Evidence map›Paper›PMID 41382998›Full record

ArticleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences2025

[Prospects and technical challenges of non-invasive brain-computer interfaces in manned space missions].

Yumeng Ju, Jiajun Liu, Zejun Li, Yiming Liu, Hairuo He, Jin Liu, Bangshan Liu, Mi Wang, Yan Zhang

Abstract readEnglish Abstract
In one paragraph

Article in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences, 2025. 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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0cells of the map it votes in
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

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

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

9 authors.

Yumeng JuDepartment of Psychiatry, Second Xiangya Hospital, Central South University, Changsha 410011. yumeng.ju@csu.edu.cn.
Jiajun LiuDepartment of Psychiatry, Second Xiangya Hospital, Central South University, Changsha 410011.
Zejun LiDepartment of Psychiatry, Second Xiangya Hospital, Central South University, Changsha 410011.
Yiming LiuDepartment of Psychiatry, Second Xiangya Hospital, Central South University, Changsha 410011.
Hairuo HeDepartment of Psychiatry, Second Xiangya Hospital, Central South University, Changsha 410011.
Jin LiuDepartment of Psychiatry, Second Xiangya Hospital, Central South University, Changsha 410011.
Bangshan LiuDepartment of Psychiatry, Second Xiangya Hospital, Central South University, Changsha 410011.
Mi WangDepartment of Psychiatry, Second Xiangya Hospital, Central South University, Changsha 410011.
Yan ZhangDepartment of Psychiatry, Second Xiangya Hospital, Central South University, Changsha 410011. yan.zhang@csu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During long-duration manned space missions, the complex and extreme space environment exerts significant impacts on astronauts' physiological, psychological, and cognitive functions, thereby posing direct risks to mission safety and operational efficiency. As a key bridge between the brain and external devices, brain-computer interface (BCI) technology enables precise acquisition and interpretation of neural signals, offering a novel paradigm for human-machine collaboration in manned spaceflight. Non-invasive BCI technology shows broad application prospects across astronaut selection, mission training, in-orbit task execution, and post-mission rehabilitation. During mission preparation, multimodal signal assessment and neurofeedback training based on BCI can effectively enhance cognitive performance and psychological resilience. During mission execution, BCI can provide real-time monitoring of physiological and psychological states and enable intention-based device control, thereby improving operational efficiency and safety. In the post-mission rehabilitation phase, non-invasive BCI combined with neuromodulation may improve emotional and cognitive functions, support motor and cognitive recovery, and contribute to long-term health management. However, the application of BCI in space still faces challenges, including insufficient signal robustness, limited system adaptability, and suboptimal data processing efficiency. Looking forward, integrating multimodal physiological sensors with deep learning algorithms to achieve accurate monitoring and individualized intervention, and combining BCI with virtual reality and robotics to develop intelligent human-machine collaboration models, will provide more efficient support for space missions.

Indexed as

AstronautsBrain-Computer InterfacesSpace FlightCognitionElectroencephalographyHumansMan-Machine SystemsNeurofeedbackaerospaceastronautbrain-computer interfacecognitionneuromodulation

Identifiers

PMID41382998
PMCPMC12723256

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.