An adaptive coding model of neural function in prefrontal cortex


The prefrontal cortex has a vital role in effective, organized behaviour. Both functional neuroimaging in humans and electrophysiology in awake monkeys indicate that a fundamental principle of prefrontal function might be adaptive neural coding — in large regions of the prefrontal cortex, neurons adapt their properties to carry specifically information that is relevant to current concerns, producing a dense, distributed representation of related inputs, actions, rewards and other information. A model based on such adaptive coding integrates the role of the prefrontal cortex in working memory, attention and control. Adaptive coding points to new perspectives on several basic questions, including mapping of cognitive to neurophysiological functions, the influences of task content and difficulty, and the nature of frontal lobe specializations.

Key Points

  • The prefrontal cortex is crucial for effective, organized behaviour. On the basis of data from functional neuroimaging in humans and single-cell electrophysiology in the behaving monkey, this paper proposes an adaptive coding model of prefrontal function.

  • Functional imaging data show some specific associations between particular cognitive functions and local prefrontal activations. However, there is also strong evidence for common regions of recruitment in response to a wide range of different cognitive demands. These regions include the cortex in and around the posterior part of the inferior frontal sulcus, the frontal operculum/anterior insula and the dorsal part of the anterior cingulate.

  • Converging data come from electrophysiology in the monkey. Over large regions of the lateral frontal cortex, many cells show activity related to whatever arbitrary task a monkey has been trained to perform. These cells code many aspects of task events, including information relevant to stimuli, responses, working memory delays, response rules and reward states. Cells of many different types are found closely intermingled and widely distributed across the lateral surface. Even individual cells show evidence for adaptability of function, coding different information in different task contexts.

  • In the adaptive coding model, the central idea is that neurons throughout large regions of prefrontal cortex have the capacity to code many different types of information. In any given task context, neurons adapt to preserve only information of relevance to current behaviour. At the same time, they support the representation of related information elsewhere in the brain, including coding of relevant stimuli, responses, representations in semantic memory and reward states. This view links previous accounts of prefrontal function that are based on concepts of working memory, selective attention and control.

  • The model implies that, within the prefrontal cortex, regional specializations will be statistical rather than absolute. Neurons with the capacity to contribute to any given function might be widely distributed across the prefrontal cortex, although possibly with different distributions for different functions. This view of quantitative rather than qualitative specialization is consistent with data from electrophysiological, imaging and lesion studies. It suggests that conclusions concerning regional specialization will depend on criteria for assessing selectivity and, in imaging experiments, on experimental demand and power.

  • The adaptive coding model points to several key issues and approaches for future work. These include an assessment of long- and short-term adaptability, a quantitative comparison of cell properties between different prefrontal regions, and an investigation of how prefrontal adaptability differs from that in other cortical regions.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: 'General intelligence' reflects prefrontal function.
Figure 2: Prefrontal activations associated with five different cognitive demands.
Figure 3: Neural responses in macaque prefrontal cortex.
Figure 4: The adaptive coding model.

Change history

  • 27 March 2018

    This article was initially published with an incorrect DOI that did not match the registered version at Crossref. The DOI has been corrected in the article.


  1. 1

    Luria, A. R. Higher Cortical Functions in Man (Tavistock, London, 1966).A rich, indispensable, clinical description of the loosened structure of thought and behaviour that can follow frontal lobe lesions.

  2. 2

    Fuster, J. M. The Prefrontal Cortex: Anatomy, Physiology, and Neuropsychology of the Frontal Lobe 2nd edn (Raven, New York, 1989).

  3. 3

    Drewe, E. A. Go–no go learning after frontal lobe lesions in humans. Cortex 11, 8–16 (1975).

  4. 4

    Shimamura, A. P. in The Cognitive Neurosciences (ed. Gazzaniga, M. S.) 803–813 (MIT Press, Cambridge, Massachusetts, 1995).

