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The brain comprises a complex network of anatomically distinct regions (each with specialized functions) that collaborate to support various cognitive processes. Therefore, it is important to understand the brain from the perspective of a complex network. Functional magnetic resonance imaging (fMRI) is increasingly being accepted for its ability to provide useful insights into brain function. Among the fMRI techniques available in clinical practice, resting-state fMRI (rsfMRI) represents the core method for mapping brain activity in the absence of specific tasks; studies have reported the usefulness of rsfMRI in the investigation of various human diseases. Functional brain networks, which consist of interconnected regions that show correlated activities, are typically depicted as functional connectivity (FC). FC analysis using rsfMRI data provides extensive information, revealing intrinsic resting-state networks and highlights deviations in network structure among patients with psychiatric disorders. Such network insights not only deepen our understanding of the brain but also facilitate assessment of network alterations associated with psychiatric and neurodegenerative diseases.
Hirotaka Onoe (Mon,) studied this question.