Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction

• Published in: Neuropsychopharmacology (New York, N.Y.) N.Y.), 2024-11, Vol.50 (1), p.114-123
• Main Authors: Ramduny, Jivesh, Kelly, Clare
• Format: Article
• Language: English
• Subjects: 631/378/2649; 692/53; Accuracy; Animals; Behavior; Behavioral Sciences; Biological Psychology; Biomarkers; Brain - diagnostic imaging; Brain - physiology; Brain architecture; Brain mapping; Brain research; Connectome - methods; Datasets; Fingerprinting; Functional magnetic resonance imaging; Functional morphology; Humans; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Medical imaging; Medicine; Medicine & Public Health; Mental Disorders - diagnostic imaging; Mental Disorders - physiopathology; Neural networks; Neuroimaging; Neurosciences; Pharmacotherapy; Phenotypes; Predictions; Psychiatry; Reproducibility; Reproducibility of Results; Review Article
• ISSN: 0893-133X; 1740-634X; 1740-634X
• DOI: 10.1038/s41386-024-01962-8

Functional magnetic resonance imaging-based functional connectivity enables the non-invasive mapping of individual differences in brain functional organization to individual differences in a vast array of behavioral phenotypes. This flexibility has renewed the search for neuroimaging-based biomarkers that exhibit reproducibility , prediction , and precision . Functional connectivity-based measures that share these three characteristics are key to achieving this goal. Here, we review the functional connectome fingerprinting approach and discuss its value, not only as a simple and intuitive conceptualization of the “functional connectome” that provides new insights into how the connectome is altered in association with psychiatric symptoms, but also as a straightforward and interpretable method for indexing the reproducibility of functional connectivity-based measures. We discuss how these advantages provide new avenues for strengthening reproducibility , precision , and behavioral prediction for functional connectomics and we consider new directions toward discovering better biomarkers for neuropsychiatric conditions.