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Nicholas B. Turk-Browne

Nicholas B. Turk-Browne

D-Index & Metrics

Neuroscience

D-Index
59
Citations
18841
World Ranking
3937
National Ranking
1785

Nicholas B. Turk-Browne 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 Nicholas B. Turk-Browne 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: 257 publications — 76th percentile

76% of scientists in this discipline score the same or lower.

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

Nicholas B. Turk-Browne 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 Nicholas B. Turk-Browne 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: 59 D-Index — 59th percentile

59% of scientists in this discipline score the same or lower.

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

Overview

Nicholas B. Turk-Browne is a researcher affiliated with Yale University in the United States, specializing primarily in the field of neuroscience. Their work encompasses a range of subfields including cognitive neuroscience, cellular and molecular neuroscience, developmental and educational psychology, computer vision and pattern recognition, and radiology, nuclear medicine, and imaging.

The main research topics Nicholas focuses on involve neural dynamics and brain function, memory and neural mechanisms, functional brain connectivity studies, visual perception and processing mechanisms, neuroscience and neuropharmacology research, face recognition and perception, and neural and behavioral psychology studies.

Their recent publications demonstrate a focus on both cognitive and neural mechanisms underlying learning and brain function. These include:

  • Learning hierarchical sequence representations across human cortex and hippocampus (2021, Science Advances)
  • The prevalence and importance of statistical learning in human cognition and behavior (2020, Current Opinion in Behavioral Sciences)
  • Statistical prediction of the future impairs episodic encoding of the present (2020, Proceedings of the National Academy of Sciences)
  • Re-imagining fMRI for awake behaving infants (2020, Nature Communications)
  • Evidence of hippocampal learning in human infants (2021, Current Biology)

Frequent collaborators in their work include Cameron T. Ellis, Tristan S. Yates, Kenneth A. Norman, Brynn E. Sherman, and Kathryn N. Graves, indicating strong collaborative research across multiple studies.

Nicholas has published frequently in venues such as bioRxiv (Cold Spring Harbor Laboratory), Journal of Vision, Journal of Cognitive Neuroscience, Proceedings of the National Academy of Sciences, and NeuroImage. These outlets highlight their engagement with both preprint and peer-reviewed formats relevant to neuroscience and cognitive science fields.

Best Publications

  • Brain charts for the human lifespan

    Unknown

  • A taxonomy of external and internal attention.

    Marvin M. Chun;Julie D. Golomb;Nicholas B. Turk-Browne

  • The Automaticity of Visual Statistical Learning

    Nicholas B. Turk-Browne;Justin A. Jungé;Brian J. Scholl

  • Interactions between attention and memory.

    Marvin M Chun;Nicholas B Turk-Browne

  • Best practices in data analysis and sharing in neuroimaging using MRI.

    Thomas E Nichols;Samir Das;Samir Das;Simon B Eickhoff;Simon B Eickhoff;Alan C Evans;Alan C Evans

  • Neural evidence of statistical learning: Efficient detection of visual regularities without awareness

    Nicholas B. Turk-Browne;Brian J. Scholl;Marvin M. Chun;Marcia K. Johnson

  • Neural representations of events arise from temporal community structure

    Anna C Schapiro;Timothy T Rogers;Natalia I Cordova;Nicholas B Turk-Browne

  • Shaping of Object Representations in the Human Medial Temporal Lobe Based on Temporal Regularities

    Anna C. Schapiro;Lauren V. Kustner;Nicholas B. Turk-Browne

  • Complementary learning systems within the hippocampus: a neural network modelling approach to reconciling episodic memory with statistical learning

    Anna C. Schapiro;Nicholas B. Turk-Browne;Matthew M. Botvinick;Kenneth A. Norman

  • Implicit Perceptual Anticipation Triggered by Statistical Learning

    Nicholas B. Turk-Browne;Brian J. Scholl;Marcia K. Johnson;Marvin M. Chun

  • Closed-loop training of attention with real-time brain imaging

    Megan T. DeBettencourt;Jonathan D. Cohen;Ray F. Lee;Kenneth Andrew Norman

  • Attention Is Spontaneously Biased Toward Regularities

    Jiaying Zhao;Naseem Al-Aidroos;Nicholas B. Turk-Browne

  • Statistical learning of temporal community structure in the hippocampus

    Anna C. Schapiro;Nicholas B. Turk-Browne;Kenneth A. Norman;Matthew M. Botvinick

  • The necessity of the medial temporal lobe for statistical learning

    Anna C. Schapiro;Emma Gregory;Barbara Landau;Michael McCloskey

  • Linking Implicit and Explicit Memory: Common Encoding Factors and Shared Representations

    Nicholas B. Turk-Browne;Do Joon Yi;Marvin M. Chun

  • Optimizing real time fMRI neurofeedback for therapeutic discovery and development

    L.E. Stoeckel;L.E. Stoeckel;K.A. Garrison;S.S. Ghosh;P. Wighton

  • Linking pattern completion in the hippocampus to predictive coding in visual cortex

    Nicholas C Hindy;Felicia Y Ng;Nicholas B Turk-Browne

  • Memory-guided attention: control from multiple memory systems

    J. Benjamin Hutchinson;Nicholas B. Turk-Browne

  • Computational approaches to fMRI analysis.

    Jonathan D Cohen;Nathaniel Daw;Barbara Engelhardt;Uri Hasson

  • Neural predictors of moment-to-moment fluctuations in cognitive flexibility

    Andrew B. Leber;Nicholas B. Turk-Browne;Marvin M. Chun

  • Mechanisms for widespread hippocampal involvement in cognition.

    Daphna Shohamy;Nicholas B. Turk-Browne

Frequent Co-Authors

Kenneth A. Norman
Kenneth A. Norman Princeton University
Marvin M. Chun
Marvin M. Chun Yale University
Jonathan D. Cohen
Jonathan D. Cohen Princeton University
Brian J. Scholl
Brian J. Scholl Yale University
Lucia Melloni
Lucia Melloni Max Planck Society
Kai Li
Kai Li Princeton University
Alexander Todorov
Alexander Todorov University of Chicago
Sabine Kastner
Sabine Kastner Princeton University
Judson A. Brewer
Judson A. Brewer Brown University
Barbara Landau
Barbara Landau Johns Hopkins University

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