited review article[46] emphasises the role of the medial part of the PFC in situations where executive functions are likely to be engaged – for example, where it is important to detect errors, identify situations where stimulus conflict may arise, make decisions under uncertainty, or when a reduced probability of obtaining favourable performance outcomes is detected. This review, like many others,[47] highlights interactions between medial and lateral PFC, whereby posterior medial frontal cortex signals the need for increased executive functions and sends this signal on to areas in dorsolateral prefrontal cortex that actually implement control. Yet there has been no compelling evidence at all that this view is correct, and indeed, one article showed that patients with lateral PFC damage had reduced ERN's (a putative sign of dorsomedial monitoring/error-feedback) Gehring and Knight, Nat Neurosci 2000 - suggesting, if anything, that the direction of flow of the control could be in the reverse direction. Another prominent theory[48] emphasises that interactions along the perpendicular axis of the frontal cortex, arguing that a 'cascade' of interactions between anterior PFC, dorsolateral PFC, and premotor cortex guides behaviour in accordance with past context, present context, and current sensorimotor associations respectively.

Advances in neuroimaging techniques have allowed studies of genetic links to executive functions, with the goal of using the imaging techniques as potential endophenotypes for discovering the genetic causes of executive function.[49]

See also


  1. Norman, D.A. & Shallice, T. (1980) Attention to action: Willed and automatic control of behaviour. Reprinted in M. Gazzaniga (ed) (2000) Cognitive Neuroscience: A Reader. Blackwell. ISBN 0-631-21660-X
  2. Shiffrin, R. M. & Schneider, W. (1977). Controlled and automatic human information processing: II: Perceptual learning, automatic attending, and a general theory. Psychological Review, 84, 127-190.
  3. Posner, M.I., & Snyder, C.R.R. (1975). Attention and cognitive control. In R. Solso (ed.), Information Processing and Cognition: The Loyola Symposium. Hillsdale, N.J.: Lawrence Erlbaum Associates.
  4. Posner, M.I. & Petersen, S.E. (1990) The attention system of the human brain. Annual Review of Neuroscience, 13, 25-42
  5. Shallice, T. (1988). From neuropsychology to mental structure, Cambridge: CUP.
  6. Baddeley, A. (1986) Working Memory. Oxford University Press. ISBN 0-19-852133-2
  7. Visscher, P.M. et al. (2008) Heritability in the genomics era- concepts and misconceptions. Nature reviews Genetics, 9, 255-266
  8. Friedman, N.M. (2008) Individual Differences in Executive Function Are Almost Entirely Genetic in Origin. Journal of Experimental Psychology: General, 137, 2, 201-225
  9. Bernier, A. (2010) From External Regulation to Self-Regulation: Early Parenting Precursors of Young Children's Executive Functioning.
  10. Matte-Gagné, C. & Bernier, A. (2011) Prospective Relations between maternal autonomy support and child executive functioning: Investigating the mediating role of child language ability. Journal of Experimental Child Psychology, 110, 611-625.
  11. Hughes, C.H. & Ensor, R.A. (2009) How Do Families Help or Hinder the Emergence of Early Executive Function? New Directions in Child and Adolescent Development, 123, 35-50.
  12. Miller, E.K. & Cohen, J.D. (2001). An integrative theory of prefrontal cortex function. Annu Rev Neurosci. 2001;24:167-202
  13. Desimone R, Duncan J (1995). Neural mechanisms of selective visual attention. Annu Rev Neurosci. 1995;18:193-222.
  14. Lehto, J.E. et al. (2003) Dimensions of Executive Functioning: Evidence from children. British Journal of Developmental psychology, 21, 59-80.
  15. Hughes, C. & Graham, A. (2002) Measuring Executive Functions in Childhood: Problems and Solutions? Child and Adolescent Mental Health, 7, 3, 131-142.
  16. Hughes, C. & Graham, A. (2002) Measuring Executive Functions in Childhood: Problems and Solutions? Child and Adolescent Mental Health, 7, 3, 131-142.
  17. Miyake, A. et al. (2000) The Unity and Diversity of Executive Functions and Their Contributions to Complex "Fronal Lobe" Tass: A Latent Variable Analysis. Cognitive Psychology, 41, 49-100.
  18. Baddeley, A. (1996). Exploring the central executive. The Quarterly Journal of Experimental Psychology, 49(1), 5–28.
  19. Lehto, J.E. et al. (2003) Dimensions of Executive Functioning: Evidence from children. British Journal of Developmental psychology, 21, 59-80.
