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Wednesday, July 22 • 3:00pm - 3:45pm
W1 S11: Synergistic information in a dynamical model implemented on the human structural connectome reveals spatially distinct associations with age

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Workshop on Methods of Information Theory in Computational Neuroscience

Daniele Marinazzo
University of Ghent

Synergistic information in a dynamical model implemented on the human structural connectome reveals spatially distinct associations with age

In a previous study implementing the Ising model on a 2D lattice, we showed that the joint synergistic information shared by two variables on a target one peaks before the transition to an ordered state (critical point). Here we implemented the same model on individual structural connectomes, to answer these questions:
  • Does the synergy still peak before the critical point in a nonuniform network?
  • Are the hubs of structural connectivity also hubs of synergy?
  • Is there association with age?
We found that synergy still peaks before the critical temperature and that hubs of structural connectivity are not among the nodes towards which synergy is highest. Furthermore, using robust measures of association we found both positive and negative associations of synergy.        

Speakers
avatar for Daniele Marinazzo

Daniele Marinazzo

University of Ghent
I am a statistical physicist working mainly in the neurosciences. The research activity of my group focuses on methodological and computational aspects of neuroscience research, and on the dynamical networks subserving function.We develop new techniques for inferring connectivity... Read More →



Wednesday July 22, 2020 3:00pm - 3:45pm CEST
Crowdcast (W01)