  A recurrent neural network with noisy input is studied analytically, on the
basis of a Discrete Time Master Equation. The latter is derived from a
biologically realizable learning rule for the weights of the connections. In a
numerical study it is found that the fixed points of the dynamics of the net
are time dependent, implying that the representation in the brain of a fixed
piece of information (e.g., a word to be recognized) is not fixed in time.
