Bistable behaviour in a neocortical neurone model

Delord, Bruno; Klaassen, Arno J.; Burnod, Yves; Costalat, Robert; Guigon, Emmanuel

doi:10.1097/00001756-199703030-00040

Cited by 18 publications

(13 citation statements)

References 18 publications

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“…The role of sustained activity in memory tasks is demonstrated by two observations: The percentage of PFC neurons which exhibit such activity is proportional to the correct performance of the animal (Alexander, 1982;Fuster, 1973), and the disruption of sustained activity by distracting stimuli often reflects an error made by the monkey (Miller et al, 1996a(Miller et al, , 1996b. The origins of sustained activities of pyramidal neurons have either been attributed to recurrent connections, consistent with the fact that they can be found at all stages of cortico-thalamocortical loops (Goldman-Rakic, 1995;Levitt et al, 1993), and/or to intrinsic neuronal mechanisms (ionic channels) (Camperi & Wang, 1998;Delord et al, 1997;Marder et al, 1996).…”

Section: Model Of Su Sta In Ed Activitymentioning

confidence: 99%

“…The origins of sustained activities of pyramidal neurons have either been attributed to recurrent connections and/or to intrinsic neuronal mechanisms (see Methods) (Camperi & Wang, 1998;Delord, Klaassen, Burnod, Costalat, & Guigon, 1997;Marder, Abbott, Turrigiano, & Golowasch, 1996). Our model combines these two properties and distinguishes basal dendrites of PFC deep-layer pyramidal neurons, receiving recurrent connections from neighboring cortical columns, from apical dendrites, receiving long-distance inputs from long-range cortical areas (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

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A Model of Prefrontal Cortex Dopaminergic Modulation during the Delayed Alternation Task

Dreher

Guigon

Burnod

2002

Journal of Cognitive Neuroscience

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Working memory performance is modulated by the level of dopamine (DA) D1 receptors stimulation in the prefrontal cortex (PFC). This modulation is exerted at different time scales. Injection of D1 agonists/antagonists exerts a long-lasting influence (several minutes or hours) on PFC pyramidal neurons. In contrast, during performance of a cognitive task, the duration of the postsynaptic effect of phasic DA release is short lasting. The functional relationships of these two time scales of DA modulation remain poorly understood. Here we propose a model that combines these two time scales of DA modulation on a prefrontal neural network. The model links the cellular and behavioral levels during performance of the delayed alternation task. The network, which represents the activity of deep-layer pyramidal neurons with intrinsic neuronal properties, exhibits two stable states of activity that can be switched on and off by excitatory inputs from long-distance cortical areas arriving in superficial layers. These stable states allow PFC neurons to maintain representations during the delay period. The role of an increase of DA receptors stimulation is to restrict inputs arriving on the prefrontal network. The model explains how the level of working memory performance follows an inverted U-shape with an increased stimulation of DA D1 receptors. The model predicts that (1) D1 receptor agonists increase perseverations, (2) D1 antagonists increase distractability, and (3) the duration of the postsynaptic effect of phasic DA release in the PFC is adjusted to the delay period of the task. These results show how the precise duration of the postsynaptic effect of phasic DA release influences behavioral performance during a simple cognitive task.

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Section: Model Of Su Sta In Ed Activitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Model of Prefrontal Cortex Dopaminergic Modulation during the Delayed Alternation Task