  5. 5

    Milner, B. Visually-guided maze learning in man: effects of bilateral hippocampal, bilateral frontal and unilateral cerebral lesions. Neuropsychologia 3, 317–338 (1965).

  6. 6

    Shallice, T. in The Neuropsychology of Cognitive Function (eds Broadbent, D. E. & Weiskrantz, L.) 199–209 (The Royal Society, London, 1982).

  7. 7

    Duncan, J. et al. A neural basis for general intelligence. Science 289, 457–460 (2000).

  8. 8

    Goldman-Rakic, P. Topography of cognition: parallel distributed networks in primate association cortex. Annu. Rev. Neurosci. 11, 137–156 (1988).

  9. 9

    Baddeley, A. D. Working Memory (Oxford Univ. Press, Oxford, UK, 1986).

  10. 10

    Cohen, J. D. & Servan-Schreiber, D. Context, cortex, and dopamine: a connectionist approach to behavior and biology in schizophrenia. Psychol. Rev. 99, 45–77 (1992).

  11. 11

    Duncan, J., Emslie, H., Williams, P., Johnson, R. & Freer, C. Intelligence and the frontal lobe: the organization of goal-directed behavior. Cogn. Psychol. 30, 257–303 (1996).

  12. 12

    Pandya, D. N. & Yeterian, E. H. Comparison of prefrontal architecture and connections. Phil. Trans. R. Soc. Lond. B 351, 1423–1432 (1996).

  13. 13

    Miller, E. K. The prefrontal cortex and cognitive control. Nature Rev. Neurosci. 1, 59–65 (2000).

  14. 14

    Miller, E. K. & Cohen, J. D. An integrative theory of prefrontal function. Annu. Rev. Neurosci. 24, 167–202 (2001).An authoritative recent review and theoretical synthesis of physiological and cognitive work on prefrontal function.

  15. 15

    Duncan, J. & Miller, E. K. in Principles of Frontal Lobe Function (eds Stuss, D. T. & Knight, R. T.) (Oxford Univ. Press, Oxford, UK, in the press).

  16. 16

    Petersen, S. E., Fox, P. T., Posner, M. I., Mintun, M. & Raichle, M. E. Positron emission tomographic studies of the cortical anatomy of single word processing. Nature 331, 585–589 (1988).

  17. 17

    Corbetta, M., Miezin, F. M., Dobmeyer, S., Shulman, G. L. & Petersen, S. E. Selective and divided attention during visual discriminations of shape, color, and speed: functional anatomy by positron emission tomography. J. Neurosci. 11, 2383–2402 (1991).

  18. 18

    Pardo, J. V., Pardo, P. J., Janer, K. W. & Raichle, M. E. The anterior cingulate cortex mediates processing selection in the Stroop attentional conflict paradigm. Proc. Natl Acad. Sci. USA 87, 256–259 (1990).

  19. 19

    Goel, V., Grafman, J., Sadato, N. & Hallett, M. Modeling other minds. Neuroreport 6, 1741–1746 (1995).

  20. 20

    Fletcher, P. C. et al. Other minds in the brain: a functional imaging study of 'theory of mind' in story comprehension. Cognition 57, 109–128 (1995).

  21. 21

    Duncan, J. & Owen, A. M. Common regions of the human frontal lobe recruited by diverse cognitive demands. Trends Neurosci. 23, 475–483 (2000).A systematic analysis of published studies showing common patterns of prefrontalrecruitment for a broad range of different cognitive demands.

  22. 22

    Wagner, A. D., Desmond, J. E., Glover, G. H. & Gabrieli, J. D. E. Prefrontal cortex and recognition memory. Functional-MRI evidence for context-dependent retrieval processes. Brain 121, 1985–2002 (1998).

  23. 23

    Stroop, J. R. Studies of interference in serial verbal reactions. J. Exp. Psychol. 18, 643–662 (1935).

  24. 24

    Asaad W. F., Rainer, G. & Miller, E. K. Neural activity in the primate prefrontal cortex during associative learning. Neuron 21, 1399–1407 (1998).

