Evidence map›Paper›PMID 40102969›Full record

ArticleJournal of neuroengineering and rehabilitation2025

Investigating the cortical effect of false positive feedback on motor learning in motor imagery based rehabilitative BCI training.

Hojun Jeong, Minsu Song, Sung-Ho Jang, Jonghyun Kim

Abstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Hojun JeongSchool of Mechanical Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea.
Minsu SongDepartment of Psychology, University of British Columbia, Vancouver, V6T 1Z4, Canada.
Sung-Ho JangDepartment of Physical Medicine and Rehabilitation, College of Medicine, Yeungnam University, Daegu, 42415, Republic of Korea.
Jonghyun KimSchool of Mechanical Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea. jonghyunkim@skku.edu.

Funding

National Research Foundation of Korea 2022 R1 A2 C1008150Translational Research Program for Rehabilitation Robots NRCTR-EX23004
6 · The paper itself

Abstract

backgroundMotor imagery-based brain-computer interface (MI-BCI) is a promising solution for neurorehabilitation. Many studies proposed that reducing false positive (FP) feedback is crucial for inducing neural plasticity by BCI technology. However, the effect of FP feedback on cortical plasticity induction during MI-BCI training is yet to be investigated.

objectiveThis study aims to validate the hypothesis that FP feedback affects the cortical plasticity of the user's MI during MI-BCI training by first comparing two different asynchronous MI-BCI paradigms (with and without FP feedback), and then comparing its effectiveness with that of conventional motor learning methods (passive and active training).

methodsTwelve healthy volunteers and four patients with stroke participated in the study. We implemented two electroencephalogram-driven asynchronous MI-BCI systems with different feedback conditions. The feedback was provided by a hand exoskeleton robot performing hand open/close task. We assessed the hemodynamic responses in two different feedback conditions and compared them with two conventional motor learning methods using functional near-infrared spectroscopy with an event-related design. The cortical effects of FP feedback were analyzed in different paradigms, as well as in the same paradigm via statistical analysis.

resultsThe MI-BCI without FP feedback paradigm induced higher cortical activation in MI, focusing on the contralateral motor area, compared to the paradigm with FP feedback. Additionally, within the same paradigm providing FP feedback, the task period immediately following FP feedback elicited a lower hemodynamic response in the channel located over the contralateral motor area compared to the MI-BCI paradigm without FP feedback (p = 0.021 for healthy people; p = 0.079 for people with stroke). In contrast, task trials where there was no FP feedback just before showed a higher hemodynamic response, similar to the MI-BCI paradigm without FP feedback (p = 0.099 for healthy people, p = 0.084 for people with stroke).

conclusionsFP feedback reduced cortical activation for the users during MI-BCI training, suggesting a potential negative effect on cortical plasticity. Therefore, minimizing FP feedback may enhance the effectiveness of rehabilitative MI-BCI training by promoting stronger cortical activation and plasticity, particularly in the contralateral motor area.

Indexed as

Brain-Computer InterfacesImaginationLearningMotor CortexStroke RehabilitationAdultElectroencephalographyFalse Positive ReactionsFemaleHumansMaleMiddle AgedNeuronal PlasticitySpectroscopy, Near-InfraredStrokeYoung AdultBrain–computer interfacesEvent-related designFeedbackMotor imageryMotor learningNear-infrared spectroscopy

Identifiers

PMID40102969
PMCPMC11916930

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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.