H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Neuroscience D-index 59 Citations 14,194 185 World Ranking 1482 National Ranking 717

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Artificial intelligence
  • Neuroscience

Theodore D. Satterthwaite focuses on Neuroscience, Cognition, Neuroimaging, Connectome and Developmental psychology. His Neuroscience study incorporates themes from Schizophrenia and Brain size. His study looks at the intersection of Cognition and topics like Cohort with Young adult and Psychiatry.

His work carried out in the field of Neuroimaging brings together such families of science as Pattern recognition, Brain mapping and Brain development. His Connectome research incorporates themes from Motion, Artificial intelligence, Artifact, Sex characteristics and Resting state fMRI. The various areas that Theodore D. Satterthwaite examines in his Motion study include Functional connectivity, Cognitive psychology and Confounding.

His most cited work include:

  • An Improved Framework for Confound Regression and Filtering for Control of Motion Artifact in the Preprocessing of Resting-State Functional Connectivity Data (979 citations)
  • Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth. (812 citations)
  • Sex differences in the structural connectome of the human brain. (648 citations)

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

His main research concerns Neuroscience, Neuroimaging, Cognition, Clinical psychology and Artificial intelligence. His research in Neuroscience focuses on subjects like Schizophrenia, which are connected to Bipolar disorder. His Neuroimaging study combines topics in areas such as White matter, Multivariate analysis, Cortical surface, Brain development and Brain mapping.

His Cognition study integrates concerns from other disciplines, such as Developmental psychology, Functional magnetic resonance imaging and Audiology. His Clinical psychology research focuses on subjects like Psychosis, which are linked to Cohort. His research on Artificial intelligence also deals with topics like

  • Resting state fMRI, which have a strong connection to Connectome,
  • Magnetic resonance imaging and related Segmentation.

He most often published in these fields:

  • Neuroscience (26.20%)
  • Neuroimaging (26.20%)
  • Cognition (22.29%)

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

  • Neuroimaging (26.20%)
  • Neuroscience (26.20%)
  • Clinical psychology (21.69%)

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

His primary areas of study are Neuroimaging, Neuroscience, Clinical psychology, Cognition and Psychosis. Theodore D. Satterthwaite combines subjects such as Schizophrenia, Multivariate analysis, Cortical surface, Meta-analysis and Artificial intelligence with his study of Neuroimaging. His research is interdisciplinary, bridging the disciplines of Schizophrenia and Neuroscience.

The Clinical psychology study combines topics in areas such as White matter, Depression and Anxiety. He focuses mostly in the field of Psychosis, narrowing it down to topics relating to Cortex and, in certain cases, Human brain. Theodore D. Satterthwaite works mostly in the field of Prefrontal cortex, limiting it down to topics relating to Connectome and, in certain cases, Resting state fMRI, as a part of the same area of interest.

Between 2019 and 2021, his most popular works were:

  • Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group (62 citations)
  • Development of structure–function coupling in human brain networks during youth (56 citations)
  • Development of structure–function coupling in human brain networks during youth (56 citations)

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

  • Statistics
  • Artificial intelligence
  • Neuroscience

Neuroimaging, Neuroscience, Cognition, Cortical surface and Schizophrenia are his primary areas of study. He has researched Neuroimaging in several fields, including Multivariate analysis, Brain development, Mood disorders, Anxiety and Multivariate statistics. Many of his research projects under Neuroscience are closely connected to Variation with Variation, tying the diverse disciplines of science together.

His studies in Cognition integrate themes in fields like Functional magnetic resonance imaging and Network dynamics. His Schizophrenia study combines topics from a wide range of disciplines, such as White matter, Artificial intelligence, Wechsler Adult Intelligence Scale, Neurocognitive and Machine learning. His Connectome research incorporates elements of Psychopathology and Network science.

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.

Best Publications

An Improved Framework for Confound Regression and Filtering for Control of Motion Artifact in the Preprocessing of Resting-State Functional Connectivity Data

Theodore D. Satterthwaite;Mark A. Elliott;Raphael T. Gerraty;Kosha Ruparel.
NeuroImage (2013)

946 Citations

Sex differences in the structural connectome of the human brain.

Madhura Ingalhalikar;Alex Smith;Drew Parker;Theodore D. Satterthwaite.
Proceedings of the National Academy of Sciences of the United States of America (2014)

911 Citations

Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth.

Theodore D. Satterthwaite;Daniel H. Wolf;James Loughead;Kosha Ruparel.
NeuroImage (2012)

835 Citations

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.
Molecular Psychiatry (2016)

589 Citations

Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity.

Rastko Ciric;Daniel H. Wolf;Jonathan D. Power;David R. Roalf.
NeuroImage (2017)

475 Citations

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

Paul M. Thompson;Jason L. Stein;Sarah E. Medland;Derrek P. Hibar.
Brain Imaging and Behavior (2014)

417 Citations

Neuroimaging of the Philadelphia neurodevelopmental cohort.

Theodore D. Satterthwaite;Mark A. Elliott;Kosha Ruparel;James Loughead.
NeuroImage (2014)

356 Citations

Cortical abnormalities in bipolar disorder : An MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group

D P Hibar;L T Westlye;L T Westlye;N T Doan;N T Doan;N Jahanshad.
Molecular Psychiatry (2018)

317 Citations

Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group

S. Kelly;S. Kelly;N. Jahanshad;A. Zalesky;P. Kochunov.
Molecular Psychiatry (2018)

290 Citations

Subcortical volumetric abnormalities in bipolar disorder

D. P. Hibar;L. T. Westlye;L. T. Westlye;T. G. M. van Erp;J. Rasmussen.
Molecular Psychiatry (2016)

286 Citations

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