Key Points
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Recent studies have reported rostro-caudal distinctions in frontal cortex activity based on the level of abstractness of action representations. Moreover, some have proposed that these differences reflect a hierarchical organization, whereby anterior frontal regions influence processing by posterior frontal regions during the realization of abstract action goals as motor acts. However, if such a processing hierarchy indeed exists, systematic rostro-caudal patterns should be evident in the anatomy and function of the frontal cortex.
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Evidence from single-unit recording and lesion studies of behavioural rule learning, conditional action selection and response sequencing in non-human primates suggest that prefrontal cortex neurons code for more abstract rules and categories of responses than do premotor neurons, which are located in the more-caudal frontal cortex.
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Studies using functional MRI of humans have consistently shown systematic within-subject differences in activation from premotor cortex (caudal) to the frontal pole (rostral) based on the degree of abstraction entailed by an action selection problem.
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Data from effective connectivity analysis of functional MRI data in humans suggests a rostral-to-caudal flow of influence, which is indirectly consistent with a rostro-caudal hierarchy of processing. Recent, preliminary evidence from lesion studies provides the first direct support for such a hierarchy by showing deficits in more-abstract action selection after caudal frontal lesions but no deficits in more-concrete action selection after rostral frontal lesions.
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There is a gradient of laminar organization within the frontal cortex from the most anterior (least differentiated) to posterior portions. In this scheme, less differentiated areas, such as those in rostral prefrontal cortex (PFC; areas 10, 9 and 46), have more diffuse projections and are thus well situated to be at the top of a hierarchy. In contrast, more differentiated areas, such as those in caudal PFC (areas 9/46 and 8), have more intrinsic connections and are well situated to be lower in a hierarchy.
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Afferent and efferent projections within the frontal cortex follow a principle of contiguity along the rostro-caudal dimension, such that each region projects to immediately adjacent regions that are rostral and caudal to it. Thus, area 9/46d projects to area 10 and area 6. However, the frontal cortex is not fully connected. For example, no direct connections are found between 9/46d and 9/46v, even though they are adjacent to one another.
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Non-adjacent regions follow an asymmetry principle from rostral to caudal within the frontal cortex. Thus, area 10 projects to area 6 but there are no projections from area 6 to area 10.
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The most rostrally localized area 10 does not project directly to parietal, temporal and occipital areas, but more-caudal frontal regions (areas 9/46 and 6) do have massive bidirectional connections with these areas.
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During development, separate regions along the rostro-caudal axis of the frontal cortex mature at different rates. Although the premotor cortex matures the earliest, development does not progress uniformly back to front. Rather, the most caudal and rostral portions of the frontal cortex mature first, followed by the interposed lateral frontal regions.
Abstract
The frontal lobes in the brain are a component of the cerebral system that supports goal-directed behaviour. However, their functional organization remains controversial. Recent studies have reported rostro-caudal distinctions in frontal cortex activity based on the abstractness of action representations. In addition, some have proposed that these differences reflect a hierarchical organization, whereby anterior frontal regions influence processing by posterior frontal regions during the realization of abstract action goals as motor acts. However, few have considered whether the anatomy and physiology of the frontal lobes support such a scheme. To address this gap, this Review surveys anatomical, neuroimaging, electrophysiological and developmental findings, and considers the question: could the organization of the frontal cortex be hierarchical?
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References
Badre, D. & Wagner, A. D. Selection, integration, and conflict monitoring; assessing the nature and generality of prefrontal cognitive control mechanisms. Neuron 41, 473–487 (2004).
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).
Carter, C. S. et al. Anterior cingulate cortex, error detection, and the on-line monitoring of performance. Science 280, 747–749 (1998).
D'Esposito, M. et al. The neural basis of the central executive system of working memory. Nature 378, 279–281 (1995).
Duncan, J. An adaptive coding model of neural function in prefrontal cortex. Nature Rev. Neurosci. 2, 820–829 (2001).
Miller, E. K. & Cohen, J. D. An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci. 24, 167–202 (2001). This authoritative review provides a fundamental background on the cognitive control function of the PFC. It focuses on the theory that action goals are maintained as distributed patterns of activity in PFC, as a consequence of which other neural systems are biased to perform in goal-relevant ways.
