Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-57694
Schlegel, Felix; Lehmann, Dietrich; Faber, Pascal L; Milz, Patricia; Gianotti, Lorena R R (2012). EEG microstates during resting represent personality differences. Brain Topography, 25(1):20-26.
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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.
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|Item Type:||Journal Article, refereed, original work|
|Communities & Collections:||04 Faculty of Medicine > Psychiatric University Hospital Zurich > Clinic for Psychiatry, Psychotherapy, and Psychosomatics
04 Faculty of Medicine > The KEY Institute for Brain-Mind Research
|DDC:||610 Medicine & health|
|Uncontrolled Keywords:||Microstate syntax, Cognition, Paranormal beliefs, Schizotypy, Transition probabilities, Schizophrenia|
|Deposited On:||03 Apr 2012 07:10|
|Last Modified:||02 Dec 2013 16:10|
|Additional Information:||The original publication is available at www.springerlink.com|
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