ArticleFrontiers in neuroinformatics2018
Detecting Large-Scale Brain Networks Using EEG: Impact of Electrode Density, Head Modeling and Source Localization.
Article in Frontiers in neuroinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
55 citing papers in PubMed, 144 citations in OpenAlex.
- Increased beta-band salience network connectivity predicts 12-month longitudinal changes in depressive and anxiety symptom severity in young adults: a resting-state EEG study.European archives of psychiatry and clinical neuroscience · 2026Article
- Article
- Virtual brain and electroencephalography explain the variance of memory alterations in mild cognitive impairment.Alzheimer's research & therapy · 2026Article
- A geometry aware framework enhances noninvasive mapping of whole human brain dynamics.Nature biomedical engineering · 2026Article
- Resting-state EEG alpha-BOLD coupling spatially follows cortical cell-type and receptor gradients.bioRxiv : the preprint server for biology · 2026Article
- High-density EEG network analysis in MCI: an exploratory study of electrode density and cognitive performance.Frontiers in aging neuroscience · 2026Article
- Establishing the link between post-concussive symptoms and brain network dysfunction: A systematic scoping review of neuroimaging evidence.NeuroImage. Clinical · 2026Article
- Multifractal Cascade Modeling Reveals Fundamental Limits of Current Neuroimaging Strategies.Sensors (Basel, Switzerland) · 2025Article
- Aberrant Salience Network Functional Connectivity in Resting-State and Fear-Related Autobiographical Memory Recall in Female Adolescents with Borderline Personality Disorder.Brain sciences · 2025Article
- Exploring electroencephalographic chronic pain biomarkers: a mega-analysis.EBioMedicine · 2025Article
- Severity of anhedonia is associated with hyper-synchronization of the salience-default mode network in non-clinical individuals: a resting state EEG connectivity study.Journal of neural transmission (Vienna, Austria : 1996) · 2025Article
- Resting-State EEG Alpha Rhythms Are Related to CSF Tau Biomarkers in Prodromal Alzheimer's Disease.International journal of molecular sciences · 2025Article
- Spatial (mis)match between EEG and fMRI signal patterns revealed by spatio-spectral source-space EEG decomposition.Frontiers in neuroscience · 2025Article
- Article
- Rapid reconfiguration of cortical networks after repeated exposure to visual-vestibular conflicts.Scientific reports · 2024Article
- Gamma power and beta envelope correlation are potential neural predictors of deep hypnosis.Scientific reports · 2024Article
- Motor imagery ability scores are related to cortical activation during gait imagery.Scientific reports · 2024Article
- Event-related modulation of alpha rhythm explains the auditory P300-evoked response in EEG.eLife · 2023Article
- Mechanisms of Change in Cognitive Function Domains Among Older Adults in Cognitive Deterioration and Improvement Groups: Evidence From Phenotypic Network Structure.Journal of the American Medical Directors Association · 2023Article
- A Novel OpenBCI Framework for EEG-Based Neurophysiological Experiments.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Resting state networks (RSNs) in the human brain were recently detected using high-density electroencephalography (hdEEG). This was done by using an advanced analysis workflow to estimate neural signals in the cortex and to assess functional connectivity (FC) between distant cortical regions. FC analyses were conducted either using temporal (tICA) or spatial independent component analysis (sICA). Notably, EEG-RSNs obtained with sICA were very similar to RSNs retrieved with sICA from functional magnetic resonance imaging data. It still remains to be clarified, however, what technological aspects of hdEEG acquisition and analysis primarily influence this correspondence. Here we examined to what extent the detection of EEG-RSN maps by sICA depends on the electrode density, the accuracy of the head model, and the source localization algorithm employed. Our analyses revealed that the collection of EEG data using a high-density montage is crucial for RSN detection by sICA, but also the use of appropriate methods for head modeling and source localization have a substantial effect on RSN reconstruction. Overall, our results confirm the potential of hdEEG for mapping the functional architecture of the human brain, and highlight at the same time the interplay between acquisition technology and innovative solutions in data analysis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.