Native EEG and treatment effects in neuroleptic-naïve schizophrenic patients: Time and frequency domain approaches

Kikuchi, Mitsuru; Koenig, Thomas; Wada, Yuji; Higashima, Masato; Koshino, Yoshifumi; Strik, Werner; Dierks, Thomas

doi:10.1016/j.schres.2007.07.012

Cited by 121 publications

(139 citation statements)

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“…The most prominent pathology studied using this approach is schizophrenia. Eight studies have examined EEG microstates in drug-free patients with schizophrenia or those experiencing their first episodes (Irisawa et al, 2006;Kikuchi et al, 2007;Koenig et al, 1999;Lehmann et al, 2005;Nishida et al, 2013;Strelets et al, 2003), while two studies have investigated microstates in patients receiving medication (Andreou et al, 2014;Tomescu et al, 2015).…”

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

confidence: 99%

“…Similar alterations were observed for microstates C and D, indicating that these microstates may represent early markers for the risk of developing schizophrenia. In addition, Kikuchi et al (Kikuchi et al, 2007) showed that successful antipsychotic treatment normalizes the patterns of microstates C and D in patients with schizophrenia, and Sverak et al, (Sverak et al, 2017) M A N U S C R I P T…”

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

confidence: 99%

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

confidence: 99%

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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“…They reproduce well across subjects and can be identified across the entire life span (15), indicating that they might be mediated by predetermined anatomical connections. Alterations of microstates have been reported in schizophrenia (16,17), depression (18), and Alzheimer's disease (19,20) and as a function of drug administration and hypnosis (21)(22)(23).…”

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confidence: 99%

EEG microstate sequences in healthy humans at rest reveal scale-free dynamics

Ville

Britz

Michel

2010

Proc. Natl. Acad. Sci. U.S.A.

496

422

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Recent findings identified electroencephalography (EEG) microstates as the electrophysiological correlates of fMRI resting-state networks. Microstates are defined as short periods (100 ms) during which the EEG scalp topography remains quasi-stable; that is, the global topography is fixed but strength might vary and polarity invert. Microstates represent the subsecond coherent activation within global functional brain networks. Surprisingly, these rapidly changing EEG microstates correlate significantly with activity in fMRI resting-state networks after convolution with the hemodynamic response function that constitutes a strong temporal smoothing filter. We postulate here that microstate sequences should reveal scale-free, self-similar dynamics to explain this remarkable effect and thus that microstate time series show dependencies over long time ranges. To that aim, we deploy wavelet-based fractal analysis that allows determining scale-free behavior. We find strong statistical evidence that microstate sequences are scale free over six dyadic scales covering the 256-ms to 16-s range. The degree of long-range dependency is maintained when shuffling the local microstate labels but becomes indistinguishable from white noise when equalizing microstate durations, which indicates that temporal dynamics are their key characteristic. These results advance the understanding of temporal dynamics of brain-scale neuronal network models such as the global workspace model. Whereas microstates can be considered the "atoms of thoughts," the shortest constituting elements of cognition, they carry a dynamic signature that is reminiscent at characteristic timescales up to multiple seconds. The scale-free dynamics of the microstates might be the basis for the rapid reorganization and adaptation of the functional networks of the brain.critical state | microstates | resting-state networks | self-similar processes | wavelet fractal analysis T he human brain is intrinsically organized into interconnected neuronal clusters that form large-scale neurocognitive networks (1, 2). These networks have to dynamically and rapidly reorganize and coordinate on subsecond temporal scales to allow the execution of mental processes in a timely fashion (3, 4). Precise timing is crucial for the government of the continuous information flow from multiple sources to ensure perception, cognition, and action and ultimately consciousness. The anatomical architecture of several large-scale networks is well known and has been studied with different methods ranging from tracer studies to resting-state fMRI (5, 6). However, much less is known about their underlying temporal dynamics.Multichannel electroencephalography (EEG) is a key method to access real-time information about the function of large-scale neuronal networks with high temporal resolution. Traditionally, spontaneous EEG analysis relies mainly on the power variation in different frequency bands at a subset of electrodes; however, observing this variation inherently sacrifices temporal accuracy due t...

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“…These four classes have been observed in independent studies with notable similarity across subjects (Koenig et al 1999;Lehmann et al 2005). Microstate parameters (duration, frequency of occurrence) of the four classes differ between schizophrenics and controls (Irisawa et al 2006;Kikuchi et al 2007;Koenig et al 1999;Lehmann et al 2005). The temporal concatenation of microstates ('syntax') showed nonrandom behavior in healthy participants (Wackermann et al 1993).…”

Section: Introductionmentioning

confidence: 83%

“…Electrophysiological relations between schizotypy and paranormal belief have been discussed (Pizzagalli et al 2000). However, the principal deviations of microstate parameters in schizophrenia (Irisawa et al 2007;Kikuchi et al 2007;Koenig et al 1999;Lehmann et al 2005;Strelets et al 2003), i.e., decreased duration of classes B and D and increased occurrence of A and C were not observed in the believers. In fact, believers showed an opposing result, decreased occurrence of C. Increased occurrence of B as seen in believers had been reported only in one schizophrenia study (Kikuchi et al 2007).…”

Section: Discussionmentioning

confidence: 99%

EEG Microstates During Resting Represent Personality Differences

Schlegel¹,

Lehmann²,

Faber³

et al. 2011

Brain Topogr

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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. 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.

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Native EEG and treatment effects in neuroleptic-naïve schizophrenic patients: Time and frequency domain approaches

Cited by 121 publications

References 24 publications

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

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

EEG microstate sequences in healthy humans at rest reveal scale-free dynamics

EEG Microstates During Resting Represent Personality Differences

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