Neuroimaging features for cognitive fatigue and its recovery with VR intervention: An EEG microstates analysis
Introduction: Cognitive fatigue is mainly caused by enduring mental stress or monotonous work, impairing cognitive and physical performance. Natural scene exposure is a promising intervention for relieving cognitive fatigue, but the efficacy of virtual reality (VR) simulated natural scene exposure i...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Brain Research Bulletin |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0361923025000358 |
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| author | Jia-Cheng Han Chi Zhang Yan-Dong Cai Yu-Ting Li Yu-Xuan Shang Zhu-Hong Chen Guan Yang Jia-Jie Song Dan Su Ke Bai Jing-Ting Sun Yu Liu Na Liu Ya Duan Wen Wang |
| author_facet | Jia-Cheng Han Chi Zhang Yan-Dong Cai Yu-Ting Li Yu-Xuan Shang Zhu-Hong Chen Guan Yang Jia-Jie Song Dan Su Ke Bai Jing-Ting Sun Yu Liu Na Liu Ya Duan Wen Wang |
| author_sort | Jia-Cheng Han |
| collection | DOAJ |
| description | Introduction: Cognitive fatigue is mainly caused by enduring mental stress or monotonous work, impairing cognitive and physical performance. Natural scene exposure is a promising intervention for relieving cognitive fatigue, but the efficacy of virtual reality (VR) simulated natural scene exposure is unclear. We aimed to investigate the effect of VR natural scene on cognitive fatigue and further explored its underlying neurophysiological alterations with electroencephalogram (EEG) microstates analysis. Methods: Ten participants performed a 20-minute 1-back task before and after VR intervention while EEG was recorded (pre-task, post-task). Performance was measured with mean accuracy rate (MAR) and mean reaction time (MRT) of the continuous 1-back task. VR simulation of the Canal Town scene was utilized to alleviate cognitive fatigue caused by 1-back tasks. Four resting-state phases were identified: beginning, pre, post, and end phases. Results: Post-task had a higher MAR and a lower MRT than pre-task. For pre-task, MAR was negatively correlated with trials, while MRT was positively correlated with trials. Four EEG microstates classes (A-D) were identified, and their temporal parameters (mean duration, time coverage and occurrence) and transition probabilities were calculated. After intervention, mean duration and time coverage of class B decreased, all parameters of class C increased, while all parameters of class D decreased. Transition probabilities between classes B and D decreased but increased between classes A and C. Conclusion: VR simulation of Canal Town scene is a potentially effective method to alleviate cognitive fatigue. Microstate is an electrophysiological trait characteristic of cognitive fatigue and might be used to indicate the effect of VR intervention. |
| format | Article |
| id | doaj-art-ca09c1c2cafe444fa19c10a58cb3d918 |
| institution | Kabale University |
| issn | 1873-2747 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Brain Research Bulletin |
| spelling | doaj-art-ca09c1c2cafe444fa19c10a58cb3d9182025-02-07T04:46:47ZengElsevierBrain Research Bulletin1873-27472025-02-01221111223Neuroimaging features for cognitive fatigue and its recovery with VR intervention: An EEG microstates analysisJia-Cheng Han0Chi Zhang1Yan-Dong Cai2Yu-Ting Li3Yu-Xuan Shang4Zhu-Hong Chen5Guan Yang6Jia-Jie Song7Dan Su8Ke Bai9Jing-Ting Sun10Yu Liu11Na Liu12Ya Duan13Wen Wang14Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, The Fourth Military Medical University, No. 569 Xinsi Road, Xi’an, Shaanxi 710038, ChinaDepartment of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, The Fourth Military Medical University, No. 569 Xinsi Road, Xi’an, Shaanxi 710038, ChinaSchool of Aerospace Engineering, Tsinghua University, Beijing 100084, China; Airborne Avionics Flight Test Institute, Chinese Flight Test Establishment, Xi’an, Shaanxi 710089, ChinaDepartment of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, The Fourth Military Medical University, No. 569 Xinsi Road, Xi’an, Shaanxi 710038, ChinaDepartment of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, The Fourth Military Medical University, No. 569 Xinsi Road, Xi’an, Shaanxi 710038, ChinaDepartment of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, The Fourth Military Medical University, No. 569 Xinsi Road, Xi’an, Shaanxi 710038, ChinaDepartment of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, The Fourth Military Medical University, No. 569 Xinsi Road, Xi’an, Shaanxi 710038, ChinaDepartment of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, The Fourth Military Medical University, No. 569 Xinsi