O'Reilly, R. C. & Frank, M. J. Making working memory work: a computational model of learning in the prefrontal cortex and basal ganglia. Neural Comput. 18, 283–328 (2006).
Passingham, R. E. & Rowe, J. B. in Principles of Frontal Lobe Function (eds Stuss, D. T. & Knight, R. T.) 221–232 (Oxford University Press, New York, 2002).
Petrides, M. Lateral prefrontal cortex: architectonic and functional organization. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360, 781–795 (2005).
Petrides, M. & Pandya, D. N. Comparative cytoarchitectonic analysis of the human and the macaque ventrolateral prefrontal cortex and corticocortical connection patterns in the monkey. Eur. J. Neurosci. 16, 291–310 (2002).
Petrides, M. & Pandya, D. N. in Principles of Frontal Lobe Function (eds Stuss, D. T. & Knight, R. T.) 31–50 (Oxford University Press, New York, 2002).
Stuss, D. T. & Alexander, M. P. Is there a dysexecutive syndrome? Philos. Trans. R. Soc. Lond. B Biol. Sci. 362, 901–915 (2007).
Sirigu, A. et al. Distinct frontal regions for processing sentence syntax and story grammar. Cortex 34, 771–778 (1998).
Duncan, J. & Owen, A. M. Common regions of the human frontal lobe recruited by diverse cognitive demands. Trends Neurosci. 23, 475–483 (2000).
Freedman, D. J., Reisenhuber, M., Poggio, T. & Miller, E. K. Categorical representation of visual stimuli in the primate prefrontal cortex. Science 291, 312–316 (2001).
Badre, D. & D'Esposito, M. Functional magnetic resonance imaging evidence for a hierarchical organization of the prefrontal cortex. J. Cogn. Neurosci. 19, 2082–2099 (2007).
Badre, D., Hoffman, J., Cooney, J. W. & D'Esposito, M. Hierarchical cognitive control deficits following damage to the human frontal lobe. Nature Neurosci. 12, 515–522 (2009). This study provides evidence that in patients with damage due to stroke the impairment at tasks requiring cognitive control at a level of abstraction depended on how far rostrally their lesion is located. This is also the first study to directly demonstrate rostral-to-caudal dependencies in processing, a necessary component of hierarchy in the frontal cortex.
Koechlin, E. & Jubault, T. Broca's area and the hierarchical organization of human behavior. Neuron 50, 963–974 (2006).
Koechlin, E., Ody, C. & Kouneiher, F. The architecture of cognitive control in the human prefrontal cortex. Science 302, 1181–1185 (2003). This paper reports the first neuroimaging experiment showing a rostro-caudal gradient of activity in frontal cortex based on a systematic manipulation of abstraction across conditions.
Lashley, K. S. in Cerebral Mechanisms in Behavior (ed. Jeffress, L. A.) 112–136 (Wiley, New York, 1951).
Miller, G. A., Galanter, E. & Pribram, K. H. Plans and the Structure of Behavior (Holt, Rinehart and Winston, Inc., New York, 1960).
Newell, A. Unified Theories of Cognition (Harvard University Press, Cambridge, Massachusetts, 1990).
Rumelhart, D. E. & Norman, D. A. Simulating a skilled typist: a study of skillled cognitive-motor performance. Cogn. Sci. 6, 1–36 (1982).
Schank, R. C. & Abelson, R. Scripts, plans, goals, and understanding (Lawrence Erlbaum Associates, Ltd, Hove, UK, 1977).
Badre, D. Cognitive control, hierarchy, and the rostro-caudal organization of the frontal lobes. Trends Cogn. Sci. 12, 193–200 (2008). This review discusses the various forms of abstraction that have been proposed to account for functional differences along the rostro-caudal axis of the frontal cortex, considering their common and potentially distinguishing characteristics.
Botvinick, M. M. Multilevel structure in behaviour and in the brain: a model of Fuster's hierarchy. Philos. Trans. R. Soc. Lond. B Biol. Sci. (2007).
Botvinick, M. M. Hierarchical models of behavior and prefrontal function. Trends Cogn. Sci. 12, 201–208 (2008). This paper reviews computational accounts of hierarchical control of behaviour and their relationship to frontal lobe function.
