Paper available: Analysis of LGN Input and Orientation Tuning

[Ken Miller]

The following paper is available as
ftp://ftp.keck.ucsf.edu/pub/ken/troyer_etal02.pdf
or from
http://www.keck.ucsf.edu/~ken (click on 'publications', then on
                              'Models of neuronal integration and circuitry')
This is a preprint of an article that has now appeared as:
Journal of Neurophysiology 87, 2741-2752 (2002).



LGN Input to Simple Cells and Contrast-Invariant Orientation Tuning:
An Analysis

Todd W. Troyer, Anton E. Krukowski and Kenneth D. Miller

Abstract:

We develop a new analysis of the 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.



Ken
 
        Kenneth D. Miller               telephone: (415) 476-8217
	Associate Professor		fax: (415) 476-4929
        Dept. of Physiology, UCSF	internet: ken at phy.ucsf.edu
        513 Parnassus			www: http://www.keck.ucsf.edu/~ken
        San Francisco, CA 94143-0444