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 in | IEEE transactions on neural systems and rehabilitation engineering Vol. 27; no. 3; pp. 358 - 367 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
01.03.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
ISSN | 1534-4320 1558-0210 1558-0210 |
DOI | 10.1109/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. |
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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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Cites_doi | 10.1109/JBHI.2016.2544061 10.1016/j.biopsycho.2013.11.010 10.1016/j.clinph.2007.04.031 10.1016/S0301-0511(00)00085-5 10.1016/j.neuroimage.2016.07.057 10.1017/S0048577201393095 10.1016/j.brainres.2009.03.015 10.3389/fnins.2017.00439 10.1016/j.clinph.2010.10.044 10.1016/j.ergon.2004.09.006 10.1016/j.neucom.2016.09.057 10.1038/s41598-017-06509-0 10.1016/j.aap.2015.10.033 10.1109/EMBC.2018.8512259 10.3390/s150819181 10.1016/j.bandc.2013.12.011 10.1016/j.neubiorev.2012.10.003 10.1177/1550059413503961 10.1016/j.neuroimage.2016.02.045 10.1007/s12021-017-9330-4 10.1002/hbm.23240 10.1152/japplphysiol.91324.2008 10.1016/j.apergo.2010.05.008 10.1016/j.biopsycho.2016.09.010 10.3389/fnhum.2016.00304 10.3233/JAD-160092 10.1016/S0001-4575(02)00014-3 10.1016/j.ijpsycho.2010.03.007 10.1016/j.aap.2011.11.019 10.1016/j.jneumeth.2003.10.009 10.1007/s11571-018-9481-5 10.1093/gigascience/gix004 |
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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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