  25. 25

    Asaad, W. F., Rainer, G. & Miller, E. K. Task-specific neural activity in the primate prefrontal cortex. J. Neurophysiol. 84, 451–459 (2000).

  26. 26

    Funahashi, S. & Inoue, M. Neuronal interactions related to working memory processes in the primate prefrontal cortex revealed by cross-correlation analysis. Cereb. Cortex 10, 535–551 (2000).

  27. 27

    Fuster, J. M., Bodner, M. & Kroger, J. K. Cross-modal and cross-temporal association in neurons of frontal cortex. Nature 405, 347–351 (2000).

  28. 28

    Wallis, J. D., Anderson, K. C. & Miller, E. K. Single neurons in prefrontal cortex encode abstract rules. Nature 411, 953–956 (2001).

  29. 29

    Fuster, J. M., Bauer, R. H. & Jervey, J. P. Functional interactions between inferotemporal and prefrontal cortex in a cognitive task. Brain Res. 330, 299–307 (1985).

  30. 30

    Funahashi, S., Bruce, C. J. & Goldman-Rakic, P. S. Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex. J. Neurophysiol. 61, 331–349 (1989).

  31. 31

    Watanabe, M. Prefrontal unit activity during delayed conditional go/no-go discrimination in the monkey. I. Relation to the stimulus. Brain Res. 382, 1–14 (1986).

  32. 32

    Sakagami, M. & Niki, H. Encoding of behavioral significance of visual stimuli by primate prefrontal neurons: relation to relevant task conditions. Exp. Brain Res. 97, 423–436 (1994).

  33. 33

    Romo, R., Brody, C. D., Hernández, A. & Lemus, L. Neuronal correlates of parametric working memory in the prefrontal cortex. Nature 399, 470–473 (1999).

  34. 34

    Watanabe, M. Prefrontal unit activity during delayed conditional go/no-go discrimination in the monkey. II. Relation to go and no-go responses. Brain Res. 382, 15–27 (1986).

  35. 35

    Di Pellegrino, G. & Wise, S. P. Visuospatial versus visuomotor activity in the premotor and prefrontal cortex of a primate. J. Neurosci. 13, 1227–1243 (1993).

  36. 36

    Fuster, J. M. & Alexander, G. E. Neuron activity related to short-term memory. Science 173, 652–654 (1971).

  37. 37

    Watanabe, M. Reward expectancy in primate prefrontal neurons. Nature 382, 629–632 (1996).A demonstration of reward-related activity in neurons of the lateral prefrontal cortex.

  38. 38

    Niki, H. & Watanabe, M. Prefrontal and cingulate unit activity during timing behavior in the monkey. Brain Res. 171, 213–224 (1979).One of the few direct comparisons of neuronal properties in dorsolateral prefrontal cortex and anterior cingulate, revealing highly similar response types in these two regions.

  39. 39

    Rao, S. C., Rainer, G. & Miller, E. K. Integration of what and where in the primate prefrontal cortex. Science 276, 821–824 (1997).

  40. 40

    Rainer, G., Asaad, W. F. & Miller, E. K. Memory fields of neurons in the primate prefrontal cortex. Proc. Natl Acad. Sci. USA 95, 15008–15013 (1998).

  41. 41

    White, I. M. & Wise, S. P. Rule-dependent neuronal activity in the prefrontal cortex. Exp. Brain Res. 126, 315–335 (1999).

  42. 42

    Freedman, D. J., Riesenhuber, M., Poggio, T. & Miller, E. K. Categorical representation of visual stimuli in the primate prefrontal cortex. Science 291, 312–316 (2001).A key experiment showing that neurons in a wide region of the lateral prefrontal cortex adapt to task context, coding just those stimulus distinctions or categorizations of current behavioural significance.

  43. 43

    Schall, J. D., Hanes, D. P., Thompson, K. G. & King, D. J. Saccade target selection in frontal eye field of macaque. I. Visual and premovement activation. J. Neurosci. 15, 6905–6918 (1995).

