Learning and Adaptation in a Recurrent Model of V1 Orientation Selectivity
Andrew F. Teich and Ning Qian, J. Neurophysiol. 2003, 89:2086-2100.
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Abstract
Learning and adaptation in the domain of orientation processing are
among the most studied topics in the literature. However, little
effort has been devoted to explaining the diverse array of
experimental findings via a physiologically based model. We have
started to address this issue in the framework of the recurrent model
of V1 orientation selectivity, and found that reported changes in V1
orientation tuning curves after learning and adaptation can both be
explained with the model. Specifically, the sharpening of orientation
tuning curves near the trained orientation after learning can be
accounted for by slightly reducing net excitatory connections to cells
around the trained orientation, while the broadening and peak shift of
the tuning curves after adaptation can be reproduced by appropriately
scaling down both excitation and inhibition around the adapted
orientation. In addition, we investigated the perceptual consequences
of the tuning curve changes induced by learning and adaptation using
signal detection theory. We found that in the case of learning, the
physiological changes can account for the psychophysical data well.
In the case of adaptation, however, there is a clear discrepancy
between the psychophysical data from alert human subjects and the
physiological data from anesthetized animals. Instead, human
adaptation studies can be better accounted for by the learning data
from behaving animals. Our work suggests that adaptation in behaving
subjects may be viewed as a short-term form of learning.
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