Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity
Emily S. Finn,Xilin Shen,Dustin Scheinost,Monica D. Rosenberg,Jessica S. Huang,Marvin M. Chun,Xenophon Papademetris,R. Todd Constable +7 more
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In this article, the authors show that every individual has a unique pattern of functional connections between brain regions, which act as a fingerprint that can accurately identify the individual from a large group.Abstract:
This study shows that every individual has a unique pattern of functional connections between brain regions. This functional connectivity profile acts as a ‘fingerprint’ that can accurately identify the individual from a large group. Furthermore, an individual's connectivity profile can predict his or her level of fluid intelligence.read more
Citations
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Journal ArticleDOI
Parsing Heterogeneity in the Brain Connectivity of Depressed and Healthy Adults During Positive Mood
Rebecca B. Price,Stephanie T. Lane,Kathleen M. Gates,Thomas E. Kraynak,Michelle S. Horner,Michael E. Thase,Greg J. Siegle +6 more
TL;DR: Data-driven parsing of neural connectivity suggests heterogeneous substrates of depression and possible resilience in control subjects in spite of biological overlap, and neural connectivity-based categorization travels with diagnostic category and is clinically predictive, but not clinically deterministic.
Posted ContentDOI
Hierarchical heterogeneity across human cortex shapes large-scale neural dynamics
Murat Demirtas,Joshua B. Burt,Markus Helmer,Jie Lisa Ji,Brendan Adkinson,Matthew F. Glasser,Matthew F. Glasser,David C. Van Essen,Stamatios N. Sotiropoulos,Stamatios N. Sotiropoulos,Alan Anticevic,John D. Murray +11 more
TL;DR: A large-scale dynamical circuit model of human cortex that incorporates heterogeneity of local synaptic strengths, following a hierarchical axis inferred from MRI-derived T1w/T2w mapping, is developed and fit the model using multimodal neuroimaging data.
Journal ArticleDOI
Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity.
Claudinei E. Biazoli,Claudinei E. Biazoli,Giovanni Abrahão Salum,Giovanni Abrahão Salum,Pedro Mario Pan,Pedro Mario Pan,André Zugman,André Zugman,Edson Amaro,Luis Augusto Rohde,Luis Augusto Rohde,Euripedes Constantino Miguel,Euripedes Constantino Miguel,Andrea Parolin Jackowski,Andrea Parolin Jackowski,Rodrigo A. Bressan,Rodrigo A. Bressan,João Ricardo Sato +17 more
TL;DR: This research presents a novel and scalable approach called “Smart phones” that allows for real-time decision-making in the rapidly changing environment and helps clarify the role of emotion in human development.
Posted ContentDOI
A distributed brain network predicts general intelligence from resting-state human neuroimaging data
TL;DR: Using a cross-validated predictive framework, 20% of the variance in general intelligence in the sampled population was predicted from their resting-state connectivity matrices, and no single anatomical structure or network was responsible or necessary for this prediction, which instead relied on redundant information distributed across the brain.
Journal ArticleDOI
Individualized perturbation of the human connectome reveals reproducible biomarkers of network dynamics relevant to cognition
Recep Ali Ozdemir,Ehsan Tadayon,Pierre Boucher,Davide Momi,Kelly A. Karakhanyan,Michael D. Fox,Michael D. Fox,Mark A. Halko,Alvaro Pascual-Leone,Alvaro Pascual-Leone,Mouhsin M. Shafi,Emiliano Santarnecchi,Emiliano Santarnecchi +12 more
TL;DR: This work used fMRI-guided transcranial magnetic stimulation (TMS) and simultaneous electroencephalography (EEG) to characterize individual brain dynamics within discrete brain networks at high temporal resolution, and observed the propagation of neural activity across local and distal regions with millisecond resolution.
References
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