How to integrate the information of structural connectivity and brain activity measured with magnetic resonance imaging (MRI) represents still an open question. Here, we addressed this problem by applying graph signal processing (GSP) to human brain data, aiming at exploring significant excursions of functional activity and its degree of alignment to the underlying structural connectivity. Two contrasting functional networks were highlighted: a primary sensory one, more aligned to the structure and characterized by less excursions, and a high-level cognitive one, more liberal and showing more fluctuations. This advanced framework opens new perspectives in the interpretation of the brain structure/function interplay.
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