V
Vince D. Calhoun
Researcher at Georgia Institute of Technology
Publications - 1467
Citations - 76510
Vince D. Calhoun is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Resting state fMRI & Medicine. The author has an hindex of 117, co-authored 1234 publications receiving 62205 citations. Previous affiliations of Vince D. Calhoun include University of Maryland, Baltimore & Johns Hopkins University School of Medicine.
Papers
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Journal ArticleDOI
A method for making group inferences from functional MRI data using independent component analysis
TL;DR: A novel approach for drawing group inferences using ICA of fMRI data is introduced, and its application to a simple visual paradigm that alternately stimulates the left or right visual field is presented.
Journal ArticleDOI
Tracking Whole-Brain Connectivity Dynamics in the Resting State
Elena A. Allen,Eswar Damaraju,Sergey M. Plis,Erik B. Erhardt,Tom Eichele,Vince D. Calhoun,Vince D. Calhoun +6 more
TL;DR: In this article, the authors describe an approach to assess whole-brain functional connectivity dynamics based on spatial independent component analysis, sliding time window correlation, and k-means clustering of windowed correlation matrices.
Journal ArticleDOI
Dynamic functional connectivity: Promise, issues, and interpretations
R. Matthew Hutchison,Thilo Womelsdorf,Elena A. Allen,Elena A. Allen,Peter A. Bandettini,Vince D. Calhoun,Vince D. Calhoun,Maurizio Corbetta,Maurizio Corbetta,Stefania Della Penna,Jeff H. Duyn,Gary H. Glover,Javier Gonzalez-Castillo,Daniel A. Handwerker,Shella D. Keilholz,Vesa Kiviniemi,David A. Leopold,Francesco de Pasquale,Olaf Sporns,Martin Walter,Martin Walter,Catie Chang +21 more
TL;DR: Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain.
Journal ArticleDOI
A Baseline for the Multivariate Comparison of Resting-State Networks
Elena A. Allen,Erik B. Erhardt,Eswar Damaraju,William Gruner,William Gruner,Judith M. Segall,Judith M. Segall,Rogers F. Silva,Rogers F. Silva,Martin Havlicek,Martin Havlicek,Srinivas Rachakonda,Jill Fries,Ravi Kalyanam,Ravi Kalyanam,Andrew M. Michael,Arvind Caprihan,Jessica A. Turner,Jessica A. Turner,Tom Eichele,Steven Adelsheim,Angela D. Bryan,Angela D. Bryan,Juan R. Bustillo,Vincent P. Clark,Vincent P. Clark,Sarah W. Feldstein Ewing,Francesca M. Filbey,Francesca M. Filbey,Corey C. Ford,Kent E. Hutchison,Kent E. Hutchison,Rex E. Jung,Rex E. Jung,Kent A. Kiehl,Kent A. Kiehl,Piyadasa W. Kodituwakku,Yuko M. Komesu,Andrew R. Mayer,Andrew R. Mayer,Godfrey D. Pearlson,John P. Phillips,John P. Phillips,Joseph Sadek,Michael Stevens,Ursina Teuscher,Ursina Teuscher,Robert J. Thoma,Vince D. Calhoun +48 more
TL;DR: A multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing is introduced and is demonstrated by identifying the effects of age and gender on the resting-state networks of 603 healthy adolescents and adults.
Journal ArticleDOI
The Chronnectome: Time-Varying Connectivity Networks as the Next Frontier in fMRI Data Discovery
TL;DR: This Perspective uses the term "chronnectome" to describe metrics that allow a dynamic view of coupling and focuses on multivariate approaches developed in the group and review a number of approaches with an emphasis on matrix decompositions such as principle component analysis and independent component analysis.