Buckner, R. L. Functional-anatomic correlates of control processes in memory. J. Neurosci. 23, 3999–4004 (2003).
Bunge, S. A. & Zelazo, P. D. A brain-based account of the development of rule use in childhood. Curr. Dir. Psychol. Sci. 15, 118–121 (2006).
Christoff, K. & Gabrieli, J. D. E. The frontopolar cortex and human cognition: evidence for a rostrocaudal hierarchal organization within the human prefrontal cortex. Psychobiology 28, 168–186 (2000).
Christoff, K. & Keramatian, K. in Perspectives on Rule-Guided Behavior (eds Bunge, S. A. & Wallis, J. D.) (Oxford University Press, New York, 2007).
Courtney, S. M. Attention and cognitive control as emergent properties of information representation in working memory. Cogn. Affect Behav. Neurosci. 4, 501–516 (2004).
Courtney, S. M., Roth, J. K. & Sala, J. B. in The Cognitive Neuroscience of Working Memory (eds Osaka, N., Logie, R. & D'Esposito, M.) 369–383 (Oxford University Press, Oxford, 2007).
Dias, R., Robbins, T. W. & Roberts, A. C. Dissociable forms of inhibitory control within prefrontal cortex with an analog of the Wisconsin Card Sort Test: restriction to novel situations and independence from “on-line” processing. J. Neurosci. 17, 9285–9297 (1997).
Fuster, J. M. The Prefrontal Cortex: Anatomy, Physiology, and Neuropsychology of the Frontal Lobe (Lippincott-Raven Publishers, Philadelphia, PA, 1997). This book provides an authoritative review of frontal lobe anatomy and function and articulates one of the first proposals of a hierarchical architecture of frontal lobe organization, termed the 'perception-action cycle'.
Fuster, J. M. The prefrontal cortex—an update: time is of the essence. Neuron 30, 319–333 (2001).
Fuster, J. M. Upper processing stages of the perception-action cycle. Trends Cogn. Sci. 8, 143–145 (2004).
Hazy, T. E., Frank, M. J. & O'Reilly, R. C. Towards an executive without a homunculus: computational models of the prefrontal cortex/basal ganglia system. Philos. Trans. R. Soc. Lond. B Biol. Sci. 362, 1601–1613 (2007).
Koechlin, E. & Hyafil, A. Anterior prefrontal function and the limits of human decision-making. Science 318, 594–598 (2007).
Koechlin, E. & Summerfield, C. An information theoretical approach to prefrontal executive function. Trends Cogn. Sci. 11, 229–235 (2007).
O'Reilly, R. C., Noelle, D. C., Braver, T. S. & Cohen, J. D. Prefrontal cortex and dynamic categorization tasks: representational organization and neuromodulatory control. Cereb Cortex 12, 246–257 (2002).
Petrides, M. in From Monkey Brain to Human Brain: A Fyssen Foundation Symposium (eds Dehaene, S., Duhamel, J.-R., Hauser, M. D. & Rizzolatti, G.) 293–314 (The MIT Press, Cambridge, Massachusetts 2006).
Ramnani, N. & Owen, A. M. Anterior prefrontal cortex: insights into function from anatomy and neuroimaging. Nature Rev. Neurosci. 5, 184–194 (2004).
Miller, B. T. & D'Esposito, M. Searching for “the top” in top-down control. Neuron 48, 535–538 (2005).
Fuster, J. M., Bodner, M. & Kroger, J. Cross-modal and cross-temporal association in neurons of frontal cortex. Nature 405, 347–351 (2000).
Rao, S. C., Rainer, G. & Miller, E. K. Integration of what and where in the primate prefrontal cortex. Science 276 (1997).
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).
Asaad, W. F., Rainer, G. & Miller, E. K. Neural activity in the primate prefrontal cortex during associative learning. Neuron 21, 1399–1407 (1998).
Passingham, R. E. The Frontal Lobes and Voluntary Action (Oxford University Press, Oxford, 1993).
Christoff, K. et al. Rostrolateral prefrontal cortex involvement in relational integration during reasoning. Neuroimage 14, 1136–1149 (2001).
