The extremely complex connected structure of the brain shapes a functional network whose activation and synchronization mechanisms still represent a major scientific challenge. We report here the results of a study of the brain functional activity from a network theory perspective. An fMRI data-set corresponding to the neuronal activity of 41 mice brains at resting state has been analyzed by applying a range of procedures (e.g. community detection, percolation analysis), in order to gain insight into the collective activity of brain areas. A statistically meaningful signal of collective neuronal activity is detectable even at resting state, permitting to identify functionally related areas.
Detecting cluster structure of resting state fMRI brain networks: percolation and modularity features
Gabrielli A.;Squartini T.;
2015
Abstract
The extremely complex connected structure of the brain shapes a functional network whose activation and synchronization mechanisms still represent a major scientific challenge. We report here the results of a study of the brain functional activity from a network theory perspective. An fMRI data-set corresponding to the neuronal activity of 41 mice brains at resting state has been analyzed by applying a range of procedures (e.g. community detection, percolation analysis), in order to gain insight into the collective activity of brain areas. A statistically meaningful signal of collective neuronal activity is detectable even at resting state, permitting to identify functionally related areas.File | Dimensione | Formato | |
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