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The relationship between oscillatory EEG activity and the laminar-specific BOLD signal
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Significance: In this study, we demonstrate that α-, β-, and γ-oscillations can be related to activity in different cortical layers in the human brain. These cortical layers are believed to instantiate feedforward and feedback information streams. Electrophysiological oscillations in α- (8–12 Hz), β- (15–30 Hz), and γ- (40–100 Hz) bands have also been associated with different roles in feedforward and feedback processes and to different cortical layers in nonhuman animals. By simultaneously recording laminar functional MRI (fMRI) and EEG, we could directly link oscillatory signals to activity in cortical layers in humans. This research provides an important neural basis for noninvasive research into the role of cortical layers in information processing using laminar fMRI alone or combined with EEG.
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“Such findings are consistent with the observable laminar profile of fMRI (187), LFP-based phase relationship (184), and effects of neuromodulation (188).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [187]
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“Additional narrow frequency bands of the LFP spectrum, such as the delta (2-4 Hz) (de Munck et al., 2009), theta (5-7 Hz) (Scheeringa et al., 2008), beta (15-30 Hz) (Laufs et al., 2006), and gamma (30-80 Hz; Ebisch et al., 2005; Scheeringa et al., 2016, 2011) bands have also been used to this end.”
BackgroundSleep, learning, and memory in human research using noninvasive neuroimaging techniques
Uji, M., & Tamaki, M. (2022) · Neuroscience Research · doi:10.1016/j.neures.2022.12.013 · Cited by 18
Wu, P., Chu, Y.-H., Lin, J.-F. L., Kuo, W., & Lin, F. (2018) · Scientific Reports · doi:10.1038/s41598-018-31292-x · Cited by 15
Mishra, A., Majumdar, S., Wang, F., Wilson, G. H., Gore, J. C., & Chen, L. M. (2018) · Human Brain Mapping · doi:10.1002/hbm.24375 · Cited by 15
“The anatomical connections between layers are well established, so the examination of functional connectivity between layers of functionally related regions may provide valuable insights into local and interareal information flow for specific brain functions, such as the somatosensory functions studied here or visual…”
BackgroundLinking visual gamma to task‐related brain networks—a simultaneous EEG‐fMRI study
Beldzik, E., Domagalik, A., Beres, A. M., & Marek, T. (2019) · Psychophysiology · doi:10.1111/psyp.13462 · Cited by 16
Spectral fingerprints of facial affect processing bias in major depression disorder
Jiang, H., Hua, L., Dai, Z., Tian, S., Yao, Z., Lü, Q., & Popov, T. G. (2019) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsz096 · Cited by 16
“, 2012; Fries, 2015) and correlate with the blood–oxygen level-dependent signal (positive correlation with gamma and negative correlation with alpha/beta) (Logothetis et al., 2001; Scheeringa et al., 2011; Scheeringa et al., 2016; Hermes et al., 2017).”
BackgroundDaniel, A. J., Smith, J. A., Spencer, G. S., Jorge, J., Bowtell, R. W., & Mullinger, K. J. (2018) · Human Brain Mapping · doi:10.1002/hbm.24396 · Cited by 14
Adapted cabling of an EEG cap improves simultaneous measurement of EEG and fMRI at 7T
Meyer, M. C., Scheeringa, R., WEBB, A. G., Petridou, N., Kraff, O., & Norris, D. G. (2019) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2019.108518 · Cited by 12
“…et al., 2010; Porcaro et al., 2010; Scheeringa et al., 2009); the relation between resting state networks and EEG (Mantini et al., 2007; Moosmann et al., 2009; Sadaghiani et al., 2010; Scheeringa et al., 2008, 2012); and the neural underpinnings of the BOLD signal (Scheeringa et al., 2011a, 2016).”
