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Nathaniel D. Daw

D-Index & Metrics

Neuroscience

D-Index
95
Citations
40382
World Ranking
893
National Ranking
479

Nathaniel D. Daw 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 Nathaniel D. Daw 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: 224 publications — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Nathaniel D. Daw 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 Nathaniel D. Daw 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: 95 D-Index — 91st percentile

91% 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

  • 2003 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

Nathaniel D. Daw is affiliated with Princeton University in the United States. Their research spans several interconnected fields, primarily focusing on neuroscience and psychology. The main fields of study include Neuroscience and Psychology, with prominent subfields such as Cognitive Neuroscience, Artificial Intelligence, Experimental and Cognitive Psychology, Cellular and Molecular Neuroscience, and Clinical Psychology.

The scientist's research interests cover a range of topics, including:

  • Neural dynamics and brain function
  • Memory and Neural Mechanisms
  • Neural and Behavioral Psychology Studies
  • Mental Health Research Topics
  • Neuroscience and Neuropharmacology Research
  • Eating Disorders and Behaviors
  • Functional Brain Connectivity Studies

Frequent co-authors in their publications include Jonathan D. Cohen (12 collaborations), Marcelo G. Mattar (11), Ari E. Kahn (9), Daphna Shohamy (9), and Thomas L. Griffiths (9). This diversity of collaborators reflects the interdisciplinary approach adopted in their research efforts.

Daw has contributed substantially to several publication venues, with repeated appearances in:

  • bioRxiv (Cold Spring Harbor Laboratory) - 32 publications
  • Nature Communications - 8 publications
  • arXiv (Cornell University) - 7 publications
  • PLoS Computational Biology - 5 publications
  • Biological Psychiatry - 4 publications

The following recent papers highlight their contributions, showing a range of topics and venues:

  • "Experience replay is associated with efficient nonlocal learning," 2021, Science
  • "A model for learning based on the joint estimation of stochasticity and volatility," 2021, Nature Communications
  • "The temporal dynamics of opportunity costs: A normative account of cognitive fatigue and boredom," 2021, Psychological Review
  • "Formalizing planning and information search in naturalistic decision-making," 2021, Nature Neuroscience
  • "A simple model for learning in volatile environments," 2020, PLoS Computational Biology

In recognition of their contributions to the scientific community, Nathaniel D. Daw was named a Fellow of the American Association for the Advancement of Science (AAAS) in 2003.

Best Publications

  • Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control

    Nathaniel D Daw;Yael Niv;Yael Niv;Peter Dayan

  • Cortical substrates for exploratory decisions in humans

    Nathaniel D. Daw;John P. O'Doherty;Peter Dayan;Ben Seymour

  • Model-based influences on humans' choices and striatal prediction errors.

    Nathaniel D. Daw;Samuel J. Gershman;Ben Seymour;Peter Dayan

  • The importance of mixed selectivity in complex cognitive tasks

    Mattia Rigotti;Omri Barak;Omri Barak;Melissa R. Warden;Melissa R. Warden;Xiao Jing Wang;Xiao Jing Wang

  • States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning

    Jan Gläscher;Nathaniel Douglass Daw;Peter Dayan;John P. O'Doherty;John P. O'Doherty

  • Tonic dopamine: opportunity costs and the control of response vigor.

    Yael Niv;Yael Niv;Nathaniel D. Daw;Daphna Joel;Peter Dayan

  • Opponent interactions between serotonin and dopamine

    Nathaniel D. Daw;Sham Kakade;Peter Dayan

  • Decision theory, reinforcement learning, and the brain

    Peter Dayan;Nathaniel D. Daw

  • Disorders of compulsivity: a common bias towards learning habits

    Valerie Voon;K Derbyshire;C Rück;MA Irvine

  • The computational neurobiology of learning and reward

    Nathaniel Douglass Daw;Kenji Doya

  • Characterizing a psychiatric symptom dimension related to deficits in goal-directed control

    Claire M Gillan;Claire M Gillan;Michal Kosinski;Robert Whelan;Elizabeth A Phelps;Elizabeth A Phelps;Elizabeth A Phelps

  • Self-evaluation of decision-making: A general Bayesian framework for metacognitive computation.

    Stephen M. Fleming;Nathaniel D. Daw

  • Trial-by-trial data analysis using computational models

    Nathaniel D. Daw

  • Bayesian theories of conditioning in a changing world

    Aaron C. Courville;Nathaniel D. Daw;David S. Touretzky

  • Working-memory capacity protects model-based learning from stress

    A. Ross Otto;Candace M. Raio;Alice Chiang;Elizabeth A. Phelps;Elizabeth A. Phelps;Elizabeth A. Phelps

  • Specialized coding of sensory, motor and cognitive variables in VTA dopamine neurons

    Ben Engelhard;Joel Finkelstein;Julia Cox;Weston Fleming

  • Differential encoding of losses and gains in the human striatum

    Ben Seymour;Nathaniel Daw;Peter Dayan;Tania Singer

  • Reinforcement Learning and Episodic Memory in Humans and Animals: An Integrative Framework.

    Samuel J Gershman;Nathaniel D Daw

  • A computational substrate for incentive salience

    Samuel M. McClure;Nathaniel Douglass Daw;P. Read Montague

  • Serotonin and dopamine: unifying affective, activational, and decision functions.

    Roshan Cools;Kae Nakamura;Nathaniel D. Daw

Frequent Co-Authors

Peter Dayan
Peter Dayan Max Planck Institute for Biological Cybernetics
Elizabeth A. Phelps
Elizabeth A. Phelps Harvard University
Daphna Shohamy
Daphna Shohamy Columbia University
Yael Niv
Yael Niv Princeton University
Jonathan D. Cohen
Jonathan D. Cohen Princeton University
John P. O'Doherty
John P. O'Doherty California Institute of Technology
A. Ross Otto
A. Ross Otto McGill University
Claire M. Gillan
Claire M. Gillan Trinity College Dublin
Ben Seymour
Ben Seymour University of Oxford
Samuel J. Gershman
Samuel J. Gershman Harvard University

External Links

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Best Scientists Citing Nathaniel D. Daw

Raymond J. Dolan

Raymond J. Dolan

University College London

Publications: 224

Peter Dayan

Peter Dayan

Max Planck Institute for Biological Cybernetics

Publications: 172

Samuel J. Gershman

Samuel J. Gershman

Harvard University

Publications: 123

Trevor W. Robbins

Trevor W. Robbins

University of Cambridge

Publications: 107

Michael J. Frank

Michael J. Frank

Brown University

Publications: 106

Karl J. Friston

Karl J. Friston

University College London

Publications: 102

Geoffrey Schoenbaum

Geoffrey Schoenbaum

National Institutes of Health

Publications: 101

John P. O'Doherty

John P. O'Doherty

California Institute of Technology

Publications: 96

Quentin J. M. Huys

Quentin J. M. Huys

University College London

Publications: 93

Timothy E.J. Behrens

Timothy E.J. Behrens

University of Oxford

Publications: 91

Roshan Cools

Roshan Cools

Radboud University

Publications: 85

Florian Schlagenhauf

Florian Schlagenhauf

Charité - University Medicine Berlin

Publications: 84

Yael Niv

Yael Niv

Princeton University

Publications: 74

Andreas Heinz

Andreas Heinz

Charité - University Medicine Berlin

Publications: 73

Klaas E. Stephan

Klaas E. Stephan

University of Zurich

Publications: 72

Lorenz Deserno

Lorenz Deserno

University of Wurzburg

Publications: 67

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