Evidence map›Paper›PMID 42088684›Full record

ArticleFrontiers in psychology2026

Motor imagery and resistance training improve strength in older adults through distinct effects on agonist-antagonist coordination.

Wan X Yao, Bernadett Mamone, Yuntao Wu, Bo Y Jiang, John Q Zhang, Jianmin Guan, Guang H Yue

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Wan X YaoDepartment of Kinesiology, College for Health, Community and Policy, University of Texas at San Antonio, San Antonio, TX, United States.
Bernadett MamoneNeurelis Inc., San Diego, CA, United States.
Yuntao WuBeijing Rehabilitation Medicine Academy, Capital Medical University, Beijing, China.
Bo Y JiangChangchun Kuancheng District Centers for Disease Control and Prevention and Health Inspection Institute, Jilin, China.
John Q ZhangDepartment of Kinesiology, College for Health, Community and Policy, University of Texas at San Antonio, San Antonio, TX, United States.
Jianmin GuanDepartment of Kinesiology, College for Health, Community and Policy, University of Texas at San Antonio, San Antonio, TX, United States.
Guang H YueCenter for Mobility and Rehabilitation Engineering, Kessler Foundation, West Orange, NJ, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Age-related declines in muscle strength are partly attributable to altered neural drive and agonist-antagonist coordination. This study aimed to evaluate the effects of motor imagery training (MIT) on maximal force production and neuromuscular activation patterns in healthy older adults, with conventional strength training (CST) included as a reference intervention. Methods: Thirty-two right-handed older adults were randomly assigned to an 8-week MIT ( Results: Both MIT and CST significantly increased maximal force compared with CTRL ( Conclusion: Both MIT and CST were associated with improvements in strength and coordination efficiency in older adults. Exploratory findings further suggest that strength gains may be more closely aligned with changes in relative agonist-antagonist coordination than with changes in absolute antagonist activation. Exploratory agonist EMG analysis further provides context suggesting that increased agonist activation may contribute, at least in part, to the observed coordination changes. These findings are consistent with a contribution of neural mechanisms, although direct neurophysiological measures are needed to confirm the underlying processes. Motor imagery training may therefore represent a viable low-load strategy for neuromuscular rehabilitation in aging populations.

Indexed as

agingantagonist muscle activationco-contractionmotor imagery trainingneuromuscular contrololder adultsrehabilitationstrength training

Identifiers

PMID42088684
PMCPMC13135940

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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.