BackgroundMethodInfluentialSelf-citationMeditation and the brain in health and diseasePreprint
Fox, K. C. R., & Cahn, B. R. (2018) · MindRxiv (OSF Preprints) · doi:10.31231/osf.io/m2sez · Cited by 13
Wu, C. W., Tsai, P.-J., Chen, S. C.-J., Li, C., Hsu, A., Wu, H.-Y., Ko, Y.-T., Hung, P.-C., Chang, C., Lin, C., et al. (2019) · Sleep and Biological Rhythms · doi:10.1007/s41105-019-00232-1 · Cited by 12
Improved cortical boundary registration for locally distorted fMRI scans
van Mourik, T., Koopmans, P. J., & Norris, D. G. (2019) · PLoS ONE · doi:10.1371/journal.pone.0223440 · Cited by 11
Self-citationUji, M., Jentzsch, I., Redburn, J., & Vishwanath, D. (2019) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2019.04.017 · Cited by 11
Orekhova, E. V., Prokofyev, A. O., Nikolaeva, A. Y., Schneiderman, J. F., & Stroganova, T. A. (2020) · PLoS ONE · doi:10.1371/journal.pone.0228937 · Cited by 9
Stefanov, K., McLean, J., McColl, A., Basu, N., Cavanagh, J., & Krishnadas, R. (2020) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.04.005 · Cited by 10
Size of the spatial correlation between ECoG and fMRI activity
Piantoni, G., Hermes, D., Ramsey, N. F., & Petridou, N. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118459 · Cited by 10
Relating neural oscillations to laminar fMRI connectivity in visual cortex
Scheeringa, R., Bonnefond, M., van Mourik, T., Jensen, O. B., Norris, D. G., & Koopmans, P. J. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac154 · Cited by 19
“This is further supported by our previous finding from this dataset that beta power correlates negatively with BOLD activity in deep layers (Scheeringa et al. 2016), which aligns well with observations in EEG and MEG that beta power, like alpha power, often decreases in regions that become actively…”
InfluentialSelf-citationChowdhury, M. E. H., Khandakar, A. A., Mullinger, K. J., Al-Emadi, N. A., & Bowtell, R. W. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00690 · Cited by 10
He, Q., Zhu, X., & Fang, F. (2023) · Journal of Vision · doi:10.1167/jov.23.14.2 · Cited by 8
“However, our results are not consistent with some studies in which anodal tDCS was effective in facilitating VPL (Olma et al., 2013; Sczesny-Kaiser et al., 2016; Van Meel, Daniels, de Beeck, & Baeck, 2016; Wu et al., 2023), or even impairing VPL with a short training session (Grasso, Tonolli,…”
ResultWei, H. T., Francois-Nienaber, A., Deschamps, T., Bellana, B., Hebscher, M., Sivaratnam, G., Zadeh, M., & Meltzer, J. A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118457 · Cited by 10
Frequency and laminar profile of feature-specific visual activity revealed by interleaved EEG–fMRIPreprint
Clausner, T., Marques, J. P., Scheeringa, R., & Bonnefond, M. (2025) · eLife · doi:10.1101/2024.07.31.605816 · Cited by 9
Self-citationDistinct alpha networks modulate different aspects of perceptual decision-making
Zhou, Y. J., van Es, M. W. J., & Haegens, S. (2025) · PLoS Biology · doi:10.1371/journal.pbio.3003461 · Cited by 8
Helbling, S. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00410 · Cited by 8
Neural basis of distractor resistance during visual working memory maintenance
Hermann, P., Weiss, B., Knakker, B., Madurka, P., Manga, A., Nárai, Á., & Vidnyánszky, Z. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118650 · Cited by 8
How to study spoken language understanding: a survey of neuroscientific methods
Rodd, J. M., & Davis, M. H. (2017) · Language Cognition and Neuroscience · doi:10.1080/23273798.2017.1323110 · Cited by 7
Metadata
- Authors
- Scheeringa, R., Koopmans, P. J., van Mourik, T., Jensen, O., & Norris, D. G.
- Affiliations
- Radboud University Nijmegen (NL)
- Donders Institute for Brain Cognition and Behaviour, Radboud University, NL-6500 HB Nijmegen, The Netherlands;
- Erwin L. Hahn Institute for Magnetic Resonance Imaging (DE)
- Corresponding author
- Scheeringa, René
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2016-05-31
- Volume
- 113
- Issue
- 24
- Pages
- 6761-6766
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4914170
- OpenAlex
- W2410089593
- Cited by
- 162
- References
- 74
- Citations by year
- 2026: 14 · 2025: 13 · 2024: 8 · 2023: 12 · 2022: 13 · 2021: 26 · 2020: 21 · 2019: 21 · 2018: 13 · 2017: 17 · 2016: 4
- FWCI
- 11.67
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- University of Twente Research Information (publishedVersion, other-oa)
- Universitätsbibliographie, Universität Duisburg-Essen (submittedVersion)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- University of Twente Research Information (submittedVersion, other-oa)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (453-09-002, 451-12-021)
- Wellcome Trust (WT100092MA)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- cortical oscillations, gamma oscillations, beta oscillations, alpha oscillations, visual cortex, EEG-fMRI correlation, high-resolution fMRI
- MeSH terms
- Adolescent, Adult, Alpha Rhythm, Beta Rhythm, Female, Humans, Magnetic Resonance Imaging, Male, Oxygen, Visual Cortex, Gamma Rhythm
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