Characterizing neural gain control using spike-triggered covariance

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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 retinal ganglion cell data. Analysis of physiological data reveals significant suppressive axes and explains neural nonlinearities. This method should be applicable to other sensory areas and modalities.

Original languageEnglish (US)
Title of host publicationAdvances in Neural Information Processing Systems 14 - Proceedings of the 2001 Conference, NIPS 2001
PublisherNeural information processing systems foundation
ISBN (Print)0262042088, 9780262042086
StatePublished - Jan 1 2002
Event15th Annual Neural Information Processing Systems Conference, NIPS 2001 - Vancouver, BC, Canada
Duration: Dec 3 2001Dec 8 2001

Publication series

NameAdvances in Neural Information Processing Systems
ISSN (Print)1049-5258

Other

Other15th Annual Neural Information Processing Systems Conference, NIPS 2001
CountryCanada
CityVancouver, BC
Period12/3/0112/8/01

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

Cite this

Schwartz, O., Chichilnisky, E. J., & Simoncelli, E. P. (2002). Characterizing neural gain control using spike-triggered covariance. In Advances in Neural Information Processing Systems 14 - Proceedings of the 2001 Conference, NIPS 2001 (Advances in Neural Information Processing Systems). Neural information processing systems foundation.