Understanding complex systems like the brain by analyzing the hidden geometry of their networks

A study published in Nature Communications and directed by Professor Carlo Vittorio Cannistraci, Director of the Center for Complex Network Intelligence (CCNI) at the Tsinghua Laboratory of Brain and Intelligence, proposes a fast algorithm to measure the relation between the variables space of an interconnected complex system, its geometry and its navigability, revealing how this can enhance our understanding of brain differences across age and sex.

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