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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/7CD0A576-AC1C-41D8-A513-76D59180FC7E | ||
| Year | 2021 | ||
| Type of Item | Conference Publication | ||
| License |
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| Bibliographic Citation | K. Politof, M. Antonakakis, A. Wollbrink, C. H. Wolters and M. Zervakis, "Reconstruction of the very early thalamo-cortical network with combined EEG and MEG on realistic head modeling," in 2021 10th International IEEE/EMBS Conference on Neural Engineering (NER), Italy, 2021, pp. 371-374, doi: 10.1109/NER49283.2021.9441387. https://doi.org/10.1109/NER49283.2021.9441387 | ||
| Appears in Collections |
The early primary somatosensory network remains a rarely investigated brain area due to the fast transitions among the involved cortical and subcortical regions. In this regard, a non-invasive and subject-specific method that quantifies the very early temporal interdependences in the thalamo-cortical/cortico-cortical pathway of the primary somatosensory network would be of particular significance. Combined electro- (EEG) and magneto- (MEG) encephalography (EMEG) source analysis has been shown to exploit the complementary content of the single modalities EEG and MEG based on subject-specific and realistic head modeling. The current study aims to investigate the connectivity of the very early primary somatosensory network using EMEG source analysis with functionally-based decomposition and time-variant effective connectivity. Three-time temporally determined components are chosen based on the combined somatosensory evoked responses to highlight the thalamo-cortical and cortico-cortical interactions. The results confirm that electrophysiological activity flows from the thalamic regions of the brain to the first tangentially oriented neurological somatosensory brain region (Broadman area 3b, thalamo-cortical connection) and then to the radially-oriented brain region (Broadman area 3a, cortico-cortical connection). We also present that the flows between the investigated components that do not fit to the flow of the neurological activity from the wrist to the somatosensory network, when increasing the confidence interval (CI). Overall, EMEG source analysis with realistic head modeling and a functionally-based connectivity estimator is able to capture very fast transitions on the early-involved somatosensory network.
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