World's Best Scientists 2026 revealed!

D-Index & Metrics

Neuroscience

D-Index
73
Citations
25592
World Ranking
2173
National Ranking
1032

Russell T. Shinohara publication distribution in Neuroscience in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Neuroscience in 2026. The highlighted bar marks where Russell T. Shinohara sits on this spectrum.

38–47 publications: 18 scientists 48–57 publications: 79 scientists 58–67 publications: 193 scientists 68–77 publications: 323 scientists 78–87 publications: 406 scientists 88–97 publications: 452 scientists 98–107 publications: 539 scientists 108–117 publications: 505 scientists 118–127 publications: 522 scientists 128–137 publications: 469 scientists 138–147 publications: 456 scientists 148–157 publications: 459 scientists 158–167 publications: 397 scientists 168–177 publications: 383 scientists 178–187 publications: 350 scientists 188–197 publications: 302 scientists 198–207 publications: 306 scientists 208–217 publications: 262 scientists 218–227 publications: 242 scientists 228–237 publications: 220 scientists 238–247 publications: 203 scientists 248–257 publications: 174 scientists 258–267 publications: 176 scientists 268–277 publications: 175 scientists 278–287 publications: 125 scientists 288–297 publications: 116 scientists 298–307 publications: 127 scientists 308–317 publications: 128 scientists 318–327 publications: 99 scientists 328–337 publications: 89 scientists 338–347 publications: 78 scientists 348–357 publications: 96 scientists 358–367 publications: 66 scientists 368–377 publications: 59 scientists 378–387 publications: 65 scientists 388–397 publications: 54 scientists 398–407 publications: 48 scientists 408–417 publications: 49 scientists 418–427 publications: 34 scientists 428–437 publications: 31 scientists 438–447 publications: 30 scientists 448–457 publications: 31 scientists 458–467 publications: 36 scientists 468–477 publications: 40 scientists 478–487 publications: 35 scientists 488–497 publications: 30 scientists 498–507 publications: 23 scientists 508–517 publications: 26 scientists 518–527 publications: 20 scientists 528–537 publications: 23 scientists 538–547 publications: 20 scientists 548–557 publications: 20 scientists 558–567 publications: 17 scientists 568–577 publications: 14 scientists 578–587 publications: 20 scientists 588–597 publications: 20 scientists 598–607 publications: 19 scientists 608–617 publications: 18 scientists 618–627 publications: 17 scientists 628–637 publications: 11 scientists 638–647 publications: 11 scientists 648–657 publications: 11 scientists 658–667 publications: 8 scientists 668–677 publications: 7 scientists 678–687 publications: 11 scientists 688–697 publications: 10 scientists 698–707 publications: 4 scientists 708–717 publications: 6 scientists 718–727 publications: 5 scientists 728–737 publications: 5 scientists 738–747 publications: 9 scientists 748–757 publications: 9 scientists 758–767 publications: 3 scientists 768–777 publications: 7 scientists 778–787 publications: 7 scientists 788–797 publications: 6 scientists 798–807 publications: 2 scientists 808–817 publications: 2 scientists 818–827 publications: 7 scientists 828–837 publications: 0 scientists 838–847 publications: 9 scientists 848–857 publications: 3 scientists 858–867 publications: 1 scientists 868–877 publications: 3 scientists 878–886 publications: 6 scientists 887+ publications: 100 scientists
38 publications 887+

This scientist: 301 publications — 82nd percentile

82% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 887 publications or more.

Russell T. Shinohara D-index placement in Neuroscience in 2026

The chart shows the D-index (discipline H-index) distribution of Neuroscience scientists ranked by Research.com in 2026. The highlighted bar marks where Russell T. Shinohara sits on this spectrum.

