title: Modeling lateral geniculate nucleus response with contrast gain control. Part 1: formulation.
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.
authors: Davis
authors: D
authors: Cope
authors: Barbara
authors: B
authors: Blakeslee
authors: Mark E
authors: ME
authors: McCourt
mesh_terms: D005829:Geniculate Bodies / Q000166:cytology* / Q000502:physiology*; D016014:Linear Models; D008959:Models, Neurological; D009474:Neurons / Q000166:cytology; D010775:Photic Stimulation; D059629:Signal-To-Noise Ratio