Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-17T17:16:05.320Z Has data issue: false hasContentIssue false

4 - A microcircuit model of prefrontal functions: ying and yang of reverberatory neurodynamics in cognition

Published online by Cambridge University Press:  11 September 2009

By
Xiao-Jing Wang
Edited by
Jarl Risberg  and
Jordan Grafman
Jarl Risberg
Affiliation:
Lunds Universitet, Sweden
Jordan Grafman
Affiliation:
National Institute of Health, Bethesda, MD, USA
Get access

Summary

Introduction

In contrast to neural systems responsible for sensory processing or motor behavior, the prefrontal cortex is a quintessentially “cognitive” structure. A bewildering gamut of complex higher brain processes depend on prefrontal cortex. It is thus a particularly challenging quest to elucidate the neurobiology of prefrontal functions at the mechanistic level. Patricia S. Goldman-Rakic voiced this difficulty in 1987:

Unlike largely sensory and motor skills, the mnemonic, associative, and command functions of the mammalian brain have eluded precise neurological explanation. The proposition that cognitive function(s) can be localized to specialized neuronal circuits is not easy to defend because the neural interactions that underlie even the most simple concept or solution of an abstract problem have not been convincingly demonstrated. Also it does not seem possible to conceptualize in neural terms what it means to generate an idea, to grasp the essentials of a situation, to be oriented in space and time, or to plan for long-range goals. Furthermore we are still learning how to formulate the structure-function problem in a way that can lead to fruitful experimentation, theory building, or modeling in terms of neural systems or synaptic mechanisms.

Since these words were written, some of the impediments have begun to yield ground, partly thanks to the development of novel techniques linking cognitive functions with underlying neural processes. The advent of functional magnetic resonance imagining (fMRI) has opened up a window with which brain activity can be probed and dissected during behavior.

Type
Chapter
Information
The Frontal Lobes
Development, Function and Pathology
 , pp. 92 - 127
Publisher: Cambridge University Press
Print publication year: 2006

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abbott, L. F. & Regehr, W. G. (2004). Synaptic computation. Nature, 431, 796–803.CrossRefGoogle ScholarPubMed
Akbarian, S., Sucher, N. J., Bradley, D., et al. (1996). Selective alterations in gene expression for NMDA receptor subunits in prefrontal cortex of schizophrenics. Journal of Neuroscience, 16, 19–30.CrossRefGoogle ScholarPubMed
Amari, S. (1977). Dynamics of pattern formation in lateral-inhibition type neural fields. Biological Cybernetics, 27, 77–87.CrossRefGoogle ScholarPubMed
Amit, D. J. (1995). The Hebbian paradigm reintegrated: local reverberations as internal representations. Behavioral and Brain Sciences, 18, 617–26.CrossRefGoogle Scholar
Amit, D. J. & Brunel, N. (1997). Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex. Cerebral Cortex, 7, 237–52.CrossRefGoogle ScholarPubMed
Arnsten, A. F. T. (1998). Catecholamine modulation of prefrontal cortical cognitive function. Trends in Cognitive Sciences, 2, 436–47.CrossRefGoogle ScholarPubMed
Bachevalier, J., Nemanic, S. & Alvarado, M. C. (2002). The medial temporal lobe structures and object recognition memory in nonhuman primates. In Neuropsychology of Memory, 3rd edn, eds. Squire, L. R. and Schacter, D. L.New York: Guilford Press, pp. 326–338.Google Scholar
Baeg, E. H., Kim, Y. B., Huh, K., et al. (2003). Dynamics of population code for working memory in the prefrontal cortex. Neuron, 40, 177–88.CrossRefGoogle ScholarPubMed