Petrides, M. in The frontal lobes revisited (ed. Perecman, E.) 91–108 (IRBN Press, New York, 1987).
Brasted, P. J. & Wise, S. P. Comparison of learning-related neuronal activity in the dorsal premotor cortex and striatum. Eur. J. Neurosci. 19, 721–740 (2004).
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).
Hadj-Bouziane, F., Meunier, M. & Boussaoud, D. Conditional visuo-motor learning in primates: a key role for the basal ganglia. J. Physiol. Paris 97, 567–579 (2003).
Lucchetti, C. & Bon, L. Time-modulated neuronal activity in the premotor cortex of macaque monkeys. Exp. Brain Res. 141, 254–260 (2001).
Mitz, A. R., Godschalk, M. & Wise, S. P. Learning-dependent neuronal activity in the premotor cortex: activity during the acquisition of conditional motor associations. J. Neurosci. 11, 1855–1872 (1991).
Hoshi, E. & Tanji, J. Differential involvement of neurons in the dorsal and ventral premotor cortex during processing of visual signals for action planning. J. Neurophysiol. 95, 3596–3616 (2006).
Hoshi, E. & Tanji, J. Distinctions between dorsal and ventral premotor areas: anatomical connectivity and functional properties. Curr. Opin. Neurobiol. 17, 234–242 (2007).
Passingham, R. E. Premotor cortex and preparation for movement. Exp. Brain Res. 70, 590–596 (1988).
Passingham, R. E. Premotor cortex and the retrieval of movement. Brain Behav. Evol. 33, 189–192 (1989).
Petrides, M. Deficits in non-spatial conditional associative learning after periarcuate lesions in the monkey. Behav. Brain Res. 16, 95–101 (1985).
Petrides, M. Deficits on conditional associative-learning tasks after frontal- and temporal-lobe lesions in man. Neuropsychologia 23, 601–614 (1985).
Amemori, K. & Sawaguchi, T. Rule-dependent shifting of sensorimotor representation in the primate prefrontal cortex. Eur. J. Neurosci. 23, 1895–1909 (2006).
Asaad, W. F., Rainer, G. & Miller, E. K. Task-specific neural activity in the primate prefrontal cortex. J. Neurophysiol. 84, 451–459 (2000).
Everling, S. & DeSouza, J. F. Rule-dependent activity for prosaccades and antisaccades in the primate prefrontal cortex. J. Cogn. Neurosci. 17, 1483–1496 (2005).
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).
White, I. M. & Wise, S. P. Rule-dependent neuronal activity in the prefrontal cortex. Exp. Brain Res. 126, 315–335 (1999).
Wallis, J. D., Anderson, K. C. & Miller, E. K. Single neurons in prefrontal cortex encode abstract rules. Nature 411, 953–956 (2001).
Wallis, J. D. & Miller, E. K. From rule to response: neuronal processes in the premotor and prefrontal cortex. J. Neurophysiol. 90, 1790–1806 (2003).
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).
Boettiger, C. A. & D'Esposito, M. Frontal networks for learning and executing arbitrary stimulus-response associations. J. Neurosci. 25, 2723–2732 (2005).
Toni, I., Krams, M., Turner, R. & Passingham, R. E. The time course of changes during motor sequence learning: a whole-brain fMRI study. Neuroimage 8, 50–61 (1998).
Genovesio, A., Brasted, P. J., Mitz, A. R. & Wise, S. P. Prefrontal cortex activity related to abstract response strategies. Neuron 47, 307–320 (2005).
Boussaoud, D. Attention versus intention in the primate premotor cortex. Neuroimage 14, S40–45 (2001).
Averbeck, B. B. & Lee, D. Prefrontal neural correlates of memory for sequences. J. Neurosci. 27, 2204–2211 (2007).
Ohbayashi, M., Ohki, K. & Miyashita, Y. Conversion of working memory to motor sequence in the monkey premotor cortex. Science 301, 233–236 (2003).
Shima, K., Isoda, M., Mushiake, H. & Tanji, J. Categorization of behavioural sequences in the prefrontal cortex. Nature 445, 315–318 (2007). This papers reports an elegant experiment showing that single-unit recording in monkeys provides evidence that neurons in prefrontal cortex are tuned to abstract categories of response sequences that generalize across the specific responses that form these sequences.
