Each week, we will be publishing layman’s abstracts of new articles from our prestigious portfolio of journals in statistics. The aim is to highlight the latest research to a broader audience in an accessible format.
Hart, B., Malone, S. and Fiecas, M. (2021), A grouped beta process model for multivariate resting‐state EEG microstate analysis on twins. Can J Statistics. https://doi.org/10.1002/cjs.11589
The electrical activity of the brain can be measured using electroencephalography (EEG). Recent work has shown that this electrical activity rapidly switches through a set of “microstates” which define the pattern of activity across the brain at a single point in time. According to one theory, each of these microstates is an “atom of thought”. When these atoms of thought are combined in different frequencies and orders, they form human cognition. This article proposes an EEG microstate model to estimate how many microstates a person uses, what patterns define each microstate, and how a person’s brain switches between these microstates. The proposed model expands on current methods by using data collected from twins and allowing them to share microstates. When applied to data collected from the Minnesota Twin Family Study (MTFS), the model showed that twins generally share a similar library of microstates, although the rates at which they use each microstate and the dynamics of how they change between microstates is individual specific. By comparing monozygotic (identical) twins to dizygotic (fraternal) twins, one can estimate the percentage of the variation of a trait in a population that is determined by genetics, a quantity known as heritability. Application of the model to the MTFS data showed that the average time spent in a microstate is highly heritable (as indicated by high similarity among identical twins compared to fraternal twins) while the total number of microstates used is not heritable.