D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Neuroscience D-index 40 Citations 8,905 113 World Ranking 3294 National Ranking 1497

Research.com Recognitions

Awards & Achievements

2013 - ACM Senior Member

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Neuroscience
  • Machine learning

Satrajit S. Ghosh spends much of his time researching Neuroimaging, Software, Neuroscience, Image processing and Data mining. His studies deal with areas such as Field, Metadata and Cognitive neuroscience as well as Neuroimaging. He has included themes like Brain morphometry, Data processing, Data science and Pattern recognition in his Software study.

In general Neuroscience study, his work on Cognition, Default mode network, Sensory system and Broca's area often relates to the realm of Premotor cortex, thereby connecting several areas of interest. His Image processing study combines topics in areas such as Pipeline, Preprocessor, Inference and Interpretability. His Data mining research is multidisciplinary, incorporating perspectives in Workflow and Thesaurus.

His most cited work include:

  • Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python. (704 citations)
  • Neural modeling and imaging of the cortical interactions underlying syllable production. (681 citations)
  • Situating the default-mode network along a principal gradient of macroscale cortical organization (650 citations)

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

His primary areas of investigation include Neuroimaging, Neuroscience, Artificial intelligence, Pattern recognition and Functional magnetic resonance imaging. The concepts of his Neuroimaging study are interwoven with issues in Metadata, Data mining, Data model, Software and Data science. His biological study spans a wide range of topics, including Visualization, Data processing and Data structure.

His Neuroscience study frequently draws connections to other fields, such as Speech production. In his research, Embedding and Functional connectivity is intimately related to Resting state fMRI, which falls under the overarching field of Artificial intelligence. His work carried out in the field of Functional magnetic resonance imaging brings together such families of science as Clinical psychology and Brain function.

He most often published in these fields:

  • Neuroimaging (41.52%)
  • Neuroscience (35.27%)
  • Artificial intelligence (25.00%)

What were the highlights of his more recent work (between 2018-2021)?

  • Neuroimaging (41.52%)
  • Neuroscience (35.27%)
  • Artificial intelligence (25.00%)

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

The scientist’s investigation covers issues in Neuroimaging, Neuroscience, Artificial intelligence, Anxiety and Functional magnetic resonance imaging. The study incorporates disciplines such as Computer graphics, Image processing, Software, Software tool and Data science in addition to Neuroimaging. His studies in Image processing integrate themes in fields like Data mining, Thesaurus, Pipeline, Interpretability and Workflow.

In the field of Neuroscience, his study on Thalamus, Auditory system and Cerebellum overlaps with subjects such as In vivo and Process. His Artificial intelligence research includes themes of Machine learning, Receiver operating characteristic, Data model and Pattern recognition. Satrajit S. Ghosh interconnects Neurophysiology, Audiology and Active listening in the investigation of issues within Functional magnetic resonance imaging.

Between 2018 and 2021, his most popular works were:

  • fMRIPrep: a robust preprocessing pipeline for functional MRI (439 citations)
  • fMRIPrep: a robust preprocessing pipeline for functional MRI (439 citations)
  • Everything Matters: The ReproNim Perspective on Reproducible Neuroimaging. (47 citations)

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

  • Artificial intelligence
  • Neuroscience
  • Machine learning

His scientific interests lie mostly in Neuroscience, Neuroimaging, Preprocessor, Image processing and Artificial intelligence. Many of his studies on Neuroscience involve topics that are commonly interrelated, such as Gradient based algorithm. His Neuroimaging research incorporates themes from Voxel and Data science.

His Preprocessor research is multidisciplinary, incorporating elements of Data mining, Thesaurus, Interpretability, Pipeline and Workflow. Satrajit S. Ghosh works mostly in the field of Image processing, limiting it down to topics relating to Inference and, in certain cases, Artificial neural network, Segmentation and Deep learning, as a part of the same area of interest. His research in Artificial intelligence focuses on subjects like Pattern recognition, which are connected to Data structure, Software, Neural correlates of consciousness and Functional magnetic resonance imaging.

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

Neural modeling and imaging of the cortical interactions underlying syllable production.

Frank H. Guenther;Satrajit S. Ghosh;Jason A. Tourville.
Brain and Language (2006)

993 Citations

Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python.

Krzysztof J. Gorgolewski;Christopher D. Burns;Cindee M. Madison;Dav Clark.
Frontiers in Neuroinformatics (2011)

895 Citations

Situating the default-mode network along a principal gradient of macroscale cortical organization

Daniel S. Margulies;Satrajit S. Ghosh;Satrajit S. Ghosh;Alexandros Goulas;Marcel Falkiewicz.
Proceedings of the National Academy of Sciences of the United States of America (2016)

650 Citations

fMRIPrep: a robust preprocessing pipeline for functional MRI

Oscar Esteban;Christopher J. Markiewicz;Ross W. Blair;Craig A. Moodie.
Nature Methods (2019)

495 Citations

NeuroVault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain

Krzysztof J. Gorgolewski;Krzysztof J. Gorgolewski;Gael Varoquaux;Gabriel Rivera;Yannick Schwarz.
Frontiers in Neuroinformatics (2015)

393 Citations

Prediction as a Humanitarian and Pragmatic Contribution from Human Cognitive Neuroscience

John D.E. Gabrieli;John D.E. Gabrieli;Satrajit S. Ghosh;Satrajit S. Ghosh;Susan Whitfield-Gabrieli.
Neuron (2015)

391 Citations

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.
Scientific Data (2016)

337 Citations

Evaluation of volume-based and surface-based brain image registration methods

Arno Klein;Satrajit S. Ghosh;Brian Avants;B.T.T. Yeo.
NeuroImage (2010)

264 Citations

Data sharing in neuroimaging research

Jean-Baptiste Poline;Jean-Baptiste Poline;Janis L. Breeze;Satrajit S. Ghosh;Krzysztof J. Gorgolewski.
Frontiers in Neuroinformatics (2012)

237 Citations

Predicting Treatment Response in Social Anxiety Disorder From Functional Magnetic Resonance Imaging

Oliver Doehrmann;Satrajit S. Ghosh;Frida E. Polli;Gretchen O. Reynolds.
JAMA Psychiatry (2013)

230 Citations

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Vince D. Calhoun

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