Tanji, J. & Hoshi, E. Role of the lateral prefrontal cortex in executive behavioral control. Physiol. Rev. 88, 37–57 (2008).
Wallis, J. D. in Neuroscience of Rule-Guided Behavior (eds Bunge, S. A. & Wallis, J. D.) (Oxford University Press, New York, 2008).
Kurata, K., Tsuji, T., Naraki, S., Seino, M. & Abe, Y. Activation of the dorsal premotor cortex and pre-supplementary motor area of humans during an auditory conditional motor task. J. Neurophysiol. 84, 1667–1672 (2000).
Moore, C. I. et al. Segregation of somatosensory activation in the human rolandic cortex using fMRI. J. Neurophysiol. 84, 558–569 (2000).
Picard, N. & Strick, P. L. Imaging the premotor areas. Curr. Opin. Neurobiol. 11, 663–672 (2001).
Pochon, J. B. et al. The role of dorsolateral prefrontal cortex in the preparation of forthcoming actions: an fMRI study. Cereb Cortex 11, 260–266 (2001).
Schumacher, E. H. & D'Esposito, M. Neural implementation of response selection in humans as revealed by localizing effects of stimulus-response compatibility on brain activation. Hum. Brain Mapp. 17, 193–201 (2002).
Schumacher, E. H., Elston, P. A. & D'Esposito, M. Neural evidence for representation-specific response selection. J. Cogn. Neurosci. 15, 1111–1121 (2003).
Kennerley, S. W., Sakai, K. & Rushworth, M. F. Organization of action sequences and the role of the pre-SMA. J. Neurophysiol. 91, 978–993 (2004).
Badre, D. & Wagner, A. D. Computational and neurobiological mechanisms underlying cognitive flexibility. Proc. Natl Acad. Sci. USA 103, 7186–7191 (2006).
Brass, M. & von Cramon, D. Y. The role of the frontal cortex in task preparation. Cereb Cortex 12, 908–914 (2002).
Dove, A., Pollmann, S., Schubert, T., Wiggins, C. J. & von Cramon, D. Y. Prefrontal cortex activation in task switching: an event-related fMRI study. Brain Res. Cogn. Brain Res. 9, 103–109 (2000).
Sohn, M. H., Ursu, S., Anderson, J. R., Stenger, V. A. & Carter, C. S. Inaugural article: the role of prefrontal cortex and posterior parietal cortex in task switching. Proc. Natl Acad. Sci. USA 97, 13448–13453 (2000).
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).
Gilbert, S. J. et al. Functional specialization within rostral prefrontal cortex (area 10): a meta-analysis. J. Cogn. Neurosci. 18, 932–948 (2006).
Braver, T. S. & Bongiolatti, S. R. The role of frontopolar cortex in subgoal processing during working memory. Neuroimage 15, 523–536 (2002).
Koechlin, E., Basso, G., Pietrini, P., Panzer, S. & Grafman, J. The role of the anterior prefrontal cortex in human cognition. Nature 399, 148–151 (1999).
Bunge, S. A., Wendelken, C., Badre, D. & Wagner, A. D. Analogical reasoning and prefrontal cortex: evidence for separable retrieval and integration mechanisms. Cereb Cortex 15, 239–249 (2005).
Christoff, K., Ream, J. M., Geddes, L. P. T. & Gabrieli, J. D. E. Evaluating self-generated information: Anterior prefrontal contributions to human cognition. Behav. Neurosci. 117, 1161–1168 (2003).
Kroger, J. K. et al. Recruitment of anterior dorsolateral prefrontal cortex in human reasoning: a parametric study of relational complexity. Cereb Cortex 12, 477–485 (2002).
Ranganath, C., Johnson, M. K. & D'Esposito, M. Left anterior prefrontal activation increases with demands to recall specific perceptual information. J. Neurosci. 20, RC108 (2000).
Ranganath, C. & Paller, K. A. Neural correlates of memory retrieval and evaluation. Brain Res. Cogn. Brain Res. 9, 209–222 (2000).
