Various aspects of human cognition are shaped and enriched by abstract rules, which help to describe, link and classify discrete events and experiences into meaningful concepts. However, where and how these entities emerge in the primate brain and the neuronal mechanisms underlying them remain the subject of extensive research and debate. Evidence from imaging studies in humans and single-neuron recordings in monkeys suggests a pivotal role for the prefrontal cortex in the representation of abstract rules; however, behavioural studies in lesioned monkeys and data from neuropsychological examinations of patients with prefrontal damage indicate substantial functional dissociations and task dependency in the contribution of prefrontal cortical regions to rule-guided behaviour. This Review describes our current understanding of the dynamic emergence of abstract rules in primate cognition, and of the distributed neural network that supports abstract rule formation, maintenance, revision and task-dependent implementation.
This is a preview of subscription content, access via your institution
Open Access articles citing this article.
Neurodynamical Computing at the Information Boundaries of Intelligent Systems
Cognitive Computation Open Access 27 December 2022
Dimension of visual information interacts with working memory in monkeys and humans
Scientific Reports Open Access 29 March 2022
Prefrontal connectomics: from anatomy to human imaging
Neuropsychopharmacology Open Access 28 September 2021
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 per month
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$189.00 per year
only $15.75 per issue
Rent or buy this article
Get just this article for as long as you need it
Prices may be subject to local taxes which are calculated during checkout
Ashby, F. G. & Ell, S. W. The neurobiology of human category learning. Trends Cogn. Sci. 5, 204–210 (2001).
Miller, E. K. & Cohen, J. D. An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci. 24, 167–202 (2001).
Mansouri, F. A. & Buckley, M. J. Context-dependent adjustments in executive control of goal-directed behaviour: contribution of frontal brain areas to conflict-induced behavioural adjustments in primates. Adv. Neurobiol. 21, 71–83 (2018).
Mansouri, F. A., Egner, T. & Buckley, M. J. Monitoring demands for executive control: shared functions between human and nonhuman primates. Trends Neurosci. 40, 15–27 (2017).
Mansouri, F. A., Koechlin, E., Rosa, M. G. P. & Buckley, M. J. Managing competing goals — a key role for the frontopolar cortex. Nat. Rev. Neurosci. 18, 645–657 (2017). This comprehensive review proposes that the frontopolar cortex is involved in adjusting the balance between exploitation and exploration in primates.
Mansouri, F. A., Tanaka, K. & Buckley, M. J. Conflict-induced behavioural adjustment: a clue to the executive functions of the prefrontal cortex. Nat. Rev. Neurosci. 10, 141–152 (2009).
Buckley, M. J. et al. Dissociable components of rule-guided behavior depend on distinct medial and prefrontal regions. Science 325, 52–58 (2009). This study examines the effects of selective lesions within different prefrontal regions on cognitive flexibility in shifting between abstract rules.
Freedman, D. J. & Assad, J. A. Neuronal mechanisms of visual categorization: an abstract view on decision making. Annu. Rev. Neurosci. 39, 129–147 (2016).
Katz, J. S., Wright, A. A. & Bodily, K. D. Issues in the comparative cognition of abstract-concept learning. Comp. Cogn. Behav. Rev. 2, 79–92 (2007).
Pan, X. & Sakagami, M. Category representation and generalization in the prefrontal cortex. Eur. J. Neurosci. 35, 1083–1091 (2012).
Alderson-Day, B. & McGonigle-Chalmers, M. Is it a bird? Is it a plane? Category use in problem-solving in children with autism spectrum disorders. J. Autism Dev. Disord. 41, 555–565 (2011).
Gastgeb, H. Z., Dundas, E. M., Minshew, N. J. & Strauss, M. S. Category formation in autism: can individuals with autism form categories and prototypes of dot patterns? J. Autism Dev. Disord. 42, 1694–1704 (2012).
Jones, E. J., Webb, S. J., Estes, A. & Dawson, G. Rule learning in autism: the role of reward type and social context. Dev. Neuropsychol. 38, 58–77 (2013).
Keri, S., Kalman, J., Kelemen, O., Benedek, G. & Janka, Z. Are Alzheimer’s disease patients able to learn visual prototypes? Neuropsychologia 39, 1218–1223 (2001).
Keri, S. et al. Abstraction is impaired at the perceptual level in schizophrenic patients. Neurosci. Lett. 243, 93–96 (1998).
