Spectral power, source localization and microstates to quantify chronic deficits from ‘mild’ closed head injury: Correlation with classic neuropsychological tests

Corradini, Paula L.; Persinger, Michael A.

doi:10.3109/02699052.2014.916819

Cited by 15 publications

(15 citation statements)

References 44 publications

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“…We then performed a two-steps k-means clustering analysis. At the individual level (firststep), global field power peaks of each participant were submitted for k-means clustering analysis, and four microstate classes were obtained per individual, which is consistent with previous studies [46][47][48]. In the second step, also known as the group-level, the dominant topographies across all individuals and groups were clustered to obtain four mean microstate classes for each group.…”

Section: Microstate Analysismentioning

confidence: 78%

Disrupted brain network dynamics and cognitive functions in methamphetamine use disorder: insights from EEG microstates

Chen

Zhong

et al. 2020

BMC Psychiatry

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Background Dysfunction in brain network dynamics has been found to correlate with many psychiatric disorders. However, there is limited research regarding resting electroencephalogram (EEG) brain network and its association with cognitive process for patients with methamphetamine use disorder (MUD). This study aimed at using EEG microstate analysis to determine whether brain network dynamics in patients with MUD differ from those of healthy controls (HC). Methods A total of 55 MUD patients and 27 matched healthy controls were included for analysis. The resting brain activity was recorded by 64-channel electroencephalography. EEG microstate parameters and intracerebral current sources of each EEG microstate were compared between the two groups. Generalized linear regression model was used to explore the correlation between significant microstates with drug history and cognitive functions. Results MUD patients showed lower mean durations of the microstate classes A and B, and a higher global explained variance of the microstate class C. Besides, MUD patients presented with different current density power in microstates A, B, and C relative to the HC. The generalized linear model showed that MA use frequency is negatively correlated with the MMD of class A. Further, the generalized linear model showed that MA use frequency, scores of Two-back task, and the error rate of MA word are correlated with the MMD and GEV of class B, respectively. Conclusions Intracranial current source densities of resting EEG microstates are disrupted in MUD patients, hence causing temporal changes in microstate topographies, which are correlated with attention bias and history of drug use.

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Section: Microstate Analysismentioning

confidence: 78%

Disrupted brain network dynamics and cognitive functions in methamphetamine use disorder: insights from EEG microstates

Chen

Zhong

et al. 2020

BMC Psychiatry

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“…delta (1.5–4 Hz); theta (4–7 Hz); low-alpha (7–10 Hz); high-alpha (10–13 Hz); beta-1 (13–20 Hz); beta-2 (20–25 Hz); beta-3 (25–30 Hz); gamma (>30 Hz)]. Corradini and Persinger [ 22 ] have found that source localization performed with 19 sensors within a clinical population was able to localize the source of infarctions and closed-head injuries and was validated against accepted psychometric inferences of the functioning of these regions. We employed the exact same methodology for computing the current source density for the parahippocampal regions as in a previously published paper [ 10 ].…”

Section: Methodsmentioning

confidence: 99%

Similar Spectral Power Densities Within the Schumann Resonance and a Large Population of Quantitative Electroencephalographic Profiles: Supportive Evidence for Koenig and Pobachenko

2016

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In 1954 and 1960 Koenig and his colleagues described the remarkable similarities of spectral power density profiles and patterns between the earth-ionosphere resonance and human brain activity which also share magnitudes for both electric field (mV/m) and magnetic field (pT) components. In 2006 Pobachenko and colleagues reported real time coherence between variations in the Schumann and brain activity spectra within the 6–16 Hz band for a small sample. We examined the ratios of the average potential differences (~3 μV) obtained by whole brain quantitative electroencephalography (QEEG) between rostral-caudal and left-right (hemispheric) comparisons of 238 measurements from 184 individuals over a 3.5 year period. Spectral densities for the rostral-caudal axis revealed a powerful peak at 10.25 Hz while the left-right peak was 1.95 Hz with beat-differences of ~7.5 to 8 Hz. When global cerebral measures were employed, the first (7–8 Hz), second (13–14 Hz) and third (19–20 Hz) harmonics of the Schumann resonances were discernable in averaged QEEG profiles in some but not all participants. The intensity of the endogenous Schumann resonance was related to the ‘best-of-fitness’ of the traditional 4-class microstate model. Additional measurements demonstrated real-time coherence for durations approximating microstates in spectral power density variations between Schumann frequencies measured in Sudbury, Canada and Cumiana, Italy with the QEEGs of local subjects. Our results confirm the measurements reported by earlier researchers that demonstrated unexpected similarities in the spectral patterns and strengths of electromagnetic fields generated by the human brain and the earth-ionospheric cavity.

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“…References not in the text: (Corradini and Persinger, 2014;Pipinis et al, 2017;Schlegel et al, 2012). …”

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

confidence: 99%

“…The microstate approach has also be used to investigated conditions such as dementia (Nishida et al, 2013), narcolepsy (Drissi et al, 2016), panic disorder (Kikuchi et al, 2011), multiple sclerosis (Gschwind et al, 2016), head injury (Corradini and Persinger, 2014), diplegia (Gao et al, 2017), and stroke (Zappasodi et al, 2017). In contrast to schizophrenia, decreased occurrence of microstate C and changes in microstate A and B have been observed in patients with most of these other conditions, indicating that imbalances in microstate C and D may be specific to schizophrenia.…”

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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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Spectral power, source localization and microstates to quantify chronic deficits from ‘mild’ closed head injury: Correlation with classic neuropsychological tests

Cited by 15 publications

References 44 publications

Disrupted brain network dynamics and cognitive functions in methamphetamine use disorder: insights from EEG microstates

Disrupted brain network dynamics and cognitive functions in methamphetamine use disorder: insights from EEG microstates

Similar Spectral Power Densities Within the Schumann Resonance and a Large Population of Quantitative Electroencephalographic Profiles: Supportive Evidence for Koenig and Pobachenko

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

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