Computational Models of Cortical Visual Processing
Published in:
Proc. National Academy of Sciences
Volume 93, pages 623-627.
January, 1996.
© National Academy of Sciences
Abstract: The visual responses of neurons in the cerebral cortex were first
adequately characterized in the 1960s by D. H. Hubel and T. N.
Wiesel [(1962) J. Physiol. (London) 160,106-154; (1968) J.
Physiol. (London) 195, 215-243] using qualitative analyses based
on simple geometric visual targets. Over the past 30 years, it
has become common to consider the properties of these neurons by
attempting to make formal descriptions of the transformations
they execute on the visual image. Most such models have their
roots in linear-systems approaches pioneered in the retina by C.
Enroth-Cugell and J. R. Robson [(1966) J. Physiol. (London) 187,
517-552], but it is clear that purely linear models of cortical
neurons are inadequate. We present two related models: one
designed to account for the responses of simple cells in primary
visual cortex (V1), and one designed to account for the responses
of pattern direction selective cells in MT (or V5), an
extrastriate visual area thought to be involved in the analysis
of visual motion. These models share a common structure that
operates in the same way on different kinds of input, and
instantiate the widely-held view that computational strategies
are similar throughout the cerebral cortex. Implementations of
these models for Macintosh microcomputers are available, and can
be used to explore the models' properties.
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