Modeling neural contrast sensitivity functions in human visual cortex

The contrast sensitivity function (CSF) characterizes visual function, and iswidely used in research on visual perception and ophthalmological disorders. TheCSF describes the lowest contrast level that participants can perceive as afunction of spatial frequency. Here, we present a new method to estimate theneural equivalent of the CSF that describes how a population of neurons respondsto contrast as a function of spatial frequency. Using functional magneticresonance imaging (fMRI) at 7 Tesla, we measured neural responses whileparticipants viewed gratings that varied systematically in contrast and spatialfrequency. We modeled the neural CSF (nCSF) using an asymmetric parabolicfunction, and we modeled the transition from no response to full response usinga contrast response function (CRF). We estimated the nCSF parameters for everycortical location by minimizing the residual variance between the modelpredictions and the fMRI data. We validated the method using simulations andparameter recovery. We show that our nCSF model explains a significant amount ofthe variance in the fMRI time series. Moreover, the properties of the nCSF varyaccording to known systematic differences across the visual cortex.Specifically, the peak spatial frequency that a cortical location responds todecreases with eccentricity and across the visual hierarchy. This new methodwill provide valuable insights into the properties of the visual cortex and howthey are altered in both healthy and clinical conditions.