No abstract

Human brain electric activity can be measured at high temporal and fairly good spatial resolution via electroencephalography (EEG). The EEG microstate analysis is an increasingly popular method used to investigate this activity at a millisecond resolution by segmenting it into quasi-stable states of approximately 100 ms duration. These so-called EEG microstates were postulated to represent atoms of thoughts and emotions and can be classified into four classes of topographies A through D, which explain up to 90% of the variance of continuous EEG. The present study investigated whether these topographies are primarily driven by alpha activity originating from the posterior cingulate cortex (all topographies), left and right posterior cortices, and the anterior cingulate cortex (topographies A, B, and C, respectively). We analyzed two 64-channel resting state EEG datasets (N = 61 and N = 78) of healthy participants. Sources of head-surface signals were determined via exact low resolution electromagnetic tomography (eLORETA). The Hilbert transformation was applied to identify instantaneous source strength of four EEG frequency bands (delta through beta). These source strength values were averaged for each participant across time periods belonging to a particular microstate. For each dataset, these averages of the different microstate classes were compared for each voxel. Consistent differences across datasets were identified via a conjunction analysis. The intracortical strength and spatial distribution of alpha band activity mainly determined whether a head-surface topography of EEG microstate class A, B, C, or D was induced. EEG microstate class C was characterized by stronger alpha activity compared to all other classes in large portions of the cortex. Class A was associated with stronger left posterior alpha activity than classes B and D, and class B was associated with stronger right posterior alpha activity than A and D. Previous results indicated that EEG microstate dynamics reflect a fundamental mechanism of the human brain that is altered in different mental states in health and disease. They are characterized by systematic transitions between four head-surface topographies, the EEG microstate classes. Our results show that intra-cortical alpha oscillations, which likely reflect decreased cortical excitability, primarily account for the emergence of these classes. We suggest that microstate class dynamics reflect transitions between four global attractor states that are characterized by selective inhibition of specific intra-cortical regions.

Brain functional states are established by functional connectivities between brain regions. In experienced meditators (13 Tibetan Buddhists, 15 QiGong, 14 Sahaja Yoga, 14 Ananda Marga Yoga, 15 Zen), 19-channel EEG was recorded before, during and after that meditation exercise which their respective tradition regards as route to the most desirable meditative state. The head surface EEG data were recomputed (sLORETA) into 19 cortical regional source model time series. All 171 functional connectivities between regions were computed as 'lagged coherence' for the eight EEG frequency bands (delta through gamma). This analysis removes ambiguities of localization, volume conduction-induced inflation of coherence, and reference-dependence. All significant differences (corrected for multiple testing) between meditation compared to no-task rest before and after meditation showed lower coherence during meditation, in all five traditions and eight (inhibitory as well as excitatory) frequency bands. Conventional coherence between the original head surface EEG time series very predominantly also showed reduced coherence during meditation. The topography of the functional connectivities was examined via PCAbased computation of principal connectivities. When going into and out of meditation, significantly different connectivities revealed clearly different topographies in the delta frequency band and minor differences in the beta-2 band. The globally reduced functional interdependence between brain regions in meditation suggests that interaction between the self process functions is minimized, and that constraints on the self process by other processes are minimized, thereby leading to the subjective experience of noninvolvement, detachment and letting go, as well as of all-oneness and dissolution of ego borders during meditation. AbstractBrain functional states are established by functional connectivities between brain regions. In experienced meditators (13 Tibetan Buddhists, 15 QiGong, 14 Sahaja Yoga, 14 Ananda Marga Yoga, 15 Zen), 19-channel EEG was recorded before, during and after that meditation exercise which their respective tradition regards as route to the most desirable meditative state. The head surface EEG data were recomputed (sLORETA) into 19 cortical regional source model time series. All 171 functional connectivities between regionswere computed as 'lagged coherence' for the eight EEG frequency bands (delta through gamma). This analysis removes ambiguities of localization, volume conduction-induced inflation of coherence, and reference-dependence. All significant differences (corrected for multiple testing) between meditation compared to no-task rest before and after meditation showed lower coherence during meditation, in all five traditions and eight (inhibitory as well as excitatory) frequency bands. Conventional coherence between the original head surface EEG time series very predominantly also showed reduced coherence during meditation. The topography of the functional connectivities was examined ...