  44. 44

    Rainer, G., Asaad, W. F. & Miller, E. K. Selective representation of relevant information by neurons in the primate prefrontal cortex. Nature 393, 577–579 (1998).

  45. 45

    Everling, S., Tinsley, C. J., Gaffan, D. & Duncan, J. Neural activity in a focused attention task in monkey prefrontal cortex. Soc. Neurosci. Abstr. 30, 2227 (2000).

  46. 46

    Shima, K. & Tanji, J. Role for cingulate motor area cells in voluntary movement selection based on reward. Science 282, 1335–1338 (1998).

  47. 47

    Procyk, E., Tanaka, Y. L. & Joseph, J. P. Anterior cingulate activity during routine and non-routine sequential behaviors in macaques. Nature Neurosci. 3, 502–508 (2000).

  48. 48

    Jacobsen, C. E. Functions of the frontal association area in primates. Arch. Neurol. Psych. 33, 558–569 (1935).

  49. 49

    Chao, L. L. & Knight, R. T. Contribution of human prefrontal cortex to delay performance. J. Cogn. Neurosci. 10, 167–177 (1998).

  50. 50

    Malmo, R. R. Interference factors in delayed response in monkeys after removal of frontal lobes. J. Neurophysiol. 5, 295–308 (1942).

  51. 51

    Engle, R. W., Kane, M. J. & Tuholski, S. W. in Models of Working Memory: Mechanisms of Active Maintenance and Executive Control (eds Miyake, A. & Shah, P.) 102–134 (Cambridge Univ. Press, Cambridge, UK, 1999).

  52. 52

    Norman, D. A. & Shallice, T. Attention to Action: Willed and Automatic Control of Behavior. Report No. 8006, Univ. California, Cent. Hum. Inf. Process. (1980).

  53. 53

    Dehaene, S., Kerszberg, M. & Changeux, J.-P. A neuronal model of a global workspace in effortful cognitive tasks. Proc. Natl Acad. Sci. USA 95, 14529–14534 (1998).A computational model sharing many central aspects with the adaptive coding model.

  54. 54

    Duncan, J. in Attention and Performance XVI (eds Inui, T. & McClelland, J. L.) 549–578 (MIT Press, Cambridge, Massachusetts, 1996).

  55. 55

    Duncan, J., Humphreys, G. & Ward, R. Competitive brain activity in visual attention. Curr. Opin. Neurobiol. 7, 255–261 (1997).

  56. 56

    Desimone, R. & Duncan, J. Neural mechanisms of selective visual attention. Annu. Rev. Neurosci. 18, 193–222 (1995).

  57. 57

    Wilson, F. A. W., Ó Scalaidhe, S. P. & Goldman-Rakic, P. S. Dissociation of object and spatial processing domains in primate prefrontal cortex. Science 260, 1955–1958 (1993).

  58. 58

    Braver, T. S. & Cohen, J. D. in Control of Cognitive Processes: Attention and Performance XVIII (eds Monsell, S. & Driver, J.) 713–737 (MIT Press, Cambridge, Massachusetts, 2000).

  59. 59

    Newell, A. Unified Theories of Cognition (Harvard Univ. Press, Cambridge, Massachusetts, 1990).

  60. 60

    Tomita, H., Ohbayashi, M., Nakahara, K., Hasegawa, I. & Miyashita, Y. Top–down signal from prefrontal cortex in executive control of memory retrieval. Nature 401, 699–703 (1999).

  61. 61

    Haxby, J. V., Petit, L., Ungerleider, L. G. & Courtney, S. M. Distinguishing the functional roles of multiple regions in distributed neural systems for visual working memory. Neuroimage 11, 380–391 (2000). Strong fMRI evidence that regional specializations in a working memory network are relative rather than absolute.

  62. 62

    Requin, J., Riehle, A. & Seal, J. in Attention and Performance XIV (eds Meyer, D. E. & Kornblum, S.) 745–769 (MIT Press, Cambridge, Massachusetts, 1993).

