World's Best Scientists 2026 revealed!
James L. McClelland

James L. McClelland

D-Index & Metrics

Psychology

D-Index
113
Citations
123269
World Ranking
347
National Ranking
219

James L. McClelland publication distribution in Psychology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Psychology in 2026. The highlighted bar marks where James L. McClelland sits on this spectrum.

31–40 publications: 6 scientists 41–50 publications: 52 scientists 51–60 publications: 138 scientists 61–70 publications: 299 scientists 71–80 publications: 461 scientists 81–90 publications: 605 scientists 91–100 publications: 713 scientists 101–110 publications: 736 scientists 111–120 publications: 686 scientists 121–130 publications: 670 scientists 131–140 publications: 644 scientists 141–150 publications: 597 scientists 151–160 publications: 576 scientists 161–170 publications: 477 scientists 171–180 publications: 450 scientists 181–190 publications: 397 scientists 191–200 publications: 343 scientists 201–210 publications: 328 scientists 211–220 publications: 313 scientists 221–230 publications: 283 scientists 231–240 publications: 226 scientists 241–250 publications: 196 scientists 251–260 publications: 201 scientists 261–270 publications: 171 scientists 271–280 publications: 151 scientists 281–290 publications: 139 scientists 291–300 publications: 113 scientists 301–310 publications: 102 scientists 311–320 publications: 100 scientists 321–330 publications: 76 scientists 331–340 publications: 92 scientists 341–350 publications: 85 scientists 351–360 publications: 69 scientists 361–370 publications: 71 scientists 371–380 publications: 63 scientists 381–390 publications: 58 scientists 391–400 publications: 57 scientists 401–410 publications: 43 scientists 411–420 publications: 33 scientists 421–430 publications: 50 scientists 431–440 publications: 41 scientists 441–450 publications: 32 scientists 451–460 publications: 27 scientists 461–470 publications: 28 scientists 471–480 publications: 25 scientists 481–490 publications: 28 scientists 491–500 publications: 20 scientists 501–510 publications: 23 scientists 511–520 publications: 26 scientists 521–530 publications: 17 scientists 531–540 publications: 21 scientists 541–550 publications: 14 scientists 551–560 publications: 16 scientists 561–570 publications: 10 scientists 571–580 publications: 22 scientists 581–590 publications: 9 scientists 591–600 publications: 14 scientists 601–610 publications: 9 scientists 611–620 publications: 11 scientists 621–630 publications: 4 scientists 631–640 publications: 7 scientists 641–650 publications: 5 scientists 651–660 publications: 10 scientists 661–670 publications: 8 scientists 671–680 publications: 8 scientists 681–690 publications: 4 scientists 691–700 publications: 3 scientists 701–704 publications: 4 scientists 705+ publications: 100 scientists
31 publications 705+

This scientist: 330 publications — 90th percentile

90% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 705 publications or more.

James L. McClelland D-index placement in Psychology in 2026

The chart shows the D-index (discipline H-index) distribution of Psychology scientists ranked by Research.com in 2026. The highlighted bar marks where James L. McClelland sits on this spectrum.

30–31 D-Index: 398 scientists 32–33 D-Index: 702 scientists 34–35 D-Index: 671 scientists 36–37 D-Index: 659 scientists 38–39 D-Index: 641 scientists 40–41 D-Index: 671 scientists 42–43 D-Index: 617 scientists 44–45 D-Index: 558 scientists 46–47 D-Index: 495 scientists 48–49 D-Index: 487 scientists 50–51 D-Index: 445 scientists 52–53 D-Index: 390 scientists 54–55 D-Index: 408 scientists 56–57 D-Index: 345 scientists 58–59 D-Index: 325 scientists 60–61 D-Index: 321 scientists 62–63 D-Index: 248 scientists 64–65 D-Index: 290 scientists 66–67 D-Index: 218 scientists 68–69 D-Index: 219 scientists 70–71 D-Index: 215 scientists 72–73 D-Index: 183 scientists 74–75 D-Index: 169 scientists 76–77 D-Index: 132 scientists 78–79 D-Index: 137 scientists 80–81 D-Index: 120 scientists 82–83 D-Index: 112 scientists 84–85 D-Index: 86 scientists 86–87 D-Index: 101 scientists 88–89 D-Index: 83 scientists 90–91 D-Index: 77 scientists 92–93 D-Index: 70 scientists 94–95 D-Index: 78 scientists 96–97 D-Index: 58 scientists 98–99 D-Index: 53 scientists 100–101 D-Index: 57 scientists 102–103 D-Index: 48 scientists 104–105 D-Index: 53 scientists 106–107 D-Index: 46 scientists 108–109 D-Index: 24 scientists 110–111 D-Index: 35 scientists 112–113 D-Index: 27 scientists 114–115 D-Index: 32 scientists 116–117 D-Index: 31 scientists 118–119 D-Index: 22 scientists 120–121 D-Index: 16 scientists 122–123 D-Index: 24 scientists 124–125 D-Index: 18 scientists 126–127 D-Index: 11 scientists 128–129 D-Index: 19 scientists 130–131 D-Index: 10 scientists 132–133 D-Index: 16 scientists 134–135 D-Index: 10 scientists 136–137 D-Index: 12 scientists 138–139 D-Index: 8 scientists 140–141 D-Index: 5 scientists 142–143 D-Index: 12 scientists 144+ D-Index: 98 scientists
30 D-Index 144+

This scientist: 113 D-Index — 97th percentile

97% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 144 D-Index or more.

