Predicting neuronal activity with simple models of the threshold type: Adaptive Exponential Integrate-and-Fire model with two compartments

Authors:
Claudia Clopath;Renaud Jolivet;Alexander Rauch;Hans-Rudolf Lüscher;Wulfram Gerstner
Affiliations:
School of Computer and Communication Sciences and Brain Mind Institute, EPFL, CH-1015 Lausanne, Switzerland;School of Computer and Communication Sciences and Brain Mind Institute, EPFL, CH-1015 Lausanne, Switzerland;Max-Plank-Institute for Biological Cybernetics, D-72012 Tübingen, Germany and Institute of Physiology, University of Bern, CH-3012 Bern, Switzerland;Institute of Physiology, University of Bern, CH-3012 Bern, Switzerland;School of Computer and Communication Sciences and Brain Mind Institute, EPFL, CH-1015 Lausanne, Switzerland
Venue:
Neurocomputing
Year:
2007

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Abstract

An adaptive Exponential Integrate-and-Fire (aEIF) model was used to predict the activity of layer-V-pyramidal neurons of rat neocortex under random current injection. A new protocol has been developed to extract the parameters of the aEIF model using an optimal filtering technique combined with a black-box numerical optimization. We found that the aEIF model is able to accurately predict both subthreshold fluctuations and the exact timing of spikes, reasonably close to the limits imposed by the intrinsic reliability of pyramidal neurons.