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dc.contributor.authorRoberts, J.en_US
dc.contributor.authorRobinson, P.en_US
dc.date.accessioned2017-04-24T12:21:35Z
dc.date.available2017-04-24T12:21:35Z
dc.date.issued2008en_US
dc.date.modified2012-04-11T22:21:11Z
dc.identifier.issn15393755en_US
dc.identifier.doi10.1103/PhysRevE.78.051901en_US
dc.identifier.urihttp://hdl.handle.net/10072/44430
dc.description.abstractThe range of conduction delays between connected neuronal populations is often modeled as a single discrete delay, assumed to be an effective value averaging over all fiber velocities. This paper shows the effects of distributed delays on signal propagation. A distribution acts as a linear filter, imposing an upper frequency cutoff that is inversely proportional to the delay width. Distributed thalamocortical and corticothalamic delays are incorporated into a physiologically based mean-field model of the cortex and thalamus to illustrate their effects on the electroencephalogram (EEG). The power spectrum is acutely sensitive to the width of the thalamocortical delay distribution, and more so than the corticothalamic distribution, because all input signals must travel along the thalamocortical pathway. This imposes a cutoff frequency above which the spectrum is overly damped. The positions of spectral peaks in the resting EEG depend primarily on the distribution mean, with only weak dependences on distribution width. Increasing distribution width increases the stability of fixed point solutions. A single discrete delay successfully approximates a distribution for frequencies below a cutoff that is inversely proportional to the delay width, provided that other model parameters are moderately adjusted. A pair of discrete delays together having the same mean, variance, and skewness as the distribution approximates the distribution over the same frequency range without needing parameter adjustment. Delay distributions with large fractional widths are well approximated by low-order differential equations.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.languageEnglishen_US
dc.publisherAmerican Physical Societyen_US
dc.publisher.placeUnited Statesen_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofpagefrom051901-1en_US
dc.relation.ispartofpageto051901-8en_US
dc.relation.ispartofissue5en_US
dc.relation.ispartofjournalPhysical Review Een_US
dc.relation.ispartofvolume78en_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchSpecialist Studies in Education not elsewhere classifieden_US
dc.subject.fieldofresearchcode130399en_US
dc.titleModeling distributed axonal delays in mean-field brain dynamicsen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.date.issued2008
gro.hasfulltextNo Full Text


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