A computational neuroscience approach to schizophrenia and its onset

Edmund T. Rolls, Gustavo Deco

Research output: Contribution to journalReview ArticleResearchpeer-review

37 Citations (Scopus)

Abstract

Computational neuroscience integrate-and-fire attractor network models can be used to understand the factors that alter the stability of cortical networks in the face of noise caused for example by neuronal spiking times. A reduction of the firing rates of cortical neurons caused for example by reduced NMDA receptor function (present in schizophrenia) can lead to instability of the high firing rate attractor states that normally implement short-term memory and attention, contributing to the cognitive and negative symptoms of schizophrenia. Reduced cortical inhibition caused by a reduction of GABA neurotransmission (present in schizophrenia) can lead to instability of the spontaneous firing states of cortical networks, leading to a noise-induced jump to a high firing rate attractor state even in the absence of external inputs, contributing to the positive symptoms of schizophrenia. We consider how effects occurring at the time of late adolescence including synaptic pruning, decreases in grey matter volume, and changes in GABA-mediated inhibition and dopamine may contribute to the onset in some individuals of schizophrenia at this time.

Original languageEnglish
Pages (from-to)1644-1653
Number of pages10
JournalNeuroscience and Biobehavioral Reviews
Volume35
Issue number8
DOIs
Publication statusPublished - Aug 2011
Externally publishedYes

Keywords

  • Adolescence
  • Attractor networks
  • Computational neuroscience
  • Dopamine
  • GABA inhibition
  • Grey matter volume
  • Neural networks
  • Neuronal spiking
  • NMDA receptors
  • Noise in the brain
  • Schizophrenia
  • Stochastic neurodynamics
  • Synaptic pruning

Cite this

@article{1d78ec8ad31d4d5eb60b7150ce192245,
title = "A computational neuroscience approach to schizophrenia and its onset",
abstract = "Computational neuroscience integrate-and-fire attractor network models can be used to understand the factors that alter the stability of cortical networks in the face of noise caused for example by neuronal spiking times. A reduction of the firing rates of cortical neurons caused for example by reduced NMDA receptor function (present in schizophrenia) can lead to instability of the high firing rate attractor states that normally implement short-term memory and attention, contributing to the cognitive and negative symptoms of schizophrenia. Reduced cortical inhibition caused by a reduction of GABA neurotransmission (present in schizophrenia) can lead to instability of the spontaneous firing states of cortical networks, leading to a noise-induced jump to a high firing rate attractor state even in the absence of external inputs, contributing to the positive symptoms of schizophrenia. We consider how effects occurring at the time of late adolescence including synaptic pruning, decreases in grey matter volume, and changes in GABA-mediated inhibition and dopamine may contribute to the onset in some individuals of schizophrenia at this time.",
keywords = "Adolescence, Attractor networks, Computational neuroscience, Dopamine, GABA inhibition, Grey matter volume, Neural networks, Neuronal spiking, NMDA receptors, Noise in the brain, Schizophrenia, Stochastic neurodynamics, Synaptic pruning",
author = "Rolls, {Edmund T.} and Gustavo Deco",
year = "2011",
month = "8",
doi = "10.1016/j.neubiorev.2010.09.001",
language = "English",
volume = "35",
pages = "1644--1653",
journal = "Neuroscience and Biobehavioral Reviews",
issn = "0149-7634",
publisher = "Elsevier",
number = "8",

}

A computational neuroscience approach to schizophrenia and its onset. / Rolls, Edmund T.; Deco, Gustavo.

In: Neuroscience and Biobehavioral Reviews, Vol. 35, No. 8, 08.2011, p. 1644-1653.

Research output: Contribution to journalReview ArticleResearchpeer-review

TY - JOUR

T1 - A computational neuroscience approach to schizophrenia and its onset

AU - Rolls, Edmund T.

AU - Deco, Gustavo

PY - 2011/8

Y1 - 2011/8

N2 - Computational neuroscience integrate-and-fire attractor network models can be used to understand the factors that alter the stability of cortical networks in the face of noise caused for example by neuronal spiking times. A reduction of the firing rates of cortical neurons caused for example by reduced NMDA receptor function (present in schizophrenia) can lead to instability of the high firing rate attractor states that normally implement short-term memory and attention, contributing to the cognitive and negative symptoms of schizophrenia. Reduced cortical inhibition caused by a reduction of GABA neurotransmission (present in schizophrenia) can lead to instability of the spontaneous firing states of cortical networks, leading to a noise-induced jump to a high firing rate attractor state even in the absence of external inputs, contributing to the positive symptoms of schizophrenia. We consider how effects occurring at the time of late adolescence including synaptic pruning, decreases in grey matter volume, and changes in GABA-mediated inhibition and dopamine may contribute to the onset in some individuals of schizophrenia at this time.

AB - Computational neuroscience integrate-and-fire attractor network models can be used to understand the factors that alter the stability of cortical networks in the face of noise caused for example by neuronal spiking times. A reduction of the firing rates of cortical neurons caused for example by reduced NMDA receptor function (present in schizophrenia) can lead to instability of the high firing rate attractor states that normally implement short-term memory and attention, contributing to the cognitive and negative symptoms of schizophrenia. Reduced cortical inhibition caused by a reduction of GABA neurotransmission (present in schizophrenia) can lead to instability of the spontaneous firing states of cortical networks, leading to a noise-induced jump to a high firing rate attractor state even in the absence of external inputs, contributing to the positive symptoms of schizophrenia. We consider how effects occurring at the time of late adolescence including synaptic pruning, decreases in grey matter volume, and changes in GABA-mediated inhibition and dopamine may contribute to the onset in some individuals of schizophrenia at this time.

KW - Adolescence

KW - Attractor networks

KW - Computational neuroscience

KW - Dopamine

KW - GABA inhibition

KW - Grey matter volume

KW - Neural networks

KW - Neuronal spiking

KW - NMDA receptors

KW - Noise in the brain

KW - Schizophrenia

KW - Stochastic neurodynamics

KW - Synaptic pruning

UR - http://www.scopus.com/inward/record.url?scp=79960046671&partnerID=8YFLogxK

U2 - 10.1016/j.neubiorev.2010.09.001

DO - 10.1016/j.neubiorev.2010.09.001

M3 - Review Article

C2 - 20851143

AN - SCOPUS:79960046671

VL - 35

SP - 1644

EP - 1653

JO - Neuroscience and Biobehavioral Reviews

JF - Neuroscience and Biobehavioral Reviews

SN - 0149-7634

IS - 8

ER -