Velanova, K. et al. Functional-anatomic correlates of sustained and transient processing components engaged during controlled retrieval. J. Neurosci. 23, 8460–8470 (2003).
Burgess, P. W., Dumontheil, I. & Gilbert, S. J. The gateway hypothesis of rostral prefrontal cortex (area 10) function. Trends Cogn. Sci. 11, 290–298 (2007).
Braver, T. S., Reynolds, J. R. & Donaldson, D. I. Neural mechanisms of transient and sustained cognitive control during task switching. Neuron 39, 713–726 (2003).
Donaldson, D. I., Petersen, S. E., Ollinger, J. M. & Buckner, R. L. Dissociating state and item components of recognition memory using fMRI. Neuroimage 13, 129–142 (2001).
Kouneiher, F., Charron, S. & Koechlin, E. Motivation and cognitive control in the human prefrontal cortex. Nature Neurosci. 12, 939–945 (2009).
Badre, D. & Wagner, A. D. Left ventrolateral prefrontal cortex and the cognitive control of memory. Neuropsychologia 45, 2883–2901 (2007).
Gold, B. T., Balota, D. A., Kirchhoff, B. A. & Buckner, R. L. Common and Dissociable Activation Patterns Associated with Controlled Semantic and Phonological Processing: Evidence from fMRI Adaptation. Cereb. Cortex 15, 1438–1450 (2005).
Gold, B. T. & Buckner, R. L. Common prefrontal regions coactivate with dissociable posterior regions during controlled semantic and phonological tasks. Neuron 35, 803–812 (2002).
Gough, P. M., Nobre, A. C. & Devlin, J. T. Dissociating linguistic processes in the left inferior frontal cortex with transcranial magnetic stimulation. J. Neurosci. 25, 8010–8016 (2005).
Poldrack, R. A. & Wagner, A. D. What can neuroimaging tell us about the mind? Insights from prefrontal cortex. Curr. Direct. Psychol. Sci. 13, 177–181 (2004).
Poldrack, R. A. et al. Functional specialization for semantic and phonological processing in the left inferior prefrontal cortex. Neuroimage 10, 15–35 (1999).
Badre, D., Poldrack, R. A., Pare-Blagoev, E. J., Insler, R. Z. & Wagner, A. D. Dissociable controlled retrieval and generalized selection mechanisms in ventrolateral prefrontal cortex. Neuron 47, 907–918 (2005).
Gold, B. T. et al. Dissociation of automatic and strategic lexical-semantics: functional magnetic resonance imaging evidence for differing roles of multiple frontotemporal regions. J. Neurosci. 26, 6523–6532 (2006).
Race, E. A., Shanker, S. & Wagner, A. D. Neural Priming in Human Frontal Cortex: Multiple Forms of Learning Reduce Demands on the Prefrontal Executive System. J. Cogn. Neurosci. 21, 1766–1781 (2009). This fMRI study of repetition priming provides within-subject evidence for a rostro-caudal functional gradient along the ventrolateral PFC.
Blumenfeld, R. S. & Ranganath, C. Prefrontal cortex and long-term memory encoding: an integrative review of findings from neuropsychology and neuroimaging. Neuroscientist 13, 280–291 (2007).
D'Esposito, M., Postle, B. R., Ballard, D. & Lease, J. Maintenance versus manipulation of information held in working memory: an event-related fMRI study. Brain Cogn. 41, 66–86 (1999).
Hampshire, A., Duncan, J. & Owen, A. M. Selective tuning of the blood oxygenation level-dependent response during simple target detection dissociates human frontoparietal subregions. J. Neurosci. 27, 6219–6223 (2007).
Sakai, K. & Passingham, R. E. Prefrontal interactions reflect future task operations. Nature Neurosci. 6, 75–81 (2003).
Sakai, K. & Passingham, R. E. Prefrontal set activity predicts rule-specific neural processing during subsequent cognitive performance. J. Neurosci. 26, 1211–1218 (2006).
Rowe, J. B. et al. Is the prefrontal cortex necessary for establishing cognitive sets? J. Neurosci. 27, 13303–13310 (2007).