Ben-Yishai, R. R., Bar-Or, L. & Sompolinsky, H. (1995). Theory of orientation tuning in visual cortex. Proceedings of the National Academy of Science USA, 92, 3844–8.CrossRefGoogle ScholarPubMed
Brederode, J. F., Mulligan, V. K. A. & Hendrickson, A. E. (1990). Calcium-binding proteins as markers for subpopulations of GABAergic neurons in monkey striate cortex. The Journal of Comparative Neurology, 298, 1–22.CrossRefGoogle ScholarPubMed
Brody, C. D., Hernandez, A., Zainos, A. & Romo, R. (2003). Timing and neural encoding of somatosensory parametric working memory in macaque prefrontal cortex. Cerebral Cortex, 13, 1196–207.CrossRefGoogle ScholarPubMed
Brunel, N. & Wang, X.-J. (2001). Effects of neuromodulation in a cortical network model of object working memory dominated by recurrent inhibition. Journal of Computational Neuroscience, 11, 63–85.CrossRefGoogle Scholar
Brunel, N. & Wang, X.-J. (2003). What determines the frequency of fast network oscillations with irregular neural discharges? I. Synaptic dynamics and excitation-inhibition balance. Journal of Neurophysiology, 90, 415–30.CrossRefGoogle ScholarPubMed
Buzsaki, G., Geisler, C., Henze, D. A. & Wang, X.-J. (2004). Interneuron Diversity series: Circuit complexity and axon wiring economy of cortical interneurons. Trends in the Neurosciences, 27, 186–93.CrossRefGoogle ScholarPubMed
Camperi, M. & Wang, X.-J, . (1998). A model of visuospatial short-term memory in prefrontal cortex: recurrent network and cellular bistability. Journal of Computational Neuroscience, 5, 383–405.CrossRefGoogle ScholarPubMed
Carlsson, A., Waters, N., Holm-Waters, S., et al. (2001). Interactions between monoamines, glutamate, and GABA in schizophrenia: new evidence. Annual Review of Pharmacology and Toxicology, 41, 237–60.CrossRefGoogle ScholarPubMed
Cauli, B., Audinat, E., Lambolez, B., et al. (1997). Molecular and physiological diversity of cortical nonpyramidal cells. Journal of Neuroscience, 17, 3894–906.CrossRefGoogle ScholarPubMed
Chafee, M. V. & Goldman-Rakic, P. S. (1998). Neuronal activity in macaque prefrontal area 8a and posterior parietal area 7ip related to memory guided saccades. Journal of Neurophysiology, 79, 2919–40.CrossRefGoogle Scholar
Chen, G., Greengard, P. & Yan, Z. (2004). Potentiation of NMDA receptor currents by dopamine D1 receptors in prefrontal cortex. Proceedings of the National Academy of Science USA, 101, 2596–600.CrossRefGoogle ScholarPubMed
Cohen, J. D., Braver, T. S. & Brown, J. W. (2002). Computational perspectives on dopamine function in prefrontal cortex. Current Opinion in Neurobiology, 12, 223–9.CrossRefGoogle ScholarPubMed
Cohen, J. D., Braver, T. S. & O'Reilly, R. C. (1996). A computational approach to prefrontal cortex, cognitive control and schizophrenia: recent developments and current challenges. Philosophical Transactions of the Royal Society of London, B Biological Sciences, 351, 1515–27.CrossRefGoogle ScholarPubMed
Compte, A., Brunel, N., Goldman-Rakic, P. S. & Wang, X.-J. (2000). Synaptic mechanisms and network dynamics underlying spatial working memory in a cortical network model. Cerebral Cortex, 10, 910–23.CrossRefGoogle Scholar
Compte, A., Constantinidis, C., Tegner, J., et al. (2003a). Temporally irregular mnemonic persistent activity in prefrontal neurons of monkeys during a delayed response task. Journal of Neurophysiology, 90, 3441–54.CrossRefGoogle Scholar
Compte, A., Sanchez-Vives, M. V., McCormick, D. A. & Wang, X.-J. (2003b). Cellular and network mechanisms of slow oscillatory activity (<1 Hz) and wave propagations in a cortical network model. Journal of Neurophysiology, 89, 2707–25.CrossRefGoogle Scholar
Conde, F., Lund, J. S., Jacobowitz, D. M., Baimbridge, K. G. & Lewis, D. A. (1994). Local circuit neurons immunoreactive for calretinin, calbindin D-28k or parvalbumin in monkey prefrontal cortex: distribution and morphology. The Journal of Comparative Neurology, 341, 95–116.CrossRefGoogle ScholarPubMed
