Can we predict real‐time <scp>fMRI</scp> neurofeedback learning success from pretraining brain activity?

  • Amelie Haugg
    Psychiatric University Hospital Zurich University of Zurich Zürich Switzerland
  • Ronald Sladky
    Faculty of Psychology University of Vienna Vienna Austria
  • Stavros Skouras
    Department of Biological and Medical Psychology University of Bergen Bergen Norway
  • Amalia McDonald
    Department of Psychology University of Virginia Charlottesville Virginia
  • Cameron Craddock
    Department of Diagnostic Medicine The University of Texas at Austin Dell Medical School Austin Texas
  • Matthias Kirschner
    Psychiatric University Hospital Zurich University of Zurich Zürich Switzerland
  • Marcus Herdener
    Psychiatric University Hospital Zurich University of Zurich Zürich Switzerland
  • Yury Koush
    Magnetic Resonance Research Center, Department of Radiology & Biomedical Imaging Yale University New Haven Connecticut
  • Marina Papoutsi
    UCL Huntington's Disease Centre Institute of Neurology, University College London London England
  • Jackob N. Keynan
    Functional Brain Center Wohl Institute for Advanced Imaging, Tel‐Aviv Sourasky Medical Center, Tel‐Aviv University Tel Aviv Israel
  • Talma Hendler
    Functional Brain Center Wohl Institute for Advanced Imaging, Tel‐Aviv Sourasky Medical Center, Tel‐Aviv University Tel Aviv Israel
  • Kathrin Cohen Kadosh
    School of Psychology University of Surrey Guildford England
  • Catharina Zich
    Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences University of Oxford Oxford England
  • Jeff MacInnes
    Institute for Learning and Brain Sciences University of Washington Seattle Washington
  • R. Alison Adcock
    Department of Psychiatry and Behavioral Sciences Duke University Durham North Carolina
  • Kathryn Dickerson
    Department of Psychiatry and Behavioral Sciences Duke University Durham North Carolina
  • Nan‐Kuei Chen
    Department of Biomedical Engineering University of Arizona Tucson Arizona
  • Kymberly Young
    Department of Psychiatry, School of Medicine University of Pittsburgh Pittsburgh Pennsylvania
  • Jerzy Bodurka
    Laureate Institute for Brain Research Tulsa Oklahoma
  • Shuxia Yao
    Clinical Hospital of Chengdu the Brain Science Institute, MOE Key Laboratory for Neuroinformation University of Electronic Science and Technology of China Chengdu China
  • Benjamin Becker
    Clinical Hospital of Chengdu the Brain Science Institute, MOE Key Laboratory for Neuroinformation University of Electronic Science and Technology of China Chengdu China
  • Tibor Auer
    School of Psychology University of Surrey Guildford England
  • Renate Schweizer
    Functional Imaging Laboratory German Primate Center Göttingen Germany
  • Gustavo Pamplona
    Hôpital and Ophtalmique Jules Gonin University of Lausanne Lausanne Switzerland
  • Kirsten Emmert
    Department of Neurology University Medical Center Schleswig‐Holstein, Kiel University Kiel Germany
  • Sven Haller
    Radiology‐Department of Surgical Sciences Uppsala University Uppsala Sweden
  • Dimitri Van De Ville
    Center for Neuroprosthetics Ecole Polytechnique Féderale de Lausanne Lausanne Switzerland
  • Maria‐Laura Blefari
    Center for Neuroprosthetics Ecole Polytechnique Féderale de Lausanne Lausanne Switzerland
  • Dong‐Youl Kim
    Department of Brain and Cognitive Engineering Korea University Seoul Korea
  • Jong‐Hwan Lee
    Department of Brain and Cognitive Engineering Korea University Seoul Korea
  • Theo Marins
    D'Or Institute for Research and Education (IDOR) Rio de Janeiro Brazil
  • Megumi Fukuda
    School of Fundamental Science and Engineering Waseda University Tokyo Japan
  • Bettina Sorger
    Department Cognitive Neuroscience, Faculty of Psychology and Neuroscience Maastricht University Maastricht The Netherlands
  • Tabea Kamp
    Department Cognitive Neuroscience, Faculty of Psychology and Neuroscience Maastricht University Maastricht The Netherlands
  • Sook‐Lei Liew
    Division of Occupational Science and Occupational Therapy University of Southern California Los Angeles California
  • Ralf Veit
    Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich University of Tübingen Tübingen Germany
  • Maartje Spetter
    School of Psychology University of Birmingham Birmingham England
  • Nikolaus Weiskopf
    Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany
  • Frank Scharnowski
    Psychiatric University Hospital Zurich University of Zurich Zürich Switzerland

抄録

<jats:title>Abstract</jats:title><jats:p>Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real‐time fMRI neurofeedback studies report large inter‐individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta‐analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no‐feedback runs (i.e., self‐regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain‐based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.</jats:p>

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