fMRI activation network analysis using Bose-Einstein entropy

Jianjia Wang*, Richard C. Wilson, Edwin R. Hancock

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

5 Citations (Scopus)


In this paper, we present a novel method for characterizing networks using the entropy associated with bosonic particles in thermal equilibrium with a heat-bath. According to this analogy, the normalized Laplacian plays the role of Hamiltonian operator, and the associated energy states are populated according to Bose-Einstein statistics. This model is subject to thermal agitation by the heat reservoir. The physics of the system can be captured by using a partition function defined over the normalized Laplacian eigenvalues. Various global thermodynamic characterizations of the network including its entropy and energy then can be computed from the derivative of corresponding partition function with respect to temperature. We explore whether the resulting entropy can be used to construct an effective information theoretic graph-kernel for the purposes of classifying different types of graph or network structure. To this end, we construct a Jensen-Shannon kernel using the Bose-Einstein entropy for a sample of networks, and then apply kernel principle components analysis (kPCA) to map graphs into low dimensional feature space. We apply the resulting method to classify fMRI activation networks from patients with suspected Alzheimer disease.

Original languageEnglish
Title of host publicationStructural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop S+SSPR 2016, Proceedings
EditorsBattista Biggio, Richard Wilson, Marco Loog, Francisco Escolano, Antonio Robles-Kelly
PublisherSpringer Verlag
Number of pages11
ISBN (Print)9783319490540
Publication statusPublished - 2016
Externally publishedYes
EventJoint IAPR International Workshops on Structural and Syntactic Pattern Recognition, SSPR 2016 - Merida, Mexico
Duration: 29 Nov 20162 Dec 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10029 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceJoint IAPR International Workshops on Structural and Syntactic Pattern Recognition, SSPR 2016


  • Bose-Einstein statistics
  • Jensen-Shannon divergence
  • Network entropy


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