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Maximum likelihood decoding of neuronal inputs from an interspike interval distribution

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Zhang, Xuejuan, You, Gongqiang, Chen, Tianping and Feng, Jianfeng (2009) Maximum likelihood decoding of neuronal inputs from an interspike interval distribution. Neural Computation, Vol.21 (No.11). pp. 3079-3105. ISSN 0899-7667

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Official URL: http://dx.doi.org/10.1162/neco.2009.06-08-807

Abstract

An expression for the probability distribution of the interspike interval of a leaky integrate-and-fire (LIF) model neuron is rigorously derived, based on recent theoretical developments in the theory of stochastic processes. This enables us to find for the first time a way of developing maximum likelihood estimates (MLE) of the input information (e.g., afferent rate and variance) for an LIF neuron from a set of recorded spike trains. Dynamic inputs to pools of LIF neurons both with and without interactions are efficiently and reliably decoded by applying the MLE, even within time windows as short as 25 msec.

Item Type:	Journal Item
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science > Centre for Scientific Computing Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH):	Neurons -- Mathematical models, Stochastic processes, Distribution (Probability theory)
Journal or Publication Title:	Neural Computation
Publisher:	MIT Press
ISSN:	0899-7667
Date:	November 2009
Volume:	Vol.21
Number:	No.11
Page Range:	pp. 3079-3105
Identification Number:	10.1162/neco.2009.06-08-807
Status:	Peer Reviewed
Access rights to Published version:	Open Access
Funder:	Engineering and Physical Sciences Research Council (EPSRC), Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Natural Science Foundation of China] (NSFC)
Grant number:	EP/ E002331/1 (EPSRC), 10305007 (NNSFC), 10771155 (NNSFC)
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URI:	http://wrap.warwick.ac.uk/id/eprint/3039