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  Reconstructing stimuli from the spike-times of leaky integrate and fire neurons

Gerwinn, S., Macke, J., & Bethge, M. (2011). Reconstructing stimuli from the spike-times of leaky integrate and fire neurons. Frontiers in Neuroscience, 5(1), 1-16. doi:10.3389/fnins.2011.00001.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-BC98-E Version Permalink: http://hdl.handle.net/21.11116/0000-0001-BCAF-7
Genre: Journal Article

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 Creators:
Gerwinn, S1, 2, Author              
Macke, JH, Author              
Bethge, M1, 2, Author              
Affiliations:
1Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Reconstructing stimuli from the spike trains of neurons is an important approach for understanding the neural code. One of the difficulties associated with this task is that signals which are varying continuously in time are encoded into sequences of discrete events or spikes. An important problem is to determine how much information about the continuously varying stimulus can be extracted from the time-points at which spikes were observed, especially if these time-points are subject to some sort of randomness. For the special case of spike trains generated by leaky integrate and fire neurons, noise can be introduced by allowing variations in the threshold every time a spike is released. A simple decoding algorithm previously derived for the noiseless case can be extended to the stochastic case, but turns out to be biased. Here, we review a solution to this problem, by presenting a simple yet efficient algorithm which greatly reduces the bias, and therefore leads to better decoding performance in the stochastic case.

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 Dates: 2011-02
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.3389/fnins.2011.00001
BibTex Citekey: 7040
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Title: Frontiers in Neuroscience
  Other : Front Neurosci
Source Genre: Journal
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Publ. Info: Lausanne, Switzerland : Frontiers Research Foundation
Pages: - Volume / Issue: 5 (1) Sequence Number: - Start / End Page: 1 - 16 Identifier: ISSN: 1662-4548
ISSN: 1662-453X
CoNE: https://pure.mpg.de/cone/journals/resource/1662-4548