Abstract
Precision psychiatry is a new subfield of precision medicine, boosted by recent advances in neuroscience. The major goal of precision psychiatry is to match patients to the best treatments, based not only on general clinical features but also on careful analyses of their multilevel individual characteristics (e.g., genetic, brain structure, and function). Herein, we provide detailed descriptions of the computational methods commonly used to construct (i.e., correlation and Granger causality) and analyze (i.e., metrics of integration and segregation, motifs, centrality, and network entropy) functional brain networks. Then, we discuss the implications of developing new mathematical approaches and technologies to foster precise psychiatric diagnosis and treatment. Finally, we also discuss some ongoing lines of investigation and opportunities in this exciting new interdisciplinary field of inquiry.
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