  20. Friedman, N.P. & Miyake, A. (2004) The Relations Among Inhibition and Interference Control Functions: A Latent-Variable Analysis. Experimental Psychology: General, 133, 1, 101-135.
  21. Miyake, A. et al. (200) The Unity and Diversity of Executive Functions and Their Contributions to Complex "Fronal Lobe" Tass: A Latent Variable Analysis. Cognitive Psychology, 41, 49-100.
  22. Miyake, A. et al. (2000) The Unity and Diversity of Executive Functions and Their Contributions to Complex "Fronal Lobe" Tass: A Latent Variable Analysis. Cognitive Psychology, 41, 49-100.
  23. Willis, J.O., Dumont, R. & KAufman, A.S. (2011) Factor-Analytic Models of Intelligence. IN: Sternberg, R.J. & Kaufman, S.B. The Cambridge Handbook of Intelligence. Cambridge: Cambridge University Press.
  24. Friedman, N.P. et al. (2008) Inidividual Differences in Executive function Are Almost Entirely Genetic in Origin. Journal of Experimental Psychology: General, 137, 2, 201-225.
  25. Burgess, P.W. (1997) Theory and methodology in executive function research. In P. Rabbit (ed) Methodology of Frontal and Executive Function. ISBN 0-86377-485-7
  26. Saver, J.L. & Damasio, A.R. (1991) Preserved access and processing of social knowledge in a patient with acquired sociopathy due to ventromedial frontal damage. Neuropsychologia, 29 (12), 1241-1249
  27. Fellows LK and Farah MJ. Is anterior cingulate cortex necessary for cognitive control? Brain. 2005 Apr;128 (Pt 4):788-96. Epub 2005 Feb 10.
  28. Rushworth MF et al. Role of the human medial frontal cortex in task switching: a combined fMRI and TMS study. J Neurophysiol. 2002 May;87(5):2577-92
  29. Sakagami M et al. A code for behavioral inhibition on the basis of color, but not motion, in ventrolateral prefrontal cortex of macaque monkey. J Neurosci. 2001 Jul 1;21(13):4801-8.
  30. Hasegawa RP et al. Prefrontal neurons coding suppression of specific saccades. Neuron. 2004 Aug 5;43(3):415-25.
  31. Hillyard SA, Anllo-Vento L (1998). Event-related brain potentials in the study of visual selective attention. Proc Natl Acad Sci U S A 95:781-7
  32. Liu T, Slotnick SD, Serences JT, Yantis S (2003). Cortical mechanisms of feature-based attentional control. Cereb. Cortex 13:1334-43.
  33. Kastner S, Pinsk MA, De Weerd P, Desimone R, Ungerleider LG (1999). Increased activity in human visual cortex during directed attention in the absence of visual stimulation. Neuron 22:751-61
  34. Miller BT, D'Esposito M (2005). Searching for "the top" in top-down control. Neuron 48:535-8
  35. Barcelo F, Suwazono S, Knight RT (2000). Prefrontal modulation of visual processing in humans. Nat Neurosci. 3:399-403
  36. Fuster JM, Bauer RH, Jervey JP. 1985. Functional interactions between inferotemporal and prefrontal cortex in a cognitive task. Brain Res. 330:299–307.
  37. Gazzaley A, Rissman J, D'esposito M (2004). Functional connectivity during working memory maintenance. Cogn Affect Behav Neurosci. 4:580-99
  38. Aron AR & Poldrack RA (2006). Cortical and subcortical contributions to stop signal response inhibition: role of the subthalamic nucleus. Journal of Neuroscience 26 2424-2433
  39. Anderson MC, Green C (2001) Suppressing unwanted memories by executive control. Nature 410:366-369.
  40. Tipper SP (2001) Does negative priming reflect inhibitory mechanisms? A review and integration of conflicting views. Q J Exp Psychol A 54:321-343.
  41. Stone, V.E., & Gerrans, P. (2006). What's domain-specific about theory of mind. Social Neuroscience, 1 (3-4), 309-319.
  42. Decety, J., & Lamm, C. (2007). The role of the right temporoparietal junction in social interaction: How low-level computational processes contribute to meta-cognition. The Neuroscientist, 13, 580-593.
  43. Ochsner KN, Gross JJ (2005) The cognitive control of emotion. Trends Cogn Sci 9:242-249
  44. Decety, J., & Grezes, J. (2006). The power of simulation: Imagining one's own and other's behavior. Brain Research, 1079, 4-14.
  45. Aron AR (2007). The Neural Basis of Inhibition in Cognitive Control. The Neuroscientist
  46. Ridderinkhof KR, Ullsperger M, Crone EA, Nieuwenhuis S (2004). The role of the medial frontal cortex in cognitive control. Science 306:443-7
  47. MM Botvinick, TS Braver, DM Barch, CS Carter, JD Cohen (2001). Conflict monitoring and cognitive control. Psychological Review 108: 624-52
  48. Koechlin E, Ody C, Kouneiher F (2003). The architecture of cognitive control in the human prefrontal cortex. Science 302:1181-5
  49. Greene CM, Braet W, Johnson KA, Bellgrove MA (2007). Imaging the genetics of executive function. Biol Psychol.

External links

This page uses Creative Commons Licensed content from Wikipedia (view authors).