World's Best Scientists 2026 revealed!
Gilles Laurent

Gilles Laurent

D-Index & Metrics

Neuroscience

D-Index
74
Citations
31828
World Ranking
2065
National Ranking
186

Gilles Laurent 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 Gilles Laurent 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: 186 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Gilles Laurent 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 Gilles Laurent 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: 74 D-Index — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Overview

Gilles Laurent is affiliated with the Max Planck Society in Germany and has conducted research spanning multiple fields including business, management, accounting, and medicine. Their scholarly work mainly focuses on marketing, cardiology and cardiovascular medicine, statistics and probability, sociology and political science, as well as cognitive neuroscience.

The primary topics addressed in Laurent's research include consumer market behavior and pricing, consumer behavior in brand consumption and identification, digital marketing and social media, neural and behavioral psychology studies, decision-making and behavioral economics, and statistical methods including Bayesian inference.

Laurent has contributed to several peer-reviewed publications across a variety of venues. Noteworthy recent papers include:

  • "Battling for consumer memory: Assessing brand exclusiveness and brand dominance from citation-list," 2022, Journal of Business Research
  • "How Do Consumers Read and Encode a Price?", 2023, Journal of Consumer Research
  • "Estimation from cross-sectional data under a semiparametric truncation model," 2020, Biometrika
  • "Exploring the temporal relationship between atrial fibrillation and heart failure development. Analysis from a nationwide database," 2020, European Heart Journal

Frequent co-authors who have collaborated with Laurent include Jean-Louis Chandon, Raphaëlle Lambert-Pandraud, Marc Vanhuele, Cédric Heuchenne, and Jacobo de Uña-Álvarez.

Laurent's research outputs have appeared in a range of scientific journals, including:

  • Journal of Business Research
  • Journal of Consumer Research
  • Biometrika
  • European Heart Journal

The diversity of publication venues reflects the interdisciplinary approach taken in Laurent's study, traversing theoretical and applied domains in both social sciences and medicine.

Best Publications

  • Measuring consumer involvement profiles

    Gilles Laurent;Jean-NOËL Kapferer

  • A BENEFIT CONGRUENCY FRAMEWORK OF SALES PROMOTION EFFECTIVENESS

    Pierre Chandon;Brian Wansink;Gilles Laurent

  • Impaired Odour Discrimination on Desynchronization of Odour-Encoding Neural Assemblies

    Mark Stopfer;Seetha Bhagavan;Seetha Bhagavan;Brian H. Smith;Gilles Laurent

  • Consumer Involvement Profiles: A New and Practical Approach to Consumer Involvement

    Jean-Noël Kapferer;Gilles Laurent

  • painless, a Drosophila gene essential for nociception

    W.Daniel Tracey;Rachel I Wilson;Gilles Laurent;Seymour Benzer

  • Oscillations and Sparsening of Odor Representations in the Mushroom Body

    Javier Perez-Orive;Ofer Mazor;Glenn C. Turner;Stijn Cassenaer

  • Olfactory network dynamics and the coding of multidimensional signals

    Gilles Laurent

  • Intensity versus Identity Coding in an Olfactory System

    Mark Stopfer;Vivek Jayaraman;Gilles Laurent

  • Transformation of olfactory representations in the Drosophila antennal lobe.

    Rachel I. Wilson;Glenn C. Turner;Gilles Laurent

  • Odour encoding by temporal sequences of firing in oscillating neural assemblies

    Michael Wehr;Gilles Laurent

  • Encoding of olfactory information with oscillating neural assemblies.

    Gilles Laurent;Hananel Davidowitz

  • Transient Dynamics for Neural Processing

    Misha Rabinovich;Ramon Huerta;Gilles Laurent

  • Transient dynamics versus fixed points in odor representations by locust antennal lobe projection neurons.

    Ofer Mazor;Gilles Laurent

  • Dynamic optimization of odor representations by slow temporal patterning of mitral cell activity.

    Rainer W. Friedrich;Gilles Laurent

  • Role of GABAergic Inhibition in Shaping Odor-Evoked Spatiotemporal Patterns in the Drosophila Antennal Lobe

    Rachel I. Wilson;Gilles Laurent

  • Odor encoding as an active, dynamical process : Experiments, computation, and theory

    Gilles Laurent;Mark Stopfer;Rainer W. Friedrich;Misha I. Rabinovich

  • Complexity and the nervous system.

    Christof Koch;Gilles Laurent

  • Dynamical encoding by networks of competing neuron groups: winnerless competition.

    M. Rabinovich;A. Volkovskii;P. Lecanda;P. Lecanda;R. Huerta;R. Huerta

  • Evolution of pallium, hippocampus, and cortical cell types revealed by single-cell transcriptomics in reptiles

    Maria Antonietta Tosches;Tracy M. Yamawaki;Robert K. Naumann;Ariel A. Jacobi

  • Distinct Mechanisms for Synchronization and Temporal Patterning of Odor-Encoding Neural Assemblies

    Katrina MacLeod;Gilles Laurent

  • Measuring consumer involvement profiles

    Jean-Noël Kapferer;Gilles Laurent

Frequent Co-Authors

Mark Stopfer
Mark Stopfer National Institutes of Health
Maxim Bazhenov
Maxim Bazhenov University of California, San Diego
Ramón Huerta
Ramón Huerta Autonomous University of Madrid
Malcolm Burrows
Malcolm Burrows University of Cambridge
Terrence J. Sejnowski
Terrence J. Sejnowski Salk Institute for Biological Studies
Mikhail I. Rabinovich
Mikhail I. Rabinovich University of California, San Diego
Christof Koch
Christof Koch Allen Institute for Brain Science
Brian Wansink
Brian Wansink Cornell University
Etienne Mullet
Etienne Mullet École Pratique des Hautes Études

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