Constantinidis, C. & Goldman-Rakic, P. S. (2002). Correlated discharges among putative pyramidal neurons and interneurons in the primate prefrontal cortex. Journal of Neurophysiology, 88, 3487–97.CrossRefGoogle ScholarPubMed
Constantinidis, C. & Procyk, E. (2004). The primate working memory networks. Cognitive, Affective & Behavioral Neuroscience, 4, 444–65.CrossRefGoogle ScholarPubMed
Constantinidis, C. & Wang, X.-J. (2004). A neural circuit basis for spatial working memory. Neuroscientist, 10, 553–65.CrossRefGoogle ScholarPubMed
Cossart, R., Aronov, D. & Yuste, R. (2003). Attractor dynamics of network UP states in the neocortex. Nature, 423, 283–8.CrossRefGoogle ScholarPubMed
Curtis, C. E. & D'Esposito, M. (2003). Persistent activity in the prefrontal cortex during working memory. Trends in Cognitive Sciences, 7, 415–23.CrossRefGoogle ScholarPubMed
Curtis, C. E. & D'Esposito, M. (2004). The effects of prefrontal lesions on working memory performance and theory. Cognitive, Affective & Behavioral Neuroscience, 4, 528–39.CrossRefGoogle ScholarPubMed
DeFelipe, J. (1997). Types of neurons, synaptic connections and chemical characteristics of cells immunoreactive for calbindin-D28K, parvalbumin and calretinin in the neocortex. Journal of Chemical Neuroanatomy, 14, 1–19.CrossRefGoogle ScholarPubMed
DeFelipe, J., Gonzalez-Albo, M. C., Del Rio, M. R. & Elston, G. N. (1999). Distribution and patterns of connectivity of interneurons containing calbindin, calretinin, and parvalbumin in visual areas of occipital and temporal lobes of the macaque monkeys. The Journal of Comparative Neurology, 412, 515–26.3.0.CO;2-1>CrossRefGoogle Scholar
Dehaene, S. & Changeux, J. P. (1995). Neuronal models of prefrontal cortical functions. Annals of the New York Academy of Science, 769, 305–19.CrossRefGoogle ScholarPubMed
Dombrowski, S. M., Hilgetag, C. C. & Barbas, H. (2001). Quantitative architecture distinguishes prefrontal cortical systems in the rhesus monkey. Cerebral Cortex, 11, 975–88.CrossRefGoogle ScholarPubMed
Douglas, R. J. & Martin, K. A. C. (2004). Neuronal circuits of the neocortex. Annual Review of Neuroscience, 27, 419–51.CrossRefGoogle ScholarPubMed
Dracheva, S., McGurk, S. R. & Haroutunian, V. (2005). mRNA expression of AMPA receptors and AMPA receptor binding proteins in the cerebral cortex of elderly schizophrenics. Journal of Neuroscience Research, 79, 868–78.CrossRefGoogle ScholarPubMed
Durstewitz, D. J., Seamans, K. & Sejnowski, T. J. (2000a). Dopamine-mediated stabilization of delay-period activity in a network model of prefrontal cortex. Journal of Neurophysiology, 83, 1733–50.CrossRefGoogle Scholar
Durstewitz, D. J., Seamans, K. & Sejnowski, T. J. (2000b). Neurocomputational models of working memory. Nature Neuroscience, 3, 1184–91.CrossRefGoogle Scholar
Egorov, A. V., Hamam, B. N., Fransen, E., Hasselmo, M. E. & Alonso, A. A. (2002). Graded persistent activity in entorhinal cortex neurons. Nature, 420, 173–8.CrossRefGoogle ScholarPubMed
Elston, G. N. (2000). Pyramidal cells of the frontal lobe: all the more spinous to think with. Journal of Neuroscience, 20-RC95, 1–4.Google Scholar
Elston, G. N. & Gonzalez-Albo, M. C. (2003). Parvalbumin-, calbindin-, and calretinin-immunoreactive neurons in the prefrontal cortex of the owl monkey (aotus trivirgatus): a standardized quantitative comparison with sensory and motor areas. Brain Behavior and Evolution, 62, 19–30.CrossRefGoogle ScholarPubMed
Ferster, D. & Miller, K. D. (2000). Neural mechanisms of orientation selectivity in the visual cortex. Annual Review of Neuroscience, 23, 441–71.CrossRefGoogle ScholarPubMed
Freund, T. F. & Buzsaki, G. (1996). Interneurons of the hippocampus. Hippocampus, 6, 347–470.3.0.CO;2-I>CrossRefGoogle ScholarPubMed