Petrides, M. & Pandya, D. N. in Handbook of Neuropsychology (eds Boller, F. & Grafman, J.) 17–58 (Elsevier, Amsterdam, 1994). In this chapter, anatomists Petrides and Pandya report an extensive comparison of the architecture of the frontal cortex between monkeys and humans.
Petrides, M. & Pandya, D. N. Dorsolateral prefrontal cortex: comparative cytoarchitectonic analysis in the human and the macaque brain and corticocortical connection patterns. Eur. J. Neurosci. 11, 1011–1036 (1999).
Barbas, H. & Pandya, D. N. in Frontal lobe function and dysfunction (eds Levin, H. S., Eisenberg, H. & Benton, A. L.) 35–58 (Oxford University Press, Oxford, 1991).
Sanides, F. in The Structure and Function of the Nervous System (ed. Bourne, G. H.) 329–453 (Academic Press, New York, 1972).
Barbas, H. & Pandya, D. N. Architecture and intrinsic connections of the prefrontal cortex in the rhesus monkey. J. Comp. Neurol. 286, 353–375 (1989). In this study, anatomists Barbas and Pandya present data from rhesus monkeys demonstrating that there is a gradient of laminar organization within the frontal cortex from the most anterior (least differentiated) to posterior portions.
Barbas, H. Anatomic organization of basoventral and mediodorsal visual recipient prefrontal regions in the rhesus monkey. J. Comp. Neurol. 276, 313–342 (1988).
Petrides, M. & Pandya, D. N. Efferent association pathways from the rostral prefrontal cortex in the macaque monkey. J. Neurosci. 27, 11573–11586 (2007). Using the autoradiographic method, this study reports the course and terminations of the efferent cortico–cortical connections of the rostral prefrontal region (area 10) in macaque monkeys.
Schmahmann, J. D.h. Fiber pathways of the brain (Oxford University Press, Oxford, 2006).
Barbas, H. & Pandya, D. N. Architecture and frontal cortical connections of the premotor cortex (area 6) in the rhesus monkey. J. Comp. Neurol. 256, 211–228 (1987).
Botvinick, M. & Plaut, D. C. Doing without schema hierarchies: a recurrent connectionist approach to normal and impaired routine sequential action. Psychol. Rev. 111, 395–429 (2004).
Vincent, J. L., Kahn, I., Snyder, A. Z., Raichle, M. E. & Buckner, R. L. Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. J. Neurophysiol. 100, 3328–3342 (2008). This study applied functional connectivity analysis to resting state fMRI data and characterized a specific fronto-parietal network that was coherent with the frontal pole (approximately area 10). In the frontal cortex, this analysis identified a dorsal rostro-caudal network that closely corresponds to the gradient of rostro-caudal regions identified in association with hierarchical control.
Buckner, R. L. & Vincent, J. L. Unrest at rest: default activity and spontaneous network correlations. Neuroimage 37, 1091–1096; discussion 1097–9 (2007).
Fox, M. D. et al. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl Acad. Sci. USA 102, 9673–9678 (2005).
Kahn, I., Andrews-Hanna, J. R., Vincent, J. L., Snyder, A. Z. & Buckner, R. L. Distinct cortical anatomy linked to subregions of the medial temporal lobe revealed by intrinsic functional connectivity. J. Neurophysiol. 100, 129–139 (2008).
Vincent, J. L. et al. Intrinsic functional architecture in the anaesthetized monkey brain. Nature 447, 83–86 (2007).
Halford, G. S. Children's Understanding: The Development of Mental Models (Erlbaum, Hillsdale, NJ, 1993).
Robin, N. & Holyoak, K. J. in The Cognitive Neurosciences (ed. Gazzaniga, M. S.) 987–997 (MIT Press, Cambridge, MA, 1995).
Daw, N. D., Niv, Y. & Dayan, P. in Recent Breakthroughs in Basal Ganglia Research (ed. Bezard, E.) (Nova Science, Inc., New York, 2006).
Dayan, P. Bilinearity, rules, and prefrontal cortex. Front. Comput. Neurosci. 1, 1–14 (2007).
Sutton, R. S. & Barto, A. G. Reinforcement Learning: An Introduction (MIT Press, Cambridge, Massachusetts, 1998).