Research.com Recognitions

  • 2005 - Mind & Brain Prize, University and Polytechnic of Turin
  • 2002 - Grawemeyer Award in Psychology, University of Louisville
  • 2001 - Member of the National Academy of Sciences
  • 1996 - APA Award for Distinguished Scientific Contributions to Psychology, American Psychological Association
  • 1993 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

James L. McClelland is affiliated with Stanford University in the United States. Their research spans primarily within the field of Computer Science, focusing on areas such as Artificial Intelligence, Cognitive Neuroscience, and Developmental and Educational Psychology, among others. The subfields of study in their work include Computer Vision and Pattern Recognition as well as Statistics and Probability.

The main topics explored in McClelland's research include:

  • Topic Modeling
  • Domain Adaptation and Few-Shot Learning
  • Child and Animal Learning Development
  • Natural Language Processing Techniques
  • Cognitive and developmental aspects of mathematical skills
  • Explainable Artificial Intelligence (XAI)
  • Multimodal Machine Learning Applications

McClelland has contributed to academic literature with notable recent publications such as:

  • Integration of new information in memory: new insights from a complementary learning systems perspective, 2020, Philosophical Transactions of the Royal Society B Biological Sciences
  • Placing language in an integrated understanding system: Next steps toward human-level performance in neural language models, 2020, Proceedings of the National Academy of Sciences

Their frequent publication venues reflect these interests and include:

  • arXiv (Cornell University)
  • Proceedings of the National Academy of Sciences
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Philosophical Transactions of the Royal Society B Biological Sciences
  • PNAS Nexus

Throughout their career, McClelland has collaborated regularly with several researchers, notably:

  • Andrew K. Lampinen
  • Felix Hill
  • Ishita Dasgupta
  • Stephanie C. Y. Chan
  • Bruce L. McNaughton

McClelland's awards include:

  • Mind & Brain Prize, University and Polytechnic of Turin, 2005
  • Grawemeyer Award in Psychology, University of Louisville, 2002
  • Member of the National Academy of Sciences, 2001
  • APA Award for Distinguished Scientific Contributions to Psychology, American Psychological Association, 1996
  • Fellow of the American Association for the Advancement of Science (AAAS), 1993

Best Publications

  • Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations

    David E. Rumelhart;James L. McClelland;Au

  • Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations

    David E. Rumelhart;James L. McClelland

  • An interactive activation model of context effects in letter perception: I. An account of basic findings.

    James L. McClelland;David E. Rumelhart

  • Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory.

    James L. McClelland;Bruce L. McNaughton;Randall C. O'Reilly

  • A Distributed, Developmental Model of Word Recognition and Naming.

    Mark S. Seidenberg;James L. McClelland

  • The TRACE model of speech perception.

    James L McClelland;Jeffrey L Elman

  • Understanding normal and impaired word reading: computational principles in quasi-regular domains.

    David C. Plaut;James L. McClelland;Mark S. Seidenberg;Karalyn Patterson

  • On learning the past tenses of English verbs

    David E. Rumelhart;James L. McClelland

  • On the control of automatic processes: A parallel distributed processing account of the stroop effect

    Jonathan D. Cohen;Kevin Dunbar;James L. McClelland

  • The time course of perceptual choice: The leaky, competing accumulator model.

    Marius Usher;James L. McClelland

  • On the time relations of mental processes: An examination of systems of processes in cascade.

    James L. McClelland

  • An Interactive Activation Model of Context Effects in Letter Perception: Part 2. The Contextual Enhancement Effect and Some Tests and Extensions of the Model

    David E. Rumelhart;James L. McClelland

  • Schemata and sequential thought processes in PDP models

    D. E. Rumelhart;P. Smolensky;J. L. McClelland;G. E. Hinton

  • Distributed memory and the representation of general and specific information.

    James L. McClelland;David E. Rumelhart

  • Exact solutions to the nonlinear dynamics of learning in deep linear neural networks

    Andrew M. Saxe;James L. McClelland;Surya Ganguli

  • Semantic Cognition: A Parallel Distributed Processing Approach

    Timothy T. Rogers;James L. McClelland

  • Hippocampal conjunctive encoding, storage, and recall: avoiding a trade-off.

    Randall C. O'Reilly;James L. McClelland

  • Parallel distributed processing: explorations in the microstructure of cognition, vol. 2: psychological and biological models

    David E. Rumelhart;James L. McClelland

  • A computational model of semantic memory impairment: modality specificity and emergent category specificity.

    Martha J. Farah;James L. McClelland

  • Learning the structure of event sequences.

    Axel Cleeremans;James L. McClelland

  • Parallel Distributed Processing: Explorations in the Microstructures of Cognition

    Geoffrey Sampson;David E. Rumelhart;James L. McClelland

  • An interactive activation model of context effects in letter perception: part 1.: an account of basic findings

    James L. McClelland;David E. Rumelhart

  • Phenomenology of perception.

    James L. Mcclelland

Frequent Co-Authors

David E. Rumelhart
David E. Rumelhart Stanford University
Karalyn Patterson
Karalyn Patterson MRC Cognition and Brain Sciences Unit
Lori L. Holt
Lori L. Holt Carnegie Mellon University
David C. Plaut
David C. Plaut Carnegie Mellon University
Timothy T. Rogers
Timothy T. Rogers University of Wisconsin–Madison
Matthew A. Lambon Ralph
Matthew A. Lambon Ralph University of Cambridge
Daniel Mirman
Daniel Mirman University of Edinburgh
Marius Usher
Marius Usher Tel Aviv University
Mark S. Seidenberg
Mark S. Seidenberg University of Wisconsin–Madison
Axel Cleeremans
Axel Cleeremans Université Libre de Bruxelles

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