• DocumentCode
    169843
  • Title

    Granger causality analysis of sleep brain-heart interactions

  • Author

    Faes, Luca ; Marinazzo, Daniele ; Jurysta, Fabrice ; Nollo, Giandomenico

  • Author_Institution
    Dept. of Ind. Eng., Univ. of Trento, Trento, Italy
  • fYear
    2014
  • fDate
    25-28 May 2014
  • Firstpage
    5
  • Lastpage
    6
  • Abstract
    We studied the networks of Granger causality (GC) between the time series of cardiac vagal autonomic activity and brain wave activities, measured respectively as the normalized high frequency (HF) component of heart rate variability and EEG power in the δ, θ, α, σ, β bands, computed in 10 healthy subjects during sleep. GC analysis was performed by vector autoregressive modeling, and significance of each link in the network was assessed using F-statistics. The whole-night analysis revealed the existence of a fully connected network of brain-heart and brain-brain interactions, with the β EEG power acting as a hub which conveys the largest number of GC links between the heart and brain nodes. These links became progressively more weak when assessed during light sleep, deep sleep, and REM sleep, thus suggesting that brain-heart GC networks are sustained mainly by sleep stage transitions.
  • Keywords
    autoregressive processes; cardiology; electroencephalography; sleep; time series; α bands; β EEG power; β bands; δ bands; θ bands; σ bands; F-statistics; Granger causality analysis; brain nodes; brain wave activity; brain-brain interactions; cardiac vagal autonomic activity; heart nodes; heart rate variability; high frequency component; sleep brain-heart interactions; sleep stage transitions; time series; vector autoregressive modeling; Brain models; Electroencephalography; Hafnium; Heart rate variability; Sleep; Time series analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cardiovascular Oscillations (ESGCO), 2014 8th Conference of the European Study Group on
  • Conference_Location
    Trento
  • Type

    conf

  • DOI
    10.1109/ESGCO.2014.6847491
  • Filename
    6847491