Dreher

Guigon

Burnod

2002

Journal of Cognitive Neuroscience

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“…Based on some aspects of the neuroanatomy of the cortical regions involved in working memory, it has been postulated that the sustained activation seen in working memory is primarily a result of the reverberating circulation of impulses through reentrant circuits of local and global cortical networks (Hebb, 1949;Amit, 1989;Sporns et al, 1989;Tononi et al, 1992;Zipser et al, 1993;Amit, 1995;Amit and Brunel, 1997a,b;Brunel, 2000a;Laing and Chow, 2001;Gutkin et al, 2001). Alternatively, it has also been suggested that the sustained activation observed in some cells during working memory primarily results from intrinsic cellular bistability produced by long-lasting synaptic and/or cellular conductances (Marder et al, 1996;Delord et al, 1997Delord et al, , 2000Lisman et al, 1998;Haj-Dahmane and Andrade, 1998;Wang, 1999;Fransen et al, 2002Fransen et al, , 2006Egorov et al, 2002;Durstewitz, 2003;Loewenstein and Sompolinsky, 2003), synaptic dynamics and/or dendritic bistability (Goldman et al, 2002Kitano et al, 2002;Amit et al, 2003;Renart et al, 2003), neuromodulatory influences (Durstewitz et al, 2000;Seamans et al, 2001;Tanaka, 2002;Camperi and Manias, 2003), or a combination of the above (Camperi and Wang, 1998;Compte et al, 2000;Brunel and Wang, 2001;Tegnér et al, 2002;Koulakov et al, 2002;Miller et al, 2003;…”

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confidence: 99%

Variability in neuronal activity in primate cortex during working memory tasks

et al. 2007

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Abstract-Persistent elevated neuronal activity has been identified as the neuronal correlate of working memory. It is generally assumed in the literature and in computational and theoretical models of working memory that memory-cell activity is stable and replicable; however, this assumption may be an artifact of the averaging of data collected across trials, and needs experimental verification. In this study, we introduce a classification scheme to characterize the firing frequency trends of cells recorded from the cortex of monkeys during performance of working memory tasks. We examine the frequency statistics and variability of firing during baseline and memory periods. We also study the behavior of cells on individual trials and across trials, and explore the stability of cellular firing during the memory period. We find that cells from different firing-trend classes possess markedly different statistics. We also find that individual cells show substantial variability in their firing behavior across trials, and that firing frequency also varies markedly over the course of a single trial. Finally, the average frequency distribution is wider, the magnitude of the frequency increases from baseline to memory smaller, and the magnitude of frequency decreases larger than is generally assumed. These results may serve as a guide in the evaluation of current theories of the cortical mechanisms of working memory. © 2007 IBRO. Published by Elsevier Ltd. All rights reserved.Key words: spike trains, monkeys, memory networks, parietal cortex, prefrontal cortex, computational models.The electrophysiological study of the neuronal basis of working memory in primates has traditionally focused on the changes in single-cell average frequency that may occur during the mnemonic retention of a stimulus cue in delayed-response tasks. Experiments dealing with this issue have led to the identification of cells, generally labeled "memory cells," that show a persistent increase in their average firing frequency (AF) during the memory period of a memory task (Fuster, 1997). Memory cells have been identified in multiple cortical regions, including prefrontal (Fuster and Alexander, 1971;Fuster, 1973;Niki, 1974;Niki and Watanabe, 1976;Funahashi et al., 1989;Miller et al., 1996;Rao et al., 1997;Romo et al., 1999), parietal (Gnadt and Andersen, 1988;Koch and Fuster, 1989;Andersen et al., 1990;Barash et al., 1991; Fuster, 1996, 1997), and inferotemporal Jervey, 1981, 1982;Miyashita and Chang, 1988;Fuster, 1990;Miller et al., 1993;Chelazzi et al., 1993Chelazzi et al., , 1998Colombo and Gross, 1994;Gibson and Maunsell, 1997) cortex. A variety of studies have shown that memory cells in all three of these associative regions are involved in the retention of a given sensory cue for a prospective motor response. It has also been shown that cells within a given region can retain associated items of more than one modality (Haenny et al., 1988;Maunsell et al., 1991;Colombo and Gross, 1994;Bodner et al., 1996;Gibson and Maunsell, 1997; Fuster, 1997,...

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“…The model studied here is of potential interest to understand the dynamics of large neural oscillatory networks or lattices [3,[7][8][9]. Such systems are characterized by rather complex intralattice connections.…”

Section: Resultsmentioning

confidence: 99%

“…Large assemblies of identical or almost identical interacting nonlinear elements play a significant role in understanding the dynamical behaviour of many systems which are studied in various fields of science [1][2][3][4][5][6][7][8][9][10]. In a wide class of such systems an important place is occupied by assemblies of globally coupled nonlinear elements.…”

Section: Introductionmentioning

confidence: 99%