  A brain microstate is characterized by a unique, fixed spatial distribution
of electrically active neurons with time varying amplitude. It is hypothesized
that a microstate implements a functional/physiological state of the brain
during which specific neural computations are performed. Based on this
hypothesis, brain electrical activity is modeled as a time sequence of
non-overlapping microstates with variable, finite durations (Lehmann and
Skrandies 1980, 1984; Lehmann et al 1987). In this study, EEG recordings from
109 participants during eyes closed resting condition are modeled with four
microstates. In a first part, a new confirmatory statistics method is
introduced for the determination of the cortical distributions of electric
neuronal activity that generate each microstate. All microstates have common
posterior cingulate generators, while three microstates additionally include
activity in the left occipital/parietal, right occipital/parietal, and anterior
cingulate cortices. This appears to be a fragmented version of the
metabolically (PET/fMRI) computed default mode network (DMN), supporting the
notion that these four regions activate sequentially at high time resolution,
and that slow metabolic imaging corresponds to a low-pass filtered version. In
the second part of this study, the microstate amplitude time series are used as
the basis for estimating the strength, directionality, and spectral
characteristics (i.e., which oscillations are preferentially transmitted) of
the connections that are mediated by the microstate transitions. The results
show that the posterior cingulate is an important hub, sending alpha and beta
oscillatory information to all other microstate generator regions.
Interestingly, beyond alpha, beta oscillations are essential in the maintenance
of the brain during resting state.
