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Cited by 620Neural dynamics and brain functionMemory and Neural MechanismsNeuroscience and Neuropharmacology Research

Effects of Neuromodulation in a Cortical Network Model of Object Working Memory Dominated by Recurrent Inhibition

Brunel, Nicolas, Wang, Xiao-Jing·2001·Journal of Computational Neuroscience
DOI 10.1023/a:1011204814320
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Abstract

Experimental evidence suggests that the maintenance of an item in working memory is achieved through persistent activity in selective neural assemblies of the cortex. To understand the mechanisms underlying this phenomenon, it is essential to investigate how persistent activity is affected by external inputs or neuromodulation. We have addressed these questions using a recurrent network model of object working memory. Recurrence is dominated by inhibition, although persistent activity is generated through recurrent excitation in small subsets of excitatory neurons. Our main findings are as follows. (1) Because of the strong feedback inhibition, persistent activity shows an inverted U shape as a function of increased external drive to the network. (2) A transient external excitation can switch off a network from a selective persistent state to its spontaneous state. (3) The maintenance of the sample stimulus in working memory is not affected by intervening stimuli (distractors) during the delay period, provided the stimulation intensity is not large. On the other hand, if stimulation intensity is large enough, distractors disrupt sample-related persistent activity, and the network is able to maintain a memory only of the last shown stimulus. (4) A concerted modulation of GABA(A) and NMDA conductances leads to a decrease of spontaneous activity but an increase of persistent activity; the enhanced signal-to-noise ratio is shown to increase the resistance of the network to distractors. (5) Two mechanisms are identified that produce an inverted U shaped dependence of persistent activity on modulation. The present study therefore points to several mechanisms that enhance the signal-to-noise ratio in working memory states. These mechanisms could be implemented in the prefrontal cortex by dopaminergic projections from the midbrain.

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  • Biophysically realistic computational models have delineated a neural circuit basis of WM activity through strong recurrent excitation to sustain persistent activity and recruitment of lateral inhibition to shape selectivity.

    “Biophysically realistic computational models have delineated a neural circuit basis of WM activity through 2 key network properties: Strong recurrent excitation to sustain persistent activity and recruitment of lateral inhibition to shape selectivity of representations (Compte et al. 2000;Brunel and Wang 2001).”

    From Linking microcircuit dysfunction to cognitive impairment: Effects of disinhibition associated with schizophrenia in a cortical working memory model (2014) · cites this paper as Brunel and Wang 2001

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Authors
Brunel, N., & Wang, X.-J.
Affiliations
  • École Normale Supérieure - PSL (FR)
  • Brandeis University (US)
ORCID
Venue
Journal of Computational Neuroscience
Publisher
Springer Science and Business Media LLC
Published
2001-07
Volume
11
Issue
1
Pages
63-85
ISSN
  • 0929-5313 (ISSN-L)
  • 1573-6873
DOI
10.1023/a:1011204814320
OpenAlex
W4253613142
Cited by
620
References
73
Citations by year
2026: 15 · 2025: 20 · 2024: 25 · 2023: 28 · 2022: 30 · 2021: 35 · 2020: 24 · 2019: 22 · 2018: 17 · 2017: 25 · 2016: 21 · 2015: 28 · 2014: 27 · 2013: 43 · 2012: 28
FWCI
7.05
Type
journal article
Language
en
Update notices
correction (2014-06-24)
Open access
closed
Licence
Locations
  • Journal of Computational Neuroscience (publishedVersion)
  • Archivio istituzionale della Ricerca - Bocconi (submittedVersion)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
Keywords
object working memory, persistent activity, recurrent inhibition, cortical network model, neuromodulation, external drive, distractor interference, signal-to-noise ratio, prefrontal cortex, dopaminergic modulation, spontaneous activity

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