30–31 D-Index: 42 scientists 32–33 D-Index: 172 scientists 34–35 D-Index: 296 scientists 36–37 D-Index: 435 scientists 38–39 D-Index: 459 scientists 40–41 D-Index: 456 scientists 42–43 D-Index: 467 scientists 44–45 D-Index: 478 scientists 46–47 D-Index: 512 scientists 48–49 D-Index: 435 scientists 50–51 D-Index: 425 scientists 52–53 D-Index: 418 scientists 54–55 D-Index: 392 scientists 56–57 D-Index: 357 scientists 58–59 D-Index: 334 scientists 60–61 D-Index: 328 scientists 62–63 D-Index: 260 scientists 64–65 D-Index: 278 scientists 66–67 D-Index: 239 scientists 68–69 D-Index: 250 scientists 70–71 D-Index: 210 scientists 72–73 D-Index: 200 scientists 74–75 D-Index: 189 scientists 76–77 D-Index: 170 scientists 78–79 D-Index: 146 scientists 80–81 D-Index: 113 scientists 82–83 D-Index: 126 scientists 84–85 D-Index: 100 scientists 86–87 D-Index: 84 scientists 88–89 D-Index: 99 scientists 90–91 D-Index: 84 scientists 92–93 D-Index: 85 scientists 94–95 D-Index: 72 scientists 96–97 D-Index: 76 scientists 98–99 D-Index: 45 scientists 100–101 D-Index: 49 scientists 102–103 D-Index: 43 scientists 104–105 D-Index: 32 scientists 106–107 D-Index: 45 scientists 108–109 D-Index: 50 scientists 110–111 D-Index: 32 scientists 112–113 D-Index: 39 scientists 114–115 D-Index: 32 scientists 116–117 D-Index: 29 scientists 118–119 D-Index: 27 scientists 120–121 D-Index: 19 scientists 122–123 D-Index: 23 scientists 124–125 D-Index: 27 scientists 126–127 D-Index: 16 scientists 128–129 D-Index: 24 scientists 130–131 D-Index: 13 scientists 132–133 D-Index: 21 scientists 134–135 D-Index: 17 scientists 136–137 D-Index: 14 scientists 138–139 D-Index: 15 scientists 140–141 D-Index: 10 scientists 142–143 D-Index: 10 scientists 144–145 D-Index: 13 scientists 146–147 D-Index: 9 scientists 148–149 D-Index: 8 scientists 150–151 D-Index: 6 scientists 152–153 D-Index: 6 scientists 154–155 D-Index: 7 scientists 156–157 D-Index: 7 scientists 158–159 D-Index: 10 scientists 160–161 D-Index: 4 scientists 162 D-Index: 8 scientists 163+ D-Index: 100 scientists
30 D-Index 163+

This scientist: 73 D-Index — 78th percentile

78% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 163 D-Index or more.

Overview

Russell T. Shinohara is affiliated with the University of Pennsylvania in the United States. Their research spans multiple fields, with a significant focus on medicine and neuroscience. They have contributed notably to subfields such as radiology, nuclear medicine and imaging, cognitive neuroscience, molecular biology, experimental and cognitive psychology, and pathology and forensic medicine.

Their research topics include:

  • Functional Brain Connectivity Studies
  • Advanced Neuroimaging Techniques and Applications
  • Advanced MRI Techniques and Applications
  • Multiple Sclerosis Research Studies
  • Radiomics and Machine Learning in Medical Imaging
  • Mental Health Research Topics
  • Neural dynamics and brain function

Shinohara's work has appeared in several frequent publication venues, including:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Biological Psychiatry
  • Human Brain Mapping
  • NeuroImage
  • Scientific Reports

Their recent papers demonstrate a range of topics and publication years:

  • SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network, 2021, Nature Methods
  • Image segmentations produced by BAMF under the AIMI Annotations initiative, 2024, arXiv (Cornell University)
  • Individual Variation in Functional Topography of Association Networks in Youth, 2020, Neuron
  • Longitudinal ComBat: A method for harmonizing longitudinal multi-scanner imaging data, 2020, NeuroImage
  • Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning, 2020, Brain

Shinohara frequently collaborates with other researchers, including:

  • Theodore D. Satterthwaite
  • Ruben C. Gur
  • Raquel E. Gur
  • Christos Davatzikos
  • Aaron Alexander-Bloch

Best Publications

  • Brain charts for the human lifespan

    Unknown

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • Harmonization of cortical thickness measurements across scanners and sites.

    Jean-Philippe Fortin;Nicholas C. Cullen;Yvette I. Sheline;Warren D. Taylor

  • Harmonization of multi-site diffusion tensor imaging data.

