title: Identifying Dendritic Processing.
abstract: 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.
authors.affiliation: Department of Electrical Engineering Columbia University New York, NY 10027 aurel@ee.columbia.edu.
authors.forename: Aurel A
authors.initials: AA
authors.lastname: Lazar
authors.affiliation: Department of Electrical Engineering Columbia University New York, NY 10027 ys2146@columbia.edu.
authors.forename: Yevgeniy B
authors.initials: YB
authors.lastname: Slutskiy