World's Best Scientists 2026 revealed!

D-Index & Metrics

Neuroscience

D-Index
52
Citations
12169
World Ranking
5255
National Ranking
105

Sven Haller 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 Sven Haller 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: 256 publications — 76th percentile

76% of scientists in this discipline score the same or lower.

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

Sven Haller 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 Sven Haller 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: 52 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Sven Haller is affiliated with Uppsala University in Sweden and is an active researcher mainly in the fields of Medicine and Neuroscience. Their work focuses on several specialized subfields including Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, Psychiatry and Mental Health, Neurology, and Physiology.

Their research spans multiple topics, with significant contributions in:

  • Functional Brain Connectivity Studies
  • Dementia and Cognitive Impairment Research
  • Advanced Neuroimaging Techniques and Applications
  • Advanced MRI Techniques and Applications
  • Alzheimer's Disease Research and Treatments
  • Traumatic Brain Injury and Neurovascular Disturbances
  • Radiomics and Machine Learning in Medical Imaging

Haller has published extensively in a number of scientific journals, with frequent appearances in:

  • Alzheimer's & Dementia
  • Radiology
  • Neuroradiology
  • Radiology Artificial Intelligence
  • bioRxiv (Cold Spring Harbor Laboratory)

Some key recent publications include:

  • "Susceptibility-weighted Imaging: Technical Essentials and Clinical Neurologic Applications" (2021) in Radiology
  • "Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update" (2024) in Radiology Artificial Intelligence
  • "Current state and guidance on arterial spin labeling perfusion MRI in clinical neuroimaging" (2023) in Magnetic Resonance in Medicine
  • "Application of the ATN classification scheme in a population without dementia: Findings from the EPAD cohort" (2021) in Alzheimer's & Dementia
  • "Spatial-Temporal Patterns of β-Amyloid Accumulation" (2022) in Neurology

Frequent co-authors collaborating with Haller include:

  • Frederik Barkhof
  • Juan Domingo Gispert
  • Alle Meije Wink
  • Henk Mutsaerts
  • Luigi Lorenzini

Best Publications

  • Closed-loop brain training: the science of neurofeedback

    Ranganatha Sitaram;Tomas Ros;Luke Stoeckel;Sven Haller

  • New ischaemic brain lesions on MRI after stenting or endarterectomy for symptomatic carotid stenosis: a substudy of the International Carotid Stenting Study (ICSS)

    Leo H Bonati;Leo H Bonati;Lisa M Jongen;Sven Haller;H Zwenneke Flach

  • Real-time fMRI neurofeedback: Progress and challenges

    J. Sulzer;S. Haller;F. Scharnowski;F. Scharnowski;N. Weiskopf

  • Arterial Spin Labeling Perfusion of the Brain: Emerging Clinical Applications.

    Sven Haller;Greg Zaharchuk;David L. Thomas;Karl Olof Lovblad

  • Resting-State Functional MR Imaging: A New Window to the Brain

    Frederik Barkhof;Sven Haller;Serge A R B Rombouts

  • Regional gray matter volume abnormalities in the at risk mental state

    Stefan J. Borgwardt;Anita Riecher-Rössler;Paola Dazzan;Xavier Chitnis

  • Cerebral Microbleeds: Imaging and Clinical Significance

    Sven Haller;Meike W. Vernooij;Joost P.A. Kuijer;Elna Marie Larsson

  • On sex/gender related similarities and differences in fMRI language research

    Anelis Kaiser;Sven Haller;Sven Haller;Sigrid Schmitz;Cordula Nitsch

  • Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated?

    Kirsten Emmert;Kirsten Emmert;Rotem Kopel;Rotem Kopel;James Samuel Sulzer;Annette B. Brühl;Annette B. Brühl

  • Imaging of Neurovascular Compression Syndromes: Trigeminal Neuralgia, Hemifacial Spasm, Vestibular Paroxysmia, and Glossopharyngeal Neuralgia

    Sven Haller;Léonard Etienne;Eniko Veronika Kovari;A D Varoquaux

  • The impact of gut hormones on the neural circuit of appetite and satiety: A systematic review

    Davide Zanchi;Antoinette Depoorter;Laura Egloff;Sven Haller

  • Real-time fMRI feedback training may improve chronic tinnitus

    Sven Haller;Sven Haller;Niels Birbaumer;Ralf Veit

  • Susceptibility-weighted Imaging: Technical Essentials and Clinical Neurologic Applications

    Sven Haller;E Mark Haacke;Majda M Thurnher;Frederik Barkhof

  • Combined analysis of grey matter voxel-based morphometry and white matter tract-based spatial statistics in late-life bipolar disorder.

    Sven Haller;Aikaterini Xekardaki;Christophe Delaloye;Alessandra Canuto

  • Do brain T2/FLAIR white matter hyperintensities correspond to myelin loss in normal aging? A radiologic-neuropathologic correlation study

    Sven Haller;Enikö Kövari;François R. Herrmann;Victor Cuvinciuc

  • Individual Detection of Patients with Parkinson Disease using Support Vector Machine Analysis of Diffusion Tensor Imaging Data: Initial Results

    Sven Haller;Simon Badoud;Duy Nguyen;Valentina Garibotto

  • The age of second language acquisition determines the variability in activation elicited by narration in three languages in Broca's and Wernicke's area.

    Constantine Bloch;Anelis Kaiser;Esther Kuenzli;Daniela Zappatore

  • Arterial spin labeling may contribute to the prediction of cognitive deterioration in healthy elderly individuals.

    Aikaterini Xekardaki;Cristelle Rodriguez;Marie-Louise Montandon;Simona Toma

  • Overt sentence production in event-related fMRI.

    Sven Haller;E.W. Radue;Michael Erb;Wolfgang Grodd

  • Black holes in multiple sclerosis: definition, evolution, and clinical correlations

    M. A. Sahraian;E.-W. Radue;S. Haller;L. Kappos

  • Pitfalls in FMRI.

    Sven Haller;Sven Haller;Andreas J. Bartsch;Andreas J. Bartsch

Frequent Co-Authors

Panteleimon Giannakopoulos
Panteleimon Giannakopoulos University of Geneva
Dimitri Van De Ville
Dimitri Van De Ville École Polytechnique Fédérale de Lausanne
Frederik Barkhof
Frederik Barkhof University College London
Valentina Garibotto
Valentina Garibotto University of Geneva
François Herrmann
François Herrmann University of Geneva
Stefan Borgwardt
Stefan Borgwardt University of Lübeck
Nikolaus Weiskopf
Nikolaus Weiskopf Max Planck Society
Klaus Scheffler
Klaus Scheffler Max Planck Society
Dinggang Shen
Dinggang Shen ShanghaiTech University
Elna-Marie Larsson
Elna-Marie Larsson Uppsala University

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