Computational Modeling of Orientation Tuning Dynamics in Monkey
Primary Visual Cortex
with
D. L. Ringach, R. Shapley and M. J. Shelley,
J. of Computational Neuroscience vol. 8 no. 2, March 2000, pp 143-159.
Abstract
In the primate visual pathway, orientation tuning of neurons is
first observed in the primary visual cortex. The LGN cells that
comprise the thalamic input to V1 are not orientation tuned, but
some V1 neurons are quite selective. Two main classes of
theoretical models have been offered to explain orientation
selectivity: feedforward models, in which inputs from spatially
aligned LGN cells are summed together by one cortical neuron; and
feedback models, in which an initial weak orientation bias due to
convergent LGN input is sharpened and amplified by intracortical
feedback. Recent data on the dynamics of orientation tuning,
obtained by a cross-correlation technique, may help to distinguish
between these classes of models. To test this possibility, we
simulated the measurement of orientation tuning dynamics on various
receptive field models, including a simple Hubel-Wiesel type
feedforward model: a linear spatio-temporal filter followed by an
integrate-and-fire spike generator. The computational study reveals
that simple feedforward models may account for some aspects of the
experimental data, but fail to explain many salient features of
orientation tuning dynamics in V1 cells.
A simple feedback model of interacting cells is also considered.
This model is successful in explaining the appearance of Mexican-hat
orientation profiles, but other features of the data continue to be
unexplained.
See some of the
experimental data
click here for the *.ps file of
the article.
click here for the *.pdf file of
the article.
M. P. was partially supported by an NSF post-doctoral fellowship and
NSF-DMS--9709128/9896077. D. L. R. and R. S. were supported by
NSF-IBN-9720305, NIH-EY01472, and a Sloan Foundation grant to NYU's
Program in Theoretical Neuroscience.