EEG microstates associated with intra- and inter-subject alpha variability

Abstract

Variation of the magnitude of posterior alpha rhythm (8-12 Hz) has functional and behavioural effects in sensory processing and cognitive performances. Electrical brain activity, as revealed by electroencephalography (EEG), can be represented by a sequence of microstates of about 40-120 ms duration, in which distributed neural pools are synchronously active and generate stable spatial potential topographies on the scalp. Microstate dynamics may reflect transitions between global states characterized by selective inhibition of specific intra-cortical regions, mediated by alpha activity. We investigated the intra-subject and inter-subject relationship between microstate features and alpha band. High-density EEG signals were acquired in 29 healthy subjects during ten minutes of eyes closed rest. Individual EEG signal epochs were classified into four groups depending on the amount of occipital alpha power, and microstate metrics (duration, coverage and frequency of occurrence) were calculated and compared across groups. Correlations between alpha power and microstate metrics between individuals were also performed. To assess if microstate parameter variations are specific for the alpha band, the same analysis was also performed for theta and beta bands, as well as for global field power. We observed an increase in the metrics of microstate, previously associated to the visual system, with the level of intra-subject amplitude alpha oscillations, together with lower coverage of microstate associated with executive attention network and a higher frequency of microstate associated with task negative network. Other modulation effects of broad-band EEG power level on microstate metrics were observed. These effects are not specific for the alpha band, since they can equally be attributed to fluctuations in other frequency bands. We can interpret our results as a regulation mechanism mediated by posterior alpha level, dynamically interacting with other frequency bands, responsible for the switching between active areas.The dynamics of human brain signals uncover organized fluctuations both at rest and during task or sensory input. Such time signal variability has been recently linked to the efficiency of functional abilities and directly associated to cognitive performances in functional Magnetic Resonance Imaging (fMRI), Magnetoencephalographic (MEG), Electrocorticographic (ECoG) and Electroencephalographic (EEG) studies (for a review see Buzsáki and colleagues 1 ).Alpha rhythm (8-12 Hz) is a prominent component of the spectral content of electrical brain signals, as recorded at the scalp surface by EEG or MEG 2 . Although the parieto-occipital alpha rhythm has been supposed for years to reflect an idle status, it is currently considered to play a crucial role in higher cognitive processes and memory performances and to have a functional significance even at rest 3,4 . Specifically, perception and other ongoing neural activities have been related to alpha rhythm modulation 5 . In this regards, Hanslmayr 6 hypothesised that ...

Transcutaneous Vagus Nerve Stimulation Modulates EEG Microstates and Delta Activity in Healthy Subjects

“…GFP peaks can be considered as corresponding to intervals of highest topographic stability, when the probability of observing a transition to a different (stable) topographical configuration is lower [ 15 ]. For this reason, for each subject and for each condition, the scalp potential corresponding to the maximum values of GFP were fed to a modified version of a k-means clustering algorithm [ 26 ]. To identify the optimal number of microstate templates, we applied the clustering k-algorithm, varying k from 2 to 12.…”

EEG Microstate in Obstructive Sleep Apnea Patients

“…However, Milz et al investigated head-surface localization-or sourcedependent power effects on the occurrence of the EEG microstate classes, and found that the EEG microstate topography was predominantly determined by intracortical sources in the alpha band 28 . Croce et al investigated EEG microstates associated with intra-and inter-subject alpha variability, and observed an increase in the metrics of microstate B, with the level of intra-subject amplitude alpha oscillations, together with lower coverage of microstate D and a higher frequency of microstate C 29 . Although their study found the relationship between alpha power and microstate metrics, the authors also pointed out that there was no speci city for alpha power.…”

“…The modulation effect on microstate metrics is not unique to the alpha band. It may be caused by uctuations in other frequency bands 29 . Therefore, we can infer that when apnea occurred in N1 and N3 stages, the intensity and spatial distribution of alpha activity in the cortex changed, which induced microstate E. Or because of the mediation by alpha band and the dynamic interaction with other bands (such as delta, theta bands), the original scalp potential distribution is changed, and an additional microstate E is generated.…”

Canonical EEG Microstate Dynamic Properties and Their Associations with fMRI Signals at Resting Brain

“…Additionally, EEG-ms classes have been shown to be predominantly impacted by the strength and spatial distribution of alpha rhythm (Milz et al, 2017). Also, the inter-and intra-subject variability of alpha rhythm along with another frequency modulates the EEG-ms metrics like occurrence, duration and coverage (Croce et al, 2020). There are consistently reported results about the role of alpha power in modulating the BOLD signal (Mantini et al, 2007;Scheeringa et al, 2012).…”

“…The results revealed that the intracortical strength of alpha oscillation and its distribution predominantly determined the EEG-ms topographies. Additionally, the authors in (Croce, Quercia, Costa, & Zappasodi, 2020) showed that EEG-ms occurrence, coverage, and duration are influenced by EEG alpha oscillation, and are sensitive to intra-and inter-subject alpha rhythm variability, further indicating a prominent influence of brain oscillation on the EEG-ms. The alpha rhythm was shown to decrease during task-related mental activity (Goldman, Stern, Engel Jr, & Cohen, 2002;G Pfurtscheller, 2003;Salenius, Kajola, Thompson, Kosslyn, & Hari, 1995;Scheeringa, Petersson, Kleinschmidt, Jensen, & Bastiaansen, 2012).…”