CoChat
Sign Up
Cited by 41

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Pupil size reveals arousal level fluctuations in human sleep

Carro-Domínguez, Manuel, Huwiler, Stephanie, Oberlin, Stella, Oesch, Timona Leandra, Badii, Gabriela, Lüthi, Anita, Wenderoth, Nicole, Meissner, Sarah Nadine, Lustenberger, Caroline·2025·Nature Communications
DOI 10.1038/s41467-025-57289-5PMC PMC11871316

Published version of a preprint

Open this paper in CoChat — free account

Abstract

Recent animal research has revealed the intricate dynamics of arousal levels that are important for maintaining proper sleep resilience and memory consolidation. In humans, changes in arousal level are believed to be a determining characteristic of healthy and pathological sleep but tracking arousal level fluctuations has been methodologically challenging. Here we measured pupil size, an established indicator of arousal levels, by safely taping the right eye open during overnight sleep and tested whether pupil size affects cortical response to auditory stimulation. We show that pupil size dynamics change as a function of important sleep events across different temporal scales. In particular, our results show pupil size to be inversely related to the occurrence of sleep spindle clusters, a marker of sleep resilience. Additionally, we found pupil size prior to auditory stimulation to influence the evoked response, most notably in delta power, a marker of several restorative and regenerative functions of sleep. Recording pupil size dynamics provides insights into the interplay between arousal levels and sleep oscillations.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41467-025-57289-5

Cites

10 of 10 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Show all 10 references

