Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?,Human Brain Mapping

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Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?
Human Brain Mapping ( IF 3.5 ) Pub Date : 2020-07-30 , DOI: 10.1002/hbm.25089
Amelie Haugg _{1,

2} , Ronald Sladky ₂ , Stavros Skouras ₃ , Amalia McDonald ₄ , Cameron Craddock ₅ , Matthias Kirschner _{1,

6} , Marcus Herdener ₁ , Yury Koush ₇ , Marina Papoutsi ₈ , Jackob N Keynan ₉ , Talma Hendler ₉ , Kathrin Cohen Kadosh ₁₀ , Catharina Zich ₁₁ , Jeff MacInnes ₁₂ , R Alison Adcock ₁₃ , Kathryn Dickerson ₁₃ , Nan-Kuei Chen ₁₄ , Kymberly Young ₁₅ , Jerzy Bodurka ₁₆ , Shuxia Yao ₁₇ , Benjamin Becker ₁₇ , Tibor Auer ₁₀ , Renate Schweizer ₁₈ , Gustavo Pamplona ₁₉ , Kirsten Emmert ₂₀ , Sven Haller ₂₁ , Dimitri Van De Ville _{22,

23} , Maria-Laura Blefari ₂₂ , Dong-Youl Kim ₂₄ , Jong-Hwan Lee ₂₄ , Theo Marins ₂₅ , Megumi Fukuda ₂₆ , Bettina Sorger ₂₇ , Tabea Kamp ₂₇ , Sook-Lei Liew ₂₈ , Ralf Veit ₂₉ , Maartje Spetter ₃₀ , Nikolaus Weiskopf ₃₁ , Frank Scharnowski _{1,

2}

Affiliation

Psychiatric University Hospital Zurich, University of Zurich, Zürich, Switzerland.
Faculty of Psychology, University of Vienna, Vienna, Austria.
Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway.
Department of Psychology, University of Virginia, Charlottesville, Virginia.
Department of Diagnostic Medicine, The University of Texas at Austin Dell Medical School, Austin, Texas.
McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada.
Magnetic Resonance Research Center, Department of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut.
UCL Huntington's Disease Centre, Institute of Neurology, University College London, London, England.
Functional Brain Center, Wohl Institute for Advanced Imaging, Tel-Aviv Sourasky Medical Center, Tel-Aviv University, Tel Aviv, Israel.
School of Psychology, University of Surrey, Guildford, England.
Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England.
Institute for Learning and Brain Sciences, University of Washington, Seattle, Washington.
Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina.
Department of Biomedical Engineering, University of Arizona, Tucson, Arizona.
Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
Laureate Institute for Brain Research, Tulsa, Oklahoma.
Clinical Hospital of Chengdu the Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.
Functional Imaging Laboratory, German Primate Center, Göttingen, Germany.
Hôpital and Ophtalmique Jules Gonin, University of Lausanne, Lausanne, Switzerland.
Department of Neurology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany.
Radiology-Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Center for Neuroprosthetics, Ecole Polytechnique Féderale de Lausanne, Lausanne, Switzerland.
Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Department of Brain and Cognitive Engineering, Korea University, Seoul, Korea.
D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil.
School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan.
Department Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.
Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, California.
Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich, University of Tübingen, Tübingen, Germany.
School of Psychology, University of Birmingham, Birmingham, England.
Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

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.

中文翻译：

我们可以通过预训练大脑活动来预测实时功能磁共振成像神经反馈学习的成功吗？

神经反馈训练已被证明可以影响健康参与者的行为，并减轻神经、心身和精神病患者群体的临床症状。然而，许多实时功能磁共振成像神经反馈研究报告称，学习成功率存在巨大的个体差异。导致参与者之间巨大差异的因素仍然未知，识别这些因素可以提高治疗的成功率。因此，我们在这里采用了荟萃分析方法，包括来自 24 项不同神经反馈研究的数据，共有 401 名参与者（包括 140 名患者），以确定在预训练功能定位器或无反馈运行期间目标大脑区域的活动水平是否存在变化（即，在没有神经反馈的情况下的自我调节）可以预测神经反馈学习的成功。我们观察到功能定位器运行期间的训练前活动水平与神经反馈学习成功之间存在轻微的正相关性，但我们无法在不同的研究队列中识别出常见的基于大脑的成功预测因素。因此，需要在寻找一般神经反馈学习的稳健模型和测量方面取得进展，并增加当前的研究数据库以允许研究可能影响神经反馈学习的进一步因素。

更新日期：2020-09-03

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