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
Link To Document