A neural mass model based on single cell dynamics to model pathophysiology

Bas-Jan Zandt*, Sid Visser, Michel J.A.M. van Putten, Bennie ten Haken

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Scopus)
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Abstract

Abstract Neural mass models are successful in modeling brain rhythms as observed in macroscopic measurements such as the electroencephalogram (EEG). While the synaptic current is explicitly modeled in current models, the single cell electrophysiology is not taken into account. To allow for investigations of the effects of channel pathologies, channel blockers and ion concentrations on macroscopic activity, we formulate neural mass equations explicitly incorporating the single cell dynamics by using a bottom-up approach. The mean and variance of the firing rate and synaptic input distributions are modeled. The firing rate curve (F(I)-curve) is used as link between the single cell and macroscopic dynamics. We show that this model accurately reproduces the behavior of two populations of synaptically connected Hodgkin-Huxley neurons, also in non-steady state. Keywords Mean field · Neural mass · Recurring network · Firing rate curve · Pathology · Hodgkin-Huxley · Variance · Channel blockers
Original languageEnglish
Pages (from-to)549-568
JournalJournal of computational neuroscience
Volume37
Issue number3
DOIs
Publication statusPublished - 2014

Keywords

  • Mean field
  • Neural mass
  • Recurring network
  • Firing rate curve
  • Pathology
  • Hodgkin-Huxley
  • Variance
  • Channel blockers

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