A biophysical model of cortical up and down states: Excitatory-inhibitory balance and H-current

Zaneta Navratilova, Jean Marc Fellous

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

During slow-wave sleep, cortical neurons oscillate between up and down states. Using a computational model of cortical neurons with realistic synaptic transmission, we determined that reverberation of activity in a small network of about 40 pyramidal cells could account for the properties of up states in vivo. We found that experimentally accessible quantities such as membrane potential fluctuations, firing rates and up state durations could be used as indicators of the size of the network undergoing the up state. We also show that the H-current, together with feed-forward inhibition can act as a gating mechanism for up state initiation.

Original languageEnglish (US)
Title of host publicationDynamic Brain - from Neural Spikes to Behaviors - 12th International Summer School on Neural Networks, Revised Lectures
Pages61-66
Number of pages6
DOIs
StatePublished - Dec 1 2008
Event12th International Summer School on Neural Networks - Erice, Italy
Duration: Dec 5 2007Dec 12 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5286 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Summer School on Neural Networks
CountryItaly
CityErice
Period12/5/0712/12/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Navratilova, Z., & Fellous, J. M. (2008). A biophysical model of cortical up and down states: Excitatory-inhibitory balance and H-current. In Dynamic Brain - from Neural Spikes to Behaviors - 12th International Summer School on Neural Networks, Revised Lectures (pp. 61-66). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5286 LNCS). https://doi.org/10.1007/978-3-540-88853-6-5