Abstract
There is a gap in understanding on how physiologically observed activity is related to the subjective, internally oriented experience during resting state. Microstate analysis is a frequent approach to evaluate resting-state EEG. But the relationship of commonly observed resting-state microstates to psychological domains of resting is not clear. The Amsterdam Resting-State Questionnaire (ARSQ) was recently introduced, offering an effective way to quantify subjective states after a period of resting and associate these quantifiers to psychological and physiological variables. In a sample of 94 healthy volunteers who participated in closed-eyes 5 min resting session with concurrent EEG recording and subsequent filling of the ARSQ we evaluated parameters of microstate Classes A, B, C, D. We showed a moderate negative association between contribution (r = −0.40) of Class C and experienced somatic awareness (SA). The negative correlation between Class C and SA seems reasonable as Class C becomes more dominant when connections to contextual information (and bodily sensations as assessed with SA) are loosened (in reduced attention states, during sleep, hypnosis, or psychosis). We suggest that the use of questionnaires such as the ARSQ is helpful in exploring the variation of resting-state EEG parameters and its relationship to variation in sensory and non-sensory experiences.
References
Andrews-Hanna JR, Reidler JS, Huang C, Buckner RL (2010) Evidence for the default network’s role in spontaneous cognition. J Neurophysiol 104:322–335. doi:10.1152/jn.00830.2009
Brandeis D, Lehmann D (1989) Segments of event-related potential map series reveal landscape changes with visual attention and subjective contours. Electroencephalogr Clin Neurophysiol 73:507–519
Britz J, Van De Ville D, Michel CM (2010) BOLD correlates of EEG topography reveal rapid resting-state network dynamics. Neuroimage 52:1162–1170. doi:10.1016/j.neuroimage.2010.02.052
Brodbeck V, Kuhn A, von Wegner F et al (2012) EEG microstates of wakefulness and NREM sleep. Neuroimage 62:2129–2139. doi:10.1016/j.neuroimage.2012.05.060
Diaz BA, Van Der Sluis S, Moens S et al (2013) The Amsterdam resting-state questionnaire reveals multiple phenotypes of resting-state cognition. Front Hum Neurosci 7:446. doi:10.3389/fnhum.2013.00446
Diaz BA, Van Der Sluis S, Benjamins JS et al (2014) The ARSQ 2.0 reveals age and personality effects on mind-wandering experiences. Front Psychol 5:271. doi:10.3389/fpsyg.2014.00271
Diaz BA, Hardstone R, Mansvelder HD et al (2016) Resting-state subjective experience and EEG biomarkers are associated with sleep-onset latency. Front Psychol 7:492. doi:10.3389/fpsyg.2016.00492
Katayama H, Gianotti LRR, Isotani T et al (2007) Classes of multichannel EEG microstates in light and deep hypnotic conditions. Brain Topogr 20:7–14. doi:10.1007/s10548-007-0024-3
Koenig T, Melie-García L (2010) A method to determine the presence of averaged event-related fields using randomization tests. Brain Topogr 23:233–242. doi:10.1007/s10548-010-0142-1
Koenig T, Lehmann D, Merlo MC et al (1999) A deviant EEG brain microstate in acute, neuroleptic-naive schizophrenics at rest. Eur Arch Psychiatry Clin Neurosci 249:205–211
Lehmann D, Ozaki H, Pal I (1987) EEG alpha map series: brain micro-states by space-oriented adaptive segmentation. Electroencephalogr Clin Neurophysiol 67:271–288
Lehmann D, Strik WK, Henggeler B et al (1998) Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: I. Visual imagery and abstract thoughts. Int J Psychophysiol 29:1–11
Lehmann D, Pascual-Marqui RD, Strik WK, Koenig T (2010) Core networks for visual-concrete and abstract thought content: a brain electric microstate analysis. Neuroimage 49:1073–1079. doi:10.1016/j.neuroimage.2009.07.054
Milz P, Faber PL, Lehmann D et al (2016) The functional significance of EEG microstates-associations with modalities of thinking. Neuroimage 125:643–656. doi:10.1016/j.neuroimage.2015.08.023
Rieger K, Diaz Hernandez L, Baenninger A, Koenig T (2016) 15 Years of Microstate research in schizophrenia—where are we? a meta-analysis. Front psychiatry 7:22. doi:10.3389/fpsyt.2016.00022
Schlegel F, Lehmann D, Faber PL et al (2012) EEG microstates during resting represent personality differences. Brain Topogr 25:20–26. doi:10.1007/s10548-011-0189-7
Stoffers D, Diaz BA, Chen G et al (2015) Resting-state fmri functional connectivity is Associated with sleepiness, imagery, and discontinuity of mind. PLoS One 10:e0142014. doi:10.1371/journal.pone.0142014
Uddin LQ, Menon V (2010) Introduction to special topic—resting-state brain activity: implications for systems neuroscience. Front Syst Neurosci. doi:10.3389/fnsys.2010.00037
van Diessen E, Numan T, van Dellen E et al (2015) Opportunities and methodological challenges in EEG and MEG resting state functional brain network research. Clin Neurophysiol 126:1468–1481. doi:10.1016/j.clinph.2014.11.018
Acknowledgments
We would like to thank all study volunteers for their participation. We also appreciate the help with data collection provided by Vaida Genyte. The study was supported by Lithuanian Research Council Grant MIP-009/2014.
Author information
Authors and Affiliations
Corresponding author
Additional information
Evaldas Pipinis and Sigita Melynyte have contributed equally to this work.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Pipinis, E., Melynyte, S., Koenig, T. et al. Association Between Resting-State Microstates and Ratings on the Amsterdam Resting-State Questionnaire. Brain Topogr 30, 245–248 (2017). https://doi.org/10.1007/s10548-016-0522-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10548-016-0522-2