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D-Index & Metrics

Neuroscience

D-Index
41
Citations
6899
World Ranking
7847
National Ranking
3367

Jürgen Kayser 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 Jürgen Kayser 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: 86 publications — 10th percentile

10% of scientists in this discipline score the same or lower.

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

Jürgen Kayser 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 Jürgen Kayser 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: 41 D-Index — 19th percentile

19% of scientists in this discipline score the same or lower.

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

Overview

Jürgen Kayser is affiliated with Columbia University in the United States and works primarily within the field of neuroscience. Their research focuses heavily on cognitive neuroscience, with additional work in experimental and cognitive psychology, health, cardiology and cardiovascular medicine, and psychiatry and mental health.

The main topics covered by Kayser's research include functional brain connectivity studies, neural and behavioral psychology studies, EEG and brain-computer interfaces, religion and spirituality related to psychology, heart rate variability and autonomic control, anxiety, depression, psychometrics, treatment, and cognitive processes, as well as broader mental health research topics.

Kayser has contributed to a number of publications in well-regarded scientific venues, frequently publishing in Biological Psychiatry, Psychophysiology, the Journal of Psychiatric Research, the Journal of Affective Disorders, and Psychiatry Research.

Some recent papers authored or co-authored by Kayser include:

  • Putamen Structure and Function in Familial Risk for Depression: A Multimodal Imaging Study, 2022, Biological Psychiatry
  • Resting posterior alpha power and adolescent major depressive disorder, 2021, Journal of Psychiatric Research
  • Predicting Depression Symptoms in Families at Risk for Depression: Interrelations of Posterior EEG Alpha and Religion/Spirituality, 2020, Journal of Affective Disorders
  • Feedback negativity and feedback-related P3 in individuals at risk for depression: Comparing surface potentials and current source densities, 2023, Psychophysiology
  • Neurophysiological responses to emotional faces predict dynamic fluctuations in affect in adolescents, 2023, Psychophysiology

Kayser frequently collaborates with a range of co-authors, with notable recurring collaborators including Myrna M. Weissman, Gerard E. Bruder, Marc J. Gameroff, Priya Wickramaratne, and Lidia Y.X. Panier.

Best Publications

  • Principal components analysis of Laplacian waveforms as a generic method for identifying ERP generator patterns: I. Evaluation with auditory oddball tasks.

    Jürgen Kayser;Craig E. Tenke

  • Is Resting Anterior EEG Alpha Asymmetry a Trait Marker for Depression

    Stefan Debener;André Beauducel;Doreen Nessler;Burkhard Brocke

  • Optimizing PCA methodology for ERP component identification and measurement: theoretical rationale and empirical evaluation

    Jürgen Kayser;Craig E Tenke

  • Principal components analysis of Laplacian waveforms as a generic method for identifying ERP generator patterns: II. Adequacy of low-density estimates.

    Jürgen Kayser;Craig E. Tenke

  • Generator localization by current source density (CSD): implications of volume conduction and field closure at intracranial and scalp resolutions.

    Craig E. Tenke;Jürgen Kayser

  • On the benefits of using surface Laplacian (Current Source Density) methodology in electrophysiology

    Jürgen Kayser;Craig E. Tenke

  • Event-related potentials (ERPs) to hemifield presentations of emotional stimuli: differences between depressed patients and healthy adults in P3 amplitude and asymmetry.

    Jürgen Kayser;Gerard E Bruder;Craig E Tenke;Jonathan E Stewart

  • Issues and considerations for using the scalp surface Laplacian in EEG/ERP research: A tutorial review.

    Jürgen Kayser;Craig E. Tenke

  • Reference-free quantification of EEG spectra: Combining current source density (CSD) and frequency principal components analysis (fPCA)

    Craig E. Tenke;Jürgen Kayser

  • Current Source Density Measures of Electroencephalographic Alpha Predict Antidepressant Treatment Response

    Craig E. Tenke;Jürgen Kayser;Carlye G. Manna;Shiva Fekri

  • Event-related potential (ERP) asymmetries to emotional stimuli in a visual half-field paradigm.

    Jürgen Kayser;Craig Tenke;Helge Nordby;Dag Hammerborg

  • Pretreatment Rostral Anterior Cingulate Cortex Theta Activity in Relation to Symptom Improvement in Depression: A Randomized Clinical Trial

    Diego A. Pizzagalli;Christian A. Webb;Daniel G. Dillon;Craig E. Tenke

  • Emotion recognition deficits as predictors of transition in individuals at clinical high risk for schizophrenia: a neurodevelopmental perspective.

    C. M. Corcoran;J. G. Keilp;J. Kayser;C. Klim

  • Reduced brain responses to novel sounds in depression: P3 findings in a novelty oddball task

    Gerard E. Bruder;Christopher J. Kroppmann;Jürgen Kayser;Jonathan W. Stewart

  • Left temporal lobe dysfunction in schizophrenia: event-related potential and behavioral evidence from phonetic and tonal dichotic listening tasks.

    Gerard Bruder;Jürgen Kayser;Craig Tenke;Xavier Amador

  • In search of the Rosetta Stone for scalp EEG: converging on reference-free techniques.

    Jürgen Kayser;Craig E. Tenke

  • Cognitive ERPs in depressive and anxiety disorders during tonal and phonetic oddball tasks.

    Gerard E. Bruder;Jürgen Kayser;Craig E. Tenke;Paul Leite

  • Trusting in or breaking with convention: towards a renaissance of principal components analysis in electrophysiology.

    Jürgen Kayser;Craig E. Tenke

  • A convenient method for detecting electrolyte bridges in multichannel electroencephalogram and event-related potential recordings.

    Craig E. Tenke;Jürgen Kayser

  • Dissociation of brain ERP topographies for tonal and phonetic oddball tasks

    Jürgen Kayser;Craig E. Tenke;Gerard E. Bruder

  • On the Reliability of Augmenting/Reducing Peak Amplitudes and Principal Component Analysis of Auditory Evoked Potentials

    André Beauducel;Stefan Debener;Burkhard Brocke;Jürgen Kayser

Frequent Co-Authors

Craig E. Tenke
Craig E. Tenke Columbia University
Gerard E. Bruder
Gerard E. Bruder Columbia University
Myrna M. Weissman
Myrna M. Weissman Columbia University
Priya Wickramaratne
Priya Wickramaratne Columbia University
Virginia Warner
Virginia Warner Columbia University
Diego A. Pizzagalli
Diego A. Pizzagalli Harvard University
Madhukar H. Trivedi
Madhukar H. Trivedi The University of Texas Southwestern Medical Center
Jack M. Gorman
Jack M. Gorman Icahn School of Medicine at Mount Sinai
Marc J. Gameroff
Marc J. Gameroff Columbia University
Melvin G. McInnis
Melvin G. McInnis University of Michigan–Ann Arbor

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