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A model of human visual detection performance has been developed, based on available anatomical and physiological data for the primate visual system. The inhomogeneous retino-cortical (IRC) model computes detection thresholds by comparing simulated neural responses to target patterns with responses to a uniform background of the same luminance. The model incorporates human ganglion cell sampling distributions; macaque monkey ganglion cell receptive field properties; macaque cortical cell contrast nonlinearities; and a optimal decision rule based on ideal observer theory. Spatial receptive field properties of cortical neurons were not included. Two parameters were allowed to vary while minimizing the squared error between predicted and observed thresholds. One parameter was decision efficiency, the other was the relative strength of the ganglion-cell center and surround. The latter was only allowed to vary within a small range consistent with known physiology. Contrast sensitivity was measured for sinewave gratings as a function of spatial frequency, target size and eccentricity. Contrast sensitivity was also measured for an airplane target as a function of target size, with and without artificial scotomas. The results of these experiments, as well as contrast sensitivity data from the literature were compared to predictions of the IRC model. Predictions were reasonably good for grating and airplane targets. To test the model, we compared its predictions with measurements of contrast sensitivity for sinewave grating patterns as a function of spatial frequency, target size, and retinal eccentricity. Predictions are shown for the contrast sensitivity data of Robson and Graham1 and Arnow and Geisler2. We also show predictions (but no data) for the detection of sinewave grating targets assuming sharply defined retinal scotomas of various sizes and eccentricities. Finally, we show measurements of (and predictions for) the detectability of an "airplane" target as a function of its size, and the size of an artificial scotoma which obscured part of the airplane. We begin by describing the specific components of the model, and how predictions were generated.

<title>Visual detection following retinal damage: predictions of an inhomogeneous retino-cortical model</title>