Yerys, B. E. et al. Neural correlates of set-shifting in children with autism. Autism Res. 8, 386–397 (2015).
Bunge, S. A. How we use rules to select actions: a review of evidence from cognitive neuroscience. Cogn. Affect. Behav. Neurosci. 4, 564–579 (2004).
Koechlin, E., Ody, C. & Kouneiher, F. The architecture of cognitive control in the human prefrontal cortex. Science 302, 1181–1185 (2003).
Koechlin, E. & Summerfield, C. An information theoretical approach to prefrontal executive function. Trends Cogn. Sci. 11, 229–235 (2007).
Seger, C. A. & Miller, E. K. Category learning in the brain. Annu. Rev. Neurosci. 33, 203–219 (2010).
Viswanathan, P. & Nieder, A. Neuronal correlates of a visual ‘sense of number’ in primate parietal and prefrontal cortices. Proc. Natl Acad. Sci. USA 110, 11187–11192 (2013).
Cole, M. W., Etzel, J. A., Zacks, J. M., Schneider, W. & Braver, T. S. Rapid transfer of abstract rules to novel contexts in human lateral prefrontal cortex. Front. Hum. Neurosci. 5, 142 (2011).
Buckley, M. J. & Sigala, N. Is top-down control from prefrontal cortex necessary for visual categorization? Neuron 66, 471–473 (2010).
Dias, R., Robbins, T. W. & Roberts, A. C. Dissociation in prefrontal cortex of affective and attentional shifts. Nature 380, 69–72 (1996).
Hoshi, E., Shima, K. & Tanji, J. Neuronal activity in the primate prefrontal cortex in the process of motor selection based on two behavioral rules. J. Neurophysiol. 83, 2355–2373 (2000).
Mansouri, F. A., Buckley, M. J., Fehring, D. J. & Tanaka, K. The role of primate prefrontal cortex in bias and shift between visual dimensions. Cereb. Cortex 30, 85–99 (2020). This cross-species study reveals that both monkeys and humans show bias to a particular dimension in the WCST and that such biases are not dependent on the PFC.
Mansouri, F. A., Buckley, M. J., Mahboubi, M. & Tanaka, K. Behavioral consequences of selective damage to frontal pole and posterior cingulate cortices. Proc. Natl Acad. Sci. USA 112, E3940–E3949 (2015).
Mansouri, F. A., Buckley, M. J. & Tanaka, K. Mnemonic function of the dorsolateral prefrontal cortex in conflict-induced behavioral adjustment. Science 318, 987–990 (2007).
Mansouri, F. A., Buckley, M. J. & Tanaka, K. The essential role of primate orbitofrontal cortex in conflict-induced executive control adjustment. J. Neurosci. 34, 11016–11031 (2014).
Mansouri, F. A., Fehring, D. J., Gaillard, A., Jaberzadeh, S. & Parkington, H. Sex dependency of inhibitory control functions. Biol. Sex. Differ. 7, 11 (2016).
Mansouri, F. A., Matsumoto, K. & Tanaka, K. Prefrontal cell activities related to monkeys’ success and failure in adapting to rule changes in a Wisconsin Card Sorting Test analog. J. Neurosci. 26, 2745–2756 (2006).
Mansouri, F. A., Rosa, M. G. & Atapour, N. Working memory in the service of executive control functions. Front. Syst. Neurosci. 9, 166 (2015).
Mansouri, F. A. & Tanaka, K. Behavioral evidence for working memory of sensory dimension in macaque monkeys. Behav. Brain Res. 136, 415–426 (2002).
Wallis, J. D., Anderson, K. C. & Miller, E. K. Single neurons in prefrontal cortex encode abstract rules. Nature 411, 953–956 (2001). This paper shows how the activity of single neurons in the monkey PFC conveys information about abstract rules.
Wallis, J. D. & Miller, E. K. From rule to response: neuronal processes in the premotor and prefrontal cortex. J. Neurophysiol. 90, 1790–1806 (2003).
Nieder, A. Counting on neurons: the neurobiology of numerical competence. Nat. Rev. Neurosci. 6, 177–190 (2005).
Nieder, A. & Dehaene, S. Representation of number in the brain. Annu. Rev. Neurosci. 32, 185–208 (2009).
