Classes of Multichannel EEG Microstates in Light and Deep Hypnotic Conditions

Katayama, Hitoshi; Gianotti, Lorena R. R.; Isotani, Toshiaki; Faber, Pascal L.; Sasada, Kyohei; Kinoshita, Toshihiko; Lehmann, Dietrich

doi:10.1007/s10548-007-0024-3

Cited by 95 publications

(74 citation statements)

References 52 publications

(74 reference statements)

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“…Somatic Awareness was evaluated by questions related to the sensation of bodily signals ("I was conscious of my body"; "I thought about my heartbeat"; "I thought about my breathing"). The negative correlation between Class C and SA thus seems reasonable: it was previously proposed by Rieger et al (2016) that Class C becomes more dominant when connections to contextual information (including perception of bodily signals, as measured with SA) are loosened, similarly to what happens in reduced attention states (Brandeis and Lehmann 1989), during sleep (Brodbeck et al 2012), hypnosis (Katayama et al 2007), or psychosis (metaanalysis by Rieger et al 2016). A negative association between Class C and D measures (r values from -0.29 to -0.52, Supplement 5) and the positive association of SA and Class D measures (not surviving correction, GFP: r = 0.35, Contribution: r = 0.30, Table 1) is also worth mentioning as it fits to the notion of antagonistic functional roles of Class C and D (Rieger et al 2016).…”

Section: Resultssupporting

confidence: 51%

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

et al. 2016

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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 non-sensory experiences.

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Section: Resultssupporting

confidence: 51%

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

et al. 2016

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“…Notably, even if the optimal number of microstates for explaining the EEG data was identified as four, the topography of some microstate maps was rather dissimilar. Katayama and colleagues (Katayama et al, 2007) evaluated changes in EEG microstates in participants undergoing…”

Section: A C C E P T E D Accepted Manuscriptmentioning

confidence: 99%

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

2018

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SummaryThe present review discusses a well-established method for characterizing resting-state activity of the human brain using multichannel electroencephalography (EEG). This method involves the examination of electrical microstates in the brain, which are defined as successive short time periods during which the configuration of the scalp potential field remains semi-stable, suggesting quasi-simultaneity of activity among the nodes of largescale networks. A few prototypic microstates, which occur in a repetitive sequence across time, can be reliably identified across participants. Researchers have proposed that these microstates represent the basic building blocks of the chain of spontaneous conscious mental processes, and that their occurrence and temporal dynamics determine the quality of mentation. Several studies have further demonstrated that disturbances of mental processes associated with neurological and psychiatric conditions manifest as changes in the temporal dynamics of specific microstates. Combined EEG-fMRI studies and EEG source imaging studies have indicated that EEG microstates are closely associated with resting-state networks as identified using fMRI. The scale-free properties of the time series of EEG microstates explain why similar networks can be observed at such different time scales.The present review will provide an overview of these EEG microstates, available methods for analysis, the functional interpretations of findings regarding these microstates, and their behavioral and clinical correlates.

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“…[1,43,63]), behavioral/mental states (e.g. [26,28]), and/or parametric variations in stimulus conditions (e.g. [47,51]).…”

Section: Spatial Correlation-based Fitting and Its Dependent Measuresmentioning

confidence: 99%

Topographic ERP Analyses: A Step-by-Step Tutorial Review

2008

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In this tutorial review, we detail both the rationale for as well as the implementation of a set of analyses of surface-recorded event-related potentials (ERPs) that uses the reference-free spatial (i.e. topographic) information available from high-density electrode montages to render statistical information concerning modulations in response strength, latency, and topography both between and within experimental conditions. In these and other ways these topographic analysis methods allow the experimenter to glean additional information and neurophysiologic interpretability beyond what is available from canonical waveform analyses. In this tutorial we present the example of somatosensory evoked potentials (SEPs) in response to stimulation of each hand to illustrate these points. For each step of these analyses, we provide the reader with both a conceptual and mathematical description of how the analysis is carried out, what it yields, and how to interpret its statistical outcome. We show that these topographic analysis methods are intuitive and easy-to-use approaches that can remove much of the guesswork often confronting ERP researchers and also assist in identifying the information contained within highdensity ERP datasets.

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Classes of Multichannel EEG Microstates in Light and Deep Hypnotic Conditions

Cited by 95 publications

References 52 publications

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

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

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

Topographic ERP Analyses: A Step-by-Step Tutorial Review

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