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A Pilot Study on Brain Source Localization and Connectivity Analysis with MEG Responses to Unilateral Tactile Stimuli in Healthy Children Using Normalized Principal Component Analysis

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Abstract

Study on the interactions between brain regions during electrophysiological measurements provides deep insights into the mechanisms of brain information processing. However, the strong spatial correlations from background spontaneous activity might mask the local evoked activity and lead to spurious connectivity results in connectivity analysis for event-related EEG and MEG. In this paper, we applied normalized Principal Component Analysis (PCA) preprocessing, Minimum Norm Estimation (MNE) and Granger causal connectivity analysis to identify stimulus-elicited neural sources and measure the effective connectivity among the sources for left somatosensory MEG responses of five healthy subjects. After normalized PCA preprocessing our results demonstrated increased coherences between channels with somatosensory evoked response at major physiological frequency bands, including Alpha and Beta band for somatosensory evoked response. The sources were located at contralateral primary somatosensory cortex, contralateral secondary somatosensory cortex and cingulate cortex. The information flow was processed through a complex pattern of both feedforward and feedback interactions between the sources. Compare with the results without normalized PCA preprocessing, our results are consistent with established connections between somatosensory regions and previous source modeling studies, which provides validation of the proposed approach.

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Acknowledgements

The research was supported by the NIH grants (J. Stephen and T. Zhang - P20AA017068, NCRR P20RR021938, NIGMS P20GM103472), and Suzhou Science and Technology Planning Projects (No.: SYS201510).

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Correspondence to Jue Wang or Julia Stephen.

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Gao, L., Zhang, T., Wang, J. et al. A Pilot Study on Brain Source Localization and Connectivity Analysis with MEG Responses to Unilateral Tactile Stimuli in Healthy Children Using Normalized Principal Component Analysis. J Sign Process Syst 87, 259–267 (2017). https://doi.org/10.1007/s11265-016-1203-9

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  • DOI: https://doi.org/10.1007/s11265-016-1203-9

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