Evidence map›Paper›PMID 39104677›Full record

ArticleCognitive neurodynamics2024

A delayed matching task-based study on action sequence of motor imagery.

Mengfan Li, Enming Qi, Guizhi Xu, Jing Jin, Qi Zhao, Miaomiao Guo, Wenzhe Liao

Abstract read
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In one paragraph

Article in Cognitive neurodynamics, 2024. 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

The trial behind it

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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

Who cites it

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No citing paper in PubMed yet.

4 · The record

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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.

Mengfan LiState Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin, 300132 China.ORCID 0000-0003-1501-9516
Enming QiState Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin, 300132 China.
Guizhi XuState Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin, 300132 China.
Jing JinKey Laboratory of Advanced Control and Optimization for Chemical Processes, East China, University of Science and Technology, Shanghai, 518063 China.
Qi ZhaoState Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin, 300132 China.
Miaomiao GuoState Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin, 300132 China.
Wenzhe LiaoSchool of Artificial Intelligence, Hebei University of Technology, Tianjin, 300132 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The way people imagine greatly affects performance of brain-computer interface (BCI) based on motion imagery (MI). Action sequence is a basic unit of imitation, learning, and memory for motor behavior. Whether it influences the MI-BCI is unknown, and how to manifest this influence is difficult since the MI is a spontaneous brain activity. To investigate the influence of the action sequence, this study proposes a novel paradigm named action sequences observing and delayed matching task to use images and videos to guide people to observe, match and reinforce the memory of sequence. Seven subjects' ERPs and MI performance are analyzed under four different levels of complexities or orders of the sequence. Results demonstrated that the action sequence in terms of complexity and sequence order significantly affects the MI. The complex action in positive order obtains stronger ERD/ERS and more pronounced MI feature distributions, and yields an MI classification accuracy that is 12.3% higher than complex action in negative order (

Indexed as

Action observationAction sequenceBrain-computer interfaceEvent-related potentialMotor imagery

Identifiers

PMID39104677
PMCPMC11297855

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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.