We  investigate  if  well-known  LGN   ion   channel  properties  can
   facilitate  information-theoretic  optimal  coding  through  temporal
   decorrelation;  and   if   so,   whether   the   degree  of  temporal
   decorrelation can be adapted dynamically to  ensure such optimization
   at longer time scales.  Significant  temporal  decorrelation for time
   lags above $50$ ms is achievable  in  a  LGN  cell  model with inputs
   generated  from  natural  visual  stimuli.   Dynamic decorrelation is
   obtainable through adaptive temporal filtering by varying the resting
   membrane potential.  We conclude that  the  biophysical properties of
   LGN cells support the role  of  temporal  decorrelation  and enable a
   plausible  feedback  control  mechanism  that  dynamically  adapt  to
   changes in input statistics.

   (Neurocomputing. Vol~38-40, page 993-1001. 2001)

   (Papers' Index of Dawei Dong)