Evidence map›Paper›PMID 33580093›Full record

ArticleScientific reports2021

Characterization of kinesthetic motor imagery compared with visual motor imageries.

Yu Jin Yang, Eun Jeong Jeon, June Sic Kim, Chun Kee Chung

Registry-linked trialAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06209801 (Comparison of the Effects of Mirror Therapy Integrated With Electrical Stimulation and Motor Imagery on Cortical Modulations in Patients With Peripheral Nerve Injury and Healthy Adults), which is not on this map. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

NCT06209801 naactive not recruitingnot on this mapstarted 2024, after this paper: background citation

Comparison of the Effects of Mirror Therapy Integrated With Electrical Stimulation and Motor Imagery on Cortical Modulations in Patients With Peripheral Nerve Injury and Healthy Adults

TypeinterventionalSponsorChang Gung Memorial HospitalRan2024 to 2027Enrolled32ConditionsPeripheral Nerve InjuriesArmsMirror therapy, Neuromuscular electrical stimulation, Motor imagery
3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  10. Do menstrual symptoms affect motor imagery skills in young women?Archives of gynecology and obstetrics · 2025
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  11. Motor imagery enhances performance beyond the imagined action.Proceedings of the National Academy of Sciences of the United States of America · 2025
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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.

Yu Jin YangDepartment of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, 08826, Republic of Korea.
Eun Jeong JeonDepartment of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, 08826, Republic of Korea.
June Sic KimDepartment of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, 08826, Republic of Korea. junesic.kim@gmail.com.
Chun Kee ChungDepartment of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, 08826, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motor imagery (MI) is the only way for disabled subjects to robustly use a robot arm with a brain-machine interface. There are two main types of MI. Kinesthetic motor imagery (KMI) is proprioceptive (OR somato-) sensory imagination and Visual motor imagery (VMI) represents a visualization of the corresponding movement incorporating the visual network. Because these imagery tactics may use different networks, we hypothesized that the connectivity measures could characterize the two imageries better than the local activity. Electroencephalography data were recorded. Subjects performed different conditions, including motor execution (ME), KMI, VMI, and visual observation (VO). We tried to classify the KMI and VMI by conventional power analysis and by the connectivity measures. The mean accuracies of the classification of the KMI and VMI were 98.5% and 99.29% by connectivity measures (alpha and beta, respectively), which were higher than those by the normalized power (p < 0.01, Wilcoxon paired rank test). Additionally, the connectivity patterns were correlated between the ME-KMI and between the VO-VMI. The degree centrality (DC) was significantly higher in the left-S1 at the alpha-band in the KMI than in the VMI. The MI could be well classified because the KMI recruits a similar network to the ME. These findings could contribute to MI training methods.

Identifiers

PMID33580093
PMCPMC7881019

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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.