World's Best Scientists 2026 revealed!

D-Index & Metrics

Neuroscience

D-Index
39
Citations
8887
World Ranking
8241
National Ranking
243

David McAlpine 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 David McAlpine 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: 142 publications — 39th percentile

39% of scientists in this discipline score the same or lower.

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

David McAlpine 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 David McAlpine 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: 39 D-Index — 15th percentile

15% of scientists in this discipline score the same or lower.

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

Overview

David McAlpine is affiliated with Macquarie University in Australia and has a research focus in the field of Neuroscience, with a notable emphasis on Cognitive Neuroscience. Their work spans several subfields including Sensory Systems, Radiology, Nuclear Medicine and Imaging, Speech and Hearing, and Biomedical Engineering.

Their research topics broadly cover areas such as Hearing Loss and Rehabilitation, Hearing, Cochlea, Tinnitus, and Genetics. Further topics of investigation include Neural dynamics and brain function, Neuroscience and Music Perception, Noise Effects and Management, EEG and Brain-Computer Interfaces, and Multisensory perception and integration.

Frequent publication venues where David McAlpine has contributed include bioRxiv (Cold Spring Harbor Laboratory) and The Journal of the Acoustical Society of America, each with 10 publications. Other venues include arXiv (Cornell University) with 4 publications, Neural Networks with 3, and Frontiers in Neuroscience also with 3.

Among their recent papers are the following:

  • "A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers" (2020), Journal of Neural Engineering
  • "Analysis methods for measuring passive auditory fNIRS responses generated by a block-design paradigm" (2021), Neurophotonics
  • "Deep reinforcement learning guided graph neural networks for brain network analysis" (2022), Neural Networks
  • "Hidden Hearing Loss Impacts the Neural Representation of Speech in Background Noise" (2020), Current Biology
  • "Cross-modal functional connectivity supports speech understanding in cochlear implant users" (2022), Cerebral Cortex

David McAlpine has collaborated frequently with several researchers, including Jessica J. M. Monaghan, Paul F. Sowman, Heivet Hernández-Pérez, Jason Mikiel-Hunter, and Robert Luke, reflecting a network of ongoing research partnerships.

Best Publications

  • Tinnitus with a normal audiogram: physiological evidence for hidden hearing loss and computational model.

    Roland Schaette;David McAlpine

  • Mechanisms of Sound Localization in Mammals

    Benedikt Grothe;Michael Pecka;David McAlpine

  • Precise inhibition is essential for microsecond interaural time difference coding

    Antje Brand;Oliver Behrend;Torsten Marquardt;David McAlpine

  • Neural population coding of sound level adapts to stimulus statistics.

    Isabel Dean;Nicol S Harper;David McAlpine

  • A neural code for low-frequency sound localization in mammals

    David McAlpine;David McAlpine;Dan Jiang;Alan R. Palmer

  • Optimal neural population coding of an auditory spatial cue

    Nicol S. Harper;David McAlpine

  • Sound localization and delay lines - do mammals fit the model?

    David McAlpine;Benedikt Grothe

  • A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers.

    Xiang Zhang;Lina Yao;Xianzhi Wang;Jessica J M Monaghan

  • Rapid neural adaptation to sound level statistics.

    Isabel Dean;Ben L. Robinson;Nicol S. Harper;David McAlpine

  • The ototoxic mechanism of cisplatin.

    David McAlpine;Brian M. Johnstone

  • Hidden hearing loss selectively impairs neural adaptation to loud sound environments

    Warren Michael Henry Bakay;Warren Michael Henry Bakay;Lucy Anne Anderson;Jose Alberto Garcia-Lazaro;David McAlpine;David McAlpine

  • Creating a sense of auditory space

    David McAlpine

  • A Survey on Deep Learning based Brain Computer Interface: Recent Advances and New Frontiers.

    Xiang Zhang;Lina Yao;Xianzhi Wang;Jessica Monaghan

  • Response properties of neurons in the inferior colliculus of the monaurally deafened ferret to acoustic stimulation of the intact ear.

    David McAlpine;Russell L. Martin;Jennifer E. Mossop;David R. Moore

  • Convergent Input from Brainstem Coincidence Detectors onto Delay-Sensitive Neurons in the Inferior Colliculus

    David McAlpine;Dan Jiang;Trevor M. Shackleton;Alan R. Palmer

  • Meta-adaptation in the auditory midbrain under cortical influence.

    Benjamin L. Robinson;Nicol S. Harper;David McAlpine;David McAlpine

  • Analysis methods for measuring passive auditory fNIRS responses generated by a block-design paradigm.

    Robert Luke;Robert Luke;Eric D. Larson;Maureen J. Shader;Maureen J. Shader;Hamish Innes-Brown

  • Responses of neurons in the inferior colliculus to dynamic interaural phase cues: evidence for a mechanism of binaural adaptation.

    David McAlpine;Dan Jiang;Trevor M. Shackleton;Alan R. Palmer

  • Interaural delay sensitivity and the classification of low best-frequency binaural responses in the inferior colliculus of the guinea pig.

    David McAlpine;Dan Jiang;Alan R. Palmer

  • Gain control mechanisms in the auditory pathway

    Benjamin Louis Robinson;David McAlpine

  • Spike-frequency adaptation in the inferior colliculus.

    Neil J. Ingham;David McAlpine

Frequent Co-Authors

Alan R. Palmer
Alan R. Palmer University of Nottingham
Timothy D. Griffiths
Timothy D. Griffiths University College London
Benedikt Grothe
Benedikt Grothe Ludwig-Maximilians-Universität München
Maneesh Sahani
Maneesh Sahani University College London
Tiago H. Falk
Tiago H. Falk Institut National de la Recherche Scientifique
John Rinzel
John Rinzel New York University
Lina Yao
Lina Yao Commonwealth Scientific and Industrial Research Organisation
Misha B. Ahrens
Misha B. Ahrens Howard Hughes Medical Institute
Xiang Zhang
Xiang Zhang University of Hong Kong

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