  We analyze a simple dynamical network model which describes the limited
capacity of nodes to process the input information. For a suitable choice of
the parameters, the information flow pattern is characterized by exponential
distribution of the incoming information and a fat-tailed distribution of the
outgoing information, as a signature of the law of diminishing marginal
returns. The analysis of a real EEG data-set shows that similar phenomena may
be relevant for brain signals.