Fries, P., Reynolds, J. H., Rorie, A. E. & Desimone, R. (2001). Modulation of oscillatory neuronal synchronization by selective visual attention. Science, 291, 1560–3.CrossRefGoogle ScholarPubMed
Funahashi, S., Bruce, C. J. & Goldman-Rakic, P. S. (1989). Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex. Journal of Neurophysiology, 61, 331–49.CrossRefGoogle ScholarPubMed
Fuster, J. M. (1988). The Prefrontal Cortex, 2nd edn. New York: Raven.CrossRefGoogle Scholar
Fuster, J. M. & Alexander, G. (1971). Neuron activity related to short-term memory. Science, 173, 652–4.CrossRefGoogle ScholarPubMed
Fuster, J. M. & Jervey, J. P. (1982). Neuronal firing in the inferotemporal cortex of the monkey in a visual memory task. Journal of Neuroscience, 2, 361–75.CrossRefGoogle Scholar
Gabbott, P. L. A. & Bacon, S. J. (1996). Local circuit neurons in the medial prefrontal cortex (areas 24a,b,c, 25 and 32) in the monkey: II. Quantitative areal and laminar distributions. The Journal of Comparative Neurology, 364, 609–36.3.0.CO;2-7>CrossRefGoogle ScholarPubMed
Gao, W.-J., Wang, Y. & Goldman-Rakic, P. S. (2003). Dopamine modulation of perisomatic and peridendritic inhibition in prefrontal cortex. Journal of Neuroscience, 23, 1622–30.CrossRefGoogle ScholarPubMed
Gnadt, J. W. & Andersen, R. A. (1988). Memory related motor planning activity in posterior parietal cortex of macaque. Experimental Brain Research, 70, 216–20.Google ScholarPubMed
Goldman, M. S., Levine, J. H., Major, G., Tank, D. W. & Seung, H. S. (2003). Robust persistent neural activity in a model integrator with multiple hysteretic dendrites per neuron. Cerebral Cortex, 13, 1185–95.CrossRefGoogle Scholar
Goldman-Rakic, P. S. (1987). Circuitry of primate prefrontal cortex and regulation of behavior by representational memory. In Handbook of Physiology – The Nervous System V, eds. Plum,, F. and Mountcastle, V.Bethesda, Maryland: American Physiological Society, pp. 373–417.Google Scholar
Goldman-Rakic, P. S. (1995). Cellular basis of working memory. Neuron, 14, 477–85.CrossRefGoogle ScholarPubMed
Gonchar, Y. & Burkhalter, A. (1999). Connectivity of GABAergic calretinin-immunoreactive neurons in rat primary visual cortex. Cerebral Cortex, 9, 683–96.CrossRefGoogle ScholarPubMed
Grunze, H. C., Rainnie, D. G., Hasselmo, M. E., et al. (1996). NMDA-dependent modulation of CA1 local circuit inhibition. Journal of Neuroscience, 16, 2034–43.CrossRefGoogle ScholarPubMed
Gulyás, A. I., Hájos, N. & Freund, T. (1996). Interneurons containing calretinin are specialized to control other interneurons in the rate hippocampus. Journal of Neuroscience, 16, 3397–411.CrossRefGoogle Scholar
Harrison, P. J. & Weinberger, D. R. (2005). Schizophrenia genes, gene expression, and neuropathology: on the matter of their convergence. Molecular Psychiatry, 10, 40–68.CrossRefGoogle ScholarPubMed
Healy, D. J., Haroutunian, V., Powchik, P., et al. (1998). AMPA receptor binding and subunit mRNA expression in prefrontal cortex and striatum of elderly schizophrenics. Neuropsychopharmacology, 19, 278–86.CrossRefGoogle ScholarPubMed
Hebb, D. O. (1949). Organization of Behavior. New York: Wiley.Google Scholar
Hestrin, S., Perkel, D. J., Sah, P., et al. (1990a). Physiological properties of excitatory synaptic transmission in the central nervous system. Cold Spring Harbor Symposia on Quantitative Biology, 55, 87–93.CrossRefGoogle Scholar
Hestrin, S., Sah, P. & Nicoll, R. (1990b). Mechanisms generating the time course of dual component excitatory synaptic currents recorded in hippocampal slices. Neuron, 5, 247–53.CrossRefGoogle Scholar
Hikosaka, O. & Wurtz, R. H. (1983). Visual and oculomotor functions of monkey substantia nigra pars reticulata. III. Memory-contingent visual and saccade responses. Journal of Neurophysiology, 49, 1268–84.CrossRefGoogle ScholarPubMed
