Information Flow in Networks and the Law of Diminishing Marginal Returns: Evidence from Modeling and Human Electroencephalographic Recordings

@inproceedings{Marinazzo2012InformationFI,
  title={Information Flow in Networks and the Law of Diminishing Marginal Returns: Evidence from Modeling and Human Electroencephalographic Recordings},
  author={Daniele Marinazzo and Guorong Wu and Mario Pellicoro and L Angelini and Sebastiano Stramaglia},
  booktitle={PloS one},
  year={2012}
}
We analyze simple dynamical network models which describe the limited capacity of nodes to process the input information. For a proper range of their parameters, the information flow pattern in these models 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. We apply this analysis to effective connectivity networks from human EEG signals, obtained by Granger… CONTINUE READING
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