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J Neurophysiol (April 1, 2003). 10.1152/jn.00970.2002
Submitted on Submitted 28 October 2002; accepted in final form 10 December 2002
Center for Neurobiology and Behavior and Department of Physiology and Cellular Biophysics, Columbia University, New York, New York 10032
Teich, Andrew F. and
Ning Qian.
Learning and Adaptation in a Recurrent Model of V1 Orientation
Selectivity. J. Neurophysiol. 89: 2086-2100, 2003. 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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