Evidence map›Paper›PMID 32729652›Full record

SynthesisHuman brain mapping2020

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

Amelie Haugg, Ronald Sladky, Stavros Skouras, Amalia McDonald, Cameron Craddock, Matthias Kirschner, Marcus Herdener, Yury Koush, Marina Papoutsi, Jackob N Keynan and 29 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in Human brain mapping, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Psilocybin-assisted neurofeedback for the improvement of executive functions: a randomized semi-naturalistic-lab feasibility study.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Trial
  6. Trial
  7. Trial
  8. Review
  9. Article
  10. Neurofeedback: Applications, advancements, and future directions.PCN reports : psychiatry and clinical neurosciences · 2025
    Review
  11. Article
  12. Article
  13. Mechanisms of brain self-regulation: psychological factors, mechanistic models and neural substrates.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Review
  14. Regulation of craving for real-time fMRI neurofeedback based on individual classification.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Article
  15. Amygdala self-neuromodulation capacity as a window for process-related network recruitment.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

39 authors.

Amelie HauggPsychiatric University Hospital Zurich, University of Zurich, Zürich, Switzerland.ORCID 0000-0002-9583-6585
Ronald SladkyFaculty of Psychology, University of Vienna, Vienna, Austria.
Stavros SkourasDepartment of Biological and Medical Psychology, University of Bergen, Bergen, Norway.
Amalia McDonaldDepartment of Psychology, University of Virginia, Charlottesville, Virginia.
Cameron CraddockDepartment of Diagnostic Medicine, The University of Texas at Austin Dell Medical School, Austin, Texas.
Matthias KirschnerPsychiatric University Hospital Zurich, University of Zurich, Zürich, Switzerland.
Marcus HerdenerPsychiatric University Hospital Zurich, University of Zurich, Zürich, Switzerland.
Yury KoushMagnetic Resonance Research Center, Department of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut.ORCID 0000-0002-3684-5641
Marina PapoutsiUCL Huntington's Disease Centre, Institute of Neurology, University College London, London, England.
Jackob N KeynanFunctional Brain Center, Wohl Institute for Advanced Imaging, Tel-Aviv Sourasky Medical Center, Tel-Aviv University, Tel Aviv, Israel.
Talma HendlerFunctional Brain Center, Wohl Institute for Advanced Imaging, Tel-Aviv Sourasky Medical Center, Tel-Aviv University, Tel Aviv, Israel.
Kathrin Cohen KadoshSchool of Psychology, University of Surrey, Guildford, England.
Catharina ZichWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England.
Jeff MacInnesInstitute for Learning and Brain Sciences, University of Washington, Seattle, Washington.
R Alison AdcockDepartment of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina.
Kathryn DickersonDepartment of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina.
Nan-Kuei ChenDepartment of Biomedical Engineering, University of Arizona, Tucson, Arizona.
Kymberly YoungDepartment of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
Jerzy BodurkaLaureate Institute for Brain Research, Tulsa, Oklahoma.ORCID 0000-0003-0053-9746
Shuxia YaoClinical Hospital of Chengdu the Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0000-0002-5259-6374
Benjamin BeckerClinical Hospital of Chengdu the Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0000-0002-9014-9671
Tibor AuerSchool of Psychology, University of Surrey, Guildford, England.
Renate SchweizerFunctional Imaging Laboratory, German Primate Center, Göttingen, Germany.
Gustavo PamplonaHôpital and Ophtalmique Jules Gonin, University of Lausanne, Lausanne, Switzerland.ORCID 0000-0002-0278-203X
Kirsten EmmertDepartment of Neurology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany.
Sven HallerRadiology-Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Dimitri Van De VilleCenter for Neuroprosthetics, Ecole Polytechnique Féderale de Lausanne, Lausanne, Switzerland.
Maria-Laura BlefariCenter for Neuroprosthetics, Ecole Polytechnique Féderale de Lausanne, Lausanne, Switzerland.
Dong-Youl KimDepartment of Brain and Cognitive Engineering, Korea University, Seoul, Korea.
Jong-Hwan LeeDepartment of Brain and Cognitive Engineering, Korea University, Seoul, Korea.
Theo MarinsD'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil.
Megumi FukudaSchool of Fundamental Science and Engineering, Waseda University, Tokyo, Japan.ORCID 0000-0002-8608-4756
Bettina SorgerDepartment Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.
Tabea KampDepartment Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.ORCID 0000-0002-4868-3248
Sook-Lei LiewDivision of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, California.
Ralf VeitInstitute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich, University of Tübingen, Tübingen, Germany.
Maartje SpetterSchool of Psychology, University of Birmingham, Birmingham, England.
Nikolaus WeiskopfMax Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Frank ScharnowskiPsychiatric University Hospital Zurich, University of Zurich, Zürich, Switzerland.

Funding

Forschungskredit of the University of Zurich FK-18-030Foundation for Research in Science and the Humanities at the University of Zurich STWF-17-012Medical Research Council MR/L012936/1Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 100014_178841Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 32003B_166566Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung BSSG10_155915
6 · The paper itself

Abstract

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.

Indexed as

Brain MappingMagnetic Resonance ImagingPractice, PsychologicalAdultBrainHumansNeurofeedbackPrognosisfMRIfunctional neuroimaginglearningmeta-analysisneurofeedbackreal-time fMRI

Identifiers

PMID32729652
PMCPMC7469782

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.