H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Neuroscience H-index 132 Citations 75,066 950 World Ranking 76 National Ranking 49
Computer Science H-index 109 Citations 44,032 695 World Ranking 93 National Ranking 61

Research.com Recognitions

Awards & Achievements

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

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Neuroscience
  • Statistics

Neuroscience, Artificial intelligence, Functional magnetic resonance imaging, Independent component analysis and Brain mapping are his primary areas of study. As part of his studies on Neuroscience, he often connects relevant areas like Schizophrenia. His Artificial intelligence research includes themes of Algorithm, Machine learning, Electroencephalography and Pattern recognition.

His Functional magnetic resonance imaging course of study focuses on Schizophrenia and Voxel. He has researched Independent component analysis in several fields, including Communication, Speech recognition, Principal component analysis, Sensor fusion and Component. His Brain mapping study combines topics in areas such as Nerve net, Event-related potential, Event, Cerebral cortex and Sensory system.

His most cited work include:

  • A method for making group inferences from functional MRI data using independent component analysis (2101 citations)
  • A method for making group inferences from functional MRI data using independent component analysis (2101 citations)
  • Tracking Whole-Brain Connectivity Dynamics in the Resting State (1555 citations)

What are the main themes of his work throughout his whole career to date?

Vince D. Calhoun focuses on Artificial intelligence, Neuroscience, Functional magnetic resonance imaging, Pattern recognition and Independent component analysis. His Artificial intelligence research is multidisciplinary, incorporating elements of Schizophrenia, Machine learning and Neuroimaging. Many of his studies on Neuroscience apply to Schizophrenia as well.

The study incorporates disciplines such as Brain activity and meditation and Magnetic resonance imaging in addition to Functional magnetic resonance imaging. His biological study spans a wide range of topics, including Cluster analysis, Blind signal separation, Sensor fusion and Electroencephalography. His research integrates issues of Infomax, Data mining, Speech recognition and Component in his study of Independent component analysis.

He most often published in these fields:

  • Artificial intelligence (50.51%)
  • Neuroscience (53.63%)
  • Functional magnetic resonance imaging (43.84%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (50.51%)
  • Pattern recognition (36.42%)
  • Functional magnetic resonance imaging (43.84%)

In recent papers he was focusing on the following fields of study:

Vince D. Calhoun spends much of his time researching Artificial intelligence, Pattern recognition, Functional magnetic resonance imaging, Neuroimaging and Neuroscience. His Artificial intelligence study incorporates themes from Resting state fMRI, Machine learning and Cognition. Vince D. Calhoun studies Independent component analysis, a branch of Pattern recognition.

He is interested in Dynamic functional connectivity, which is a field of Functional magnetic resonance imaging. His Dynamic functional connectivity research integrates issues from Sliding window protocol and Algorithm. His Neuroscience study frequently links to adjacent areas such as Schizophrenia.

Between 2019 and 2021, his most popular works were:

  • The genetic architecture of the human cerebral cortex. (116 citations)
  • Questions and controversies in the study of time-varying functional connectivity in resting fMRI (111 citations)
  • Questions and controversies in the study of time-varying functional connectivity in resting fMRI (111 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Internal medicine

The scientist’s investigation covers issues in Artificial intelligence, Neuroimaging, Neuroscience, Functional magnetic resonance imaging and Resting state fMRI. His work deals with themes such as Machine learning, Schizophrenia and Pattern recognition, which intersect with Artificial intelligence. His Neuroimaging research incorporates elements of Cognition, Neuropsychology, Cortical surface, Clinical psychology and Autism spectrum disorder.

The Neuroscience study which covers Magnetic resonance imaging that intersects with Schizophrenia spectrum. His work carried out in the field of Functional magnetic resonance imaging brings together such families of science as Graphical model, Statistics and Hidden Markov model. The various areas that Vince D. Calhoun examines in his Resting state fMRI study include Classifier, Sliding window protocol, Functional networks, Functional connectivity and Basal ganglia.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

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

V. D. Calhoun;V. D. Calhoun;T. Adali;G. D. Pearlson;J. J. Pekar;J. J. Pekar.
Human Brain Mapping (2001)

2364 Citations

Dynamic functional connectivity: Promise, issues, and interpretations

R. Matthew Hutchison;Thilo Womelsdorf;Elena A. Allen;Elena A. Allen;Peter A. Bandettini.
NeuroImage (2013)

1526 Citations

Tracking Whole-Brain Connectivity Dynamics in the Resting State

Elena A. Allen;Elena A. Allen;Eswar Damaraju;Sergey M. Plis;Erik B. Erhardt.
Cerebral Cortex (2014)

1499 Citations

Aberrant "default mode" functional connectivity in schizophrenia.

Abigail G. Garrity;Godfrey D. Pearlson;Kristen McKiernan;Dan Lloyd.
American Journal of Psychiatry (2007)

1114 Citations

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.
Proceedings of the National Academy of Sciences of the United States of America (2007)

1041 Citations

A Baseline for the Multivariate Comparison of Resting-State Networks

Elena A. Allen;Erik B. Erhardt;Eswar Damaraju;William Gruner;William Gruner.
Frontiers in Systems Neuroscience (2011)

899 Citations

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.
NeuroImage (2009)

885 Citations

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.
NeuroImage (2008)

770 Citations

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

Yi Ou Li;Tülay Adali;Vince D. Calhoun.
Human Brain Mapping (2007)

733 Citations

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.
Human Brain Mapping (2001)

716 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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