Nieder, A., Freedman, D. J. & Miller, E. K. Representation of the quantity of visual items in the primate prefrontal cortex. Science 297, 1708–1711 (2002). This pioneering study shows how single neurons in the monkey PFC encode abstract numerical information.
Drewe, E. A. The effect of type and area of brain lesion on Wisconsin Card Sorting Test performance. Cortex 10, 159–170 (1974).
Milner, B. Effects of different brain lesions on card sorting. Arch. Neurol. 9, 90–100 (1963).
Stuss, D. T. et al. The involvement of orbitofrontal cerebrum in cognitive tasks. Neuropsychologia 21, 235–248 (1983).
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).
La Camera, G., Bouret, S. & Richmond, B. J. Contributions of lateral and orbital frontal regions to abstract rule acquisition and reversal in monkeys. Front. Neurosci. 12, 165 (2018).
Matsumoto, N., Eldridge, M. A., Saunders, R. C., Reoli, R. & Richmond, B. J. Mild perceptual categorization deficits follow bilateral removal of anterior inferior temporal cortex in rhesus monkeys. J. Neurosci. 36, 43–53 (2016).
Crescentini, C. et al. Mechanisms of rule acquisition and rule following in inductive reasoning. J. Neurosci. 31, 7763–7774 (2011).
Miller, E. K., Nieder, A., Freedman, D. J. & Wallis, J. D. Neural correlates of categories and concepts. Curr. Opin. Neurobiol. 13, 198–203 (2003).
Bunge, S. A. & Wallis, J. D. Neuroscience of Rule-Guided Behavior (Oxford Univ. Press, 2008).
Lazarowski, L., Goodman, A., Galizio, M. & Bruce, K. Effects of set size on identity and oddity abstract-concept learning in rats. Anim. Cogn. 22, 733–742 (2019).
Smith, J. D. et al. Generalization of category knowledge and dimensional categorization in humans (Homo sapiens) and nonhuman primates (Macaca mulatta). J. Exp. Psychol. Anim. Learn. Cogn. 41, 322–335 (2015).
Freedman, D. J. & Assad, J. A. Experience-dependent representation of visual categories in parietal cortex. Nature 443, 85–88 (2006).
Freedman, D. J. & Miller, E. K. Neural mechanisms of visual categorization: insights from neurophysiology. Neurosci. Biobehav. Rev. 32, 311–329 (2008).
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). This pioneering study shows how single neurons in the monkey PFC encode multifaceted categories.
Baugh, A. T., Akre, K. L. & Ryan, M. J. Categorical perception of a natural, multivariate signal: mating call recognition in tungara frogs. Proc. Natl Acad. Sci. USA 105, 8985–8988 (2008).
Veit, L. & Nieder, A. Abstract rule neurons in the endbrain support intelligent behaviour in corvid songbirds. Nat. Commun. 4, 2878 (2013).
Wyttenbach, R. A., May, M. L. & Hoy, R. R. Categorical perception of sound frequency by crickets. Science 273, 1542–1544 (1996). This pioneering study provides solid evidence for category-guided behaviour in insects.
Giurfa, M., Zhang, S., Jenett, A., Menzel, R. & Srinivasan, M. V. The concepts of ‘sameness’ and ‘difference’ in an insect. Nature 410, 930–933 (2001).
DeGutis, J. & D’Esposito, M. Distinct mechanisms in visual category learning. Cogn. Affect. Behav. Neurosci. 7, 251–259 (2007).
Freedman, D. J., Riesenhuber, M., Poggio, T. & Miller, E. K. A comparison of primate prefrontal and inferior temporal cortices during visual categorization. J. Neurosci. 23, 5235–5246 (2003).
Mahon, B. Z. & Caramazza, A. Concepts and categories: a cognitive neuropsychological perspective. Annu. Rev. Psychol. 60, 27–51 (2009).
Sigala, N. & Logothetis, N. K. Visual categorization shapes feature selectivity in the primate temporal cortex. Nature 415, 318–320 (2002).
ten Cate, C. & Okanoya, K. Revisiting the syntactic abilities of non-human animals: natural vocalizations and artificial grammar learning. Philos. Trans. R. Soc. Lond. B Biol. Sci. 367, 1984–1994 (2012).
Tanji, J., Shima, K. & Mushiake, H. Concept-based behavioral planning and the lateral prefrontal cortex. Trends Cogn. Sci. 11, 528–534 (2007).
