Identifying Dendritic Processing

author: Aurel A. Lazar, Department of Electrical Engineering, Columbia University
published: March 25, 2011,   recorded: December 2010,   views: 215
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Description

In system identification both the input and the output of a system are available to an observer and an algorithm is sought to identify parameters of a hypothesized model of that system. Here we present a novel formal methodology for identifying dendritic processing in a neural circuit consisting of a linear dendritic processing filter in cascade with a spiking neuron model. The input to the circuit is an analog signal that belongs to the space of bandlimited functions. The output is a time sequence associated with the spike train. We derive an algorithm for identification of the dendritic processing filter and reconstruct its kernel with arbitrary precision.

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Download slides icon Download slides: nips2010_lazar_idp_01.pdf (453.4 KB)

Download article icon Download article: nips2010_0495.pdf (943.8 KB)


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