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

Jonathan Harvy, Nitish V Thakor, Anastasios Bezerianos, Junhua Li

Research output: Contribution to journalArticle

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 used 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, and associated-HOFCθα, associated-HOFCαβ, the connectionlevel metrics in frontal-central, central-central, and centralparietal/ 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 reliably significant increases in the alpha, theta-alpha, and alpha-beta bands. Modularity indexes of associated-HOFCα and associated-HOFCθα also exhibited reliably significant differences. Our study 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.

Original languageEnglish (US)
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
DOIs
StateAccepted/In press - Jan 1 2019
Externally publishedYes

Fingerprint

Sleep Stages
Electroencephalography
Healthy Volunteers
Synchronization
Frequency bands
Power (Psychology)
Datasets

Keywords

  • Automobiles
  • Between-frequency connectivity
  • Coherence
  • Correlation
  • Driving drowsiness
  • Dynamic connectivity
  • EEG
  • Electroencephalography
  • Fatigue
  • High-order functional connectivity
  • Reliability
  • Supra-adjacency matrix

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biomedical Engineering
  • Computer Science Applications

Cite this

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title = "Between-Frequency Topographical and Dynamic High-Order Functional Connectivity for Driving Drowsiness Assessment",
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 used 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, and associated-HOFCθα, associated-HOFCαβ, the connectionlevel metrics in frontal-central, central-central, and centralparietal/ 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 reliably significant increases in the alpha, theta-alpha, and alpha-beta bands. Modularity indexes of associated-HOFCα and associated-HOFCθα also exhibited reliably significant differences. Our study 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.",
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