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Identifying Dendritic Processing
Aurel A Lazar · Yevgeniy B Slutskiy

Tue Dec 07 12:00 PM -- 12:05 PM (PST) @ Regency Ballroom

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.

Author Information

Aurel A Lazar (Columbia University)
Yevgeniy B Slutskiy (Columbia University)

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