by Daniele Marinazzo, Gent University, Belgium

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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.

Information transfer is minimized both in the completely ordered and in the disordered state.

We use the Ising model as a simple yet general paradigm

But what comes before? Transition to order or peak info?

Question 1: global transfer entropy requires dynamical data. Can we have precursors based also on static data (i.e. behavioral scores across several subjects)?

Question 2: Do we really have to measure all the variables, or we can build precursors based on a small number (e.g. 3) of variables?

Using Partial Information Decomposition, allowing for distinct non-negative measures of redundancy and synergy, accounting for the possibility that redundancy and synergy may coexist as separate elements of information modification, we showed that is the synergy the responsible of the peak.

Hubs of structural connectivity are not among the nodes towards which synergy is highest

Positive and negative associations of synergy with age, in localized clusters

In some regions this association is continuous with age, in other ones it’s limited to the first ~30 years

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