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Best Scientists

D-Index
177
Citations
166248
World Ranking
663
National Ranking
416

Neuroscience

D-Index
179
Citations
163455
World Ranking
55
National Ranking
35

Computer Science

D-Index
136
Citations
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Terrence J. Sejnowski 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 Terrence J. Sejnowski 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: 840 publications — 99th percentile

99% of scientists in this discipline score the same or lower.

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

Terrence J. Sejnowski 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 Terrence J. Sejnowski 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: 179 D-Index — 99th percentile

99% of scientists in this discipline score the same or lower.

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

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 Best Scientists Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2025 - Research.com Neuroscience in United States Leader Award
  • 2022 - Research.com Computer Science in United States Leader Award
  • 2017 - Fellow, National Academy of Inventors
  • 2014 - Fellow of American Physical Society (APS) Citation For pioneering work in computational biological physics towards understanding the structure and function of correlations in large scale biological systems, including representation of memories in the brain, protein sequences, and statistical learning algorithms
  • 2013 - IEEE Frank Rosenblatt Award
  • 2013 - Fellow of the American Academy of Arts and Sciences
  • 2011 - Member of the National Academy of Engineering For contributions to artificial and real neural network algorithms and applying signal processing models to neuroscience.
  • 2010 - Member of the National Academy of Sciences
  • 2008 - Member of the National Academy of Medicine (NAM)
  • 2006 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2002 - Neural Networks Pioneer Award, IEEE Computational Intelligence Society
  • 2000 - IEEE Fellow For fundamental advances in the theory and practice of neural networks and for contributions to computational neuroscience.

Overview

Terrence J. Sejnowski is affiliated with the Salk Institute for Biological Studies in the United States. Their research primarily spans the field of neuroscience, with a focus on subfields such as cognitive neuroscience, cellular and molecular neuroscience, molecular biology, electrical and electronic engineering, and artificial intelligence.

The scientist has contributed extensively to topics including neural dynamics and brain function, advanced memory and neural computing, neuroscience and neuropharmacology research, EEG and brain-computer interfaces, functional brain connectivity studies, photoreceptor and optogenetics research, and neural networks and applications.

Terrence J. Sejnowski has a number of frequently collaborating co-authors, including Thomas M. Bartol, Claudia Lainscsek, Lyle Muller, Hava T. Siegelmann, and Padmini Rangamani.

Their publication record includes contributions to several frequent venues, among them:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • Proceedings of the National Academy of Sciences
  • UNC Libraries
  • Neural Computation

Among recent papers authored or co-authored by Sejnowski are:

  • The unreasonable effectiveness of deep learning in artificial intelligence (2020), Proceedings of the National Academy of Sciences
  • Spontaneous travelling cortical waves gate perception in behaving primates (2020), Nature
  • Catalyzing next-generation Artificial Intelligence through NeuroAI (2023), Nature Communications
  • Biological underpinnings for lifelong learning machines (2022), Nature Machine Intelligence
  • The Mind of a Mouse (2020), Cell

Over the course of their career, Terrence J. Sejnowski has received several awards and honors. These include being named Fellow of the National Academy of Inventors in 2017 and Fellow of the American Physical Society in 2014, cited for pioneering work in computational biological physics. They were also the recipient of the IEEE Frank Rosenblatt Award in 2013 and have been recognized as a Fellow of the American Academy of Arts and Sciences the same year.

Sejnowski was elected to the National Academy of Engineering in 2011 for contributions to artificial and real neural network algorithms and for applying signal processing models to neuroscience. Additionally, they are a member of the National Academy of Sciences (2010) and the National Academy of Medicine (2008). Multiple fellowships with scientific associations, including the American Association for the Advancement of Science in 2006 and IEEE Fellow status in 2000, further mark their career.

Best Publications

  • An information-maximization approach to blind separation and blind deconvolution

    Anthony J. Bell;Terrence J. Sejnowski

  • A learning algorithm for Boltzmann machines

    David H. Ackley;Geoffrey E. Hinton;Terrence J. Sejnowski

  • Thalamocortical oscillations in the sleeping and aroused brain

    Mircea Steriade;David A. McCormick;Terrence J. Sejnowski

  • Running enhances neurogenesis, learning, and long-term potentiation in mice

    H M van Praag;B R Christie;T J Sejnowski;F H Gage

  • Removing electroencephalographic artifacts by blind source separation.

    Tzyy-Ping Jung;Tzyy-Ping Jung;Scott Makeig;Colin Humphries;Te-Won Lee;Te-Won Lee

  • The Computational Brain

    Patricia Smith Churchland;Terrence J. Sejnowski

  • The "independent components" of natural scenes are edge filters.

    Anthony J. Bell;Terrence J. Sejnowski

  • Face recognition by independent component analysis

    M.S. Bartlett;J.R. Movellan;T.J. Sejnowski

  • Independent Component Analysis of Electroencephalographic Data

    Scott Makeig;Anthony J. Bell;Tzyy-Ping Jung;Terrence J. Sejnowski

  • Parallel Networks that Learn to Pronounce English Text

    T. J. Sejnowski

  • Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources

    Te-Won Lee;Mark Girolami;Terrence J. Sejnowski;Terrence J. Sejnowski

  • A framework for mesencephalic dopamine systems based on predictive Hebbian learning

    PR Montague;P Dayan;TJ Sejnowski

  • Analysis of fMRI data by blind separation into independent spatial components

    Martin J. Mckeown;Scott Makeig;Greg G. Brown;Tzyy-Ping Jung

  • Reliability of spike timing in neocortical neurons

    Zachary F. Mainen;Terrence J. Sejnowski;Terrence J. Sejnowski

  • Learning and relearning in Boltzmann machines

    G. E. Hinton;T. J. Sejnowski

  • Dynamic Brain Sources of Visual Evoked Responses

    S. Makeig;M. Westerfield;T.-P. Jung;S. Enghoff

  • Global Epigenomic Reconfiguration During Mammalian Brain Development

    Ryan Lister;Ryan Lister;Eran A. Mukamel;Joseph R. Nery;Mark Urich

  • Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis

    Arnaud Delorme;Terrence J. Sejnowski;Scott Makeig

  • Slow feature analysis: unsupervised learning of invariances

    Laurenz Wiskott;Terrence J. Sejnowski

  • Predicting the secondary structure of globular proteins using neural network models.

    Ning Qian;Terrence J. Sejnowski

Frequent Co-Authors

Maxim Bazhenov
Maxim Bazhenov University of California, San Diego
Te-Won Lee
Te-Won Lee Qualcomm (United States)
Tzyy-Ping Jung
Tzyy-Ping Jung University of California, San Diego
Scott Makeig
Scott Makeig University of California, San Diego
Jean-Marc Fellous
Jean-Marc Fellous University of Arizona
Paul H. E. Tiesinga
Paul H. E. Tiesinga Radboud University
Igor Timofeev
Igor Timofeev Université Laval
Alain Destexhe
Alain Destexhe Centre national de la recherche scientifique, CNRS
Mircea Steriade
Mircea Steriade Université Laval
Robert N. Weinreb
Robert N. Weinreb University of California, San Diego

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