Evidence map›Paper›PMID 39555294›Full record

ArticleCognitive neurodynamics2024

Functional connectivity of EEG motor rhythms after spinal cord injury.

Jiancai Leng, Xin Yu, Chongfeng Wang, Jinzhao Zhao, Jianqun Zhu, Xinyi Chen, Zhaoxin Zhu, Xiuquan Jiang, Jiaqi Zhao, Chao Feng and 5 more

Abstract read
PubMed Full text at PMC Publisher
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. Cited by 1 paper.

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

15 authors.

Jiancai Leng *International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China.
Xin Yu *International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China.
Chongfeng WangInternational School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China.
Jinzhao ZhaoInternational School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China.
Jianqun ZhuInternational School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China.
Xinyi ChenInternational School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China.
Zhaoxin ZhuInternational School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China.
Xiuquan JiangInternational School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China.
Jiaqi ZhaoInternational School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China.
Chao FengInternational School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China.
Qingbo YangSchool of Mathematics and Statistics, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China.
Jianfei LiInternational School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China.
Lin JiangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No.2006, Xiyuan Road West Hi-Tech District, Chengdu, 611731 Sichuan China.
Fangzhou XuInternational School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), No.3501, Daxue Road Changqing District, Jinan, 250353 Shandong China.ORCID 0000-0001-7660-1206
Yang ZhangRehabilitation and Physical Therapy Department, Shandong University of Traditional Chinese Medicine Affiliated Hospital, No.42, Wenhuaxi Road Lixia District, Jinan, 250012 Shandong China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spinal cord injury (SCI), which is the injury of the spinal cord site resulting in motor dysfunction, has prompted the use of motor imagery (MI)-based brain computer interface (BCI) systems for motor function reconstruction. However, analyzing electroencephalogram signals and brain function mechanisms for SCI patients is challenging. This is due to their low signal-to-noise ratio and high variability. We propose using the phase locking value (PLV) to construct the brain network in α and β rhythms for both SCI patients and healthy individuals. This approach aims to analyze the changes in brain network connectivity and brain function mechanisms following SCI. The results show that the connection strength of the α rhythm in the healthy control (HC) group is stronger than that in the SCI group, and the connection strength in the β rhythm of the SCI group is stronger than that in the HC group. Moreover, we extract the PLV with common spatial pattern (PLV-CSP) feature from the MI data of the SCI group. The experimental results for 12 SCI patients include that the peak classification accuracy is 100%, and the average accuracy of the ten-fold cross-verification is 95.6%. Our proposed approach can be used as a potential valuable method for SCI pathological studies and MI-based BCI rehabilitation systems.

Indexed as

Brain networkMotor imageryPattern recognitionPhase locking valueSpinal cord injury

Identifiers

PMID39555294
PMCPMC11564577

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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.