TY - JOUR
T1 - Between-Frequency Topographical and Dynamic High-Order Functional Connectivity for Driving Drowsiness Assessment
AU - Harvy, Jonathan
AU - Thakor, Nitish
AU - Bezerianos, Anastasios
AU - Li, Junhua
N1 - Funding Information:
Manuscript received June 29, 2018; revised November 21, 2018; accepted January 3, 2019. Date of publication January 21, 2019; date of current version March 22, 2019. This work was supported in part by the National Natural Science Foundation of China under Grant 61806149, in part by the Ministry of Education of Singapore under Grant MOE2014-T2-1-115, and in part by the NUS Startup under Grant R-719-000-200-133. (Corresponding author: Junhua Li.) J. Harvy, N. Thakor, and A. Bezerianos are with the Singapore Institute for Neurotechnology, National University of Singapore, Singapore 117456.
Publisher Copyright:
© 2001-2011 IEEE.
PY - 2019/3
Y1 - 2019/3
N2 - Previous studies exploring driving drowsiness utilized spectral power and functional connectivity without considering between-frequency and more complex synchronizations. To complement such lacks, we explored inter-regional synchronizations based on the topographical and dynamic properties between frequency bands using high-order functional connectivity (HOFC) and envelope correlation. We proposed the dynamic interactions of HOFC, associated-HOFC, and a global metric measuring the aggregated effect of the functional connectivity. The EEG dataset was collected from 30 healthy subjects, undergoing two driving sessions. The two-session setting was employed for evaluating the metric reliability across sessions. Based on the results, we observed reliably significant metric changes, mainly involving the alpha band. In HOFCθ α HOFC α β associated-HOFC θ α , and associated-HOFC α β the connection-level metrics in frontal-central, central-central, and central-parietal/occipital areas were significantly increased, indicating a dominance in the central region. Similar results were also obtained in the HOFC θ α β and aHOFC θ α β. For dynamic-low-order-FC and dynamic-HOFC, the global metrics revealed a reliably significant increment in the alpha, theta-alpha, and alpha-beta bands. Modularity indexes of associated-HOFCα and associated-HOFC θ α also exhibited reliably significant differences. This paper demonstrated that within-band and between-frequency topographical and dynamic FC can provide complementary information to the traditional individual-band LOFC for assessing driving drowsiness.
AB - Previous studies exploring driving drowsiness utilized spectral power and functional connectivity without considering between-frequency and more complex synchronizations. To complement such lacks, we explored inter-regional synchronizations based on the topographical and dynamic properties between frequency bands using high-order functional connectivity (HOFC) and envelope correlation. We proposed the dynamic interactions of HOFC, associated-HOFC, and a global metric measuring the aggregated effect of the functional connectivity. The EEG dataset was collected from 30 healthy subjects, undergoing two driving sessions. The two-session setting was employed for evaluating the metric reliability across sessions. Based on the results, we observed reliably significant metric changes, mainly involving the alpha band. In HOFCθ α HOFC α β associated-HOFC θ α , and associated-HOFC α β the connection-level metrics in frontal-central, central-central, and central-parietal/occipital areas were significantly increased, indicating a dominance in the central region. Similar results were also obtained in the HOFC θ α β and aHOFC θ α β. For dynamic-low-order-FC and dynamic-HOFC, the global metrics revealed a reliably significant increment in the alpha, theta-alpha, and alpha-beta bands. Modularity indexes of associated-HOFCα and associated-HOFC θ α also exhibited reliably significant differences. This paper demonstrated that within-band and between-frequency topographical and dynamic FC can provide complementary information to the traditional individual-band LOFC for assessing driving drowsiness.
KW - EEG
KW - High-order functional connectivity
KW - between-frequency connectivity
KW - driving drowsiness
KW - dynamic connectivity
KW - supra-adjacency matrix
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U2 - 10.1109/TNSRE.2019.2893949
DO - 10.1109/TNSRE.2019.2893949
M3 - Article
C2 - 30668477
AN - SCOPUS:85060916453
SN - 1534-4320
VL - 27
SP - 358
EP - 367
JO - IEEE Transactions on Neural Systems and Rehabilitation Engineering
JF - IEEE Transactions on Neural Systems and Rehabilitation Engineering
IS - 3
M1 - 8620342
ER -