Research works printed but not linked: 84

  1. Poe, G. R. et al. Locus coeruleus: a new look at the blue spot. Nat. Rev. Neurosci. 21, 644–659 (2020). · DOI · Paper page
  2. Osorio-Forero, A., Cherrad, N., Banterle, L., Fernandez, L. M. J. & Lüthi, A. When the Locus Coeruleus speaks up in sleep: recent insights, emerging perspectives. Int. J. Mol. Sci. 23. https://doi.org/10.3390/ijms23095028 (2022). · DOI
  3. Aston-Jones, G. & Cohen, J. D. An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance. Annu. Rev. Neurosci. 28, 403–450 (2005). · DOI · Paper page
  4. Jones, B. E. Activity, modulation and role of basal forebrain cholinergic neurons innervating the cerebral cortex. Prog. Brain Res. 145, 157–169 (2004). · DOI
  5. Jones, B. E. Arousal systems. Front. Biosci. 8, 438–451 (2003). · DOI
  6. de Lecea, L. et al. The hypocretins: hypothalamus-specific peptides with neuroexcitatory activity. Proc. Natl Acad. Sci. USA 95, 322–327 (1998). · DOI · Paper page
  7. Cazettes, F., Reato, D., Morais, J. P., Renart, A. & Mainen Z. F. Phasic activation of dorsal raphe serotonergic neurons increases pupil size. Curr. Biol. 192–197. https://doi.org/10.1016/j.cub.2020.09.090 (2020). · DOI
  8. Grujic, N., Tesmer, A., Bracey, E., Peleg-Raibstein, D. & Burdakov D. Control and coding of pupil size by hypothalamic orexin neurons. Nat. Neurosci. 26, 1160–1164 (2023). · DOI
  9. Xu, Y. L. et al. Neuropeptide S: a neuropeptide promoting arousal and anxiolytic-like effects. Neuron 43, 487–497 (2004). · DOI
  10. Jodoj, E., Chiang, C. & Aston-Jones, G. Potent excitatory influence of prefrontal cortex activity on noradrenergic locus coeruleus neurons. Neuroscience 83, 63–79 (1998). · DOI · Paper page
  11. Dorr, A. E. & Debonnel, G. Effect of vagus nerve stimulation on serotonergic and noradrenergic transmission. J. Pharmacol. Exp. Therap. 318, 890–898 (2006). · DOI · Paper page
  12. Halász, P., Terzano, M., Parrino, L. & Bódizs R. The nature of arousal in sleep. J Sleep Res. 13:1–23. https://doi.org/10.1111/J.1365-2869.2004.00388.X (2004). · DOI
  13. Halász, P. The K-complex as a special reactive sleep slow wave-a theoretical update. Sleep. Med Rev. 29, 34–40 (2016). · DOI
  14. Osorio-Forero, A. et al. Noradrenergic circuit control of non-REM sleep substates. Curr. Biol. 31, 5009–5023.e7 (2021). · DOI · Paper page
  15. Iber, C., Ancoli-Israel, S., Chesson, A. L. & Quan, S. F. The AASM Manual for the Scoring of Sleep and Associated Events (October 2012) 1–17 (American Academy of Sleep Medicine, Westchester, 2007) · DOI
  16. Kjaerby, C. et al. Memory-enhancing properties of sleep depend on the oscillatory amplitude of norepinephrine. Nat Neurosci. 25(August). https://doi.org/10.1038/s41593-022-01102-9 (2022). · DOI · Paper page
  17. Yüzgeç, Ö., Prsa, M., Zimmermann, R. & Huber, D. Pupil size coupling to cortical states protects the stability of deep sleep via parasympathetic modulation. Curr. Biol. 28, 392–400.e3 (2018). · DOI
  18. Lázár, Z. I., Dijk, D. J. & Lázár, A. S. Infraslow oscillations in human sleep spindle activity. J. Neurosci. Methods. 316, 22–34 (2019). · DOI · Paper page
  19. Joshi, S. & Gold, J. I. Pupil size as a window on neural substrates of cognition. Trends Cogn. Sci. 24, 466–480 (2020). · DOI
  20. Zerbi, V. et al. Rapid reconfiguration of the functional connectome after chemogenetic locus coeruleus activation article rapid reconfiguration of the functional connectome after chemogenetic locus coeruleus activation. Neuron 103, 702–718 (2019). · DOI
  21. Megemont, M., McBurney-Lin, J. & Yang, H. Pupil diameter is not an accurate real-time readout of locus coeruleus activity. Elife 11, e70510 (2022). · DOI
  22. Hayat, H. et al. Locus coeruleus norepinephrine activity mediates sensory-evoked awakenings from sleep. Sci. Adv. 6, https://doi.org/10.1126/sciadv.aaz4232 (2020). · DOI
  23. Alnæs, D. et al. Pupil size signals mental effort deployed during multiple object tracking and predicts brain activity in the dorsal attention network and the locus coeruleus. J, Vis. 14, 1 (2014). · DOI
  24. de Gee, J. W. et al. Dynamic modulation of decision biases by brainstem arousal systems. Elife 6. https://doi.org/10.7554/ELIFE.23232 (2017). · DOI
  25. Oswald, I. Falling asleep open-eyed during intense rhythmic stimulation. Br. Med J. 1, 1450–1455 (1960). · DOI
  26. McNab, A. A. The eye and sleep. Clin. Exp. Ophthalmol. 33, 117–125 (2005). · DOI
  27. Weygandt Mathis, M. & Bethge, M. DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nat. Neurosci. https://doi.org/10.1038/s41593-018-0209-y. · DOI · Paper page
