TY - GEN
T1 - Mining cross-frequency coupling microstates (CFCμstates) from EEG recordings during resting state and mental arithmetic tasks
AU - Dimitriadis, Stavros I.
AU - Sun, Yu
AU - Thakor, Nitish
AU - Bezerianos, Anastasios
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/10/13
Y1 - 2016/10/13
N2 - The functional brain connectivity has been studied by analyzing synchronization between dynamic oscillations of identical frequency or between different frequencies of distinct brain areas. It has been hypothesized that cross-frequency coupling (CFC) between different frequency bands is the carrier mechanism for the coordination of global and local neural processes and hence supports the distributed information processing in the brain. In the present study, we attempt to study the dynamic evolution of CFC at resting-state and during a mental task. The concept of CFC microstates (CFCμstates) is introduced as emerged short-lived patterns of CFC. We analyzed dynamic CFC (dCFC) at resting-state and during a comparison task by adopting a phase-amplitude coupling (PAC) estimator for [δ phase-γ-amplitude] coupling at every sensor. Modifying a well-established framework for mining brain dynamics, we show that a small sized repertoire of CFCμstates can be derived so as to encapsulate connectivity variations and further provide novel insights into network's functional reorganization. By analyzing the transition dynamics among CFCμstates, in both tasks, we provided a clear evidence about intrinsic networks that may play a crucial role in information integration.
AB - The functional brain connectivity has been studied by analyzing synchronization between dynamic oscillations of identical frequency or between different frequencies of distinct brain areas. It has been hypothesized that cross-frequency coupling (CFC) between different frequency bands is the carrier mechanism for the coordination of global and local neural processes and hence supports the distributed information processing in the brain. In the present study, we attempt to study the dynamic evolution of CFC at resting-state and during a mental task. The concept of CFC microstates (CFCμstates) is introduced as emerged short-lived patterns of CFC. We analyzed dynamic CFC (dCFC) at resting-state and during a comparison task by adopting a phase-amplitude coupling (PAC) estimator for [δ phase-γ-amplitude] coupling at every sensor. Modifying a well-established framework for mining brain dynamics, we show that a small sized repertoire of CFCμstates can be derived so as to encapsulate connectivity variations and further provide novel insights into network's functional reorganization. By analyzing the transition dynamics among CFCμstates, in both tasks, we provided a clear evidence about intrinsic networks that may play a crucial role in information integration.
KW - Cross frequency coupling
KW - Default mode network
KW - Delta
KW - Gamma
KW - Hierarchical organization
KW - Microstates
KW - Resting state
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U2 - 10.1109/EMBC.2016.7591976
DO - 10.1109/EMBC.2016.7591976
M3 - Conference contribution
C2 - 28269507
AN - SCOPUS:85009104595
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 5517
EP - 5520
BT - 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Y2 - 16 August 2016 through 20 August 2016
ER -