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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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
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Journal ArticleDOI
Individual-Specific Areal-Level Parcellations Improve Functional Connectivity Prediction of Behavior
Ru Kong,Qing Yang,Evan Gordon,Aihuiping Xue,Xiaoxuan Yan,Csaba Orban,Xi-Nian Zuo,Xi-Nian Zuo,Nathan Spreng,Nathan Spreng,Tian Ge,Avram J. Holmes,Simon B. Eickhoff,B.T. Thomas Yeo +13 more
TL;DR: Yeo et al. as discussed by the authors proposed a hierarchical Bayesian model (MS-HBM) to estimate individual-specific areal-level cortical parcellations, which can capture behaviorally meaningful individual-level parcellation features beyond group-level Parcellations.
Journal ArticleDOI
Optimising experimental design for MEG resting state functional connectivity measurement.
Lucrezia Liuzzi,Lauren E. Gascoyne,Prejaas Tewarie,Eleanor L. Barratt,Elena Boto,Matthew J. Brookes +5 more
TL;DR: It is shown that the use of a foam head‐cast, which is known to improve co‐registration accuracy, increased significantly the between session repeatability of both beamformer reconstruction and connectivity estimation, and that recording duration is a critical parameter.
Book ChapterDOI
Image Pre-Processing
TL;DR: This chapter describes the methods used to prepare images for further analysis, including interest point and feature extraction, and some of these methods are also useful for global and local feature description, particularly the metrics derived from transforms and basis spaces.
Journal ArticleDOI
The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity.
Michael Eyre,Sean P. Fitzgibbon,Judit Ciarrusta,Lucilio Cordero-Grande,Anthony N. Price,Tanya Poppe,Andreas Schuh,Emer Hughes,Camilla O’Keeffe,Jakki Brandon,Daniel Cromb,Katy Vecchiato,Jesper L. R. Andersson,Eugene P. Duff,Serena J. Counsell,Stephen M. Smith,Daniel Rueckert,Joseph V. Hajnal,Tomoki Arichi,Tomoki Arichi,Jonathan O'Muircheartaigh,D Batallea,Alexander D. Edwards +22 more
TL;DR: In this article, the maturation and integrity of resting state networks (RSNs) at term-equivalent age in 337 infants (including 65 born preterm) were characterized in unprecedented detail.
Journal ArticleDOI
Considering factors affecting the connectome-based identification process: Comment on Waller et al.
TL;DR: It is shown here that the amount of data collected per subject and in‐scanner motion are the predominant factors influencing identification rates, not the spatiotemporal resolution of the acquisition, which suggests individual differences in the connectome are readily observable.
References
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Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain
Nathalie Tzourio-Mazoyer,B. Landeau,D. Papathanassiou,Fabrice Crivello,Octave Etard,Nicolas Delcroix,Bernard Mazoyer,Marc Joliot +7 more
TL;DR: An anatomical parcellation of the spatially normalized single-subject high-resolution T1 volume provided by the Montreal Neurological Institute was performed and it is believed that this tool is an improvement for the macroscopical labeling of activated area compared to labeling assessed using the Talairach atlas brain.
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Mikail Rubinov,Olaf Sporns +1 more
TL;DR: Construction of brain networks from connectivity data is discussed and the most commonly used network measures of structural and functional connectivity are described, which variously detect functional integration and segregation, quantify centrality of individual brain regions or pathways, and test resilience of networks to insult.
Journal ArticleDOI
The organization of the human cerebral cortex estimated by intrinsic functional connectivity
B.T. Thomas Yeo,Fenna M. Krienen,Jorge Sepulcre,Jorge Sepulcre,Mert R. Sabuncu,Mert R. Sabuncu,Danial Lashkari,Marisa O. Hollinshead,Marisa O. Hollinshead,Joshua L. Roffman,Jordan W. Smoller,Lilla Zöllei,Jonathan R. Polimeni,Bruce Fischl,Bruce Fischl,Hesheng Liu,Randy L. Buckner +16 more
TL;DR: In this paper, the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI data from 1,000 subjects and a clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex.
Journal ArticleDOI
Research domain criteria (RDoC): toward a new classification framework for research on mental disorders
Journal ArticleDOI
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
TL;DR: It is concluded that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically “active” even when at “rest.”