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
More filters
Journal ArticleDOI
Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI
Alexander Schaefer,Ru Kong,Evan M. Gordon,Timothy O. Laumann,Xi-Nian Zuo,Avram J. Holmes,Simon B. Eickhoff,B.T. Thomas Yeo,B.T. Thomas Yeo +8 more
TL;DR: The results suggest that gwMRF parcellations reveal neurobiologically meaningful features of brain organization and are potentially useful for future applications requiring dimensionality reduction of voxel-wise fMRI data.
Journal ArticleDOI
Precision Functional Mapping of Individual Human Brains
Evan M. Gordon,Timothy O. Laumann,Adrian W. Gilmore,Adrian W. Gilmore,Dillan J. Newbold,Deanna J. Greene,Jeffrey J. Berg,Mario Ortega,Catherine Hoyt-Drazen,Caterina Gratton,Haoxin Sun,Jacqueline M. Hampton,Rebecca S. Coalson,Annie L. Nguyen,Kathleen B. McDermott,Joshua S. Shimony,Abraham Z. Snyder,Bradley L. Schlaggar,Steven E. Petersen,Steven M. Nelson,Steven M. Nelson,Nico U.F. Dosenbach +21 more
TL;DR: A novel MRI dataset containing 5 hr of RSFC data, 6 hour of task fMRI, multiple structural MRIs, and neuropsychological tests from each of ten adults generated ten high-fidelity, individual-specific functional connectomes, revealing several new types of spatial and organizational variability in brain networks.
Journal ArticleDOI
A neuromarker of sustained attention from whole-brain functional connectivity.
Monica D. Rosenberg,Emily S. Finn,Dustin Scheinost,Xenophon Papademetris,Xilin Shen,R. Todd Constable,Marvin M. Chun +6 more
TL;DR: It is demonstrated that whole-brain functional network strength provides a broadly applicable neuromarker of sustained attention, and predicts a clinical measure of attention—symptoms of attention deficit hyperactivity disorder—from resting-state connectivity in an independent sample of children and adolescents.
Journal ArticleDOI
Using connectome-based predictive modeling to predict individual behavior from brain connectivity.
Xilin Shen,Emily S. Finn,Dustin Scheinost,Monica D. Rosenberg,Marvin M. Chun,Xenophon Papademetris,R. Todd Constable +6 more
TL;DR: This protocol includes the following steps: feature selection, feature summarization, model building, and assessment of prediction significance, and it has been demonstrated that the CPM protocol performs as well as or better than many of the existing approaches in brain-behavior prediction.
Posted ContentDOI
Local-Global Parcellation of the Human Cerebral Cortex From Intrinsic Functional Connectivity MRI
Alexander Schaefer,Ru Kong,Evan M. Gordon,Timothy O. Laumann,Xi-Nian Zuo,Avram J. Holmes,Simon B. Eickhoff,B.T. Thomas Yeo +7 more
TL;DR: The results suggest that gwMRF parcellations reveal neurobiologically meaningful features of brain organization and are potentially useful for future applications requiring dimensionality reduction of voxel-wise fMRI data.
References
More filters
Journal ArticleDOI
Groupwise whole-brain parcellation from resting-state fMRI data for network node identification.
TL;DR: Three atlases at the 100-, 200- and 300-parcellation levels derived from 79 healthy normal volunteers are made freely available online along with tools to interface this atlas with SPM, BioImage Suite and other analysis packages.
Journal ArticleDOI
Intelligence and socioeconomic success: A meta-analytic review of longitudinal research ☆
TL;DR: This paper conducted a meta-analysis of the longitudinal studies that have investigated intelligence as a predictor of success (as measured by education, occupation, and income) in order to better evaluate the predictive power of intelligence, also including meta-analyses of parental socioeconomic status (SES) and academic performance (school grades).
Journal ArticleDOI
Functional System and Areal Organization of a Highly Sampled Individual Human Brain.
Timothy O. Laumann,Evan M. Gordon,Babatunde Adeyemo,Abraham Z. Snyder,Sung Jun Joo,Mei Yen Chen,Adrian W. Gilmore,Kathleen B. McDermott,Steven M. Nelson,Nico U.F. Dosenbach,Bradley L. Schlaggar,Jeanette A. Mumford,Russell A. Poldrack,Steven E. Petersen +13 more
TL;DR: The brain organization of a single individual repeatedly measured over more than a year is characterized and a reproducible and internally valid subject-specific areal-level parcellation that corresponds with subject- specific task activations is reported.
Journal ArticleDOI
Age-related changes in modular organization of human brain functional networks
TL;DR: Human brain functional networks are derived from fMRI measurements of endogenous, low frequency, correlated oscillations in 90 cortical and subcortical regions for two groups of healthy participants and both young and older brain networks demonstrated significantly non-random modularity.
Journal ArticleDOI
Brodmann's Areas 17 and 18 Brought into Stereotaxic Space—Where and How Variable?
TL;DR: These maps of Brodmann's areas 17 and 18 are the first of their kind and contain precise stereotaxic information on both interhemispheric and interindividual differences.