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
TLDR
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
Functional Connectivity Predicts Individual Development of Inhibitory Control during Adolescence.
Haiyan Wang,Lingzhong Fan,Ming Song,Bing Liu,Dongya Wu,Rongtao Jiang,Jin Li,Ang Li,Tobias Banaschewski,Arun L.W. Bokde,Erin Burke Quinlan,Sylvane Desrivières,Herta Flor,Herta Flor,Antoine Grigis,Hugh Garavan,Bader Chaarani,Penny A. Gowland,Andreas Heinz,Bernd Ittermann,Jean-Luc Martinot,Marie-Laure Paillère Martinot,Eric Artiges,Frauke Nees,Dimitri Papadopoulos Orfanos,Luise Poustka,Sabina Millenet,Juliane H. Fröhner,Michael N. Smolka,Henrik Walter,Robert Whelan,Gunter Schumann,Tianzi Jiang +32 more
TL;DR: In this article, the authors used a large-scale longitudinal dataset in which the same subjects performed a stop signal task during functional magnetic resonance imaging at ages 14 and 19, and tried to find the brain features predicting their development by constructing prediction models using 14-year-olds' functional connections within a network or between a pair of networks.
Journal ArticleDOI
Functional connectome fingerprinting: Identifying individuals and predicting cognitive functions via autoencoder.
Biao Cai,Gemeng Zhang,Aiying Zhang,Li Xiao,Wenxing Hu,Julia M. Stephen,Tony W. Wilson,Vince D. Calhoun,Yu-Ping Wang +8 more
TL;DR: In this article, the authors proposed to enhance the uniqueness of individual connectome based on an autoencoder network, which can be regarded as "brain fingerprinting" to identify an individual from a pool of subjects.
Journal ArticleDOI
Enhancing Intelligence: From the Group to the Individual.
Roberto Colom,Francisco J. Román +1 more
TL;DR: The training program was based on the adaptive dual n-back task, and participants completed a comprehensive battery measuring fluid and crystallized ability, along with working memory and attention control, before and after training, which revealed positive effects for visuospatial processing across cognitive domains.
Proceedings ArticleDOI
Controlling a confound in predictive models with a test set minimizing its effect
TL;DR: This work introduces a non-sparametric approach to control for a confounding effect in a predictive model, based on crafting a test set on which the effect of interest is independent from the confounding effect, and demonstrates the approach with a large sample resting-state fMRI and psychometric data of healthy aging subjects.
Journal ArticleDOI
A Gaussian Process Model of Human Electrocorticographic Data.
Lucy L. W. Owen,Tudor A Muntianu,Andrew C. Heusser,Patrick M. Daly,Katherine W. Scangos,Jeremy R. Manning +5 more
TL;DR: The approach makes the simplifying assumptions that different people’s brains exhibit similar correlational structure, and that activity and correlation patterns vary smoothly over space, and provides a person- and task-general means of inferring high spatiotemporal resolution full-brain neural dynamics from standard low-density intracranial recordings.
References
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