Huang, Y.-Y., Simpson, E., Kellendonk, C. & Kandel, E. R. (2004). Genetic evidence for the bidirectional modulation of synaptic plasticity in the prefrontal cortex by D1 receptors. Proceedings of the National Academy of Science USA, 101, 3236–41.CrossRefGoogle ScholarPubMed
Hunter, W. S. (1913). The delayed reactions in animals and children. Behavoral Monographs, 2, 1–86.Google Scholar
Jacobsen, C. F. (1936). Studies of cerebral function in primates: I. the functions of the frontal association areas in monkeys. Comparative Psychological Monographs, 13, 1–68.Google Scholar
Jodo, E., Suzuki, Y., Katayama, T., et al. (2005). Activation of medial prefrontal cortex by phencyclidine is mediated via a hippocampo-prefrontal pathway. Cerebral Cortex, 15, 663–9.CrossRefGoogle Scholar
Kawaguchi, Y. & Kubota, Y. (1997). GABAergic cell subtypes and their synaptic connections in rat frontal cortex. Cerebral Cortex, 7, 476–86.CrossRefGoogle ScholarPubMed
Kim, J. N. & Shadlen, M. N. (1999). Neural correlates of a decision in the dorsolateral prefrontal cortex of the macaque. Nature Neuroscience, 2, 176–85.CrossRefGoogle ScholarPubMed
Kisvarday, Z. F., Ferecska, A. S., Kovaics, K., et al. (2003). One axon-multiple functions: Specificity of lateral inhibitory connections by large basket cells. Journal of Neurocytology, 31, 255–64.CrossRefGoogle Scholar
Kondo, H., Tanaka, K., Hashikawa, T. & Jones, E. G. (1999). Neurochemical gradients along monkey sensory cortical pathways: calbindin-immunoreactive pyramidal neurons in layers II and III. European Journal of Neuroscience, 11, 4197–203.CrossRefGoogle ScholarPubMed
Koulakov, A. A., Raghavachari, S., Kepecs, A. & Lisman, J. E. (2002). Model for a robust neural integrator. Nature Neuroscience, 5, 775–82.CrossRefGoogle ScholarPubMed
Krimer, L. S. & Goldman-Rakic, P. S. (2001). Prefrontal microcircuits: membrane properties and excitatory input of local, medium, and wide arbor interneurons. Journal of Neuroscience, 21, 3788–96.CrossRefGoogle ScholarPubMed
Kritzer, M. F. & Goldman-Rakic, P. S. (1995). Intrinsic circuit organization of the major layers and sublayers of the dorsolateral prefrontal cortex in the rhesus monkey. The Journal of Comparative Neurology, 359, 131–43.CrossRefGoogle ScholarPubMed
Krystal, J. H., Karper, L. P., Seibyl, J. P., et al. (1994). Subanesthetic effects of the noncompetitive NMDA antagonist, ketamine, in humans. psychotomimetic, perceptual, cognitive, and neuroendocrine responses. Archives of General Psychiatry, 51, 199–214.CrossRefGoogle ScholarPubMed
Lee, K.-H., Williams, L. M., Breakspear, M. & Gordon, E. (2003). Synchronous gamma activity: a review and contribution to an integrative neuroscience model of schizophrenia. Brain Research. Brain Research Reviews, 41, 57–78.CrossRefGoogle Scholar
Levitt, B., Lewis, D. A., Yoshioka, T. & Lund, J. (1993). Topography of pyramidal neuron intrinsic connections in macaque monkey prefrontal cortex (areas 9 and 46). The Journal of Comparative Neurology, 338, 360–76.CrossRefGoogle Scholar
Lewis, D. A., Hashimoto, T. & Volk, D. W. (2005). Cortical inhibitory neurons and schizophrenia. Nature Reviews. Neuroscience, 6, 312–24.CrossRefGoogle Scholar
Lisman, J. E., Fellous, J. M. & Wang, X.-J. (1998). A role for NMDA-receptor channels in working memory. Nature Neuroscience, 1, 273–5.CrossRefGoogle ScholarPubMed
Liu, G. (2004). Local structural balance and functional interaction of excitatory and inhibitory synapses in hippocampal dendrites. Nature Neuroscience, 7, 373–9.CrossRefGoogle ScholarPubMed
Llinas, R. R. (1988). The intrinsic electrophysiological properties of mammalian neurons: insights into central nervous system function. Science, 242, 1654–64.CrossRefGoogle ScholarPubMed
Loewenstein, Y. & Sompolinsky, H. (2003). Temporal integration by calcium dynamics in a model neuron. Nature Neuroscience, 6, 961–7.CrossRefGoogle Scholar