    Jean-Philippe Fortin;Drew Parker;Birkan Tunç;Takanori Watanabe

  • 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

  • The extent and drivers of gender imbalance in neuroscience reference lists.

    Jordan D. Dworkin;Kristin A. Linn;Erin G. Teich;Perry Zurn

  • On testing for spatial correspondence between maps of human brain structure and function.

    Aaron F. Alexander-Bloch;Haochang Shou;Siyuan Liu;Theodore D. Satterthwaite

  • Development of structure–function coupling in human brain networks during youth

    Graham L. Baum;Graham L. Baum;Zaixu Cui;Zaixu Cui;David R. Roalf;David R. Roalf;Rastko Ciric

  • Linked dimensions of psychopathology and connectivity in functional brain networks.

    Cedric Huchuan Xia;Zongming Ma;Rastko Ciric;Shi Gu;Shi Gu

  • Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan.

    Raymond Pomponio;Guray Erus;Mohamad Habes;Jimit Doshi

  • Quantitative assessment of structural image quality.

    Adon F.G. Rosen;David R. Roalf;Kosha Ruparel;Jason Blake

  • Statistical harmonization corrects site effects in functional connectivity measurements from multi-site fMRI data.

    Meichen Yu;Kristin A. Linn;Philip A. Cook;Mary L. Phillips

  • Statistical normalization techniques for magnetic resonance imaging

    Russell T. Shinohara;Elizabeth M. Sweeney;Jeff Goldsmith;Navid Shiee

  • Modular Segregation of Structural Brain Networks Supports the Development of Executive Function in Youth

    Graham L. Baum;Rastko Ciric;David R. Roalf;Richard F. Betzel

  • The central vein sign and its clinical evaluation for the diagnosis of multiple sclerosis: a consensus statement from the North American Imaging in Multiple Sclerosis Cooperative.

    Pascal Sati;Jiwon Oh;R. Todd Constable;Nikos Evangelou

  • Individual Variation in Functional Topography of Association Networks in Youth

    Zaixu Cui;Hongming Li;Cedric H. Xia;Bart Larsen

  • Large-scale Radiomic Profiling of Recurrent Glioblastoma Identifies an Imaging Predictor for Stratifying Anti-Angiogenic Treatment Response

    Philipp Kickingereder;Michael Götz;John Muschelli;Antje Wick

  • Longitudinal ComBat: A method for harmonizing longitudinal multi-scanner imaging data.

    Joanne C. Beer;Nicholas J. Tustison;Philip A. Cook;Christos Davatzikos

  • Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning.

    Ganesh B Chand;Dominic B Dwyer;Guray Erus;Aristeidis Sotiras;Aristeidis Sotiras

  • Impact of puberty on the evolution of cerebral perfusion during adolescence

    Theodore D. Satterthwaite;Russell T. Shinohara;Daniel H. Wolf;Ryan D. Hopson

  • Normative brain size variation and brain shape diversity in humans

    P. K. Reardon;Jakob Seidlitz;Simon Vandekar;Siyuan Liu

  • Common and Dissociable Mechanisms of Executive System Dysfunction Across Psychiatric Disorders in Youth.

    Sheila Shanmugan;Daniel H. Wolf;Monica E. Calkins;Tyler M. Moore

  • Neurological injury in adults treated with extracorporeal membrane oxygenation

    Farrah J. Mateen;Rajanandini Muralidharan;Russell T. Shinohara;Joseph E. Parisi

Frequent Co-Authors

Theodore D. Satterthwaite
Theodore D. Satterthwaite University of Pennsylvania
Raquel E. Gur
Raquel E. Gur University of Pennsylvania
Christos Davatzikos
Christos Davatzikos University of Pennsylvania
Ruben C. Gur
Ruben C. Gur University of Pennsylvania
David R. Roalf
David R. Roalf University of Pennsylvania
Kosha Ruparel
Kosha Ruparel University of Pennsylvania
Danielle S. Bassett
Danielle S. Bassett University of Pennsylvania
Tyler M. Moore
Tyler M. Moore University of Pennsylvania
Daniel H. Wolf
Daniel H. Wolf University of Pennsylvania
Daniel S. Reich
Daniel S. Reich National Institutes of Health

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