Between-Frequency Topographical and Dynamic High-Order Functional Connectivity for Driving Drowsiness Assessment

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 f...

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Published inIEEE transactions on neural systems and rehabilitation engineering Vol. 27; no. 3; pp. 358 - 367
Main Authors Harvy, Jonathan, Thakor, Nitish, Bezerianos, Anastasios, Li, Junhua
Format Journal Article
LanguageEnglish
Published United States IEEE 01.03.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN1534-4320
1558-0210
1558-0210
DOI10.1109/TNSRE.2019.2893949

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Abstract 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 HOFC θα , HOFC αβ , associated-HOFC θα , and associatedHOFC αβ , the connection-level metrics in frontal-central, central-central,and central-parietal/occipitalareas were significantly increased, indicating a dominance in the central region. Similar results were also obtained in the HOFC θαβ and aHOFC θαβ . For dynamic-low-order-FC and dynamicHOFC, the global metrics revealed a reliably significant increment in the alpha, theta-alpha, and alpha-beta bands. Modularity indexes of associated-HOFC α and associatedHOFC θα also exhibited reliably significant differences. This paper demonstrated that within-band and betweenfrequency topographical and dynamic FC can provide complementary information to the traditional individual-band LOFC for assessing driving drowsiness.
AbstractList 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 [Formula Omitted], [Formula Omitted], associated-[Formula Omitted], and associated-[Formula Omitted], 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 [Formula Omitted] and [Formula Omitted]. 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-[Formula Omitted] and associated-[Formula Omitted] 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.
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 HOFC θα , HOFC αβ , associated-HOFC θα , and associatedHOFC αβ , the connection-level metrics in frontal-central, central-central,and central-parietal/occipitalareas were significantly increased, indicating a dominance in the central region. Similar results were also obtained in the HOFC θαβ and aHOFC θαβ . For dynamic-low-order-FC and dynamicHOFC, the global metrics revealed a reliably significant increment in the alpha, theta-alpha, and alpha-beta bands. Modularity indexes of associated-HOFC α and associatedHOFC θα also exhibited reliably significant differences. This paper demonstrated that within-band and betweenfrequency topographical and dynamic FC can provide complementary information to the traditional individual-band LOFC for assessing driving drowsiness.
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 HOFC , HOFC , associated- HOFC , and associated- HOFC , 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 and aHOFC . 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- HOFC and associated- HOFC 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.
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 HOFCθα , HOFCαβ , associated- HOFCθα , and associated- HOFCαβ , 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 HOFCθαβ and aHOFCθαβ . 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- HOFCθα 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.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 HOFCθα , HOFCαβ , associated- HOFCθα , and associated- HOFCαβ , 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 HOFCθαβ and aHOFCθαβ . 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- HOFCθα 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.
Author Thakor, Nitish
Bezerianos, Anastasios
Harvy, Jonathan
Li, Junhua
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Snippet Previous studies exploring driving drowsiness utilized spectral power and functional connectivity without considering between-frequency and more complex...
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SubjectTerms Adult
Alpha Rhythm - physiology
Automobile Driving - psychology
Automobiles
Beta Rhythm - physiology
between-frequency connectivity
Cerebral Cortex - physiology
Coherence
Correlation
driving drowsiness
Drowsiness
dynamic connectivity
EEG
Electroencephalography
Electroencephalography - methods
Fatigue
Female
Frequencies
Healthy Volunteers
High-order functional connectivity
Humans
Male
Modularity
Neural Pathways - physiology
Reliability
Reliability analysis
Reproducibility of Results
Sleepiness
supra-adjacency matrix
Theta Rhythm - physiology
Young Adult
Title Between-Frequency Topographical and Dynamic High-Order Functional Connectivity for Driving Drowsiness Assessment
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Volume 27
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