Optimal Coding

o Temporal decorrelation: a theory of the lateral geniculate nucleus


   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}

o Spatiotemporal inseparability of natural images and visual sensitivities

   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}

( Papers' Index of Dawei Dong )


Send comments to Dawei Dong: dawei@ccs.fau.edu