Abstract
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.
Highlights
Sixteenth Annual Computational Neuroscience Meeting: CNS*2007 William R Holmes Meeting abstracts – A single PDF containing all abstracts in this Supplement is available here http://www.biomedcentral.com/content/pdf/1471-2202-8-S2-info.pdf
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 analysis could be applied to probe circuitry in a large range of neuronal systems
Summary
Sixteenth Annual Computational Neuroscience Meeting: CNS*2007 William R Holmes Meeting abstracts – A single PDF containing all abstracts in this Supplement is available here http://www.biomedcentral.com/content/pdf/1471-2202-8-S2-info.pdf . Network reconstruction in the presence of unmeasured neurons
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