Simulating cortical network activity states constrained by intracellular
Fabian Alvarez and Alain Destexhe
Neurocomputing 58: 285-290, 2004.
We present a method for studying states of network activity while incorporating
constraints provided by intracellular measurements. Taking into account
measurements of the average membrane potential, input resistance changes and
membrane potential fluctuations, narrows down the possible region of parameter
space (connectivity, quantal conductances) where this activity can appear in
networks. Searching in those specific regions greatly enhances the efficiency of
the network level modeling because irrelevant parameter combinations are
automatically eliminated. We illustrate this approach by modeling self-sustained
stochastic states in networks of excitatory and inhibitory neurons, based on
intracellular recordings in vivo.
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