| Keyword search (4,165 papers available) | ![]() |
"oscillation" Keyword-tagged Publications:
| Title | Authors | PubMed ID | |
|---|---|---|---|
| 1 | How vigilance states influence source imaging of physiological brain oscillations: evidence from intracranial EEG | Wei X; Afnan J; Avigdor T; von Ellenrieder N; Delaire É; Royer J; Ho A; Minato E; Schiller K; Jaber K; Wang YL; Moye M; Bernhardt BC; Lina JM; Grova C; Frauscher B; | 41687693 SOH |
| 2 | Climate variability is an important driver of water treatability in a shallow reservoir | Spence DS; Painter KJ; Nazemi A; Venkiteswaran JJ; Baulch HM; | 41166973 ENCS |
| 3 | Neurophysiological effects of targeting sleep spindles with closed-loop auditory stimulation | Jourde HR; Sobral M; Beltrame G; Coffey EBJ; | 40626105 PSYCHOLOGY |
| 4 | Effect of chronic benzodiazepine and benzodiazepine receptor agonist use on sleep architecture and brain oscillations in older adults with chronic insomnia | Barbaux L; Perrault AA; Cross NE; Weiner OM; Es-Sounni M; Pomares FB; Tarelli L; McCarthy M; Maltezos A; Smith D; Gong K; O' Byrne J; Yue V; Desrosiers C; Clerc D; Andriamampionona F; Lussier D; Gilbert S; Tannenbaum C; Gouin JP; Dang-Vu TT; | 40570297 CSBN |
| 5 | Phase-Amplitude Coupling of NREM Sleep Oscillations Shows Between-Night Stability and is Related to Overnight Memory Gains | Cross N; O' Byrne J; Weiner OM; Giraud J; Perrault AA; Dang-Vu TT; | 40214027 PERFORM |
| 6 | Sleep spindles and slow oscillations predict cognition and biomarkers of neurodegeneration in mild to moderate Alzheimer's disease | Páez A; Gillman SO; Dogaheh SB; Carnes A; Dakterzada F; Barbé F; Dang-Vu TT; Ripoll GP; | 39878233 CONCORDIA |
| 7 | Challenges and Approaches in the Study of Neural Entrainment | Duecker K; Doelling KB; Breska A; Coffey EBJ; Sivarao DV; Zoefel B; | 39358026 CONCORDIA |
| 8 | The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study | Jourde HR; Merlo R; Brooks M; Rowe M; Coffey EBJ; | 37675803 CONCORDIA |
| 9 | Neurophysiology, Neuropsychology, and Epilepsy, in 2022: Hills We Have Climbed and Hills Ahead. Neurophysiology in epilepsy | Frauscher B; Bénar CG; Engel JJ; Grova C; Jacobs J; Kahane P; Wiebe S; Zjilmans M; Dubeau F; | 37119580 PERFORM |
| 10 | Slow oscillation-spindle cross-frequency coupling predicts overnight declarative memory consolidation in older adults | Oren M Weiner | 37002805 PERFORM |
| 11 | Sigma oscillations protect or reinstate motor memory depending on their temporal coordination with slow waves | Nicolas J; King BR; Levesque D; Lazzouni L; Coffey EBJ; Swinnen S; Doyon J; Carrier J; Albouy G; | 35726850 PSYCHOLOGY |
| 12 | How cerebral cortex protects itself from interictal spikes: The alpha/beta inhibition mechanism | Pellegrino G; Hedrich T; Sziklas V; Lina JM; Grova C; Kobayashi E; | 34002916 PERFORM |
| 13 | Using Models to (Re-)Design Synthetic Circuits. | McCallum G, Potvin-Trottier L | 33405217 BIOLOGY |
| 14 | Cerebellar Cortex 4-12 Hz Oscillations and Unit Phase Relation in the Awake Rat. | Lévesque M; Gao H; Southward C; Langlois JMP; Léna C; Courtemanche R; | 33240052 HKAP |
| 15 | Brain Rhythms During Sleep and Memory Consolidation: Neurobiological Insights. | Marshall L, Cross N, Binder S, Dang-Vu TT | 31799908 PERFORM |
| 16 | State-Dependent Entrainment of Prefrontal Cortex Local Field Potential Activity Following Patterned Stimulation of the Cerebellar Vermis. | Tremblay SA, Chapman CA, Courtemanche R | 31736718 HKAP |
| 17 | Sleep spindles may predict response to cognitive-behavioral therapy for chronic insomnia | Dang-Vu TT; Hatch B; Salimi A; Mograss M; Boucetta S; O' Byrne J; Brandewinder M; Berthomier C; Gouin JP; | 29157588 PERFORM |
| 18 | Cortical reactivations during sleep spindles following declarative learning. | Jegou A, Schabus M, Gosseries O, Dahmen B, Albouy G, Desseilles M, Sterpenich V, Phillips C, Maquet P, Grova C, Dang-Vu TT | 30928690 PERFORM |
| Title: | How vigilance states influence source imaging of physiological brain oscillations: evidence from intracranial EEG | ||||
| Authors: | Wei X, Afnan J, Avigdor T, von Ellenrieder N, Delaire É, Royer J, Ho A, Minato E, Schiller K, Jaber K, Wang YL, Moye M, Bernhardt BC, Lina JM, Grova C, Frauscher B | ||||
| Link: | https://pubmed.ncbi.nlm.nih.gov/41687693/ | ||||
| DOI: | 10.1016/j.neuroimage.2026.121803 | ||||
| Publication: | NeuroImage | ||||
