Channel Identification Machines for Multidimensional Receptive Fields

Channel Identification Machines for Multidimensional Receptive Fields

We present algorithms for identifying multidimensional receptive fields directly from spike trains produced by biophysically-grounded neuron models. We demonstrate that only the projection of a receptive field onto the input stimulus space may be perfectly identified and derive conditions under whic...

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Bibliographic Details
Main Authors: Aurel A Lazar, Yevgeniy B. Slutskiy
Format: Article
Language:English
Published: Frontiers Media S.A. 2014-09-01
Series:Frontiers in Computational Neuroscience
Subjects:
receptive fields
system identification
biophysical models
spiking neural circuits
RKHS
Online Access:http://journal.frontiersin.org/Journal/10.3389/fncom.2014.00117/full

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