ArticleBrain sciences2022
Functional Connectivity States of Alpha Rhythm Sources in the Human Cortex at Rest: Implications for Real-Time Brain State Dependent EEG-TMS.
Article in Brain sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- State-Guided TMS-EEG for N100 Enhancement Study Based on Whole-Brain EEG Microstates.CNS neuroscience & therapeutics · 2026Article
- Fully Hyperbolic Neural Networks: A Novel Approach to Studying Aging Trajectories.IEEE journal of biomedical and health informatics · 2025Article
- Online functional connectivity analysis of large all-to-all networks in MNE Scan.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Neuroimaging Study of Brain Functional Differences in Generalized Anxiety Disorder and Depressive Disorder.Brain sciences · 2023Article
- Dynamic Connectivity Analysis Using Adaptive Window Size.Sensors (Basel, Switzerland) · 2022Article
- Modern Developments in Transcranial Magnetic Stimulation: The Editorial.Brain sciences · 2022Article
- The Electroencephalographic Brainwave Spectrum, Mindful Meditation, and Awareness: Hypothesis.International journal of yogaArticle
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Authors and funding
4 authors at 2 institutions in 3 countries.
Funding
Abstract
Alpha is the predominant rhythm of the human electroencephalogram, but its function, multiple generators and functional coupling patterns are still relatively unknown. In this regard, alpha connectivity patterns can change between different cortical generators depending on the status of the brain. Therefore, in the light of the communication through coherence framework, an alpha functional network depends on the functional coupling patterns in a determined state. This notion has a relevance for brain-state dependent EEG-TMS because, beyond the local state, a network connectivity overview at rest could provide further and more comprehensive information for the definition of 'instantaneous state' at the stimulation moment, rather than just the local state around the stimulation site. For this reason, we studied functional coupling at rest in 203 healthy subjects with MEG data. Sensor signals were source localized and connectivity was studied at the Individual Alpha Frequency (IAF) between three different cortical areas (occipital, parietal and prefrontal). Two different and complementary phase-coherence metrices were used. Our results show a consistent connectivity between parietal and prefrontal regions whereas occipito-prefrontal connectivity is less marked and occipito-parietal connectivity is extremely low, despite physical closeness. We consider our results a relevant add-on for informed, individualized real-time brain state dependent stimulation, with possible contributions to novel, personalized non-invasive therapeutic approaches.
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