Publication

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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.

Reference

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@inproceedings{LAS10,
  author = "A. A. Lazar and Y. B. Slutskiy",
  title = "Identifying Dendritic Processing",
  year = 2010,
  booktitle = "Advances in Neural Information Processing Systems 23",
  publisher = "J. Lafferty and C. K. I. Williams and J. Shawe-Taylor and R.S. Zemel and A. Culotta",
  pages = "1261-1269"
}