Evidence map›Paper›PMID 33400306›Full record

ArticleHuman brain mapping2021

Putamen volume predicts real-time fMRI neurofeedback learning success across paradigms and neurofeedback target regions.

Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, Keith M Kendrick, Huafu Chen, Klaus Mathiak, Benjamin Becker

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Human brain mapping, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06866028 (Enhancing Emotion Regulation Through fNIRS-informed Real-time Neurofeedback), which is not on this map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 6% of its field
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.

NCT06866028 narecruitingnot on this mapstarted 2024, after this paper: background citation

Enhancing Emotion Regulation Through fNIRS-informed Real-time Neurofeedback

TypeinterventionalSponsorUniversity of Electronic Science and Technology of ChinaRan2024 to 2026Enrolled50ConditionsNeurofeedback, Emotion Regulation, StressArmsReal-time fNIRS neurofeedback from Turbo-Satori, Yoked sham feedback from Turbo-Satori
3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.

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  6. 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
  7. 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
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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

9 authors at 2 institutions in 3 countries.

Zhiying ZhaoDepartment of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut, USA.ORCID 0000-0002-0369-1308
Shuxia YaoThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0000-0002-5259-6374
Jana ZweeringsDepartment of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, Germany.ORCID 0000-0002-5724-1054
Xinqi ZhouThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0000-0002-5032-9141
Feng ZhouThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0000-0002-4509-4026
Keith M KendrickThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0000-0002-0371-5904
Huafu ChenThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0000-0002-4062-4753
Klaus MathiakDepartment of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, Germany.
Benjamin BeckerThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.ORCID 0000-0002-9014-9671
University of Electronic Science and Technology of China · CNUniversitätsklinikum Aachen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Real-time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in learning success and treatment response have been observed, yet the neural substrates underlying the learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for learning success with pooled data from three real-time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback learning success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with learning success independent of specific aspects of the experimental design. Given the role of the putamen in associative learning this finding may reflect an important role of instrumental learning processes and brain structural variations in associated brain regions for successful acquisition of fMRI neurofeedback-guided self-regulation.

Indexed as

ConnectomeSelf-ControlAdultCerebral CortexDatasets as TopicFemaleFunctional NeuroimagingHumansLearningMagnetic Resonance ImagingMaleNerve NetNeurofeedbackPutamenYoung Adultbrain morphometryinstrumental learningneurofeedbackreal-time fMRIstriatum

Identifiers

PMID33400306
PMCPMC7978128
OpenAlexW3119183813

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.