Evidence map›Paper›PMID 41913234›Full record

Trial reportJournal of neuroengineering and rehabilitation2026

The reorganization mechanism of brain functional networks by long term actual exercise and exercise imagination training: spectrum and network topology analysis based on EEG.

Jinglong Wu, Wangjun Zou, Jinyan Zhang, Binbin Gao, Ruiqing Li, Zhilin Zhang, Jian Zhang, Tianyi Yan

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of neuroengineering and rehabilitation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

8 authors.

Jinglong WuSchool of Medical Technology, Beijing Institute of Technology, Beijing, China.
Wangjun ZouSchool of Medical Technology, Beijing Institute of Technology, Beijing, China.
Jinyan ZhangSchool of Mechatronics Engineering, Beijing Institute of Technology, Beijing, China.
Binbin GaoSchool of Life Science, Beijing Institute of Technology, Beijing, China.
Ruiqing LiSchool of Medical Technology, Beijing Institute of Technology, Beijing, China.
Zhilin ZhangResearch Center for Medical Artificial Intelligence, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Jian ZhangSchool of Medical Technology, Beijing Institute of Technology, Beijing, China. zhangjian2023@bit.edu.cn.
Tianyi YanSchool of Medical Technology, Beijing Institute of Technology, Beijing, China. yantianyi@bit.edu.cn.

Funding

Beijing Nova Program No. 20230484465National Natural Science Foundation of China 62306035National Natural Science Foundation of China 62336002National Natural Science Foundation of China 62373056Shenzhen Basic Research Program JCYJ20241202124804007Shenzhen Basic Research Program JCYJ20241202124859016STI 2030-Major Projects No. 2022ZD0208500
6 · The paper itself

Abstract

backgroundMotor learning optimizes motor skills and promotes neuroplasticity through motor execution (ME) and motor imagery (MI). However, the mechanisms underlying long-term training-induced reorganization of functional brain networks remain unclear. Existing studies predominantly focus on short-term effects, and their analytical methods are limited to spectral properties, with insufficient exploration of complex network interactions. Elucidating differential regulation of functional brain networks by different training modes is important for understanding the characteristics of motor learning stages and optimizing rehabilitation strategies.

methodsThis randomized controlled trial compares seven-day ME and MI training effects on cortical reorganization and behavioral performance. Forty-eight healthy right-handed participants were randomly assigned to four groups: ball rotation task (BRT), video guide imagery (VGI), tactile stimulation (Tactile), and control group (Control). All groups underwent a one-week training intervention. Behavioral performance was quantified by ball-rotation scores, while brain function was evaluated using resting-state electroencephalography (EEG) pre- and post-training. Power spectral density (PSD) in theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) bands, phase-lag index (PLI) connectivity, and graph-theoretical metrics (clustering coefficient, node degree) were analyzed. Statistical comparisons used paired t-tests, ANOVA, Kruskal–Wallis tests and post hoc test (α = 0.05).

resultsAll groups showed significant motor improvement (p < 0.001), with BRT demonstrating superior gains versus others (F = 32.279, p < 0.001, η2 = 0.6876). Frontal β-band power increased significantly in BRT, suggesting enhanced skill output via neuronal recruitment, whereas VGI exhibited attenuated β-power, indicating optimized neural resource integration. θ-band frontal-parietal functional connectivity was enhanced in both the BRT and the VGI groups, supporting motor-cognitive integration. Parietal β-band connectivity weakened, implying enhanced neural efficiency and reduced visual dependence. α-band clustering coefficients decreased in BRT, indicating network reorganization toward distributed processing, while θ-band frontoparietal node degree increased in VGI, reflecting elevated cognitive control demands.

conclusionME and MI enhance motor skills through distinct network reorganization: ME sustains neuronal recruitment via beta-enhancement and local network dispersion, whereas MI optimizes efficiency through beta-suppression and frontoparietal integration. These frequency-specific mechanisms provide preliminary neurophysiological insights that may inform future development of personalized rehabilitation approaches for motor disorders. Future investigations should validate these findings in clinical populations with motor impairments.

Indexed as

BrainExerciseImaginationNerve NetNeuronal PlasticityAdultElectroencephalographyFemaleHumansMaleMotor SkillsYoung AdultBrain functional networkEEG signalMotor imageryMotor trainingSpectrum analysis

Identifiers

PMID41913234
PMCPMC13159314

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.