Muhammad, R., Wallis, J. D. & Miller, E. K. A comparison of abstract rules in the prefrontal cortex, premotor cortex, inferior temporal cortex, and striatum. J. Cogn. Neurosci. 18, 974–989 (2006).
Bunge, S. A., Kahn, I., Wallis, J. D., Miller, E. K. & Wagner, A. D. Neural circuits subserving the retrieval and maintenance of abstract rules. J. Neurophysiol. 90, 3419–3428 (2003).
Elliott, R. & Dolan, R. J. Differential neural responses during performance of matching and nonmatching to sample tasks at two delay intervals. J. Neurosci. 19, 5066–5073 (1999).
Balsters, J. H., Whelan, C. D., Robertson, I. H. & Ramnani, N. Cerebellum and cognition: evidence for the encoding of higher order rules. Cereb. Cortex 23, 1433–1443 (2013).
Bongard, S. & Nieder, A. Basic mathematical rules are encoded by primate prefrontal cortex neurons. Proc. Natl Acad. Sci. USA 107, 2277–2282 (2010).
Eiselt, A. K. & Nieder, A. Representation of abstract quantitative rules applied to spatial and numerical magnitudes in primate prefrontal cortex. J. Neurosci. 33, 7526–7534 (2013).
Eiselt, A. K. & Nieder, A. Rule activity related to spatial and numerical magnitudes: comparison of prefrontal, premotor, and cingulate motor cortices. J. Cogn. Neurosci. 26, 1000–1012 (2014).
Kutter, E. F., Bostroem, J., Elger, C. E., Mormann, F. & Nieder, A. Single neurons in the human brain encode numbers. Neuron 100, 753–761.e4 (2018).
Nieder, A. Supramodal numerosity selectivity of neurons in primate prefrontal and posterior parietal cortices. Proc. Natl Acad. Sci. USA 109, 11860–11865 (2012).
Vallentin, D., Bongard, S. & Nieder, A. Numerical rule coding in the prefrontal, premotor, and posterior parietal cortices of macaques. J. Neurosci. 32, 6621–6630 (2012).
Daitch, A. L. et al. Mapping human temporal and parietal neuronal population activity and functional coupling during mathematical cognition. Proc. Natl Acad. Sci. USA 113, E7277–E7286 (2016).
Cromer, J. A., Roy, J. E. & Miller, E. K. Representation of multiple, independent categories in the primate prefrontal cortex. Neuron 66, 796–807 (2010). This pioneering study shows a dynamic training-dependent representation of category information in PFC neuronal activity.
Forstmann, B. U., Brass, M., Koch, I. & von Cramon, D. Y. Internally generated and directly cued task sets: an investigation with fMRI. Neuropsychologia 43, 943–952 (2005).
Bengtsson, S. L., Haynes, J. D., Sakai, K., Buckley, M. J. & Passingham, R. E. The representation of abstract task rules in the human prefrontal cortex. Cereb. Cortex 19, 1929–1936 (2009).
Mian, M. K. et al. Encoding of rules by neurons in the human dorsolateral prefrontal cortex. Cereb. Cortex 24, 807–816 (2014).
Kuwabara, M., Mansouri, F. A., Buckley, M. J. & Tanaka, K. Cognitive control functions of anterior cingulate cortex in macaque monkeys performing a Wisconsin Card Sorting Test analog. J. Neurosci. 34, 7531–7547 (2014).
Kamigaki, T., Fukushima, T. & Miyashita, Y. Cognitive set reconfiguration signaled by macaque posterior parietal neurons. Neuron 61, 941–951 (2009).
Kamigaki, T., Fukushima, T., Tamura, K. & Miyashita, Y. Neurodynamics of cognitive set shifting in monkey frontal cortex and its causal impact on behavioral flexibility. J. Cogn. Neurosci. 24, 2171–2185 (2012).
Sleezer, B. J., Castagno, M. D. & Hayden, B. Y. Rule encoding in orbitofrontal cortex and striatum guides selection. J. Neurosci. 36, 11223–11237 (2016).
Sleezer, B. J. & Hayden, B. Y. Differential contributions of ventral and dorsal striatum to early and late phases of cognitive set reconfiguration. J. Cogn. Neurosci. 28, 1849–1864 (2016).
