Modeling lateral geniculate nucleus response with contrast gain control. Part 1: Formulation

Davis Cope, Barbara Blakeslee, Mark E. McCourt

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

A class of models for lateral geniculate nucleus (LGN) on-cell behavior is proposed. The models consist of a linear filter with divisive normalization by root mean square local contrast and include an intrinsic noise density parameter. The properties of these models are shown to match observed LGN behavior: (1) a linear response to low-magnitude stimuli; (2) a linear response without saturation (luxotonic behavior) for zero-contrast stimuli (homogeneous fields) with increasing magnitude; and (3) response saturation for nonzero contrast stimuli with increasing magnitude. The models possess an intrinsic scale for signal-to-noise ratio (SNR). The models show under and supersaturation, as well as saturation, for sinusoidal grating stimuli with increasing contrast and predict that different SNR regimes will cause a single neuron to show different contrast response curves. A companion paper [1] provides a detailed analysis of the full nonlinear response for sinusoidal grating stimuli and circular spot stimuli.

Original languageEnglish (US)
Pages (from-to)2401-2408
Number of pages8
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Volume30
Issue number11
DOIs
StatePublished - Nov 1 2013

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Computer Vision and Pattern Recognition

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