Makarov , Valeri A. and Panetsos, Fivos and Feo, Óscar de (2005) A method for determining neural connectivity and inferring the underlying network dynamics using extracellular spike recordings. Journal of Neuroscience Methods , 144 (2). 265-279 . ISSN 0165-0270
Restricted to Repository staff only until 31 December 2020.
In the present paper we propose a novel method for the identification and modeling of neural networks using extracellular spike recordings. We create a deterministic model of the effective network, whose dynamic behavior fits experimental data. The network obtained by our method includes explicit mathematical models of each of the spiking neurons and a description of the effective connectivity between them. Such a model allows us to study the properties of the neuron ensemble independently from the original data. It also permits to infer properties of the ensemble that cannot be directly obtained from the observed spike trains. The performance of the method is tested with spike trains artificially generated by a number of different neural networks. (c) 2004 Elsevier B.V. All rights reserved.
|Uncontrolled Keywords:||Neural circuits; Spike trains; Connectivity identification; Network modeling; Stochastic point processes; Directed transfer-function; Synaptic connections; Models; Identification; Trains; Systems; Accuracy; Neurons|
|Subjects:||Sciences > Mathematics > Group Theory|
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|Deposited On:||23 Oct 2012 08:17|
|Last Modified:||07 Feb 2014 09:36|
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