Alterations in EEG connectivity in healthy young adults provide an indicator of sleep depth

Abstract

Current sleep analyses have used electroencephalography (EEG) to establish sleep intensity through linear and nonlinear measures. Slow wave activity (SWA) and entropy are the most commonly used markers of sleep depth. The purpose of this study is to evaluate changes in brain EEG connectivity during sleep in healthy subjects and compare them with SWA and entropy. Four different connectivity metrics: coherence (MSC), synchronization likelihood (SL), cross mutual information function (CMIF), and phase locking value (PLV), were computed focusing on their correlation with sleep depth. These measures provide different information and perspectives about functional connectivity. All connectivity measures revealed to have functional changes between the different sleep stages. The averaged CMIF seemed to be a more robust connectivity metric to measure sleep depth (correlations of 0.78 and 0.84 with SWA and entropy, respectively), translating greater linear and nonlinear interdependences between brain regions especially during slow wave sleep. Potential changes of brain connectivity were also assessed throughout the night. Connectivity measures indicated a reduction of functional connectivity in N2 as sleep progresses. The validation of connectivity indexes is necessary because they can reveal the interaction between different brain regions in physiological and pathological conditions and help understand the different functions of deep sleep in humans.

Keywords: electroencephalography; entropy; functional connectivity; slow wave activity.

Figure 1.

Time course of the hypnogram, SWA, sample entropy, and different averaged connectivity measures (MIF, SL, MSC, and PLV) obtained for a subject during the night as an example. Thick lines in the graphs were calculated by means of a moving average filter using a 5 min sliding window. All the connectivity measures represent the average value from the 19 electrodes, except for MIF, which were also calculated averaging only six electrodes (Fp1, Fp2, C3, C4, O1, and O2).

Figure 2.

Time courses of SWA (0.5–4 Hz), sample entropy and different connectivity measures obtained as the grand mean average of 19 EEG electrodes and 27 subjects. To compensate for the individual differences in occurrence and duration of the NREM-REM cycles, individual NREMs and REMs episodes were subdivided in nine and three equal time bins, respectively for each subject. Red points represent averaged NREM bins and green points REM values. Dashed vertical lines delimit NREM-REM cycles.

Figure 3.

SPMs showing statistical changes on connectivity measures between sleep stages. Increases and decreases of connectivity values are indicated with hot and cold colors. Color intensity and line thickness were related to the associated probability value of significant differences (p < 0.01 dark and thick; 0.01 < p < 0.05 light and thick; 0.05 < p < 0.10 light and thin). FDR-based multiple comparison correction procedure was applied.

Figure 4.

SPM showing statistical connectivity alterations after FDR correction in sleep stages N2, N3, and REM between the first and the last NREM-REM cycles. Only first and last sleep cycles located at the first and last thirds of the night were considered (n = 27 for N2 and REM, and n = 17 for N3). For more details on line meanings, see the legend of Figure 3.