Natural time-varying images possess significant temporal correlations
when sampled frame by frame by the photoreceptors. These
correlations persist even after retinal processing and hence, under
natural activation conditions, the signal sent to the lateral
geniculate nucleus is temporally redundant or inefficient. We
explore the hypothesis that the LGN is concerned, among other things,
with improving efficiency of visual representation through active
temporal decorrelation of the retinal signal much in the same way
that the retina improves efficiency by spatially decorrelating
incoming images. Using some recently measured statistical properties
of time-varying images, we predict the spatio-temporal receptive
fields that achieve this decorrelation. It is shown that, because of
neuronal nonlinearities, temporal decorrelation requires two response
types, the {\it lagged} and {\it nonlagged}, just as spatial
decorrelation requires {\it on} and {\it off} response types. The
tuning and response properties of the predicted LGN cells compare
quantitatively well with what is observed in recent physiological
experiments.
^{Dong D W and Atick J J 1995}
{Temporal decorrelation: a theory of lagged and nonlagged
responses in the lateral geniculate nucleus}
{Network: Computation in Neural Systems}{ Vol~6(2) pp~159-178}
The visual system is concerned with the perception of objects in a
dynamic world. A significant fact about natural time-varying images
is that they do not change randomly over space-time; instead image
intensities at different times and/or spatial positions are highly
correlated. We measured the spatiotemporal correlation function --
equivalently the power spectrum -- of natural images and we find that
it is non-separable, i.e., coupled in space and time, and exhibits a
very interesting scaling behaviour. This behaviour is shown to be
related to the motion in the images and the power spectrum is
naturally separable into a spatial term and a velocity term. The
same kind of spatiotemporal coupling and scaling exists in visual
sensitivity measured in physiological and psychophysical experiments.
By assuming that the visual system is optimized to process
information of natural images, a quantitative relationship can be
derived between the power spectrum of natural images and the visual
sensitivity, This reveals some interesting aspects of motion vision.
^{Dong D W 2001}
{In: Computational, neural & ecological constraints of visual motion
processing (Zanker JM, Zeil J, eds)} {pp~371-380}
Send comments to Dawei Dong: dawei@dove.ccs.fau.edu