EEG Microstates During Resting Represent Personality Differences

Abstract

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.

EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review

“…References not in the text: (Corradini and Persinger, 2014;Pipinis et al, 2017;Schlegel et al, 2012). …”

Association Between Resting-State Microstates and Ratings on the Amsterdam Resting-State Questionnaire

“…Earlier studies point to the correspondence of individual microstates to particular classes of mentation by influencing how incoming information is processed and reacted to, and reported afterwards to some degree: Class A has been associated with abstract thoughts (Lehmann et al 1998;Lehmann et al 2010), activity within auditory areas (Britz et al 2010) and visualization (Milz et al 2016); Class B was associated with visual imagery-type activities (Britz et al 2010), verbalization (Milz et al 2016) and paranormal belief (Schlegel et al 2012). MRI-EEG coupled studies suggested that Class C stems from a network related to saliency, whereas Class D -from a dorsal attention network (Britz et al 2010).…”

Bridging the gap between cognitive neuroscience and education: Psychophysiological and behavioral data collection in authentic contexts

“…Research to date indicates that class A refers to abstraction, class B to concrete thought, class C to decreased attention with decreased excitation, while the interpretation of class D remains unclear. Their prevalence (mean duration, frequency of occurrence per second, percentage of occupied total analysis time) and sequence reflect different higher-order mental processes (Schlegel, Lehmann, Faber, Milz, & Gianotti, 2012). For the time being, microstates may be among the most promising notions when using EEG in neuroeducation, as they appear to be suited for the discovery of psychophysiological signatures of cognitive functions responsible for learning (for example, social learning, metacognitive regulation in problem solving, insight in problem solving, implicit and explicit learning, etc.).…”