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The Journal of Neurophysiology Vol. 87 No. 6 June 2002, pp. 2741-2752
Copyright ©2002 by the American Physiological Society
1Department of Psychology, Neuroscience and Cognitive Science Program, University of Maryland, College Park, Maryland 20742; 2National Aeronautics and Space Administration Ames Research Center, Moffett Field 94035-1000; and 3Departments of Physiology and Otolaryngology, W. M. Keck Center for Integrative Neuroscience, Sloan-Swartz Center for Theoretical Neurobiology, University of California, San Francisco, California 94143-0444
Troyer, Todd W.,
Anton
E. Krukowski, and
Kenneth D. Miller.
LGN Input to Simple Cells and Contrast-Invariant Orientation
Tuning: An Analysis. J. Neurophysiol. 87: 2741-2752, 2002. We develop a new analysis of the
lateral geniculate nucleus (LGN) input to a cortical simple cell,
demonstrating that this input is the sum of two terms, a linear term
and a nonlinear term. In response to a drifting grating, the linear
term represents the temporal modulation of input, and the nonlinear
term represents the mean input. The nonlinear term, which grows with
stimulus contrast, has been neglected in many previous models of simple cell response. We then analyze two scenarios by which
contrast-invariance of orientation tuning may arise. In the first
scenario, at larger contrasts, the nonlinear part of the LGN input, in
combination with strong push-pull inhibition, counteracts the nonlinear
effects of cortical spike threshold, giving the result that orientation tuning scales with contrast. In the second scenario, at low contrasts, the nonlinear component of LGN input is negligible, and noise smooths
the nonlinearity of spike threshold so that the input-output function
approximates a power-law function. These scenarios can be combined to
yield contrast-invariant tuning over the full range of stimulus
contrast. The model clarifies the contribution of LGN nonlinearities to
the orientation tuning of simple cells and demonstrates how these
nonlinearities may impact different models of contrast-invariant tuning.
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