Simulating cortical network activity states constrained by intracellular recordings

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 0uctuations, narrows down the possible region of parameter space (connectivity, quantal conductances) where this activity can appear in networks. Searching in those speci2c regions greatly enhances the e3ciency 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. c © 2003 Elsevier B.V. All rights reserved.