About this Research Topic
Resting-state EEG and fMRI are a dominant paradigms widely used to study brain function, brain development, plasticity, and neurodegeneration in disease. They are attractive for developmental neuropsychology and clinical research because of their simplicity for subjects, straightforward standardization, sensitivity to brain disorders and high test-retest reliability. Importantly, non-sensory experiences like mind wandering may arise from ongoing brain activity. Their applications have an expanding tendency in research of neurological or psychiatric disease.
This Research Topic on ”Resting-state EEG and fMRI” intends to break down the barrier between resting-state fMRI (rs-fMRI) and resting-state EEG (rsEEG). Firstly, there are many common methods for both modalities: independent component analysis (ICA), functional connectivity and graph theory are currently widely utilized to discuss the systematic structure of brain networks. Secondly, both modalities suffer from the problem of reliability and reproducibility, desiring stability measures of the human brain functional connectomics. In addition, the simultaneous EEG-fMRI technique provides new potential to match the findings from previous studies with any modal individually. An extensive discussion between rs-fMRI and rsEEG may benefit both fields and encourage further cooperation from various disciplines. Our target is to address the challenges in analysis, modelling and interpreting the resting-state EEG and fMRI data from different perspectives: neural computation, biomedical engineering, and cognitive neuroscience.
This Research Topic welcomes submissions of all types (original research, case report, case series, viewpoint, review articles, etc.) around a variety of behavioral states and neuropsychiatric disorders. We will discuss the potential utility of these methods in detecting neurophysiological impairments in disease and monitoring neurophysiological changes in response to an intervention. The crucial point is to provide a objective comparison of the brain networks extracted from rsEEG and rsfMRI about brain function and disorders. We welcome submissions focused on innovative technologies and methods that can foster resting-state neuroimaging. We also welcome our colleagues to submit paper with theoretical work, simulation studies, practical experimental data analysis as well as critical reviews.
Keywords: Resting-state fMRI, resting-state EEG, resting-state brain network, microstate, default mode
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