ArticleNeuroImage2013
The spatiospectral characterization of brain networks: fusing concurrent EEG spectra and fMRI maps.
Article in NeuroImage, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Overlaps and distinctions between attention deficit/hyperactivity disorder and autism spectrum disorder in young adulthood: Systematic review and guiding framework for EEG-imaging research.Neuroscience and biobehavioral reviews · 2019Pooled it
- Consistency of resting-state correlations between fMRI networks and EEG band power.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Spatial (mis)match between EEG and fMRI signal patterns revealed by spatio-spectral source-space EEG decomposition.Frontiers in neuroscience · 2025Article
- Exploring the Skin Brain Link: Biomarkers in the Skin with Implications for Aging Research and Alzheimer's Disease Diagnostics.International journal of molecular sciences · 2023Article
- Is There a Relation between Brain and Muscle Activity after Virtual Reality Training in Individuals with Stroke? A Cross-Sectional Study.International journal of environmental research and public health · 2022Article
- Modeling the Hemodynamic Response Function Using EEG-fMRI Data During Eyes-Open Resting-State Conditions and Motor Task Execution.Brain topography · 2022Article
- Blood Oxygen Level-Dependent Lag Patterns Differ Between Rest and Task Conditions, but Are Largely Typical in Autism.Brain connectivity · 2022Article
- Blind Visualization of Task-Related Networks From Visual Oddball Simultaneous EEG-fMRI Data: Spectral or Spatiospectral Model?Frontiers in neurology · 2021Article
- Atypical Relationships Between Spontaneous EEG and fMRI Activity in Autism.Brain connectivity · 2020Article
- Mobile EEG in research on neurodevelopmental disorders: Opportunities and challenges.Developmental cognitive neuroscience · 2019Review
- Dynamic Functional Network Connectivity in Schizophrenia with Magnetoencephalography and Functional Magnetic Resonance Imaging: Do Different Timescales Tell a Different Story?Brain connectivity · 2019Article
- Frequency-dependent neural activity in primary angle-closure glaucoma.Neuropsychiatric disease and treatment · 2019Article
- Comparison of local spectral modulation, and temporal correlation, of simultaneously recorded EEG/fMRI signals during ketamine and midazolam sedation.Psychopharmacology · 2018Article
- Multimodal approaches to functional connectivity in autism spectrum disorders: An integrative perspective.Developmental neurobiology · 2018Review
- Spatiospectral Decomposition of Multi-subject EEG: Evaluating Blind Source Separation Algorithms on Real and Realistic Simulated Data.Brain topography · 2018Article
- EEG Signatures of Dynamic Functional Network Connectivity States.Brain topography · 2018Article
- Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI.Frontiers in neuroscience · 2018Article
- Moving Beyond ERP Components: A Selective Review of Approaches to Integrate EEG and Behavior.Frontiers in human neuroscience · 2018Review
- Single-trial EEG-informed fMRI analysis of emotional decision problems in hot executive function.Brain and behavior · 2017Article
- Deriving frequency-dependent spatial patterns in MEG-derived resting state sensorimotor network: A novel multiband ICA technique.Human brain mapping · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Different imaging modalities capture different aspects of brain activity. Functional magnetic resonance imaging (fMRI) reveals intrinsic networks whose BOLD signals have periods from 100 s (0.01 Hz) to about 10s (0.1 Hz). Electroencephalographic (EEG) recordings, in contrast, commonly reflect cortical electrical fluctuations with periods up to 20 ms (50 Hz) or above. We examined the correspondence between intrinsic fMRI and EEG network activity at rest in order to characterize brain networks both spatially (with fMRI) and spectrally (with EEG). Brain networks were separately identified within the concurrently recorded fMRI and EEG at the aggregate group level with group independent component analysis and the association between spatial fMRI and frequency by spatial EEG sources was examined by deconvolving their component time courses. The two modalities are considered linked if the estimated impulse response function (IRF) is significantly non-zero at biologically plausible delays. We found that negative associations were primarily present within two of five alpha components, which highlights the importance of considering multiple alpha sources in EEG-fMRI. Positive associations were primarily present within the lower (e.g. delta and theta) and higher (e.g. upper beta and lower gamma) spectral regions, sometimes within the same fMRI components. Collectively, the results demonstrate a promising approach to characterize brain networks spatially and spectrally, and reveal that positive and negative associations appear within partially distinct regions of the EEG spectrum.
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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.