Lenroot, R. K. & Giedd, J. N. Brain development in children and adolescents: insights from anatomical magnetic resonance imaging. Neurosci. Biobehav Rev. 30, 718–729 (2006).
Inder, T. E. & Huppi, P. S. In vivo studies of brain development by magnetic resonance techniques. Ment Retard Dev. Disabil Res. Rev. 6, 59–67 (2000).
Toga, A. W., Thompson, P. M. & Sowell, E. R. Mapping brain maturation. Trends Neurosci. 29, 148–159 (2006).
Shaw, P. et al. Neurodevelopmental trajectories of the human cerebral cortex. J. Neurosci. 28, 3586–3594 (2008).
Giedd, J. N. et al. Brain development during childhood and adolescence: a longitudinal MRI study. Nature Neurosci. 2, 861–863 (1999).
Jernigan, T. L., Trauner, D. A., Hesselink, J. R. & Tallal, P. A. Maturation of human cerebrum observed in vivo during adolescence. Brain 114, 2037–2049 (1991).
Solomon, M., Ozonoff, S. J., Cummings, N. & Carter, C. S. Cognitive control in autism spectrum disorders. Int. J. Dev. Neurosci. 26, 239–247 (2008).
Sowell, E. R., Thompson, P. M., Tessner, K. D. & Toga, A. W. Mapping continued brain growth and gray matter density reduction in dorsal frontal cortex: inverse relationships during postadolescent brain maturation. J. Neurosci. 21, 8819–8829 (2001).
Sowell, E. R. et al. Longitudinal mapping of cortical thickness and brain growth in normal children. J. Neurosci. 24, 8223–8231 (2004).
Gogtay, N. et al. Dynamic mapping of human cortical development during childhood through early adulthood. Proc. Natl Acad. Sci. USA 101, 8174–8179 (2004).
Hazy, T. E., Frank, M. J. & O'Reilly, R. C. Banishing the homunculus: making working memory work. Neuroscience 139, 105–118 (2006).
Brodmann, K. Beiträge zur histologischen Lokalisation der Grosshirnrinde. VI. Mitteilung. Die Cortexgliederung des Menschen. J. Psychol. Neurol. (Lzp.) 10, 231–246 (1908) (in German).
Brodmann, K. Beiträge zur histologischen Lokalisation der Grosshirnrinde. III. Mitteilung. Die Rindenfelder der niederen Affen. J. Psychol. Neurol. (Lzp.) 4, 177–226 (1905) (in German).
Walker, A. E. A cytoarchitectural study of the prefrontal area of the macaque monkey. J. Comp. Neurol. 73, 59–86 (1940).
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Supported by the National Institutes of Health (MH63901 and NS40813) and the Veterans Administration Research Service.
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Domain generality along rostro-caudal frontal cortex (PDF 271 kb)
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Glossary
- Cognitive control
-
Also termed executive function, cognitive control allows flexible behaviour by guiding thought and action based on goals, plans and intentions.
- Double dissociation
-
When two experimental manipulations have different effects on two dependent variables (for example, on the left and right hemisphere or on the medial and lateral prefrontal cortex).
- Domain (stimulus/input domains)
-
A type of information, such as spatial versus verbal versus object-related information. Domains are often associated with independent or modular input systems.
- Action rule
-
A type of knowledge that specifies how to behave given a particular state. A stimulus-to-response mapping is a simple rule.
- Semantic
-
Conceptual knowledge, beliefs and facts about the world. In the verbal domain, semantic refers to word meanings.
- Phonology (phonological)
-
The sound structure of a word in terms of the smallest sound units that distinguish different words in a language.
- Repetition priming
-
Facilitated processing of a stimulus upon repetition, which happens even following an extended delay.
- Structural equation modelling
-
A statistical approach for testing proposed causal relationships between variables.
- Seeding
-
A step in functional connectivity analysis whereby a region of interest is defined to which connectivity of all other regions is estimated.
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Badre, D., D'Esposito, M. Is the rostro-caudal axis of the frontal lobe hierarchical?. Nat Rev Neurosci 10, 659–669 (2009). https://doi.org/10.1038/nrn2667
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DOI: https://doi.org/10.1038/nrn2667
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