Lorente de Nó, R. (1933). Vestibulo-ocular reflex arc. Archives of Neurology and Psychiatry, 30, 245–91.CrossRefGoogle Scholar
McCormick, D., Connors, B., Lighthall, J. & Prince, D. (1985). Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons in the neocortex. Journal of Neurophysiology, 54, 782–806.CrossRefGoogle ScholarPubMed
Machens, C. K., Romo, R. & Brody, C. D. (2005). Flexible control of mutual inhibition: a neural model of two-interval discrimination. Science, 307, 1121–4.CrossRefGoogle ScholarPubMed
Magee, J., Hoffman, D., Colbert, C. & Johnston, D. (1998). Electrical and calcium signaling in dendrites of hippocampal pyramidal neurons. Annual Review of Physiology, 60, 327–46.CrossRefGoogle ScholarPubMed
Major, G. & Tank, D. (2004). Persistent neural activity: prevalence and mechanisms. Current Opinion in Neurobiology, 14, 675–84.CrossRefGoogle ScholarPubMed
Markram, H., Gupta, A., Uziel, A., Wang, Y. & Tsodyks, M. (1998). Information processing with frequency-dependent synaptic connections. Neurobiology of Learning and Memory, 70, 101–12.CrossRefGoogle ScholarPubMed
Markram, H., Toledo-Rodriguez, M., Wang, Y., et al. (2004). Interneurons of the neocortical inhibitory system. Nature Reviews. Neuroscience, 5, 793–807.CrossRefGoogle ScholarPubMed
Meskenaite, V. (1997). Calretinin-immunoreactive local circuit neurons in the area 17 of the cynomolgus monkey, Macaca fascicularis. The Journal of Comparative Neurology, 379, 113–32.3.0.CO;2-7>CrossRefGoogle ScholarPubMed
Mesulam, M.-M. (2000). Principles of Behavioral and Cognitive Neurology, 2nd edn. New York: Oxford University Press.Google Scholar
Miller, P., Brody, C. D., Romo, R. & Wang, X.-J. (2003). A recurrent network model of somatosensory parametric working memory in the prefrontal cortex. Cerebral Cortex, 13, 1208–18.CrossRefGoogle ScholarPubMed
Miller, E. K. & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167–202.CrossRefGoogle ScholarPubMed
Miller, E. K., Erickson, C. A. & Desimone, R. (1996). Neural mechanisms of visual working memory in prefrontal cortex of the macaque. Journal of Neuroscience, 16, 5154–67.CrossRefGoogle ScholarPubMed
Milner, B. (1972). Disorders of learning and memory after temporal lobe lesions in man. Clinical Neurosurgery, 19, 421–46.CrossRefGoogle ScholarPubMed
Miyashita, Y. (1988). Neuronal correlate of visual associative long-term memory in the primate temporal cortex. Nature, 335, 817–20.CrossRefGoogle ScholarPubMed
Newsome, W. T., Britten, K. H. & Movshon, J. A. (1989). Neuronal correlates of a perceptual decision. Nature, 341, 52–4.CrossRefGoogle ScholarPubMed
O'Reilly, R. L., Braver, T. S. & Cohen, J. D. (1999). A biologically based computational model of working memory. In Models of Working Memory: Mechanisms of Active Maintenance and Executive Control, Miyake, A. and Shah, V.New York: Cambridge University Press, pp. 375–411.CrossRefGoogle Scholar
O'Reilly, R. L. & Munakata, Y. (2000). Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain. MA: MIT Press.Google Scholar
Parker, A. J. & Newsome, W. T. (1998). Sense and the single neuron: Probing the physiology of perception. Annual Review of Neuroscience, 21, 227–77.CrossRefGoogle Scholar
Pasternak, T. & Greenlee, M. W. (2005). Working memory in primate sensory systems. Nature Reviews. Neuroscience, 6, 97–107.CrossRefGoogle ScholarPubMed
Pesaran, B., Pezaris, J. S., Sahani, M., Mitra, P. P. & Andersen, R. A. (2002). Temporal structure in neuronal activity during working memory in macaque parietal cortex. Nature Neuroscience, 5, 805–11.CrossRefGoogle ScholarPubMed
Powell, K. D. & Goldberg, M. E. (2000). Response of neurons in the lateral intraparietal area to a distractor flashed during the delay period of a memory-guided saccade. Journal of Neurophysiology, 84, 301–10.CrossRefGoogle ScholarPubMed
