ArticleFrontiers in human neuroscience2013
The Quest for EEG Power Band Correlation with ICA Derived fMRI Resting State Networks.
Article in Frontiers in human neuroscience, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- Group differences in MEG-ICA derived resting state networks: Application to major depressive disorder.NeuroImage · 2015Trial
- Spatial (mis)match between EEG and fMRI signal patterns revealed by spatio-spectral source-space EEG decomposition.Frontiers in neuroscience · 2025Article
- Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI.Progress in neurobiology · 2021Review
- Multimodal EEG-fMRI: advancing insight into large-scale human brain dynamics.Current opinion in biomedical engineering · 2021Article
- Joint Estimation of Effective Brain Wave Activation Modes Using EEG/MEG Sensor Arrays and Multimodal MRI Volumes.Neural computation · 2018Article
- Functional integration between brain regions at rest occurs in multiple-frequency bands.Brain connectivity · 2015Article
- Pathophysiology of ADHD and associated problems-starting points for NF interventions?Frontiers in human neuroscience · 2015Review
- Multimodal imaging of dynamic functional connectivity.Frontiers in neurology · 2015Article
- Detection of EEG-resting state independent networks by eLORETA-ICA method.Frontiers in human neuroscience · 2015Article
- Abnormal baseline brain activity in patients with pulsatile tinnitus: a resting-state FMRI study.Neural plasticity · 2014Article
- ICA of fMRI Studies: New Approaches and Cutting Edge Applications.Frontiers in human neuroscience · 2013Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The neuronal underpinnings of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) resting state networks (RSNs) are still unclear. To investigate the underlying mechanisms, specifically the relation to the electrophysiological signal, we used simultaneous recordings of electroencephalography (EEG) and fMRI during eyes open resting state (RS). Earlier studies using the EEG signal as independent variable show inconclusive results, possibly due to variability in the temporal correlations between RSNs and power in the low EEG frequency bands, as recently reported (Goncalves et al., 2006, 2008; Meyer et al., 2013). In this study we use three different methods including one that uses RSN timelines as independent variable to explore the temporal relationship of RSNs and EEG frequency power in eyes open RS in detail. The results of these three distinct analysis approaches support the hypothesis that the correlation between low EEG frequency power and BOLD RSNs is instable over time, at least in eyes open RS.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.