Spatio-temporal properties of sleep slow waves and implications for development
Open accessAbstract
Objective sleep quality can be measured by electroencephalography (EEG), a non-invasive technique to quantify electrical activity generated by the brain. With EEG, sleep depth is measured by appearance and an increase in slow wave activity (scalp-SWA). EEG slow waves (scalp-SW) are the manifestation of underlying synchronous membrane potential transitions between silent (DOWN) and active (UP) states. This bistable periodic rhythm is defined as slow oscillation (SO). During its "silent state" cortical neurons are hyperpolarized and appear inactive, while during its "active state" cortical neurons are depolarized, fire spikes and exhibit continuous synaptic activity, excitatory and inhibitory. In adults, data from high-density EEG revealed that scalp-SW propagate across the cortical mantle in complex patterns. However, scalp-SW propagation undergoes modifications across development. We present novel data from children, indicating that scalp-SW originate centro-parietally, and emerge more frontally by adolescence. Based on the concept that SO and SW could actively modify neuronal connectivity, we discuss whether they fulfill a key purpose in brain development by actively conveying modifications of the maturing brain.
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SO activity during the first 1.5 years of life dominates over occipital cortical regions, whereas in adults it dominates over frontal cortical regions.
“For example, SO activity during the first 1.5 years of life dominates over occipital cortical regions, whereas in adults it dominates over frontal cortical regions.254”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [254]
The Conclusions (page unavailable) say that sleep slow waves originate mostly in frontal cortex in adults, supporting the adult comparison. For young children, however, they identify centro-parietal—not occipital—origins, and do not establish the claim for the first 1.5 years of life. (LLM, conf=0.88)
Experimental — accuracy not yet measuredCue delivery during TMR is associated with increased SO power, amplitude and density, increased spindle power and density, and improved SO-spindle coupling, often associated with TMR-induced memory advantage.
“It is associated with increased SO power, amplitude and density, 120,125,128 increased spindle power and density, 116,117,120,128 as well as improved SO-spindle coupling, 120 and these characteristics are often associated with the TMRinduced memory advantage.”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [128]
The “Function of propagating SO” section links slow waves to sleep-dependent memory consolidation and reports stronger fast-spindle coupling for global slow waves. It does not address TMR cue delivery or report the claimed increases in SO or spindle measures, improved coupling after cues, or a TMR-induced memory advantage. Searches for TMR and cue delivery found no relevant passage in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measured
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Schoch, S. F., Riedner, B. A., Deoni, S. C., Huber, R., LeBourgeois, M. K., & Kurth, S. (2018) · Sleep · doi:10.1093/sleep/zsy165 · Cited by 31 · see citing works
Self-citationPlumes of neuronal activity propagate in three dimensions through the nuclear avian brain
Beckers, G. J. L., van der Meij, J., Lesku, J. A., & Rattenborg, N. C. (2014) · BMC Biology · doi:10.1186/1741-7007-12-16 · Cited by 30 · see citing works
Bird-like propagating brain activity in anesthetized Nile crocodiles
Tisdale, R. K., Lesku, J. A., Beckers, G. J. L., & Rattenborg, N. C. (2018) · SLEEP · doi:10.1093/sleep/zsy105 · Cited by 24 · see citing works
Human fronto-parietal response scattering subserves vigilance at night
Gaggioni, G., Ly, J. Q. M., Chellappa, S. L., Wallant, D. C. ’., Rosanova, M., Sarasso, S., Luxen, A., Salmon, É., Middleton, B., Massimini, M., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.055 · Cited by 21 · see citing works
Kung, Y., Li, C., Chen, S., Chen, S. C.-J., Lo, C. Z., Lane, T. J., Biswal, B. B., Wu, C. W., & Lin, C. (2019) · Human Brain Mapping · doi:10.1002/hbm.24590 · Cited by 21 · see citing works
Slow wave detection in sleeping mice: Comparison of traditional and machine learning methods
Bukhtiyarova, O., Soltani, S., Chauvette, S., & Timofeev, I. (2018) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2018.08.016 · Cited by 14 · see citing works
Self-citationLocal Sleep Taking Care of High-Maintenance Cortical Circuits under Sleep Restriction
Fisher, S. P., & Vyazovskiy, V. V. (2014) · SLEEP · doi:10.5665/sleep.4156 · Cited by 13 · see citing works
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Sleep—A brain-state serving systems memory consolidation
Brodt, S., Inostroza, M., Niethard, N., & Born, J. (2023) · Neuron · doi:10.1016/j.neuron.2023.03.005 · Cited by 343 · see citing works
Contreras, M. P., Fechner, J., Born, J., & Inostroza, M. (2023) · The Journal of Neuroscience · doi:10.1523/jneurosci.1967-22.2023 · Cited by 9 · see citing works
- Authors
- Timofeev, I., Schoch, S. F., LeBourgeois, M. K., Huber, R., Riedner, B. A., & Kurth, S.
- Affiliations
- Université Laval (CA)
- University Hospital Zurich (CH)
- University of Colorado Boulder (US)
- University Children's Hospital Zurich (CH)
- University of Wisconsin–Madison (US)
- Venue
- Current Opinion in Physiology
- Publisher
- Elsevier BV
- Published
- 2020-06
- Volume
- 15
- Pages
- 172-182
- ISSN
- 2468-8673 (ISSN-L)
- PMC
- PMC7243595
- OpenAlex
- W3003601878
- Cited by
- 83
- References
- 97
- Citations by year
- 2026: 9 · 2025: 16 · 2024: 10 · 2023: 19 · 2022: 14 · 2021: 9 · 2020: 6
- FWCI
- 1.62
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Current Opinion in Physiology (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, cc-by)
- PubMed Central (acceptedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, cc-by)
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- National Institutes of Health (MH-086566)
- Canadian Institutes of Health Research (MOP-136967, MOP-136969, NS104368)
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (P0ZHP1-178697, PBZHP3-138801, PBZHP3-147180, PCEFP1-181279, PP00A-114923)
- Universität Zürich (FK-18-047)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Sleep and Wakefulness Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Keywords
- sleep slow waves, slow oscillations, sleep depth, sleep quality, slow wave propagation, brain development, children, adolescence, neuronal connectivity, high-density EEG
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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