Evidence map›Paper›PMID 27272616›Full record

ArticleHuman brain mapping2016

How feedback, motor imagery, and reward influence brain self-regulation using real-time fMRI.

Pradyumna Sepulveda, Ranganatha Sitaram, Mohit Rana, Cristian Montalba, Cristian Tejos, Sergio Ruiz

Abstract read
In one paragraph

Article in Human brain mapping, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 6 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

46 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  6. The potential of real-time fMRI neurofeedback for stroke rehabilitation: A systematic review.Cortex; a journal devoted to the study of the nervous system and behavior · 2018
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  18. 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
  19. Online self-evaluation of fMRI-based neurofeedback performance.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
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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

6 authors.

Pradyumna SepulvedaBiomedical Imaging Center, Pontificia Universidad Católica De Chile, Santiago, Chile.
Ranganatha SitaramLaboratory of Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica De Chile, Santiago, Chile.
Mohit RanaLaboratory of Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica De Chile, Santiago, Chile.
Cristian MontalbaBiomedical Imaging Center, Pontificia Universidad Católica De Chile, Santiago, Chile.
Cristian TejosBiomedical Imaging Center, Pontificia Universidad Católica De Chile, Santiago, Chile.
Sergio RuizLaboratory of Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica De Chile, Santiago, Chile.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The learning process involved in achieving brain self-regulation is presumed to be related to several factors, such as type of feedback, reward, mental imagery, duration of training, among others. Explicitly instructing participants to use mental imagery and monetary reward are common practices in real-time fMRI (rtfMRI) neurofeedback (NF), under the assumption that they will enhance and accelerate the learning process. However, it is still not clear what the optimal strategy is for improving volitional control. We investigated the differential effect of feedback, explicit instructions and monetary reward while training healthy individuals to up-regulate the blood-oxygen-level dependent (BOLD) signal in the supplementary motor area (SMA). Four groups were trained in a two-day rtfMRI-NF protocol: GF with NF only, GF,I with NF + explicit instructions (motor imagery), GF,R with NF + monetary reward, and GF,I,R with NF + explicit instructions (motor imagery) + monetary reward. Our results showed that GF increased significantly their BOLD self-regulation from day-1 to day-2 and GF,R showed the highest BOLD signal amplitude in SMA during the training. The two groups who were instructed to use motor imagery did not show a significant learning effect over the 2 days. The additional factors, namely motor imagery and reward, tended to increase the intersubject variability in the SMA during the course of training. Whole brain univariate and functional connectivity analyses showed common as well as distinct patterns in the four groups, representing the varied influences of feedback, reward, and instructions on the brain. Hum Brain Mapp 37:3153-3171, 2016. © 2016 Wiley Periodicals, Inc.

Indexed as

RewardAdolescentAdultBrainBrain MappingHumansImagery, PsychotherapyLearningMagnetic Resonance ImagingMaleNeurofeedbackYoung Adultlearningmental strategymotor imageryneurofeedbackreal-time fMRIreward

Identifiers

PMID27272616
PMCPMC6867497

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.