Extracting non-linear integrate-and-fire models from experimental data using dynamic I

Badel, LaurentLefort, SandrineBerger, Thomas K.Petersen, Carl C. H.Gerstner, WulframRichardson, Magnus J. E.2009-08-062009-08-062009-08-06200810.1007/s00422-008-0259-4https://infoscience.epfl.ch/handle/20.500.14299/41993WOS:000260938100010The 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.IV curveExponential integrate-and-fireRefractorinessExtracting non-linear integrate-and-fire models from experimental data using dynamic I – V curvestext::journal::journal article::research article