Noise in attractor networks in the brain produced by graded firing rate representations

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• dc.contributor.author Webb, Tristan J.ca
• dc.contributor.author Rolls, Edmund Tca
• dc.contributor.author Deco, Gustavoca
• dc.contributor.author Feng, Jianfengca
• dc.date.accessioned 2016-02-17T14:09:09Z
• dc.date.available 2016-02-17T14:09:09Z
• dc.date.issued 2011
• dc.description.abstract Representations in the cortex are often distributed with graded firing rates in the neuronal populations. The firing rate/nprobability distribution of each neuron to a set of stimuli is often exponential or gamma. In processes in the brain, such as/ndecision-making, that are influenced by the noise produced by the close to random spike timings of each neuron for a given/nmean rate, the noise with this graded type of representation may be larger than with the binary firing rate distribution that/nis usually investigated. In integrate-and-fire simulations of an attractor decision-making network, we show that the noise is/nindeed greater for a given sparseness of the representation for graded, exponential, than for binary firing rate distributions./nThe greater noise was measured by faster escaping times from the spontaneous firing rate state when the decision cues are/napplied, and this corresponds to faster decision or reaction times. The greater noise was also evident as less stability of the/nspontaneous firing state before the decision cues are applied. The implication is that spiking-related noise will continue to/nbe a factor that influences processes such as decision-making, signal detection, short-term memory, and memory recall/neven with the quite large networks found in the cerebral cortex. In these networks there are several thousand recurrent/ncollateral synapses onto each neuron. The greater noise with graded firing rate distributions has the advantage that it can/nincrease the speed of operation of cortical circuitryca
• dc.format.mimetype application/pdfca
• dc.identifier.citation Webb TJ, Rolls ET, Deco G, Feng J. Noise in attractor networks in the brain produced by graded firing rate representations. PLoS ONE. 2011;6(9):1-15. DOI: 10.1371/journal.pone.0023630
• dc.identifier.doi http://dx.doi.org/10.1371/journal.pone.0023630
• dc.identifier.issn 1932-6203
• dc.identifier.uri http://hdl.handle.net/10230/25857
• dc.language.iso engca
• dc.publisher Public Library of Scienceca
• dc.relation.ispartof PLoS ONE. 2011;6(9):1-15
• dc.rights © 2011 Webb et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits/nunrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedca
• dc.rights.accessRights info:eu-repo/semantics/openAccessca
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.title Noise in attractor networks in the brain produced by graded firing rate representationsca
• dc.type info:eu-repo/semantics/articleca
• dc.type.version info:eu-repo/semantics/publishedVersionca