Sleezer, B. J., LoConte, G. A., Castagno, M. D. & Hayden, B. Y. Neuronal responses support a role for orbitofrontal cortex in cognitive set reconfiguration. Eur. J. Neurosci. 45, 940–951 (2017).
Nakahara, K., Hayashi, T., Konishi, S. & Miyashita, Y. Functional MRI of macaque monkeys performing a cognitive set-shifting task. Science 295, 1532–1536 (2002). This pioneering fMRI study in monkeys and humans reveals how shifting between rules is represented in the PFC.
Petrides, M., Tomaiuolo, F., Yeterian, E. H. & Pandya, D. N. The prefrontal cortex: comparative architectonic organization in the human and the macaque monkey brains. Cortex 48, 46–57 (2012).
Konishi, S. et al. Contribution of working memory to transient activation in human inferior prefrontal cortex during performance of the Wisconsin Card Sorting Test. Cereb. Cortex 9, 745–753 (1999).
Konishi, S. et al. Transient activation of inferior prefrontal cortex during cognitive set shifting. Nat. Neurosci. 1, 80–84 (1998).
Asari, T., Konishi, S., Jimura, K. & Miyashita, Y. Multiple components of lateral posterior parietal activation associated with cognitive set shifting. Neuroimage 26, 694–702 (2005).
Buchsbaum, B. R., Greer, S., Chang, W. L. & Berman, K. F. Meta-analysis of neuroimaging studies of the Wisconsin card-sorting task and component processes. Hum. Brain Mapp. 25, 35–45 (2005).
Menon, V. & Uddin, L. Q. Saliency, switching, attention and control: a network model of insula function. Brain Struct. Funct. 214, 655–667 (2010).
Mentzel, H. J. et al. Cognitive stimulation with the Wisconsin Card Sorting Test: functional MR imaging at 1.5T. Radiology 207, 399–404 (1998).
Monchi, O., Petrides, M., Petre, V., Worsley, K. & Dagher, A. Wisconsin card sorting revisited: distinct neural circuits participating in different stages of the task identified by event-related functional magnetic resonance imaging. J. Neurosci. 21, 7733–7741 (2001).
Ravizza, S. M. & Carter, C. S. Shifting set about task switching: behavioral and neural evidence for distinct forms of cognitive flexibility. Neuropsychologia 46, 2924–2935 (2008).
Wang, J., Cao, B., Cai, X., Gao, H. & Li, F. Brain activation of negative feedback in rule acquisition revealed in a segmented Wisconsin Card Sorting Test. PLoS ONE 10, e0140731 (2015).
Zeithamova, D. et al. Brain mechanisms of concept learning. J. Neurosci. 39, 8259–8266 (2019).
Konishi, S. et al. Hemispheric asymmetry in human lateral prefrontal cortex during cognitive set shifting. Proc. Natl Acad. Sci. USA 99, 7803–7808 (2002).
Genovesio, A., Brasted, P. J., Mitz, A. R. & Wise, S. P. Prefrontal cortex activity related to abstract response strategies. Neuron 47, 307–320 (2005).
Bussey, T. J., Wise, S. P. & Murray, E. A. The role of ventral and orbital prefrontal cortex in conditional visuomotor learning and strategy use in rhesus monkeys (Macaca mulatta). Behav. Neurosci. 115, 971–982 (2001).
Stoet, G. & Snyder, L. H. Single neurons in posterior parietal cortex of monkeys encode cognitive set. Neuron 42, 1003–1012 (2004).
Stoet, G. & Snyder, L. H. Neural correlates of executive control functions in the monkey. Trends Cogn. Sci. 13, 228–234 (2009).
White, I. M. & Wise, S. P. Rule-dependent neuronal activity in the prefrontal cortex. Exp. Brain Res. 126, 315–335 (1999).
Asaad, W. F., Rainer, G. & Miller, E. K. Task-specific neural activity in the primate prefrontal cortex. J. Neurophysiol. 84, 451–459 (2000).
Mante, V., Sussillo, D., Shenoy, K. V. & Newsome, W. T. Context-dependent computation by recurrent dynamics in prefrontal cortex. Nature 503, 78–84 (2013).
Crowe, D. A. et al. Prefrontal neurons transmit signals to parietal neurons that reflect executive control of cognition. Nat. Neurosci. 16, 1484–1491 (2013).
