Information flow in a network model and the law of diminishing marginal   returns
  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. 
Daniele Marinazzo, Mario Pellicoro, Guorong Wu, Leonardo Angelini,   Sebastiano Stramaglia
physics.data-an cs.SI physics.soc-ph q-bio.NC