Cortical layers, rhythms and BOLD signals
Open accessAbstract
This review investigates how laminar fMRI can complement insights into brain function derived from the study of rhythmic neuronal synchronization. Neuronal synchronization in various frequency bands plays an important role in neuronal communication between brain areas, and it does so on the backbone of layer-specific interareal anatomical projections. Feedforward projections originate predominantly in supragranular cortical layers and terminate in layer 4, and this pattern is reflected in inter-laminar and interareal directed gamma-band influences. Thus, gamma-band synchronization likely subserves feedforward signaling. By contrast, anatomical feedback projections originate predominantly in infragranular layers and terminate outside layer 4, and this pattern is reflected in inter-laminar and interareal directed alpha- and/or beta-band influences. Thus, alpha-beta band synchronization likely subserves feedback signaling. Furthermore, these rhythms explain part of the BOLD signal, with independent contributions of alpha-beta and gamma. These findings suggest that laminar fMRI can provide us with a potentially useful method to test some of the predictions derived from the study of neuronal synchronization. We review central findings regarding the role of layer-specific neuronal synchronization for brain function, and regarding the link between neuronal synchronization and the BOLD signal. We discuss the role that laminar fMRI could play by comparing it to invasive and non-invasive electrophysiological recordings. Compared to direct electrophysiological recordings, this method provides a metric of neuronal activity that is slow and indirect, but that is uniquely non-invasive and layer-specific with potentially whole brain coverage.
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Specific functional roles have been proposed for different frequency bands and cell types, with beta and gamma corresponding to respective predictions and prediction-errors from deep and superficial pyramidal neurons.
“Notably with respect to the present discussion—and as a source of empirical support for HPP—specific functional roles have been proposed for different frequency bands and cell types, with beta and gamma corresponding to respective predictions and prediction-errors from deep and superficial pyramidal neurons (Bastos et al., 2012; Chao et al., 2018; Scheeringa and Fries, 2019).”
From An Integrated World Modeling Theory (IWMT) of Consciousness (2020) · cites this paper as Scheeringa and Fries, 2019
The ‘Layer-specific neuronal rhythms and brain function’ section says that superficial-layer gamma synchronization is thought to reflect prediction errors and deep-layer beta synchronization the projection of predictions. It does not identify the neurons carrying those respective signals as superficial and deep pyramidal neurons; its Introduction mentions pyramidal neurons only in a general description of EEG and MEG signals. Page numbers were not available in our copy. (LLM, conf=0.85)
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Top-Down Beta Enhances Bottom-Up Gamma
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“The study by van Kerkoerle et al (van Kerkoerle et al., 2014). suggests that alpha-band feed-back signals target both, superficial and deep layers, which is in line with alpha-BOLD correlations in both superficial and deep layers observed by Scheeringa et al. (2016).”
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Self-citationfMRI at High Spatial Resolution: Implications for BOLD-Models
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Gamma-Rhythmic Gain Modulation
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Evaluating the neurophysiological evidence for predictive processing as a model of perception
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“…support for HPP—specific functional roles have been proposed for different frequency bands and cell types, with beta and gamma corresponding to respective predictions and prediction-errors from deep and superficial pyramidal neurons (Bastos et al., 2012; Chao et al., 2018; Scheeringa and Fries, 2019).”
BackgroundMultimodal EEG-fMRI: advancing insight into large-scale human brain dynamics
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- Authors
- Scheeringa, R., & Fries, P.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Radboud University Nijmegen (NL)
- Corresponding author
- Fries, Pascal
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2019-08
- Volume
- 197
- Pages
- 689-698
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC6666418
- OpenAlex
- W2766305832
- Cited by
- 88
- References
- 135
- Citations by year
- 2026: 10 · 2025: 9 · 2024: 6 · 2023: 13 · 2022: 11 · 2021: 15 · 2020: 11 · 2019: 9 · 2018: 3 · 2017: 1
- FWCI
- 0.73
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- NeuroImage (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion, cc-by)
- PubMed Central (acceptedVersion, cc-by)
- Radboud Repository (Radboud University) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt) (submittedVersion, cc-by)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (SPP 1665)
- National Institutes of Health (1U54MH091657-WU-Minn-Consortium-HCP)
- European Geosciences Union (FP7-600730-Magnetrodes, HEALTH-F2-2008-200728-BrainSynch, FP7-604102-HBP)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- laminar fMRI, cortical layers, neuronal synchronization, BOLD signal, gamma oscillations, alpha and beta oscillations, feedback projections, layer 4, directed connectivity
- MeSH terms
- Animals, Brain, Cortical Synchronization, Humans, Magnetic Resonance Imaging, Brain Waves, Neuroimaging
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