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Network reconstruction in the presence of unmeasured neurons

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We present a method to determine whether a correlation in the spikes of two neurons is due to a causal connection between the neurons or due to common input originating from unmeasured neurons. The distinction is based on a point-process model of how a neuron's spiking probability can depend on both its own spiking history and a stimulus (or other external variables). Although the results depend on selecting a parametric model that captures essential features of the neural response, a large class of models can be used with the network analysis. Hence, the analysis could be applied to probe circuitry in a large range of neuronal systems.

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Correspondence to Duane Q Nykamp.

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Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Nykamp, D.Q. Network reconstruction in the presence of unmeasured neurons. BMC Neurosci 8, P20 (2007) doi:10.1186/1471-2202-8-S2-P20

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Keywords

  • Animal Model
  • Network Analysis
  • Large Range
  • Large Class
  • Essential Feature