Characterizing neural gain control using spike-triggered covariance

Odelia Schwartz , E.J. Chichilnisky , and Eero P. Simoncelli

Presented (as a talk) at:
Neural Information Processing Systems, Vancouver BC, Dec 2001.

Published in:

Advances in Neural Information Processing Systems 14
eds. T.G. Dietterich, S. Becker and Z Ghahramani, pp. 269-276, May 2002.
© MIT Press, Cambridge, MA.

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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