ArticleHuman brain mapping2013
Simultaneous EEG and MEG source reconstruction in sparse electromagnetic source imaging.
Article in Human brain mapping, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Increasing EEG electrode density improves decoding of visual categories and source localization: an exploratory ultra-high-density EEG study.Communications engineering · 2026Article
- Inferring neural sources from electroencephalography: foundations and frontiers.Journal of neural engineering · 2026Review
- Time-resolved large-scale neural coactivations in macaque monkey.NeuroImage · 2025Article
- A novel, robust, and portable platform for magnetoencephalography using optically-pumped magnetometers.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Article
- A Novel, Robust, and Portable Platform for Magnetoencephalography using Optically Pumped Magnetometers.bioRxiv : the preprint server for biology · 2024Article
- Multi-Modal Electrophysiological Source Imaging With Attention Neural Networks Based on Deep Fusion of EEG and MEG.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2024Article
- From MEG to clinical EEG: evaluating a promising non-invasive estimator of defense-related muscle sympathetic nerve inhibition.Scientific reports · 2023Article
- The temporal dynamics of Large-Scale brain network changes in disorders of consciousness: A Microstate-Based study.CNS neuroscience & therapeutics · 2023Article
- A systematic evaluation of source reconstruction of resting MEG of the human brain with a new high-resolution atlas: Performance, precision, and parcellation.Human brain mapping · 2021Article
- Neuromodulation Management of Chronic Neuropathic Pain in The Central Nervous system.Advanced functional materials · 2020Article
- Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy.Human brain mapping · 2018Article
- Cortical Statistical Correlation Tomography of EEG Resting State Networks.Frontiers in neuroscience · 2018Article
- Neuronal Correlates of Product Feature Attractiveness.Frontiers in behavioral neuroscience · 2018Article
- A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies.Brain sciences · 2017Review
- Interacting parallel pathways associate sounds with visual identity in auditory cortices.NeuroImage · 2016Article
- MEG-EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy.Brain topography · 2015Article
- Gamma activity modulated by naming of ambiguous and unambiguous images: intracranial recording.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2015Article
- Lasting modulation effects of rTMS on neural activity and connectivity as revealed by resting-state EEG.IEEE transactions on bio-medical engineering · 2014Article
- Extreme learning machine-based classification of ADHD using brain structural MRI data.PloS one · 2013Article
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2 authors.
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Abstract
Electroencephalography (EEG) and magnetoencephalography (MEG) have different sensitivities to differently configured brain activations, making them complimentary in providing independent information for better detection and inverse reconstruction of brain sources. In the present study, we developed an integrative approach, which integrates a novel sparse electromagnetic source imaging method, i.e., variation-based cortical current density (VB-SCCD), together with the combined use of EEG and MEG data in reconstructing complex brain activity. To perform simultaneous analysis of multimodal data, we proposed to normalize EEG and MEG signals according to their individual noise levels to create unit-free measures. Our Monte Carlo simulations demonstrated that this integrative approach is capable of reconstructing complex cortical brain activations (up to 10 simultaneously activated and randomly located sources). Results from experimental data showed that complex brain activations evoked in a face recognition task were successfully reconstructed using the integrative approach, which were consistent with other research findings and validated by independent data from functional magnetic resonance imaging using the same stimulus protocol. Reconstructed cortical brain activations from both simulations and experimental data provided precise source localizations as well as accurate spatial extents of localized sources. In comparison with studies using EEG or MEG alone, the performance of cortical source reconstructions using combined EEG and MEG was significantly improved. We demonstrated that this new sparse ESI methodology with integrated analysis of EEG and MEG data could accurately probe spatiotemporal processes of complex human brain activations. This is promising for noninvasively studying large-scale brain networks of high clinical and scientific significance.
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