  63. 63

    Ó Scalaidhe, P., Wilson, F. A. W. & Goldman-Rakic, P. S. Face-selective neurons during passive viewing and working memory performance of rhesus monkeys: evidence for intrinsic specialization of neuronal coding. Cereb. Cortex 9, 459–475 (1999).An important demonstration that regional specificity within prefrontal cortex depends on the criterion for cell classification; although the most highly face-selective cells are clustered on the ventrolateral surface, more weakly selective cells are more broadly distributed.

  64. 64

    Milner, B. Interhemispheric differences in the localization of psychological processes in man. Br. Med. Bull. 27, 272–277 (1971).

  65. 65

    Bechara, A., Damasio, H., Tranel, D. & Anderson, S. W. Dissociation of working memory from decision making within the human prefrontal cortex. J. Neurosci. 18, 428–437 (1998).

  66. 66

    Stuss, D. T. et al. Wisconsin Card Sorting Test performance in patients with focal frontal and posterior brain damage: effects of lesion location and test structure on separable cognitive processes. Neuropsychologia 38, 388–402 (2000).A comparison of cognitive deficits after lesions in different regions of prefrontal cortex, showing comparative preservation of function in orbitofrontal patients.

  67. 67

    Passingham, R. Delayed matching after selective prefrontal lesions in monkeys (Macaca mulatta). Brain Res. 92, 89–102 (1975).

  68. 68

    Mishkin, M. & Manning, F. J. Nonspatial memory after selective prefrontal lesions in monkeys. Brain Res. 143, 313–323 (1978).

  69. 69

    Petrides, M. Impairments on nonspatial self-ordered and externally ordered working memory tasks after lesions of the mid-dorsal part of the lateral frontal cortex of the monkey. J. Neurosci. 15, 359–375 (1995).

  70. 70

    Postle, B. R. & D'Esposito, M. Evaluating models of the topographical organization of working memory function in frontal cortex with event-related fMRI. Psychobiology 28, 146–155 (2000).

  71. 71

    Nystrom, L. E. et al. Working memory for letters, shapes, and locations: fMRI evidence against stimulus-based regional organization in human prefrontal cortex. Neuroimage 11, 424–446 (2000).

  72. 72

    Nolde, S. F., Johnson, M. K. & Raye, C. L. The role of prefrontal cortex during tests of episodic memory. Trends Cogn. Sci. 2, 399–406 (1998).

  73. 73

    Thulborn, K. R., Carpenter, P. A. & Just, M. A. Plasticity of language-related brain function during recovery from stroke. Stroke 30, 749–754 (1999).

  74. 74

    Rosen, H. J. et al. Neural correlates of recovery from aphasia after damage to left inferior frontal cortex. Neurology 55, 1883–1894 (2000).

  75. 75

    Butter, C. M. Perseveration in extinction and in discrimination reversal tasks following selective frontal ablations in Macaca mulatta. Physiol. Behav. 4, 163–171 (1969).

  76. 76

    Dias, R., Robbins, T. W. & Roberts, A. C. Dissociation in prefrontal cortex of affective and attentional shifts. Nature 380, 69–72 (1996).

  77. 77

    Drevets, W. C. Neuroimaging and neuropathological studies of depression: implications for the cognitive-emotional features of mood disorders. Curr. Opin. Neurobiol. 11, 240–249 (2001).

  78. 78

    Elliott, R., Frith, C. D. & Dolan, R. J. Differential neural response to positive and negative feedback in planning and guessing tasks. Neuropsychologia 35, 1395–1404 (1997).

  79. 79

    O'Doherty, J., Kringelbach, M. L., Rolls, E. T., Hornak, J. & Andrews, C. Abstract reward and punishment representations in the human orbitofrontal cortex. Nature Neurosci. 4, 95–102 (2001).

  80. 80

    Rolls, E. T. The orbitofrontal cortex. Phil. Trans. R. Soc. Lond. B 351, 1433–1444 (1996).