Rainer, G., Assad, W. F. & Miller, E. K. (1998). Memory fields of neurons in the primate prefrontal cortex. Proceedings of the National Academy of Science USA, 95, 15008–13.CrossRefGoogle ScholarPubMed
Rao, S. G., Williams, G. V. & Goldman-Rakic, P. S. (2000). Destruction and creation of spatial tuning by disinhibition: GABA(A) blockade of prefrontal cortical neurons engaged by working memory. Journal of Neuroscience, 20, 485–94.CrossRefGoogle ScholarPubMed
Renart, A., Brunel, N. & Wang, X.-J. (2003a). Mean-field theory of recurrent cortical networks: Working memory circuits with irregularly spiking neurons. In Computational Neuroscience: A Comprehensive Approach, ed. Feng, J.. Boca Raton: CRC Press.CrossRefGoogle Scholar
Renart, A., Song, P. & Wang, X.-J. (2003b). Robust spatial working memory through homeostatic synaptic scaling in heterogeneous cortical networks. Neuron, 38, 473–85.CrossRefGoogle Scholar
Roitman, J. D. & Shadlen, M. N. (2002). Response of neurons in the lateral intraparietal area (LIP) during a combined visual discrimination reaction time task. Journal of Neuroscience, 22, 9475–89.CrossRefGoogle ScholarPubMed
Romo, R., Brody, C. D., Hernandez, A. & Lemus, L. (1999). Neuronal correlates of parametric working memory in the prefrontal cortex. Nature, 399, 470–3.CrossRefGoogle ScholarPubMed
Romo, R. & Salinas, E. (2000). Touch and go: Decision-making mechanisms in somatosensation. Annual Review of Neuroscience, 24, 107–37.CrossRefGoogle Scholar
Rowland, L. M., Astur, R. S., Jung, R. E., et al. (2005). Selective cognitive impairments associated with NMDA receptor blockade in humans. Neuropsychopharmacology, 30, 633–9.CrossRefGoogle ScholarPubMed
Sakai, K., Rowe, J. B. & Passingham, R. E. (2002). Active maintenance in prefrontal area 46 creates distractor-resistant memory. Nature Neuroscience, 5, 479–84.CrossRefGoogle ScholarPubMed
Sanchez-Vives, M. V. & McCormick, D. A. (2000). Cellular and network mechanisms of rhythmic recurrent activity in neocortex. Nature Neuroscience, 3, 1027–34.CrossRefGoogle ScholarPubMed
Schall, J. D. (2001). Neural basis of deciding, choosing and acting. Nature Neuroscience, 2, 33–42.CrossRefGoogle ScholarPubMed
Scherzer, C. R., Landwehrmeyer, G. B., Kerner, J. A., et al. (1998). Expression of N-methyl-D-aspartate receptor subunit mRNAs in the human brain: hippocampus and cortex. The Journal of Comparative Neurology, 390, 75–90.3.0.CO;2-N>CrossRefGoogle ScholarPubMed
Seamans, J. K. & Yang, C. R. (2004). The principal features and mechanisms of dopamine modulation in the prefrontal cortex. Progress in Neurobiology, 74, 1–58.CrossRefGoogle ScholarPubMed
Seung, H. S., Lee, D. D., Reis, B. Y. & Tank, D. W. (2000). Stability of the memory of eye position in a recurrent network of conductance-based model neurons. Neuron, 26, 259–71.CrossRefGoogle Scholar
Shadlen, M. N. & Newsome, W. T. (1994). Noise, neural codes and cortical organization. Current Opinion in Neurobiology, 4, 569–79.CrossRefGoogle ScholarPubMed
Shadlen, M. N. & Newsome, W. T. (2001). Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. Journal of Neurophysiology, 86, 1916–36.CrossRefGoogle ScholarPubMed
Shima, K. & Tanji, J. (1998). Involvement of NMDA and non-NMDA receptors in the neuronal responses of the primary motor cortex to input from the supplementary motor area and somatosensory cortex: studies of task-performing monkeys. Japanese Journal of Physiology, 48, 275–90.CrossRefGoogle ScholarPubMed
Shu, Y., Hasenstab, A. & McCormick, D. A. (2003). Turning on and off recurrent balanced cortical activity. Nature, 423, 288–93.CrossRefGoogle ScholarPubMed
Singer, W. & Gray, C. M. (1995). Visual feature integration and the temporal correlation hypothesis. Annual Review of Neuroscience, 18, 555–86.CrossRefGoogle ScholarPubMed
