2020/03/10 by Ali Safari, Paolo Moretti, Safari, Ali +7
Neuroscience · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #EEG and Brain-Computer Interfaces #FOS: Biological sciences #FOS: Physical sciences #Functional Brain Connectivity Studies #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #Physics and Society (physics.soc-ph)
paper · pdf · doi:10.48550/arxiv.2003.04741
openalex publication_date 2020/03/10 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
Functional networks provide a topological description of activity patterns in\nthe brain, as they stem from the propagation of neural activity on the\nunderlying anatomical or structural network of synaptic connections. This\nlatter is well known to be organized in hierarchical and modular way. While it\nis assumed that structural networks shape their functional counterparts, it is\nalso hypothesized that alterations of brain dynamics come with transformations\nof functional connectivity. In this computational study, we introduce a novel\nmethodology to monitor the persistence and breakdown of hierarchical order in\nfunctional networks, generated from computational models of activity spreading\non both synthetic and real structural connectomes. We show that hierarchical\nconnectivity appears in functional networks in a persistent way if the dynamics\nis set to be in the quasi-critical regime associated with optimal processing\ncapabilities and normal brain function, while it breaks down in other\n(supercritical) dynamical regimes, often associated with pathological\nconditions. Our results offer important clues for the study of optimal\nneurocomputing architectures and processes, which are capable of controlling\npatterns of activity and information flow. We conclude that functional\nconnectivity patterns achieve optimal balance between local specialized\nprocessing (i.e. segregation) and global integration by inheriting the\nhierarchical organization of the underlying structural architecture.\n