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Computer Science
USA
2026
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Neuroscience
USA
2026

D-Index & Metrics

Neuroscience

D-Index
160
Citations
113700
World Ranking
112
National Ranking
73

Computer Science

D-Index
141
Citations
83528
World Ranking
61
National Ranking
35

Research.com Recognitions

  • 2026 - Research.com Computer Science in United States Leader Award
  • 2026 - Research.com Neuroscience in United States Leader Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2025 - Research.com Neuroscience in United States Leader Award
  • 2023 - Research.com Computer Science in United States Leader Award
  • 2022 - Research.com Computer Science in United States Leader Award
  • 2014 - Fellow of the Indian National Academy of Engineering (INAE)
  • 2013 - IEEE Fellow For contributions to data-driven processing of multimodal brain imaging and genetic data
  • 2012 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

Vince D. Calhoun is affiliated with Georgia State University in the United States. Their research primarily spans the fields of Neuroscience and Medicine, with a strong focus on Cognitive Neuroscience and Radiology, Nuclear Medicine, and Imaging. Other subfields include Experimental and Cognitive Psychology, Psychiatry and Mental Health, and Molecular Biology.

The scientist's work covers a range of topics related to brain function and imaging techniques. Key research areas include:

  • Functional Brain Connectivity Studies
  • Neural dynamics and brain function
  • Advanced Neuroimaging Techniques and Applications
  • EEG and Brain-Computer Interfaces
  • Mental Health Research Topics
  • Advanced MRI Techniques and Applications
  • Health, Environment, Cognitive Aging

Vince D. Calhoun has contributed extensively to publications in several leading venues. The most frequent publication venues are:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Human Brain Mapping
  • NeuroImage
  • Journal of Neuroscience Methods
  • Biological Psychiatry

Among their recent papers are:

  • Brain charts for the human lifespan, 2022, published in Nature
  • NeuroMark: An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders, 2020, published in NeuroImage Clinical
  • Neuroimaging-based Individualized Prediction of Cognition and Behavior for Mental Disorders and Health: Methods and Promises, 2020, published in Biological Psychiatry
  • Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years, 2021, published in Human Brain Mapping
  • Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA, 2020, published in NeuroImage

Frequent co-authors who have collaborated with Vince D. Calhoun include:

  • Zening Fu
  • Yu-Ping Wang
  • Jessica A. Turner
  • Jing Sui
  • Julia M. Stephen

The scientist has received several honors, including:

  • Fellow of the Indian National Academy of Engineering (INAE), 2014
  • IEEE Fellow, 2013, for contributions to data-driven processing of multimodal brain imaging and genetic data
  • Fellow of the American Association for the Advancement of Science (AAAS), 2012

Best Publications

  • A method for making group inferences from functional MRI data using independent component analysis

    V.D. Calhoun;T. Adali;G.D. Pearlson;J.J. Pekar;J.J. Pekar

  • Tracking Whole-Brain Connectivity Dynamics in the Resting State

    Elena A. Allen;Eswar Damaraju;Sergey M. Plis;Erik B. Erhardt

  • Dynamic functional connectivity: Promise, issues, and interpretations

    R. Matthew Hutchison;Thilo Womelsdorf;Elena A. Allen;Elena A. Allen;Peter A. Bandettini

  • Brain charts for the human lifespan

    Unknown

  • The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments.

    Krzysztof J. Gorgolewski;Tibor Auer;Vince D. Calhoun;R. Cameron Craddock

  • The Chronnectome: Time-Varying Connectivity Networks as the Next Frontier in fMRI Data Discovery

    Vince D. Calhoun;Vince D. Calhoun;Robyn Miller;Godfrey Pearlson;Tulay Adalı

  • A Baseline for the Multivariate Comparison of Resting-State Networks

    Elena A. Allen;Erik B. Erhardt;Eswar Damaraju;William Gruner;William Gruner

  • Aberrant "default mode" functional connectivity in schizophrenia.

    Abigail G. Garrity;Godfrey D. Pearlson;Kristen McKiernan;Dan Lloyd

  • A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data.

    Vince D. Calhoun;Jingyu Liu;Jingyu Liu;Tülay Adalı

  • Selective changes of resting-state networks in individuals at risk for Alzheimer's disease

    Christian Sorg;Valentin Riedl;Valentin Riedl;Mark Mühlau;Vince D. Calhoun

  • Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium

    T. G M van Erp;D. P. Hibar;J. M. Rasmussen;D. C. Glahn

  • Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia

    E. Damaraju;E.A. Allen;E.A. Allen;A. Belger;J.M. Ford;J.M. Ford

  • Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium

    Unknown

  • A method for functional network connectivity among spatially independent resting-state components in schizophrenia.

    Madiha J. Jafri;Godfrey D. Pearlson;Michael C. Stevens;Vince D. Calhoun

  • Estimating the number of independent components for functional magnetic resonance imaging data.

    Yi Ou Li;Tülay Adali;Vince D. Calhoun

  • Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.

    Mohammad R. Arbabshirani;Sergey M. Plis;Jing Sui;Vince D. Calhoun

  • Common genetic variants influence human subcortical brain structures.

    Derrek P. Hibar;Jason L. Stein;Jason L. Stein;Miguel E. Renteria;Alejandro Arias-Vasquez

  • Alterations in Memory Networks in Mild Cognitive Impairment and Alzheimer's Disease: An Independent Component Analysis

    Kim A. Celone;Vince D. Calhoun;Bradford C. Dickerson;Alireza Atri

  • The NKI-Rockland Sample: A Model for Accelerating the Pace of Discovery Science in Psychiatry.

    Kate Brody Nooner;Kate Brody Nooner;Stanley J. Colcombe;Russell H. Tobe;Maarten Mennes;Maarten Mennes

  • Spatial and temporal independent component analysis of functional MRI data containing a pair of task-related waveforms.

    V.D. Calhoun;T. Adali;G.D. Pearlson;J.J. Pekar;J.J. Pekar

  • The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

    Paul M. Thompson;Jason L. Stein;Sarah E. Medland;Derrek P. Hibar

  • Erratum: Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium (Molecular Psychiatry (2015) DOI:10.1038/mp.2015.63)

    T. G.M. Van Erp;D. P. Hibar;J. M. Rasmussen;D. C. Glahn

  • Supplementary Material to: Tracking Whole-Brain Connectivity Dynamics in the Resting State.

    Elena A. Allen;Eswar Damaraju;Sergey M. Plis;Erik B. Erhardt

Frequent Co-Authors

Godfrey D. Pearlson
Godfrey D. Pearlson Yale University
Jessica A. Turner
Jessica A. Turner The Ohio State University
Jing Sui
Jing Sui Beijing Normal University
Tulay Adali
Tulay Adali University of Maryland, Baltimore County
Kent A. Kiehl
Kent A. Kiehl University of New Mexico
Daniel H. Mathalon
Daniel H. Mathalon University of California, San Francisco
Juan R. Bustillo
Juan R. Bustillo University of New Mexico
Andrew R. Mayer
Andrew R. Mayer Mind Research Network
Theo G.M. van Erp
Theo G.M. van Erp University of California, Irvine
Randy L. Gollub
Randy L. Gollub Harvard Medical School

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