World's Best Scientists 2026 revealed!

D-Index & Metrics

Neuroscience

D-Index
51
Citations
17678
World Ranking
5435
National Ranking
319

Martin J. McKeown 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 Martin J. McKeown 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: 276 publications — 79th percentile

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

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

Martin J. McKeown 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 Martin J. McKeown 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: 51 D-Index — 44th percentile

44% of scientists in this discipline score the same or lower.

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

Overview

Martin J. McKeown is affiliated with the University of British Columbia in Canada. Their research primarily spans the fields of Medicine and Neuroscience, with significant contributions to subfields such as Neurology, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, and Computer Vision and Pattern Recognition.

The scientist's research topics cover a variety of specialized areas including:

  • Neurological disorders and treatments
  • Parkinson's Disease Mechanisms and Treatments
  • EEG and Brain-Computer Interfaces
  • Functional Brain Connectivity Studies
  • Advanced Neuroimaging Techniques and Applications
  • Vestibular and auditory disorders
  • Advanced MRI Techniques and Applications

Martin J. McKeown has published extensively in multiple academic venues. The most frequent publication outlets include:

  • arXiv (Cornell University)
  • Frontiers in Neurology
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Sensors
  • Brain Stimulation

Collaborations have been an important part of McKeown's work, with frequent co-authors including:

  • Maryam S. Mirian
  • Soojin Lee
  • Z. Jane Wang
  • Aiping Liu
  • Xun Chen

Recent papers authored or co-authored by Martin J. McKeown demonstrate their focus on neural signal processing and neurological disorder treatment methodologies. These include:

  • A convolutional-recurrent neural network approach to resting-state EEG classification in Parkinson's disease, 2021, Journal of Neuroscience Methods
  • Toward Open-World Electroencephalogram Decoding Via Deep Learning: A comprehensive survey, 2022, IEEE Signal Processing Magazine
  • Semi-dilated convolutional neural networks for epileptic seizure prediction, 2021, Neural Networks
  • Repetitive transcranial magnetic stimulation improves Parkinson's freezing of gait via normalizing brain connectivity, 2020, npj Parkinson's Disease
  • A Deep Learning Strategy for Automatic Sleep Staging Based on Two-Channel EEG Headband Data, 2021, Sensors

Best Publications

  • Removing electroencephalographic artifacts by blind source separation.

    Tzyy-Ping Jung;Tzyy-Ping Jung;Scott Makeig;Colin Humphries;Te-Won Lee;Te-Won Lee

  • Analysis of fMRI data by blind separation into independent spatial components

    Martin J. Mckeown;Scott Makeig;Greg G. Brown;Tzyy-Ping Jung

  • Imaging brain dynamics using independent component analysis

    T.-P. Jung;S. Makeig;M.J. McKeown;A.J. Bell

  • Extended ICA Removes Artifacts from Electroencephalographic Recordings

    Tzyy-Ping Jung;Colin Humphries;Te-Won Lee;Scott Makeig

  • Independent Component Analysis of fMRI Data: Examining the Assumptions

    Martin J. McKeown;Terrence J. Sejnowski;Terrence J. Sejnowski

  • Spatially independent activity patterns in functional MRI data during the Stroop color-naming task

    Martin J. McKeown;Tzyy-Ping Jung;Scott Makeig;Greg Brown

  • Independent component analysis of functional MRI: what is signal and what is noise?

    Martin J McKeown;Lars Kai Hansen;Terrence J Sejnowsk;Terrence J Sejnowsk

  • Brain activity evoked by the perception of human walking: controlling for meaningful coherent motion.

    Kevin A. Pelphrey;Teresa V. Mitchell;Martin J. McKeown;Jeremy Goldstein

  • Polysensory Interactions along Lateral Temporal Regions Evoked by Audiovisual Speech

    Tarra M. Wright;Kevin A. Pelphrey;Truett Allison;Martin J. McKeown

  • 3D CNN Based Automatic Diagnosis of Attention Deficit Hyperactivity Disorder Using Functional and Structural MRI

    Liang Zou;Jiannan Zheng;Chunyan Miao;Martin J. Mckeown

  • Removing electroencephalographic artifacts: comparison between ICA and PCA

    T.-P. Jung;C. Humphries;T.-W. Lee;S. Makeig

  • Detection of consistently task-related activations in fMRI data with hybrid independent component analysis.

    Martin J. McKeown

  • Exercise increases caudate dopamine release and ventral striatal activation in Parkinson's disease.

    Matthew A. Sacheli;Jason L. Neva;Bimal Lakhani;Danielle K. Murray

  • INDEPENDENT COMPONENT ANALYSIS OF BIOMEDICAL SIGNALS

    Tzyy-Ping Jung;Scott Makeig;Te-Won Lee;Martin J. McKeown

  • Task specific influences of Parkinson’s disease on the striato-thalamo-cortical and cerebello-thalamo-cortical motor circuitries

    M.M. Lewis;C.G. Slagle;A.B. Smith;Y. Truong

  • The Use of Multivariate EMD and CCA for Denoising Muscle Artifacts From Few-Channel EEG Recordings

    Xun Chen;Xueyuan Xu;Aiping Liu;Martin J. McKeown

  • Advances in imaging in Parkinson's disease

    A Jon Stoessl;WR Wayne Martin;Martin J McKeown;Vesna Sossi

  • Acute and persistent pain modulation of attention-related anterior cingulate fMRI activations

    Angela L.H. Buffington;Colleen A. Hanlon;Martin J. McKeown

  • Linking Hemodynamic and Electrophysiological Measures of Brain Activity: Evidence from Functional MRI and Intracranial Field Potentials

    Scott A. Huettel;Martin J. McKeown;Allen W. Song;Sarah Hart

  • Removing Muscle Artifacts From EEG Data: Multichannel or Single-Channel Techniques?

    Xun Chen;Aiping Liu;Joyce Chiang;Z. Jane Wang

Frequent Co-Authors

Z. Jane Wang
Z. Jane Wang University of British Columbia
Xun Chen
Xun Chen University of Science and Technology of China
A. Jon Stoessl
A. Jon Stoessl University of British Columbia
Terrence J. Sejnowski
Terrence J. Sejnowski Salk Institute for Biological Studies
Xuemei Huang
Xuemei Huang Pennsylvania State University
Tzyy-Ping Jung
Tzyy-Ping Jung University of California, San Diego
Scott Makeig
Scott Makeig University of California, San Diego
Mechelle M. Lewis
Mechelle M. Lewis Penn State Milton S. Hershey Medical Center
Te-Won Lee
Te-Won Lee Qualcomm (United States)
Yi Liu
Yi Liu Lawrence Berkeley National Laboratory

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