State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses - Strijbis, Eva M. M.; Timar, Yannick S. S.; Schoonhoven, Deborah N.; Nauta, Ilse M.; Kulik, Shanna D.; de Ruiter, Lodewijk R. J.; Schoonheim, Menno M.; Hillebrand, Arjan; Stam, Cornelis J. (Frontiers in Neuroscience, 2022)
Background: A common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements such as magnetoencephalography (MEG), the specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how state-changes alter quantitative estimates of oscillatory activity, functional connectivity and network topology. Methods: Eight-minute MEG recordings of 19 healthy subjects, split in ~13 second epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC) or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity and network analyses in 6 canonical frequency bands were compared between these states on a global and regional level. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), network topology using the minimum spanning tree (MST). Results: Drowsiness was present in >55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs D-EC) and conditions (EO vs A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures. Conclusions: Drowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology this seems of far less importance.