  81. 81

    Tremblay, L. & Schultz, W. Relative reward preference in primate orbitofrontal cortex. Nature 398, 704–708 (1999).

  82. 82

    Hikosaka, K. & Watanabe, M. Delay activity of orbital and lateral prefrontal neurons of the monkey varying with different rewards. Cereb. Cortex 10, 263–271 (2000).

  83. 83

    MacDonald, A. W., Cohen, J. D., Stenger, V. A. & Carter, C. S. Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. Science 280, 1835–1838 (2000).

  84. 84

    Owen, A. M. The functional organization of working memory processes within human lateral frontal cortex: the contribution of functional neuroimaging. Eur. J. Neurosci. 9, 1329–1339 (1997).

  85. 85

    Chen, L. L. & Wise, S. P. Neuronal activity in the supplementary eye field during acquisition of conditional oculomotor association. J. Neurophysiol. 73, 1101–1121 (1995).

  86. 86

    Chafee, M. W. & Goldman-Rakic, P. S. Matching patterns of activity in primate prefrontal area 8a and parietal area 7ip neurons during a spatial working memory task. J. Neurophysiol. 79, 2919–2940 (1998).

  87. 87

    Anderson, K. C. & Miller, E. K. Neural activity in the prefrontal and posterior parietal cortices during a what-then-where memory task. Soc. Neurosci. Abstr. 30, 975 (2000).

  88. 88

    Roelfsema, P. R., Lamme, V. A. F. & Spekreijse, H. Object-based attention in the primary visual cortex of the macaque monkey. Nature 395, 376–381 (1998).

  89. 89

    Moran, J. & Desimone, R. Selective attention gates visual processing in the extrastriate cortex. Science 229, 782–784 (1985).

  90. 90

    Miller, E. K., Erickson, C. A. & Desimone, R. Neural mechanisms of visual working memory in prefrontal cortex of the macaque. J. Neurosci. 16, 5154–5167 (1996).

  91. 91

    Williams, G. V. & Goldman-Rakic, P. S. Modulation of memory fields by dopamine D1 receptors in prefrontal cortex. Nature 376, 572–575 (1995).

  92. 92

    Diamond, A. & Goldman-Rakic, P. S. Comparison of human infants and rhesus monkeys on Piaget's A-not-B task: evidence for dependence on dorsolateral prefrontal cortex. Exp. Brain Res. 74, 24–40 (1989).

  93. 93

    Gaffan D. & Harrison, S. A comparison of the effects of fornix transection and sulcus principalis ablation upon spatial learning by monkeys. Behav. Brain Res. 31, 207–220 (1989).

  94. 94

    Desimone, R. & Ungerleider, L. G. in Handbook of Neuropsychology Vol. 2 (eds Boller, F. & Grafman, J.) 267–299 (Elsevier, Amsterdam, 1989).

  95. 95

    Duncan, J. Selective attention and the organization of visual information. J. Exp. Psychol. Gen. 113, 501–517 (1984).

  96. 96

    Hodges, J. R., Patterson, K., Oxbury, S. & Funnell, E. Semantic dementia: progressive fluent aphasia with temporal lobe atrophy. Brain 115, 1783–1806 (1992).

  97. 97

    Spearman, C. General intelligence, objectively determined and measured. Am. J. Psychol. 15, 201–293 (1904).

Download references


I am grateful to E. Miller for his contribution to many of the ideas presented in this paper.

Author information

Related links

Related links


MIT Encyclopedia of Cognitive Sciences


hemispheric specialization

magnetic resonance imaging

positron emission tomography

working memory



Tasks in which simple stimuli, such as lights or tones, call for speeded keypress or other responses.


The recollection of events in an autobiographical context.


High-level processes that are proposed to organize and control cognitive function.


A requirement to process two or more simultaneous stimuli in a visual display.


A requirement to combine information from different sensory modalities.

Rights and permissions

Reprints and Permissions

About this article

Further reading