International Federation of Clinical Neurophysiology (IFCN) – EEG research workgroup: Recommendations on frequency and topographic analysis of resting state EEG rhythms. Part 1: Applications in clinical research studies

Babiloni, Claudio; Barry, Robert J.; Başar, Erol; Blinowska, Katarzyna J.; Cichocki, Andrzej; Drinkenburg, W.H.I.M.; Klimesch, Wolfgang; Knight, Robert T.; Silva, Fernando Lopes da; Nunez, Paul L.; Oostenveld, Robert; Jeong, Jaeseung; Pascual-Marqui, Roberto D.; Valdés‐Sosa, Pedro A.; Hallett, Mark

doi:10.1016/j.clinph.2019.06.234

Cited by 178 publications

(179 citation statements)

References 199 publications

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“…Third, compared with whole-night PSG, it requires a relatively short time to record. Therefore, the research on resting-state brain imaging is becoming popular, and many big data platforms have been built from the fields of psychology, neuroscience, and clinical radiology (10).…”

Section: Introductionmentioning

confidence: 99%

Aberrant Awake Spontaneous Brain Activity in Obstructive Sleep Apnea: A Review Focused on Resting-State EEG and Resting-State fMRI

Zhao

Chen

et al. 2020

Front. Neurol.

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As one of the most common sleep-related respiratory disorders, obstructive sleep apnea (OSA) is characterized by excessive snoring, repetitive apnea, arousal, sleep fragmentation, and intermittent nocturnal hypoxemia. Focused on the resting-state brain imaging techniques, we reviewed the OSA-related resting-state electroencephalogram and resting-state functional magnetic resonance imaging (rsfMRI) studies. Compared with the healthy control group, patients with OSA presented increased frontal and central δ/θ powers during resting-state wakefulness, and their slow-wave activity showed a positive correlation with apnea-hypopnea index. For rsfMRI, the prefrontal cortex and insula may be the vital regions for OSA and are strongly related to the severity of the disease. Meanwhile, some large-scale brain networks, such as the default-mode network, salience network, and central executive network, play pivotal roles in the pathology of OSA. We then discussed the contribution of resting-state brain imaging as an evaluation approach for disease interventions. Finally, we briefly introduced the effects of OSA-related physiological and mental diseases and discussed some future research directions from the perspective of resting-state brain imaging.

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Section: Introductionmentioning

confidence: 99%

Aberrant Awake Spontaneous Brain Activity in Obstructive Sleep Apnea: A Review Focused on Resting-State EEG and Resting-State fMRI

Zhao

Chen

et al. 2020

Front. Neurol.

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“…We consider this P3-like network reflecting high temporal resolution synchrony of neuronal signaling across the cerebral cortex, which differs from the various networks reported by resting-state MRI work [32] reflecting synchronized BOLD signal changes, that are indirect measures of neuronal signaling. We note that although current work focuses on the characterization of the network spatial configuration, the more frequently used frequency domain analysis [7] can be used together to offer both spatial and temporal information in quantifying individual differences.…”

Section: Discussionmentioning

confidence: 99%

“…The third is the lack of identification of neuromarkers based on neurocomputationally relevant parameters. Here, building upon decades of effort on EEGbased source imaging [7][8][9][10][11][12][13], we present an EEG-based source-imaging study of the resting-state brain to show that a neurobiologically-grounded and network configuration-based characterization can be provided for each individual without using group data, and that cross-individual variability as well as consistency in the involvement of each brain region in a globally synchronized cortical network can be quantitatively characterized.…”

Section: Introductionmentioning

confidence: 99%

Task-Free Recovery and Spatial Characterization of a P3-Like Global Network from Resting-State EEG

Tang

Privitera

2020

Preprint

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Diagnosis of mental illness, testing of treatment effects, and design of prevention strategies all require brain-based biomarkers that can serve as effective targets of evaluation. The search for such markers often starts with a search for neural correlates from brain imaging studies with measures of functions and behavior of interest. Yet such an approach can produce erroneous results for correlations do not guarantee causation. Only when the markers map onto neurocomputationally-relevant parameters can such markers best serve the intended function. Here we take an alternative approach to begin with targeting the neuroanatomically and neurophysiologically well-defined neuromoduatory systems that are well positioned to serve the computational role of generating globally synchronized neural activity for the purpose of functional integration [1]. By applying second-order blind identification (SOBI) [2], a blind source separation algorithm (BSS), to five minutes of resting-state EEG data (n=13), we provide evidence to support our conclusion that neuroelectrical signals associated with synchronized global network activity can be extracted using the detailed temporal information in the on-going continuously recorded EEG, instead of event-related potentials (ERPs). We report reliable extraction of a SOBI component, which we refer to as the P3-like component, in every individual studied, replicating our earlier report on data from a single participant [3]. We show that individual differences in the neural networks underlying this P3-like component can be revealed in high dimensional space by a vector of hits-based measures [4] for each of the P3-like network’s constituent structures. Given that resting-state EEG can be obtained with greater ease at natural non-hospital settings and at much lower cost in comparison with fMRI, and that mobile EEG systems have become increasingly available, the present work offers an enabling technology to support rapid and low-cost assessment of much larger and diverse populations of individuals, addressing several methodological limitations in our current investigation of brain function. Future opportunities and current limitations will be discussed.

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“…They have successfully described abnormalities in rsEEG cortical sources estimated in patients with several cognitive and psychiatric disorders in whom rsEEG activity was recorded using the present 10-20 montage system and source estimation techniques [e.g., (68)(69)(70)(71)(72)(73)(74)]. In this line of reasoning, a Workgroup of International Federation of Clinical Neurophysiology expressed the consensus position that EEG source estimation of rsEEG data collected by the traditional 10-20 montage system can be used for exploratory, retrospective studies performed on available rsEEG databases relative to neurological and psychiatric patients (75). Those exploratory studies may provide informative preliminary results motivating further investments to develop cross-validating prospective rsEEG studies using EEG techniques with higher resolution (i.e., recordings based on 48-256 scalp electrodes, etc.…”

Section: Methodological Remarksmentioning

confidence: 99%

Abnormalities of Cortical Sources of Resting State Delta Electroencephalographic Rhythms Are Related to Epileptiform Activity in Patients With Amnesic Mild Cognitive Impairment Not Due to Alzheimer's Disease

et al. 2020

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International Federation of Clinical Neurophysiology (IFCN) – EEG research workgroup: Recommendations on frequency and topographic analysis of resting state EEG rhythms. Part 1: Applications in clinical research studies

Cited by 178 publications

References 199 publications

Aberrant Awake Spontaneous Brain Activity in Obstructive Sleep Apnea: A Review Focused on Resting-State EEG and Resting-State fMRI

Aberrant Awake Spontaneous Brain Activity in Obstructive Sleep Apnea: A Review Focused on Resting-State EEG and Resting-State fMRI

Task-Free Recovery and Spatial Characterization of a P3-Like Global Network from Resting-State EEG

Abnormalities of Cortical Sources of Resting State Delta Electroencephalographic Rhythms Are Related to Epileptiform Activity in Patients With Amnesic Mild Cognitive Impairment Not Due to Alzheimer's Disease

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