Goodwin, S. J., Blackman, R. K., Sakellaridi, S. & Chafee, M. V. Executive control over cognition: stronger and earlier rule-based modulation of spatial category signals in prefrontal cortex relative to parietal cortex. J. Neurosci. 32, 3499–3515 (2012).
Sakai, K. & Passingham, R. E. Prefrontal interactions reflect future task operations. Nat. Neurosci. 6, 75–81 (2003).
Swaminathan, S. K. & Freedman, D. J. Preferential encoding of visual categories in parietal cortex compared with prefrontal cortex. Nat. Neurosci. 15, 315–320 (2012).
Lie, C. H., Specht, K., Marshall, J. C. & Fink, G. R. Using fMRI to decompose the neural processes underlying the Wisconsin Card Sorting Test. Neuroimage 30, 1038–1049 (2006).
Duncan, J. & Owen, A. M. Common regions of the human frontal lobe recruited by diverse cognitive demands. Trends Neurosci. 23, 475–483 (2000). This influential paper proposes that a distributed network including prefrontal, cingulate and parietal cortices supports the organization and execution of various goal-directed behaviours.
Brown, V. J. & Tait, D. S. Attentional set-shifting across species. Curr. Top. Behav. Neurosci. 28, 363–395 (2016).
Goldman, P. S. & Rosvold, H. E. Localization of function within the dorsolateral prefrontal cortex of the rhesus monkey. Exp. Neurol. 27, 291–304 (1970).
Petrides, M. Motor conditional associative-learning after selective prefrontal lesions in the monkey. Behav. Brain Res. 5, 407–413 (1982).
Petrides, M. Deficits in non-spatial conditional associative learning after periarcuate lesions in the monkey. Behav. Brain Res. 16, 95–101 (1985).
Podbros, L. Z., Stamm, J. S. & Denaro, F. J. Associative function of the arcuate segment of the monkey’s prefrontal cortex. Physiol. Behav. 24, 103–109 (1980).
Petrides, M. Deficits on conditional associative-learning tasks after frontal- and temporal-lobe lesions in man. Neuropsychologia 23, 601–614 (1985).
Petrides, M. Visuo-motor conditional associative learning after frontal and temporal lesions in the human brain. Neuropsychologia 35, 989–997 (1997).
Kowalska, D. M., Bachevalier, J. & Mishkin, M. The role of the inferior prefrontal convexity in performance of delayed nonmatching-to-sample. Neuropsychologia 29, 583–600 (1991).
Bachevalier, J. & Mishkin, M. Visual recognition impairment follows ventromedial but not dorsolateral prefrontal lesions in monkeys. Behav. Brain Res. 20, 249–261 (1986).
Meunier, M., Bachevalier, J. & Mishkin, M. Effects of orbital frontal and anterior cingulate lesions on object and spatial memory in rhesus monkeys. Neuropsychologia 35, 999–1015 (1997).
Bauer, R. H. & Fuster, J. M. Delayed-matching and delayed-response deficit from cooling dorsolateral prefrontal cortex in monkeys. J. Comp. Physiol. Psychol. 90, 293–302 (1976).
Elliott, R., Dolan, R. J. & Frith, C. D. Dissociable functions in the medial and lateral orbitofrontal cortex: evidence from human neuroimaging studies. Cereb. Cortex 10, 308–317 (2000).
Moore, T. L., Schettler, S. P., Killiany, R. J., Rosene, D. L. & Moss, M. B. Impairment in delayed nonmatching to sample following lesions of dorsal prefrontal cortex. Behav. Neurosci. 126, 772–780 (2012).
Rao, S. C., Rainer, G. & Miller, E. K. Integration of what and where in the primate prefrontal cortex. Science 276, 821–824 (1997).
Shallice, T. & Burgess, P. W. Deficits in strategy application following frontal lobe damage in man. Brain 114, 727–741 (1991).
Boschin, E. A., Brkic, M. M., Simons, J. S. & Buckley, M. J. Distinct roles for the anterior cingulate and dorsolateral prefrontal cortices during conflict between abstract rules. Cereb. Cortex 27, 34–45 (2017).
Glascher, J. et al. Lesion mapping of cognitive control and value-based decision making in the prefrontal cortex. Proc. Natl Acad. Sci. USA 109, 14681–14686 (2012). This paper presents a comprehensive neuropsychological examination of the effects of brain lesions on cognitive flexibility in shifting between abstract rules.
