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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Fast and Accurate Detection of Complex Imaging Genetics Associations Based on Greedy Projected Distance Correlation
TL;DR: A novel method to detect conditional associations between imaging genetics data is presented, using projected distance correlation to build a conditional dependency graph among high-dimensional mixed data, and then using multiple testing to detect significant group level associations.
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Whole-Brain Dynamics in Aging: Disruptions in Functional Connectivity and the Role of the Rich Club.
Anira Escrichs,Carles Biarnes,Josep Garre-Olmo,José Manuel Fernández-Real,Rafel Ramos,Reinald Pamplona,Ramon Brugada,Joaquín Serena,Lluís Ramió-Torrentà,Gabriel Coll-de-Tuero,Lluis Gallart,Jordi Barretina,Joan C. Vilanova,Jordi Mayneris-Perxachs,Marco Essig,Chase R. Figley,Salvador Pedraza,Josep Puig,Gustavo Deco +18 more
TL;DR: In this paper, the authors employed two data-driven whole-brain approaches based on the phase synchronization of blood-oxygen-level-dependent signals to analyze resting-state fMRI data from 620 subjects divided into two groups (middle-age group (n = 310); age range, 50-64 years versus older group(n = 210); age ranges, 65-91 years).
Journal ArticleDOI
Modelling subject variability in the spatial and temporal characteristics of functional modes
Samuel J. Harrison,Samuel J. Harrison,Janine D. Bijsterbosch,Andrew R. Segerdahl,Sean P. Fitzgibbon,Seyedeh-Rezvan Farahibozorg,Eugene P. Duff,Stephen M. Smith,Mark W. Woolrich +8 more
TL;DR: Probabilistic functional modes are extended with a hierarchical temporal model and improved spatial sensitivity is demonstrated using rfMRI data from 1000 HCP subjects.
Journal ArticleDOI
Local connectome phenotypes predict social, health, and cognitive factors.
Michael A. Powell,Javier O. Garcia,Fang-Cheng Yeh,Jean M. Vettel,Jean M. Vettel,Jean M. Vettel,Timothy Verstynen +6 more
TL;DR: This work shows, for the first time, how the local connectome has both the sensitivity and the specificity to be used as a phenotypic marker for subject-specific attributes, and shows how variability in the local connectedome is correlated in a principled way across individuals.
Journal ArticleDOI
Functional connectome fingerprinting accuracy in youths and adults is similar when examined on the same day and 1.5-years apart.
Maria Jalbrzikowski,Fuchen Liu,William Foran,Lambertus Klei,Finnegan J. Calabro,Kathryn Roeder,Bernie Devlin,Beatriz Luna +7 more
TL;DR: A framework for understanding the sensitivity and specificity of fingerprinting accuracy in adolescents and adults at multiple time scales is provided, suggesting that cognitive and default networks play a primary role in the individualization of one's connectome.
References
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Correspondence of the brain's functional architecture during activation and rest.
Stephen M. Smith,Peter T. Fox,Karla L. Miller,David C. Glahn,P. Mickle Fox,Clare E. Mackay,Nicola Filippini,Kate E. Watkins,Roberto Toro,Angela R. Laird,Christian F. Beckmann,Christian F. Beckmann +11 more
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