World's Best Scientists 2026 revealed!

D-Index & Metrics

Neuroscience

D-Index
84
Citations
37290
World Ranking
1368
National Ranking
22

Wulfram Gerstner 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 Wulfram Gerstner 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: 360 publications — 88th percentile

88% of scientists in this discipline score the same or lower.

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

Wulfram Gerstner 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 Wulfram Gerstner 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: 84 D-Index — 86th percentile

86% of scientists in this discipline score the same or lower.

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

Overview

Wulfram Gerstner is affiliated with the École Polytechnique Fédérale de Lausanne in Switzerland. Their research primarily focuses on neuroscience, with a total of 89 publications in this field. Within neuroscience, they have a significant concentration in cognitive neuroscience, electrical and electronic engineering, artificial intelligence, cellular and molecular neuroscience, and statistical and nonlinear physics.

The main topics Gerstner's work covers include neural dynamics and brain function, advanced memory and neural computing, neural networks and applications, memory and neural mechanisms, neuroscience and neuropharmacology research, functional brain connectivity studies, and neuroscience and neural engineering.

Gerstner has contributed to several scientific journals and preprint servers, with frequent publications in:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • PLoS Computational Biology
  • Zenodo (CERN European Organization for Nuclear Research)
  • Neural Networks

Significant recent papers authored or co-authored by Gerstner include:

  • "Rapid suppression and sustained activation of distinct cortical regions for a delayed sensory-triggered motor response," 2021, Neuron
  • "A taxonomy of surprise definitions," 2022, Journal of Mathematical Psychology
  • "Novelty is not surprise: Human exploratory and adaptive behavior in sequential decision-making," 2021, PLoS Computational Biology
  • "When shared concept cells support associations: Theory of overlapping memory engrams," 2021, PLoS Computational Biology
  • "Curiosity-driven exploration: foundations in neuroscience and computational modeling," 2023, Trends in Neurosciences

They have collaborated frequently with several researchers, including:

  • Alireza Modirshanechi
  • Johanni Brea
  • Guillaume Bellec
  • Carl C.H. Petersen
  • Vahid Esmaeili

Best Publications

  • Spiking Neuron Models: Single Neurons, Populations, Plasticity

    Wulfram Gerstner;Werner M. Kistler

  • Adaptive Exponential Integrate-and-Fire Model as an Effective Description of Neuronal Activity

    Romain Brette;Wulfram Gerstner

  • A neuronal learning rule for sub-millisecond temporal coding

    Wulfram Gerstner;Wulfram Gerstner;Richard Kempter;J. Leo van Hemmen;Hermann Wagner;Hermann Wagner

  • Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition

    Wulfram Gerstner;Werner M. Kistler;Richard Naud;Liam Paninski

  • Noninvasive brain-actuated control of a mobile robot by human EEG

    Jd.R. Millan;F. Renkens;J. Mourino;W. Gerstner

  • Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks

    Tim Vogels;Henning Sprekeler;Friedemann Zenke;Claudia Clopath;Claudia Clopath

  • Hebbian learning and spiking neurons

    Richard Kempter;Wulfram Gerstner;J. Leo van Hemmen

  • Spiking Neuron Models: An Introduction

    Wulfram Gerstner;Werner Kistler

  • Triplets of Spikes in a Model of Spike Timing-Dependent Plasticity

    Jean-Pascal Pfister;Wulfram Gerstner

  • Connectivity reflects coding: a model of voltage-based STDP with homeostasis

    Claudia Clopath;Lars Holger Büsing;Lars Holger Büsing;Eleni Vasilaki;Eleni Vasilaki;Wulfram Gerstner

  • Phenomenological models of synaptic plasticity based on spike timing

    Abigail Morrison;Markus Diesmann;Wulfram Gerstner

  • Time structure of the activity in neural network models

    Wulfram Gerstner

  • A History of Spike-Timing-Dependent Plasticity

    Henry Markram;Wulfram Gerstner;Per Jesper Sjöström;Per Jesper Sjöström

  • Mathematical formulations of Hebbian learning.

    Wulfram Gerstner;Werner M. Kistler

  • Population Dynamics of Spiking Neurons: Fast Transients, Asynchronous States, and Locking

    Wulfram Gerstner

  • Eligibility Traces and Plasticity on Behavioral Time Scales: Experimental Support of NeoHebbian Three-Factor Learning Rules.

    Wulfram Gerstner;Marco Lehmann;Vasiliki Liakoni;Dane Corneil

  • Spiking Neuron Models

    Unknown

  • Reduction of the hodgkin-huxley equations to a single-variable threshold model

    Werner M. Kistler;Wulfram Gerstner;J. Leo van Hemmen

  • Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules.

    Nicolas Frémaux;Wulfram Gerstner

  • Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks

    Friedemann Zenke;Everton J. Agnes;Everton J. Agnes;Wulfram Gerstner

  • Spiking neurons

    Wulfram Gerstner

  • Spatial cognition and neuro-mimetic navigation: a model of hippocampal place cell activity.

    Angelo Arleo;Wulfram Gerstner

Frequent Co-Authors

Liam Paninski
Liam Paninski Columbia University
J. Leo van Hemmen
J. Leo van Hemmen Technical University of Munich
Claudia Clopath
Claudia Clopath Imperial College London
Richard Kempter
Richard Kempter Humboldt-Universität zu Berlin
Michael H. Herzog
Michael H. Herzog École Polytechnique Fédérale de Lausanne
Henry Markram
Henry Markram École Polytechnique Fédérale de Lausanne
Carl C. H. Petersen
Carl C. H. Petersen École Polytechnique Fédérale de Lausanne
Ricardo Chavarriaga
Ricardo Chavarriaga École Polytechnique Fédérale de Lausanne
Gaute T. Einevoll
Gaute T. Einevoll Norwegian University of Life Sciences
Hans-Rudolf Lüscher
Hans-Rudolf Lüscher University of Bern

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