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

Zaneta Navratilova; Jean Marc Fellous

doi:10.1007/978-3-540-88853-6-5

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

Zaneta Navratilova, Jean Marc Fellous

Psychology

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
Title of host publication	Dynamic Brain - from Neural Spikes to Behaviors - 12th International Summer School on Neural Networks, Revised Lectures
Pages	61-66
Number of pages	6
DOIs	https://doi.org/10.1007/978-3-540-88853-6-5
State	Published - Dec 1 2008
Event	12th International Summer School on Neural Networks - Erice, Italy Duration: Dec 5 2007 → Dec 12 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5286 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	12th International Summer School on Neural Networks
Country	Italy
City	Erice
Period	12/5/07 → 12/12/07

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-88853-6-5

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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

A biophysical model of cortical up and down states : Excitatory-inhibitory balance and H-current. / Navratilova, Zaneta; Fellous, Jean Marc.

Dynamic Brain - from Neural Spikes to Behaviors - 12th International Summer School on Neural Networks, Revised Lectures. 2008. p. 61-66 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5286 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Navratilova, Z & Fellous, JM 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. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5286 LNCS, pp. 61-66, 12th International Summer School on Neural Networks, Erice, Italy, 12/5/07. https://doi.org/10.1007/978-3-540-88853-6-5

Navratilova Z, Fellous JM. 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. 2008. p. 61-66. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-88853-6-5

Navratilova, Zaneta ; Fellous, Jean Marc. / A biophysical model of cortical up and down states : Excitatory-inhibitory balance and H-current. Dynamic Brain - from Neural Spikes to Behaviors - 12th International Summer School on Neural Networks, Revised Lectures. 2008. pp. 61-66 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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