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Mining cross-frequency coupling microstates from resting state MEG: an application to mild traumatic brain injury

Antonakakis Marios, Dimitriadis Stavros I., Zervakis Michail, Papanicolaou, Andrew C, Zouridakis, George

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URI: http://purl.tuc.gr/dl/dias/2F5B708C-214A-4B4C-A04F-20ABC0C97E04
Έτος 2016
Τύπος Πλήρης Δημοσίευση σε Συνέδριο
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Βιβλιογραφική Αναφορά M. Antonakakis, S. I. Dimitriadis, M. Zervakis, A. C. Papanicolaou and G. Zouridakis, "Mining cross-frequency coupling microstates from resting state MEG: an application to mild traumatic brain injury," in 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016, pp. 5513-5516. doi: 10.1109/EMBC.2016.7591975 https://doi.org/10.1109/EMBC.2016.7591975
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Περίληψη

Recent studies have investigated the possible role of dynamic functional connectivity and the role of cross-frequency coupling (CFC) to provide the substrate for reliable biomarkers of brain disorders. In this study, we analyzed time-varying CFC profiles from resting state Magnetoencephal-ographic recordings of 30 mild Traumatic Brain Injury (mTBI) patients and 50 normal controls. Interactions among sensors at specific pairs of frequency bands were computed via estimation of phase-to-amplitude couplings. We then computed time-varying functional connectivity graphs that were described in terms of segregation (local efficiency, LE) and integration (global efficiency, GE) and mapped those graphs to time series of GE/LE estimates. The resulting dynamic network revealed transitions between a limited number of microstates for mTBI subjects compared to controls. The significant differences in transition probability between the two groups, along with the limited repertoire of possible states, can form the basis for a robust dynamic connectomic biomarker for the diagnosis of mTBI.

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