Minamimoto, T., Saunders, R. C. & Richmond, B. J. Monkeys quickly learn and generalize visual categories without lateral prefrontal cortex. Neuron 66, 501–507 (2010). This paper reports that large lesions in the PFC do not impair using learned categories or learning new categories.
Tanaka, K. Inferotemporal cortex and object vision. Annu. Rev. Neurosci. 19, 109–139 (1996). This comprehensive review describes the architecture of the ventral visual pathway of object recognition in primates.
Buckley, M. J. & Gaffan, D. Perirhinal cortical contributions to object perception. Trends Cogn. Sci. 10, 100–107 (2006).
Cools, R., Clark, L. & Robbins, T. W. Differential responses in human striatum and prefrontal cortex to changes in object and rule relevance. J. Neurosci. 24, 1129–1135 (2004).
Bowman, C. R. & Zeithamova, D. Abstract memory representations in the ventromedial prefrontal cortex and hippocampus support concept generalization. J. Neurosci. 38, 2605–2614 (2018).
Murray, E. A. & Wise, S. P. Role of the hippocampus plus subjacent cortex but not amygdala in visuomotor conditional learning in rhesus monkeys. Behav. Neurosci. 110, 1261–1270 (1996).
Orbach, J., Milner, B. & Rasmussen, T. Learning and retention in monkeys after amygdala–hippocampus resection. Arch. Neurol. 3, 230–251 (1960).
Owen, A. M., Roberts, A. C., Polkey, C. E., Sahakian, B. J. & Robbins, T. W. Extra-dimensional versus intra-dimensional set shifting performance following frontal lobe excisions, temporal lobe excisions or amygdalo-hippocampectomy in man. Neuropsychologia 29, 993–1006 (1991).
Filoteo, J. V. et al. Cortical and subcortical brain regions involved in rule-based category learning. Neuroreport 16, 111–115 (2005).
Sloutsky, V. M. From perceptual categories to concepts: what develops? Cogn. Sci. 34, 1244–1286 (2010).
Boschin, E. A., Piekema, C. & Buckley, M. J. Essential functions of primate frontopolar cortex in cognition. Proc. Natl Acad. Sci. USA 112, E1020–E1027 (2015).
Boorman, E. D., Behrens, T. E. & Rushworth, M. F. Counterfactual choice and learning in a neural network centered on human lateral frontopolar cortex. PLoS Biol. 9, e1001093 (2011).
Daw, N. D., O’Doherty, J. P., Dayan, P., Seymour, B. & Dolan, R. J. Cortical substrates for exploratory decisions in humans. Nature 441, 876–879 (2006).
Wise, S. P. & Murray, E. A. Arbitrary associations between antecedents and actions. Trends Neurosci. 23, 271–276 (2000).
Zhou, Y. & Freedman, D. J. Posterior parietal cortex plays a causal role in perceptual and categorical decisions. Science 365, 180–185 (2019).
Donohue, S. E., Wendelken, C., Crone, E. A. & Bunge, S. A. Retrieving rules for behavior from long-term memory. Neuroimage 26, 1140–1149 (2005).
Ibos, G. & Freedman, D. J. Dynamic integration of task-relevant visual features in posterior parietal cortex. Neuron 83, 1468–1480 (2014).
Tremblay, L., Gettner, S. N. & Olson, C. R. Neurons with object-centered spatial selectivity in macaque SEF: do they represent locations or rules? J. Neurophysiol. 87, 333–350 (2002).
Konishi, S. et al. Common inhibitory mechanism in human inferior prefrontal cortex revealed by event-related functional MRI. Brain 122, 981–991 (1999).
Niendam, T. A. et al. Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions. Cogn. Affect. Behav. Neurosci. 12, 241–268 (2012).
Eldridge, M. A. et al. Chemogenetic disconnection of monkey orbitofrontal and rhinal cortex reversibly disrupts reward value. Nat. Neurosci. 19, 37–39 (2016).
Whissell, P. D., Tohyama, S. & Martin, L. J. The use of DREADDs to deconstruct behavior. Front. Genet. 7, 70 (2016).
Reed, P., Watts, H. & Truzoli, R. Flexibility in young people with autism spectrum disorders on a card sort task. Autism 17, 162–171 (2013).
Luck, S. J. & Gold, J. M. The construct of attention in schizophrenia. Biol. Psychiatry 64, 34–39 (2008).
