Abstract
In this paper, we introduce a novel model for establishing brain functional connectivity based on noninvasive Electroencephalogram (EEG) data sources. We reviewed the main methods used in EEG brain functional connectivity, and the current research progress of analyzing EEG datasets. In this paper, we proposed a new model for bridging the missing link between human brain functions and real time brain wave activities. The proposed model combines graph theory/complex network methods with fuzzy logic method to deliver an explicit connection in a real time environment. We conducted the EEG data preprocessing experiments for our new model.
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Acknowledgment
This work is partially supported by Zhejiang Natural Science Fund (LY19F030010), Zhejiang Philosophy and Social Sciences Fund (20NDJC216YB), Ningbo Innovation Team (No. 2016C11024), Ningbo Natural Science Fund (No. 2019A610083), Zhejiang Provincial Education and Science Scheme 2021 (GH2021642).
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Li, Y., Zhang, H., Lu, Y., Tang, H. (2021). A Novel Hybrid Model for Brain Functional Connectivity Based on EEG. In: Mahmud, M., Kaiser, M.S., Vassanelli, S., Dai, Q., Zhong, N. (eds) Brain Informatics. BI 2021. Lecture Notes in Computer Science(), vol 12960. Springer, Cham. https://doi.org/10.1007/978-3-030-86993-9_13
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DOI: https://doi.org/10.1007/978-3-030-86993-9_13
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