pcbi.1011274.s005.pdf (80.54 kB)
Relation of driver and target control energy and effective connectivity.
journal contribution
posted on 2024-01-12, 18:41 authored by Karan Kabbur Hanumanthappa Manjunatha, Giorgia Baron, Danilo Benozzo, Erica Silvestri, Maurizio Corbetta, Alessandro Chiuso, Alessandra Bertoldo, Samir Suweis, Michele Allegra(A) For each subject, we computed the Pearson correlation R between the node driver and target centrality , (average energy to control other nodes from node i vs average energy to control node i from other nodes) and the in-strength and out-strength of effective connections, as well as the strength of functional connections . We show the distribution of |R| over subjects. (B) For each node, we computed the coefficient of variation (s.d./mean) over subjects of , , . We show the distribution of the coefficient of variation over nodes.
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symmetric structural connectomeregions one wishesprevious research ),leverage recent progressgive general predictionsfundamentally different roleseffective connectome impliesoverly ambitious focusbrain activity controleffective connectivityxlink ">target controllabilitystimulation locistimulate dependingsmall subnetworksingle regionoptimal selectionlinear modelinglarge degreeinhibitory connectionsindividual variationindividual levelinappropriate modelingcurrent applicabilitycontrol problemcontrol maybrain dynamicsbest formulated
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