Barbalat, G., Chambon, V., Franck, N., Koechlin, E. & Farrer, C. Organization of cognitive control within the lateral prefrontal cortex in schizophrenia. Arch. Gen. Psychiatry 66, 377–386 (2009).
den Braber, A. et al. Brain activation during cognitive planning in twins discordant or concordant for obsessive–compulsive symptoms. Brain 133, 3123–3140 (2010).
Badre, D. & D’Esposito, M. Is the rostro-caudal axis of the frontal lobe hierarchical? Nat. Rev. Neurosci. 10, 659–669 (2009).
Badre, D. & Nee, D. E. Frontal cortex and the hierarchical control of behavior. Trends Cogn. Sci. 22, 170–188 (2018).
Bahlmann, J., Blumenfeld, R. S. & D’Esposito, M. The rostro-caudal axis of frontal cortex is sensitive to the domain of stimulus information. Cereb. Cortex 25, 1815–1826 (2015).
Wendelken, C., Chung, D. & Bunge, S. A. Rostrolateral prefrontal cortex: domain-general or domain-sensitive? Hum. Brain Mapp. 33, 1952–1963 (2012).
Pischedda, D., Gorgen, K., Haynes, J. D. & Reverberi, C. Neural representations of hierarchical rule sets: the human control system represents rules irrespective of the hierarchical level to which they belong. J. Neurosci. 37, 12281–12296 (2017).
Tsujimoto, S., Genovesio, A. & Wise, S. P. Evaluating self-generated decisions in frontal pole cortex of monkeys. Nat. Neurosci. 13, 120–126 (2010). This pioneering study describes the activity of frontopolar cortex cells in monkeys performing cognitive tasks.
The authors thank K. Tanaka (RIKEN Centre for Brain Science, Japan) for his contribution to our proposed model of the interaction between abstract rules and executive functions. The authors also thank the Australian Research Council (ARC) Centre of Excellence in Integrative Brain Function; the authors’ research work is partially funded by an ARC Discovery project grant to F.A.M. and a UK Medical Research Project grant to M.J.B.
The authors declare no competing interests.
Peer review information
Nature Reviews Neuroscience thanks S. Bunge, G. Ashby and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
The cognitive ability to consider other goals and resources, such as reward, outside the ongoing task.
- Executive functions
Brain mechanisms that organize and optimize the use of cognitive resources to achieve a goal.
The cognitive ability to optimize gain and decrease cost while performing an ongoing task.
- Selective attention
Neural mechanisms involved in focusing cognitive resources on task-relevant sensory-perceptual processes and inhibiting goal-irrelevant stimuli to facilitate achieving goals.
- Extra-dimensional shift
In the context of object-discrimination tasks, individuals learn to select an object on the basis of a feature in a specific dimension that is reinforced by a reward; a shift in reinforcement to another feature in a different dimension (for example, from red colour to triangle shape) means that individuals need to shift their choice accordingly to get the reward.
- Intra-dimensional shift
In the context of object-discrimination tasks, individuals learn to select an object on the basis of a feature in a specific dimension that is reinforced by a reward; a shift in reinforcement to another feature in the same dimension (for example, from red to blue colour) means that individuals need to shift their choice accordingly to get the reward.
- Stimulus–reward reversal
In the context of object-discrimination tasks, the object–reward association contingency of two objects is reversed; individuals must learn to select the currently rewarded object, which was previously the unrewarded object.
- Conflict resolution
Achieving goals in cognitive tasks might require resolution of a conflict (competition) between two sources of information or between two opposing responses.
Rights and permissions
About this article
Cite this article
Mansouri, F.A., Freedman, D.J. & Buckley, M.J. Emergence of abstract rules in the primate brain. Nat Rev Neurosci 21, 595–610 (2020). https://doi.org/10.1038/s41583-020-0364-5
This article is cited by
Dimension of visual information interacts with working memory in monkeys and humans
Scientific Reports (2022)
Theta oscillations shift towards optimal frequency for cognitive control
Nature Human Behaviour (2022)
Prefrontal connectomics: from anatomy to human imaging
Neurodynamical Computing at the Information Boundaries of Intelligent Systems
Cognitive Computation (2022)
Investigating the sex-dependent effects of prefrontal cortex stimulation on response execution and inhibition
Biology of Sex Differences (2021)