Abstract
The study aimed to establish a comprehensive computational model of intensity adaptation mechanisms, which predicts key features of experimental responses (1). We elaborated on a previous adaptation model (2) which presents retinal adaptation mechanisms and predicts responses to aperiodic stimuli. The model suggests that the temporal decline in the response of the retinal ganglion cells is a reflection of the adaptation mechanism (“curve shifting”(3)). This adaptation mechanism is applied to each cell receptive-field (RF) region (center and surround) separately, and only then the subtraction operation between the two regions is performed. The elaborated model was tested by simulating various periodic sinusoidal fields, which varied in DC level, and frequency (1–30 Hz). The model’s results are in agreement with various psychophysical and physiological findings and predict most of the psychophysical key features (1). Until now, no existing model has been able to predict the key features of the experimental findings (1).
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Sherman, E., Spitzer, H. (2000). Confrontation of Retinal Adaptation Model with Key Features of Psychophysical Gain Behavior Dynamics. In: Lee, SW., Bülthoff, H.H., Poggio, T. (eds) Biologically Motivated Computer Vision. BMCV 2000. Lecture Notes in Computer Science, vol 1811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45482-9_9
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DOI: https://doi.org/10.1007/3-540-45482-9_9
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