World's Best Scientists 2026 revealed!

D-Index & Metrics

Neuroscience

D-Index
60
Citations
10663
World Ranking
3894
National Ranking
109

David A. Copland 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 A. Copland 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: 391 publications — 91st percentile

91% of scientists in this discipline score the same or lower.

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

David A. Copland 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 A. Copland 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: 60 D-Index — 61st percentile

61% of scientists in this discipline score the same or lower.

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

Overview

David A. Copland is affiliated with the University of Queensland in Australia. Their work primarily spans the fields of Medicine and Neuroscience, with a notable focus on subfields including Cognitive Neuroscience, Rehabilitation, Epidemiology, Psychiatry and Mental Health, and General Health Professions.

The main topics covered by their research include:

  • Neurobiology of Language and Bilingualism
  • Stroke Rehabilitation and Recovery
  • Acute Ischemic Stroke Management
  • Dementia and Cognitive Impairment Research
  • Interpreting and Communication in Healthcare
  • Language Development and Disorders
  • Parkinson's Disease Mechanisms and Treatments

David A. Copland has contributed numerous articles to several frequent publication venues, including:

  • Aphasiology
  • Stroke
  • BMJ Open
  • International Journal of Language & Communication Disorders
  • Brain and Language

Recent papers authored or coauthored by David A. Copland consist of the following titles and publications:

  • Predictors of Poststroke Aphasia Recovery, 2021, Stroke
  • Advancing Stroke Recovery Through Improved Articulation of Nonpharmacological Intervention Dose, 2021, Stroke
  • Multisession transcranial direct current stimulation facilitates verbal learning and memory consolidation in young and older adults, 2020, Brain and Language
  • Results of the COMPARE trial of Constraint-induced or Multimodality Aphasia Therapy compared with usual care in chronic post-stroke aphasia, 2022, Journal of Neurology Neurosurgery & Psychiatry
  • The effect of sleep on novel word learning in healthy adults: A systematic review and meta-analysis, 2021, Psychonomic Bulletin & Review

Their collaboration network includes frequent coauthors such as:

  • Sarah J. Wallace
  • Erin Godecke
  • Katie L. McMahon
  • Anthony J. Angwin
  • Miranda L. Rose

Best Publications

  • Biomarkers of Stroke Recovery: Consensus-Based Core Recommendations from the Stroke Recovery and Rehabilitation Roundtable.

    Lara A Boyd;Kathryn S Hayward;Nick S Ward;Cathy M Stinear

  • L-Dopa Modulates Functional Connectivity in Striatal Cognitive and Motor Networks: A Double-Blind Placebo-Controlled Study

    Clare Kelly;Greig de Zubicaray;Adriana Di Martino;David A. Copland

  • A core outcome set for aphasia treatment research: The ROMA consensus statement:

    Sarah J. Wallace;Linda Worrall;Tanya Rose;Guylaine Le Dorze

  • Analysis of Retinal Cellular Infiltrate in Experimental Autoimmune Uveoretinitis Reveals Multiple Regulatory Cell Populations

    Emma C. Kerr;Ben J.E. Raveney;David A. Copland;Andrew D. Dick

  • The basal ganglia and semantic engagement: potential insights from semantic priming in individuals with subcortical vascular lesions, Parkinson's disease, and cortical lesions.

    David Copland

  • Transcranial direct current stimulation over multiple days improves learning and maintenance of a novel vocabulary.

    Marcus Meinzer;Marcus Meinzer;Sophia Jähnigen;David A. Copland;Robert Darkow

  • Monoclonal antibody-mediated CD200 receptor signaling suppresses macrophage activation and tissue damage in experimental autoimmune uveoretinitis.

    David A. Copland;Claudia J. Calder;Ben J.E. Raveney;Lindsay B. Nicholson

  • A multivariate distance-based analytic framework for connectome-wide association studies.

    Zarrar Shehzad;Zarrar Shehzad;Zarrar Shehzad;Clare Kelly;Philip T. Reiss;R. Cameron Craddock

  • Brain activity during automatic semantic priming revealed by event-related functional magnetic resonance imaging.

    David A. Copland;Greig I. de Zubicaray;Katie McMahon;Stephen J. Wilson

  • The dynamics of leukocyte infiltration in experimental autoimmune uveoretinitis.

    EC Kerr;David A Copland;Andrew David Dick;Lindsay B Nicholson

  • L-Dopa Modulates Functional Connectivity in Striatal Cognitive and Motor Networks: A Double-Blind Placebo-Controlled Study

    Amc Kelly;G de Zubicaray;A di Martino;D Copland

  • Cellular senescence in the aging retina and developments of senotherapies for age-related macular degeneration.

    Keng Siang Lee;Shuxiao Lin;David A Copland;Andrew David Dick;Andrew David Dick;Andrew David Dick

  • Myeloid cells expressing VEGF and Arginase-1 following uptake of damaged retinal pigment epithelium suggests potential mechanism that drives the onset of choroidal angiogenesis in mice

    Jian Liu;David A Copland;Shintaro Horie;Wei-Kang Wu

  • Homeostatic regulation of T cell trafficking by a B cell derived peptide is impaired in autoimmune and chronic inflammatory disease

    Myriam Chimen;Helen M. McGettrick;Bonita Apta;Sahithi J. Kuravi

  • Mobile computing technology and aphasia: An integrated review of accessibility and potential uses

    Caitlin Brandenburg;Linda Worrall;Amy D. Rodriguez;David Copland

  • A functional MRI study of the relationship between naming treatment outcomes and resting state functional connectivity in post-stroke aphasia

    Sophia van Hees;Katie McMahon;Anthony Angwin;Greig de Zubicaray

  • Memory and communication support in dementia: Research-based strategies for caregivers

    Erin R. Smith;Megan Broughton;Rosemary Baker;Nancy A. Pachana

  • Intensive Versus Distributed Aphasia Therapy A Nonrandomized, Parallel-Group, Dosage-Controlled Study

    Jade Dignam;David Copland;Eril McKinnon;Penni Burfein

  • Evaluation of a caregiver education program to support memory and communication in dementia: A controlled pretest–posttest study with nursing home staff

    Megan Broughton;Erin R. Smith;Rosemary Baker;Anthony J. Angwin

  • Systemic and local anti‐C5 therapy reduces the disease severity in experimental autoimmune uveoretinitis

    D. A. Copland;K. Hussain;Sivasankar Baalasubramanian;Timothy Richard Hughes

  • A comparison of semantic feature analysis and phonological components analysis for the treatment of naming impairments in aphasia

    Sophia van Hees;Anthony Angwin;Katie McMahon;David Copland

  • The clinical time-course of experimental autoimmune uveoretinitis using topical endoscopic fundal imaging with histologic and cellular infiltrate correlation.

    David A. Copland;Michael S. Wertheim;W. John Armitage;Lindsay B. Nicholson

Frequent Co-Authors

Katie L. McMahon
Katie L. McMahon Queensland University of Technology
Andrew D. Dick
Andrew D. Dick University of Bristol
Helen J. Chenery
Helen J. Chenery Bond University
Peter A. Silburn
Peter A. Silburn University of Queensland
Gerard J. Byrne
Gerard J. Byrne University of Queensland
Bruce E. Murdoch
Bruce E. Murdoch University of Queensland
Marcus Meinzer
Marcus Meinzer Charité - University Medicine Berlin
Lyndsey Nickels
Lyndsey Nickels Macquarie University
Greig I. de Zubicaray
Greig I. de Zubicaray Queensland University of Technology
Nancy A. Pachana
Nancy A. Pachana University of Queensland

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