Somogyi, P., Tamas, G., Lujan, R. & Buhl, E. H. (1998). Salient features of synaptic organisation in the cerebral cortex. Brain Research Reviews, 26, 113–35.CrossRefGoogle ScholarPubMed
Sompolinsky, H. & Shapley, R. (1997). New perspectives on the mechanisms for orientation selectivity. Current Opinion in Neurobiology, 7, 514–22.CrossRefGoogle ScholarPubMed
Song, P. & Wang, X.-J. (2005). Angular path integration by moving “hill of activity”: a spiking neuron model without recurrent excitation of the head-direction system. Journal of Neuroscience, 25, 1002–14.CrossRefGoogle ScholarPubMed
Spencer, K. M., Nestor, P. G., Perlmutter, R., et al. (2004). Neural synchrony indexes disordered perception and cognition in schizophrenia. Proceedings of the National Academy of Science USA, 101, 17288–93.CrossRefGoogle ScholarPubMed
Stuss, D. T. & Knight, R. T. (2002). Principles of Frontal Lobe Function. New York: Oxford University Press.CrossRefGoogle Scholar
Tegnér, J., Compte, A. & Wang, X.-J. (2002). Dynamical stability of reverberatory neural circuits. Biological Cybernetics, 87, 471–81.CrossRefGoogle ScholarPubMed
Traub, R. D., Whittington, M. A., Collins, S. B., Buzsáki, G. & Jefferys, J. G. R. (1996). Analysis of gamma rythms in the rat hippocampus in vitro and in vivo. Journal of Physiology, 493, 471–84.CrossRefGoogle Scholar
Traub, R. D., Bibbig, A., LeBeau, F. E. N., Buhl, E. H., &Whittington, M. A. (2004). Cellular mechanisms of neuronal population oscillations in the hippocampus in vitro. Annual Review of Neuroscience, 27, 247–78.CrossRefGoogle ScholarPubMed
Wang, X.-J. (1999). Synaptic basis of cortical persistent activity: the importance of NMDA receptors to working memory. Journal of Neuroscience, 19, 9587–603.CrossRefGoogle ScholarPubMed
Wang, X.-J. (2001). Synaptic reverberation underlying mnemonic persistent activity. Trends in the Neurosciences, 24, 455–63.CrossRefGoogle ScholarPubMed
Wang, X.-J. (2002). Probabilistic decision making by slow reverberation in cortical circuits. Neuron, 36, 955–68.CrossRefGoogle ScholarPubMed
Wang, X.-J. (2003). Neural oscillations. In Encyclopedia of Cognitive Science, (ed.) Nadil,, L.London: MacMillan Reference Ltd., pp. 272–80.Google Scholar
Wang, X.-J. & Buzsaki, G. (1996). Gamma oscillations by synaptic inhibition in a hippocampal interneuronal network. Journal of Neuroscience, 16, 6402–13.CrossRefGoogle Scholar
Wang, X.-J. & Goldman-Rakic, P. S. (2003). Special issue: Persistent neural activity: theory and experiments. Cerebral Cortex, 13, 1123–269.CrossRefGoogle Scholar
Wang, X.-J., Tegner, J., Constantinidis, C. & Goldman-Rakic, P. S. (2004a). Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory. Proceedings of the National Academy of Science USA, 101, 1368–73.CrossRefGoogle Scholar
Wang, M., Vijayraghavan, S. & Goldman-Rakic, P. S. (2004b). Selective D2 receptor actions on the functional circuitry of working memory. Science, 303, 853–6.CrossRefGoogle Scholar
Williams, G. V. & Goldman-Rakic, P. S. (1995). Modulation of memory fields by dopamine D1 receptors in prefrontal cortex. Nature, 376, 572–5.CrossRefGoogle ScholarPubMed
Wilson, H. R. & Cowan, J. D. (1972). Excitatory and inhibitory interactions in localized populations of model neurons. Biophysical Journal, 12, 1–24.CrossRefGoogle ScholarPubMed
Wilson, H. R. & Cowan, J. D. (1973). A mathematical theory of the functional dynamics of cortical and thalamic nervous tissue. Kybernetik, 13, 55–80.CrossRefGoogle ScholarPubMed
Wood, J. N. & Grafman, J. (2003). Human prefrontal cortex: processing and representational perspectives. Nature Reviews. Neuroscience, 4, 139–47.CrossRefGoogle ScholarPubMed
Xiang, Z., Huguenard, J. R. & Prince, D. A. (1998). GABAA receptor mediated currents in interneurons and pyramidal cells of rat visual cortex. Journal of Physiology, 506, 715–30.CrossRefGoogle ScholarPubMed

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×