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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. doi:10.1162/neco.2009.06-08-807
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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 | ||||
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Subjects: | Q Science > QA Mathematics | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Centre for Scientific Computing Faculty of Science, Engineering and Medicine > Science > Computer Science |
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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 | ||||
Official Date: | November 2009 | ||||
Dates: |
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Volume: | Vol.21 | ||||
Number: | No.11 | ||||
Page Range: | pp. 3079-3105 | ||||
DOI: | 10.1162/neco.2009.06-08-807 | ||||
Status: | Peer Reviewed | ||||
Access rights to Published version: | Open Access (Creative Commons) | ||||
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) |
Data sourced from Thomson Reuters' Web of Knowledge
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