Road, Xi’an, Shaanxi 710038, ChinaDepartment of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, The Fourth Military Medical University, No. 569 Xinsi Road, Xi’an, Shaanxi 710038, ChinaDepartment of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, The Fourth Military Medical University, No. 569 Xinsi Road, Xi’an, Shaanxi 710038, ChinaDepartment of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, The Fourth Military Medical University, No. 569 Xinsi Road, Xi’an, Shaanxi 710038, ChinaHangzhou Qu’an Technology Co., Ltd, Hangzhou, Zhejiang 310000, ChinaDepartment of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, The Fourth Military Medical University, No. 569 Xinsi Road, Xi’an, Shaanxi 710038, China; Department of Nursing, The Fourth Military Medical University, Xi’an, Shaanxi 710038, China; Correspondence to: Department of Nursing, The Fourth Military Medical University, Xi’an, Shaanxi 710039, China.School of Aerospace Engineering, Tsinghua University, Beijing 100084, China; Airborne Avionics Flight Test Institute, Chinese Flight Test Establishment, Xi’an, Shaanxi 710089, China; Corresponding author at: Airborne Avionics Flight Test Institute, Chinese Flight Test Establishment, Xi’an, Shaanxi 710089, China.Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, The Fourth Military Medical University, No. 569 Xinsi Road, Xi’an, Shaanxi 710038, China; Corresponding author.Introduction: Cognitive fatigue is mainly caused by enduring mental stress or monotonous work, impairing cognitive and physical performance. Natural scene exposure is a promising intervention for relieving cognitive fatigue, but the efficacy of virtual reality (VR) simulated natural scene exposure is unclear. We aimed to investigate the effect of VR natural scene on cognitive fatigue and further explored its underlying neurophysiological alterations with electroencephalogram (EEG) microstates analysis. Methods: Ten participants performed a 20-minute 1-back task before and after VR intervention while EEG was recorded (pre-task, post-task). Performance was measured with mean accuracy rate (MAR) and mean reaction time (MRT) of the continuous 1-back task. VR simulation of the Canal Town scene was utilized to alleviate cognitive fatigue caused by 1-back tasks. Four resting-state phases were identified: beginning, pre, post, and end phases. Results: Post-task had a higher MAR and a lower MRT than pre-task. For pre-task, MAR was negatively correlated with trials, while MRT was positively correlated with trials. Four EEG microstates classes (A-D) were identified, and their temporal parameters (mean duration, time coverage and occurrence) and transition probabilities were calculated. After intervention, mean duration and time coverage of class B decreased, all parameters of class C increased, while all parameters of class D decreased. Transition probabilities between classes B and D decreased but increased between classes A and C. Conclusion: VR simulation of Canal Town scene is a potentially effective method to alleviate cognitive fatigue. Microstate is an electrophysiological trait characteristic of cognitive fatigue and might be used to indicate the effect of VR intervention.http://www.sciencedirect.com/science/article/pii/S0361923025000358EEG microstatescognitive fatiguevirtual realityintervention |
| spellingShingle | Jia-Cheng Han Chi Zhang Yan-Dong Cai Yu-Ting Li Yu-Xuan Shang Zhu-Hong Chen Guan Yang Jia-Jie Song Dan Su Ke Bai Jing-Ting Sun Yu Liu Na Liu Ya Duan Wen Wang Neuroimaging features for cognitive fatigue and its recovery with VR intervention: An EEG microstates analysis Brain Research Bulletin EEG microstates cognitive fatigue virtual reality intervention |
| title | Neuroimaging features for cognitive fatigue and its recovery with VR intervention: An EEG microstates analysis |
| title_full | Neuroimaging features for cognitive fatigue and its recovery with VR intervention: An EEG microstates analysis |
| title_fullStr | Neuroimaging features for cognitive fatigue and its recovery with VR intervention: An EEG microstates analysis |
| title_full_unstemmed | Neuroimaging features for cognitive fatigue and its recovery with VR intervention: An EEG microstates analysis |
| title_short | Neuroimaging features for cognitive fatigue and its recovery with VR intervention: An EEG microstates analysis |
| title_sort | neuroimaging features for cognitive fatigue and its recovery with vr intervention an eeg microstates analysis |
| topic | EEG microstates cognitive fatigue virtual reality intervention |
| url | http://www.sciencedirect.com/science/article/pii/S0361923025000358 |
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