Extracting non-linear integrate-and-fire models from experimental data using dynamic I– V curves.

Badel, Laurent; Lefort, Sandrine; Berger, Thomas K.; Petersen, Carl C. H.; Gerstner, Wulfram; Richardson, Magnus J. E.

The dynamic I– V curve method was recently introduced for the efficient experimental generation of reduced neuron models. The method extracts the response properties of a neuron while it is subject to a naturalistic stimulus that mimics in vivo-like fluctuating synaptic drive. The resulting history-dependent, transmembrane current is then projected onto a one-dimensional current–voltage relation that provides the basis for a tractable non-linear integrate-and-fire model. An attractive feature of the method is that it can be used in spike-triggered mode to quantify the distinct patterns of post-spike refractoriness seen in different classes of cortical neuron. The method is first illustrated using a conductance-based model and is then applied experimentally to generate reduced models of cortical layer-5 pyramidal cells and interneurons, in injected-current and injected- conductance protocols. The resulting low-dimensional neuron models—of the refractory exponential integrate-and-fire type—provide highly accurate predictions for spike-times. The method therefore provides a useful tool for the construction of tractable models and rapid experimental classification of cortical neurons.

NEURONS; INTERNEURONS; NERVOUS system; PHYSIOLOGICAL control systems; CEREBRAL cortex

Biological Cybernetics, 2008, Vol 99, Issue 4/5, p361

0340-1200

Academic Journal

10.1007/s00422-008-0259-4