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Testing Quantitative Models of BinocularDisparity Selectivity in Primary Visual Cortex

Lookup NU author(s): Professor Jenny ReadORCiD

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Abstract

Disparity-selective neurons in striate cortex (V1) probably implement the initial processing that supports binocular vision. Recently, much progress has been made in understanding the computations that these neurons perform on retinal inputs. The binocular energy model has been highly successful in providing a simple theory of these computations. A key feature of the energy model is that it is linear until after inputs from the two eyes are combined. Recently, however, a modified version of the energy model, incorporating threshold nonlinearities before binocular combination, has been proposed to account for the weaker disparity tuning observed with anticorrelated stimuli. In this study, we present new data needed for a critical assessment of these two models. We compare two key predictions of the models with responses of disparity-selective neurons recorded from V1 of awake fixating monkeys. We find that the original energy model, and a family of generalizations retaining linear binocular combination, are quantitatively inconsistent with the response of V1 neurons. In contrast, the modified version incorporating threshold nonlinearities can explain both sets of observations. We conclude that the energy model can be reconciled with experimental observations by adding a threshold before binocular combination. This gives us the clearest picture yet of the computation being carried out by disparity-selective V1 neurons.


Publication metadata

Author(s): Read JC; Cumming BG

Publication type: Article

Publication status: Published

Journal: Journal of Neurophysiology

Year: 2003

Volume: 90

Issue: 5

Pages: 2795-2817

ISSN (print): 0022-3077

ISSN (electronic): 1522-1598

Publisher: American Physiological Society

URL: http://dx.doi.org/10.1152/jn.01110.2002

DOI: 10.1152/jn.01110.2002

Notes: Cumming recorded the physiological data; I did the data analysis and mathematical modelling.


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