Does a Bayesian model of V1 contrast coding offer a neurophysiological account of human contrast discrimination? Export

@article{citeulike:346426, abstract = {The dipper effect for contrast discrimination provides strong evidence that the underlying neural response is accelerating at low contrasts and saturating at high contrasts. The contrast-response functions of V1 neurons do have this sigmoidal shape, but individual neurons do not generally have a dynamic range wide enough to account for the dipper effect. This paper presents a Bayesian model of neurons in monkey V1, whose contrast-response function is described by a modified Naka-Rushton with multiplicative noise. It is shown that a model of groups of twelve or more neurons gives a reasonable explanation of the psychophysical data of two observers, but there is a large systematic error which is apparently due to the shape of the distribution of the monkey's sensitivity parameter, c(50). A further model provides a better fit to the data by sacrificing strict adherence to V1 neuronal parameters and, instead using an arbitrary bimodal c(50) distribution, perhaps reflecting differences between M- and P-cells.}, address = {Department of Physiology, Downing Street, Cambridge CB2 3EG, UK; Istituto di Neurofisiologia CNR, Via Moruzzi, 1, Pisa 56100, Italy.}, author = {Chirimuuta, M. and Tolhurst, D. J.}, citeulike-article-id = {346426}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.visres.2005.06.022}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/16081128}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=16081128}, doi = {10.1016/j.visres.2005.06.022}, issn = {0042-6989}, journal = {Vision Res}, keywords = {bayes, coding, contrast}, month = {November}, number = {23}, pages = {2943--2959}, posted-at = {2005-10-09 15:22:53}, priority = {3}, title = {Does a Bayesian model of V1 contrast coding offer a neurophysiological account of human contrast discrimination?}, url = {http://dx.doi.org/10.1016/j.visres.2005.06.022}, volume = {45}, year = {2005} }

TY - JOUR ID - citeulike:346426 L3 - citeulike-article-id:346426 N2 - The dipper effect for contrast discrimination provides strong evidence that the underlying neural response is accelerating at low contrasts and saturating at high contrasts. The contrast-response functions of V1 neurons do have this sigmoidal shape, but individual neurons do not generally have a dynamic range wide enough to account for the dipper effect. This paper presents a Bayesian model of neurons in monkey V1, whose contrast-response function is described by a modified Naka-Rushton with multiplicative noise. It is shown that a model of groups of twelve or more neurons gives a reasonable explanation of the psychophysical data of two observers, but there is a large systematic error which is apparently due to the shape of the distribution of the monkey's sensitivity parameter, c(50). A further model provides a better fit to the data by sacrificing strict adherence to V1 neuronal parameters and, instead using an arbitrary bimodal c(50) distribution, perhaps reflecting differences between M- and P-cells. IS - 23 JF - Vision Res SN - 0042-6989 AD - Department of Physiology, Downing Street, Cambridge CB2 3EG, UK; Istituto di Neurofisiologia CNR, Via Moruzzi, 1, Pisa 56100, Italy. EP - 2959 TI - Does a Bayesian model of V1 contrast coding offer a neurophysiological account of human contrast discrimination? VL - 45 SP - 2943 KW - bayes KW - coding KW - contrast AU - Chirimuuta, M AU - Tolhurst, DJ PY - 2005/11// UR - http://dx.doi.org/10.1016/j.visres.2005.06.022 ER -