NDLI: Estimation of Synaptic Conductance in the Spiking Regime for the McKean Neuron Model

Content Provider	Society for Industrial and Applied Mathematics (SIAM)
Author	Guillamon, A. Vich, C. Prohens, R. Teruel, A. E.
Copyright Year	2017
Abstract	In this work, we aim at giving a first proof of concept to address the estimation of synaptic conductances when a neuron is spiking, a complex inverse nonlinear problem which is an open challenge in neuroscience. Our approach is based on a simplified model of neuronal activity, namely, a piecewise linear version of the FitzHugh--Nagumo model. This simplified model allows precise knowledge of the nonlinear f-I curve by using standard techniques of nonsmooth dynamical systems. In the regular firing regime of the neuron model, we obtain an approximation of the period which, in addition, improves previous approximations given in the literature to date. By knowing both this expression of the period and the current applied to the neuron, and then solving an inverse problem with a unique solution, we are able to estimate the steady synaptic conductance of the cell's oscillatory activity. Moreover, the method gives also good estimations when the synaptic conductance varies slowly in time.
Sponsorship	Generalitat de Catalunya. Spanish Ministry of Economy and Competitiveness
Starting Page	1397
Ending Page	1424
Page Count	28
File Format	PDF
DOI	10.1137/16M1088326
e-ISSN	15360040
Issue Number	3
Volume Number	16
Language	English
Publisher	Society for Industrial and Applied Mathematics
Publisher Date	2017-08-01
Access Restriction	Subscribed
Subject Keyword	Dynamical systems in biology Systems with slow and fast motions McKean model neuron model Relaxation oscillations Periodic solutions synaptic conductance piecewise linear system Singular perturbations parameter estimation, spiking neuron
Content Type	Text
Resource Type	Article

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