| Keywords: | Cortical oscillation analysis; High-density EEG; Normative intracranial EEG; Sleep/Wake Physiology; Source imaging; Vigilance states; | ||||
| PMID: | 41687693 | Category: | Date Added: | 2026-02-14 | |
| Dept Affiliation: |
SOH
1 Analytical Neurophysiological Lab, Department of Neurology, Duke University, Durham, North Carolina, USA; Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA. 2 Integrated Program in Neuroscience, McGill University, Montréal, Québec, Canada; Multimodal Functional Imaging Lab, Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada; Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, Québec, Canada. 3 Analytical Neurophysiological Lab, Department of Neurology, Duke University, Durham, North Carolina, USA; Multimodal Functional Imaging Lab, Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada; Analytical Neurophysiological Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada. 4 Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, Québec, Canada. 5 Multimodal Functional Imaging Lab, Department of Physics and Concordia School of Health, Concordia University, Montréal, Québec, Canada. 6 Multimodal Imaging and Connectome Analysis (MICA) Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada. 7 Analytical Neurophysiological Lab, Department of Neurology, Duke University, Durham, North Carolina, USA. 8 Analytical Neurophysiological Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada. 9 Schulich School of Medicine and Dentistry, Western University, London, ON, Canada. 10 Physnum Team, Centre De Recherches Mathématiques, Montréal, Québec, Canada; Electrical Engineering Department, École De Technologie Supérieure, Montréal, Québec H3C 1K3, Canada; Center for Advanced Research in Sleep Medicine, Sacré-Coeur Hospital, Montréal, Québec, Canada. 11 Multimodal Functional Imaging Lab, Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada; Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, Québec, Canada; Physnum Team, Centre De Recherches Mathématiques, Montréal, Québec, Canada; Multimodal Functional Imaging Lab, Department of Physics and Concordia School of Health, Concordia University, Montréal, Québec, Canada. 12 Analytical Neurophysiological Lab, Department of Neurology, Duke University, Durham, North Carolina, USA; Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA; Analytical Neurophysiological Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada. Electronic address: birgit.frauscher@duke.edu. |
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Description: |
Cortical oscillations across sleep-wake cycles are essential for coordinating functional brain dynamics. High-density electroencephalography (HDEEG) combined with electrical source imaging (ESI) provides a noninvasive approach to map cortical dynamics; however, its ability to capture spatial ongoing oscillations across different vigilance states remains uncertain. Here, we directly compared HDEEG source imaging by comparing it to a normative intracranial EEG (iEEG) atlas from 110 epilepsy patients with electrodes in healthy brain regions (https://mni-open-ieegatlas.research.mcgill.ca/). Wavelet-based Maximum Entropy on the Mean (wMEM) was applied to localize oscillatory patterns using overnight HDEEG recordings from 35 healthy adults (16 females, mean age 31.1±6.3 years). Virtual iEEG (ViEEG) signals were estimated by applying an iEEG forward model to wMEM sources to examine oscillatory patterns across 5 frequency bands, 38 regions, and 4 vigilance states. We found that HDEEG source imaging exhibited comparable spectral patterns of iEEG in low frequencies but overestimated oscillatory activities at high frequencies. Lateral cortical regions exhibited more accurate source estimation than medial regions (p<0.05). After removing the aperiodic components, the spectral alignment between ViEEG and iEEG significantly improved except for N3 sleep (p<0.05). Oscillatory peak patterns in ViEEG reflect state-dependent dynamics that are broadly consistent with iEEG peaks (p<0.05). HDEEG-derived ViEEG and magnetoencephalography-derived ViEEG approximated iEEG spectral features, showing complementary correspondence. These findings reveal that vigilance states significantly shape cortical oscillations by altering their spectral and spatial profiles. Our results establish high-density EEG as a powerful tool for large-scale, noninvasive investigations of human sleep neurophysiology and brain network dynamics. |