We investigated the spontaneous brain electric activity of 13 skeptics and 16 believers in paranormal phenomena; they were university students assessed with a self-report scale about paranormal beliefs. 33-channel EEG recordings during no-task resting were processed as sequences of momentary potential distribution maps. Based on the maps at peak times of Global Field Power, the sequences were parsed into segments of quasi-stable potential distribution, the 'microstates'. The microstates were clustered into four classes of map topographies (A-D). Analysis of the microstate parameters time coverage, occurrence frequency and duration as well as the temporal sequence (syntax) of the microstate classes revealed significant differences: Believers had a higher coverage and occurrence of class B, tended to decreased coverage and occurrence of class C, and showed a predominant sequence of microstate concatenations from A to C to B to A that was reversed in skeptics (A to B to C to A). Microstates of different topographies, putative "atoms of thought", are hypothesized to represent different types of information processing.The study demonstrates that personality differences can be detected in resting EEG microstate parameters and microstate syntax. Microstate analysis yielded no conclusive evidence for the hypothesized relation between paranormal belief and schizophrenia. AbstractWe investigated the spontaneous brain electric activity of 13 skeptics and 16 believers in paranormal phenomena; they were university students assessed with a self-report scale about paranormal beliefs. 33-channel EEG recordings during no-task resting were processed as sequences of momentary potential distribution maps. Based on the maps at peak times of Global Field Power, the sequences were parsed into segments of quasi-stable potential distribution, the 'microstates'. The microstates were clustered into four classes of map topographies (A-D). Analysis of the microstate parameters time coverage, occurrence frequency and duration as well as the temporal sequence (syntax) of the microstate classes revealed significant differences: Believers had a higher coverage and occurrence of class B, tended to decreased coverage and occurrence of class C, and showed a predominant sequence of microstate concatenations from A to C to B to A that was reversed in skeptics (A to B to C to A). Microstates of different topographies, putative ''atoms of thought'', are hypothesized to represent different types of information processing.The study demonstrates that personality differences can be detected in resting EEG microstate parameters and microstate syntax. Microstate analysis yielded no conclusive evidence for the hypothesized relation between paranormal belief and schizophrenia.

Functional dissociation between brain processes is widely hypothesized to account for aberrations of thought and emotions in schizophrenic patients. The typically small groups of analyzed schizophrenic patients yielded different neurophysiological findings, probably because small patient groups are likely to comprise different schizophrenia subtypes. We analyzed multichannel eyes-closed resting EEG from three small groups of acutely ill, first episode productive schizophrenic patients before start of medication (from three centers: Bern N = 9; Osaka N = 9; Berlin N = 12) and their controls. Low resolution brain electromagnetic tomography (LORETA) was used to compute intracortical source model-based lagged functional connectivity not biased by volume conduction effects between 19 cortical regions of interest (ROIs). The connectivities were compared between controls and patients of each group. Conjunction analysis determined six aberrant cortical functional connectivities that were the same in the three patient groups. Four of these six concerned the facilitating EEG alpha-1 frequency activity; they were decreased in the patients. Another two of these six connectivities concerned the inhibiting EEG delta frequency activity; they were increased in the patients. The principal orientation of the six aberrant cortical functional connectivities was sagittal; five of them involved both hemispheres. In sum, activity in the posterior brain areas of preprocessing functions and the anterior brain areas of evaluation and behavior control functions were compromised by either decreased coupled activation or increased coupled inhibition, common across schizophrenia subtypes in the three patient groups. These results of the analyzed three independent groups of schizophrenics support the concept of functional dissociation.