Journal of Computational Neuroscience

, Volume 37, Issue 3, pp 549–568

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
Article

DOI: 10.1007/s10827-014-0517-5

Cite this article as:
Zandt, BJ., Visser, S., van Putten, M.J.A.M. et al. J Comput Neurosci (2014) 37: 549. doi:10.1007/s10827-014-0517-5

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 

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Bas-Jan Zandt
    • 1
  • Sid Visser
    • 2
  • Michel J. A. M. van Putten
    • 1
  • Bennie ten Haken
    • 1
  1. 1.MIRA - Institute for Biomedical Technology and Technical MedicineUniversity of TwenteEnschedeThe Netherlands
  2. 2.School of Mathematical SciencesUniversity of NottinghamNottinghamUK

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