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Odelia
Schwartz , E.J. Chichilnisky , and Eero P. Simoncelli
Presented at:
Neural Information Processing Systems, Vancouver BC, Dec 2001.
Published in:
Advances in Neural Information Processing Systems 14, May 2002.
© MIT Press, Cambridge, MA.
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Spike-triggered averaging techniques are effective for linear characterization
of neural responses. But neurons exhibit important nonlinear behaviors,
such as gain control, that are not captured by such analyses. We describe
a spike-triggered covariance method for retrieving suppressive components
of the gain control signal in a neuron. We demonstrate the method in
simulation and on salamander retinal ganglion cell data. Analysis of
physiological data reveals meaningful suppressive axes and explains
interesting nonlinearities. We expect this method to be applicable to
other sensory areas and modalities.
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