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Poster

Psychosocial stress effects on temporal characteristics of EEG microstates

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Zitation

Krylova, M., Izyurov, I., Alizadeh, S., Jamalabadi, H., & Walter, M. (2017). Psychosocial stress effects on temporal characteristics of EEG microstates. Poster presented at 18th Conference of Junior Neuroscientists of Tübingen (NeNa 2017), Schramberg, Germany.


Zitierlink: https://hdl.handle.net/21.11116/0000-0001-00F6-9
Zusammenfassung
Multichannel records of the spontaneous brain electrical activity shows that EEG topography does not change randomly over time, but remains stable for short time periods (ca. 80-120 ms). These periods of quasi-stability are often referred to as "EEG microstates" (Lehmann et al., 1987) and are suggested to be the building blocks of brain dynamics that represent basic brain functions (Khanna et al., 2015). Recent studies show that performing various cognitive activities can affect temporal structure of the microstates. Also, changes in the parameters of microstates are associated with psychiatric disorders (schizophrenia, depression, etc.). In this study, we investigated effect of
the psychosocial stress on the temporal characteristics of EEG microstates. We analyzed resting-state, eyes-closed recordings from thirty-nine healthy male volunteers over 3 sessions of simultaneous 3 Tesla fMRI and 64-channel EEG. The experiment started with a resting-state session (RS0) that was followed by two tasks to assess attention and a second resting-state session (RS1). The stress response was induced using the ScanSTRESS (Streit et al., 2014), which uses arithmetic tasks as well as mental rotation tasks. The experiment ended with a final resting session (RS2). We identified four microstate classes using EEGLAB plugin for microstates analysis by Thomas Koenig (University of Bern, Switzerland) and calculated the average duration, frequency, and coverage fraction of these microstates. We found that frequency of occurrence and coverage fraction of the microstate class C, known to correspond to the cognitive control/Saliency networks (Britz et al., 2010) were
increased after experience of psychosocial stress (occurrence: RS2 vs RS1: p = 0.02, coverage: RS2 vs RS1: p = 0.04, paired t-test) while performance of non-stressful tasks did not affect these parameters (No significant changes between RS1 vs RS0).