Evidence map›Paper›PMID 26732846›Full record

ArticleFrontiers in human neuroscience2015

Resting and Initial Beta Amplitudes Predict Learning Ability in Beta/Theta Ratio Neurofeedback Training in Healthy Young Adults.

Wenya Nan, Feng Wan, Mang I Vai, Agostinho C Da Rosa

Open access · goldAbstract read
In one paragraph

Article in Frontiers in human neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 22% 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.

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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.

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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

4 authors at 2 institutions in 2 countries.

Wenya NanDepartment of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau Macau, China.
Feng WanDepartment of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau Macau, China.
Mang I VaiDepartment of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau Macau, China.
Agostinho C Da RosaDepartment of Bio Engineering, Instituto Superior Tecnico and Systems and Robotics Institute, University of Lisbon Lisbon, Portugal.
University of Macau · MOUniversity of Lisbon · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neurofeedback (NF) training has been proved beneficial in cognitive and behavioral performance improvement in healthy individuals. Unfortunately, the NF learning ability shows large individual difference and in a number of NF studies there are even some non-learners who cannot successfully self-regulate their brain activity by NF. This study aimed to find out the neurophysiological predictor of the learning ability in up-regulating beta-1 (15-18 Hz)/theta (4-7 Hz) ratio (BTR) training in healthy young adults. Eighteen volunteers finished five training sessions in successive 5 days. We found that low beta (12-15 Hz) amplitude in a 1-min eyes-open resting baseline measured before training and the beta-1 amplitude in the first training block with 4.5-min duration could predict the BTR learning ability across sessions. The results provide a low cost, convenient and easy way to predict the learning ability in up-regulating BTR training, and would be helpful in avoiding potential frustration and adjusting training protocol for the participants with poor learning ability.

Indexed as

beta/theta ratiolearning indicesneurofeedback trainingpredictionself-regulation

Identifiers

PMID26732846
PMCPMC4685657
OpenAlexW2206701894

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.