Expanding the transfer entropy to identify information subgraphs in complex systems.
We propose a formal expansion of the transfer entropy to put in evidence irreducible sets of variables which provide information for the future state of each assigned target. Multiplets characterized by an high value will be associated to informational circuits present in the system, with an informational character (synergetic or redundant) which can be associated to the sign of the contribution. We also present preliminary results on fMRI and EEG data sets.
Dipartimento di Fisica, Universitá degli Studi di Bari and Istituto Nazionale di Fisica Nucleare, Sezione di Bari, via Orabona 4, 70126 Bari, Italy.
S
S
Stramaglia
Guo-Rong
GR
Wu
M
M
Pellicoro
D
D
Marinazzo
D004569:Electroencephalography; D019277:Entropy; D006801:Humans; D007257:Information Theory; D008279:Magnetic Resonance Imaging