Improving SSVEP-BCI performance through repetitive anodal tDCS-based neuromodulation: insights from fractal EEG and brain functional connectivity
This study embarks on a comprehensive investigation of the effectiveness of repetitive transcranial direct current stimulation (tDCS)-based neuromodulation in augmenting steady-state visual evoked potential (SSVEP) brain-computer interfaces (BCIs), alongside exploring pertinent electroencephalograph...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
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2024
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| Online Access: | https://hdl.handle.net/10356/179982 |
| _version_ | 1811681646154350592 |
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| author | Zhang, Shangen Cui, Hongyan Li, Yong Chen, Xiaogang Gao, Xiaorong Guan, Cuntai |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Zhang, Shangen Cui, Hongyan Li, Yong Chen, Xiaogang Gao, Xiaorong Guan, Cuntai |
| author_sort | Zhang, Shangen |
| collection | NTU |
| description | This study embarks on a comprehensive investigation of the effectiveness of repetitive transcranial direct current stimulation (tDCS)-based neuromodulation in augmenting steady-state visual evoked potential (SSVEP) brain-computer interfaces (BCIs), alongside exploring pertinent electroencephalography (EEG) biomarkers for assessing brain states and evaluating tDCS efficacy. EEG data were garnered across three distinct task modes (eyes open, eyes closed, and SSVEP stimulation) and two neuromodulation patterns (sham-tDCS and anodal-tDCS). Brain arousal and brain functional connectivity were measured by extracting features of fractal EEG and information flow gain, respectively. Anodal-tDCS led to diminished offsets and enhanced information flow gains, indicating improvements in both brain arousal and brain information transmission capacity. Additionally, anodal-tDCS markedly enhanced SSVEP-BCIs performance as evidenced by increased amplitudes and accuracies, whereas sham-tDCS exhibited lesser efficacy. This study proffers invaluable insights into the application of neuromodulation methods for bolstering BCI performance, and concurrently authenticates two potent electrophysiological markers for multifaceted characterization of brain states. |
| first_indexed | 2024-10-01T03:44:15Z |
| format | Journal Article |
| id | ntu-10356/179982 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:44:15Z |
| publishDate | 2024 |
| record_format | dspace |
| spelling | ntu-10356/1799822024-09-13T15:36:37Z Improving SSVEP-BCI performance through repetitive anodal tDCS-based neuromodulation: insights from fractal EEG and brain functional connectivity Zhang, Shangen Cui, Hongyan Li, Yong Chen, Xiaogang Gao, Xiaorong Guan, Cuntai School of Computer Science and Engineering Computer and Information Science Transcranial direct current stimulation Brain-computer interface This study embarks on a comprehensive investigation of the effectiveness of repetitive transcranial direct current stimulation (tDCS)-based neuromodulation in augmenting steady-state visual evoked potential (SSVEP) brain-computer interfaces (BCIs), alongside exploring pertinent electroencephalography (EEG) biomarkers for assessing brain states and evaluating tDCS efficacy. EEG data were garnered across three distinct task modes (eyes open, eyes closed, and SSVEP stimulation) and two neuromodulation patterns (sham-tDCS and anodal-tDCS). Brain arousal and brain functional connectivity were measured by extracting features of fractal EEG and information flow gain, respectively. Anodal-tDCS led to diminished offsets and enhanced information flow gains, indicating improvements in both brain arousal and brain information transmission capacity. Additionally, anodal-tDCS markedly enhanced SSVEP-BCIs performance as evidenced by increased amplitudes and accuracies, whereas sham-tDCS exhibited lesser efficacy. This study proffers invaluable insights into the application of neuromodulation methods for bolstering BCI performance, and concurrently authenticates two potent electrophysiological markers for multifaceted characterization of brain states. Published version This work was supported in part by the National Key Research and Development Program of China under Grant 2022YFC3602803, in part by the National Natural Science Foundation of China under Grant U2241208 and Grant 62171473, in part by the Fundamental Research Funds for the Central Universities of China under Grant FRF-TP-20-017A1 and Grant 3332023170, and in part by Tianjin Municipal Science and Technology Plan Project under Grant 21JCYBJC01500. 2024-09-09T02:13:11Z 2024-09-09T02:13:11Z 2024 Journal Article Zhang, S., Cui, H., Li, Y., Chen, X., Gao, X. & Guan, C. (2024). Improving SSVEP-BCI performance through repetitive anodal tDCS-based neuromodulation: insights from fractal EEG and brain functional connectivity. IEEE Transactions On Neural Systems and Rehabilitation Engineering, 32, 1647-1656. https://dx.doi.org/10.1109/TNSRE.2024.3389051 1558-0210 https://hdl.handle.net/10356/179982 10.1109/TNSRE.2024.3389051 38625770 2-s2.0-85190730749 32 1647 1656 en IEEE Transactions on Neural Systems and Rehabilitation Engineering © 2024 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/. application/pdf |
| spellingShingle | Computer and Information Science Transcranial direct current stimulation Brain-computer interface Zhang, Shangen Cui, Hongyan Li, Yong Chen, Xiaogang Gao, Xiaorong Guan, Cuntai Improving SSVEP-BCI performance through repetitive anodal tDCS-based neuromodulation: insights from fractal EEG and brain functional connectivity |
| title | Improving SSVEP-BCI performance through repetitive anodal tDCS-based neuromodulation: insights from fractal EEG and brain functional connectivity |
| title_full | Improving SSVEP-BCI performance through repetitive anodal tDCS-based neuromodulation: insights from fractal EEG and brain functional connectivity |
| title_fullStr | Improving SSVEP-BCI performance through repetitive anodal tDCS-based neuromodulation: insights from fractal EEG and brain functional connectivity |
| title_full_unstemmed | Improving SSVEP-BCI performance through repetitive anodal tDCS-based neuromodulation: insights from fractal EEG and brain functional connectivity |
| title_short | Improving SSVEP-BCI performance through repetitive anodal tDCS-based neuromodulation: insights from fractal EEG and brain functional connectivity |
| title_sort | improving ssvep bci performance through repetitive anodal tdcs based neuromodulation insights from fractal eeg and brain functional connectivity |
| topic | Computer and Information Science Transcranial direct current stimulation Brain-computer interface |
| url | https://hdl.handle.net/10356/179982 |
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