  28. Nath, T. et al. Using DeepLabCut for 3D markerless pose estimation across species and behaviors. Nat. Protoc. 14, 2152–2176 (2019). · DOI
  29. Lendner, J. D. et al. An electrophysiological marker of arousal level in humans. Elife 9, 1–29 (2020). · DOI
  30. Höhn, C., Hahn, M. A., Lendner, J. D. & Hoedlmoser, K. Spectral slope and Lempel-Ziv complexity as robust markers of brain states during sleep and wakefulness. eNeuro 11 (2024). · DOI
  31. Joshi, S., Li, Y., Kalwani, R. M. & Gold, J. I. Relationships between pupil diameter and neuronal activity in the locus coeruleus, colliculi, and cingulate cortex. Neuron 89, 221–234 (2016). · DOI · Paper page
  32. Kobayashi, G., Tanaka, K. F. & Takata, N. Pupil dynamics-derived sleep stage classification of a head-fixed mouse using a recurrent neural network. Keio J. Med. 72, 44–59 (2023). · DOI
  33. Tsunematsu, T., Patel, A. A., Onken, A. & Sakata, S. State-dependent brainstem ensemble dynamics and their interactions with hippocampus across sleep states. Elife 9, 1–22 (2020). · DOI
  34. Gao. R., Peterson E. J. & Voytek, B. Inferring synaptic excitation/inhibition balance from field potentials. Published online. https://doi.org/10.1016/j.neuroimage.2017.06.078 (2017). · DOI
  35. Bódizs, R. et al. A set of composite, non-redundant EEG measures of NREM sleep based on the power law scaling of the Fourier spectrum. Sci. Rep. 11, 1–18 (2021). · DOI
  36. Miskovic, V., Macdonald, K. J., Rhodes, J. L. & Cote, K. A. Changes in EEG multiscale entropy and power-law frequency scaling during the human sleep cycle. Published online. https://doi.org/10.1002/hbm.24393 (2018). · DOI
  37. Antony, J. W. et al. Sleep spindle refractoriness segregates periods of memory reactivation. Curr. Biol. 28, 1736–1743.e4 (2018). · DOI · Paper page
  38. Bernardi, G. et al. Local and widespread slow waves in stable NREM sleep: evidence for distinct regulation mechanisms. Published online. https://doi.org/10.3389/fnhum.2018.00248 (2018). · DOI
  39. Cardis, R. et al. Cortico-autonomic local arousals and heightened somatosensory arousability during NREMS of mice in neuropathic pain. Elife 10, 1–27 (2021). · DOI
  40. Sforza, E., Jouny, C. & Ibanez, V. Cardiac activation during arousal in humans: further evidence for hierarchy in the arousal response. https://doi.org/10.1016/s1388-2457(00)00363-1 (2000). · DOI
  41. de Zambotti, M. et al. K-complexes: interaction between the central and autonomic nervous systems during sleep. Sleep 39, 1129–1137 (2016). · DOI
  42. Scoring, E. A. EEG arousals: scoring rules and examples: a preliminary report from the sleep disorders atlas task force of the American Sleep Disorders Association. Sleep 15, 174–184 (1992). · DOI
  43. Pfeffer, T. et al. Coupling of pupil-and neuronal population dynamics reveals diverse influences of arousal on cortical processing. Elife 11, e71890 (2022). · DOI
  44. Boutin A., Doyon J. A sleep spindle framework for motor memory consolidation. Philos.Trans. R. Soc. B Biol. Sci. 375. https://doi.org/10.1098/rstb.2019.0232 (2020). · DOI
  45. Ngo, H. V., Martinetz, T., Born, J. & Molle, M. Auditory closed-loop stimulation of the sleep slow oscillation enhances memory. Neuron. https://doi.org/10.1016/j.neuron.2013.03.006 (2013). · DOI · Paper page
  46. Ngo, H. V. V., Seibold, M., Boche, D. C., Mölle, M. & Born, J. Insights on auditory closed-loop stimulation targeting sleep spindles in slow oscillation up-states. J. Neurosci. Methods 316, 117–124 (2019). · DOI
  47. Osorio-Forero, A. et al. Infraslow noradrenergic locus coeruleus activity fluctuations are gatekeepers of the NREM–REM sleep cycle. Nat. Neurosci. 28, 84–96 (2025). · DOI
  48. Naji, M., Krishnan, G. P., McDevitt, E. A., Bazhenov, M. & Mednick, S. C. Coupling of autonomic and central events during sleep benefits declarative memory consolidation. Neurobiol. Learn Mem. 157, 139–150 (2019). · DOI
  49. Boutin, A. et al. Temporal cluster-based organization of sleep spindles underlies motor memory consolidation. Proc. R. Soc. B. 291, https://doi.org/10.1098/rspb.2023.1408 (2024). · DOI
  50. Huwiler, S. et al. Effects of auditory sleep modulation approaches on brain oscillatory and cardiovascular dynamics. Sleep zsac155. https://doi.org/10.1093/sleep/zsac155 (2022). · DOI
  51. Besedovsky, L. et al. Auditory closed-loop stimulation of EEG slow oscillations strengthens sleep and signs of its immune-supportive function. Nat. Commun. 8, 1984 (2017). · DOI · Paper page
  52. Krugliakova, E. et al. Boosting recovery during sleep. auditory stimulation. Front. Neurosci. 16, 755958 (2022). · DOI
  53. Leminen, M. M. et al. Enhanced memory consolidation via automatic sound stimulation during non-REM sleep. Sleep 40, zsx003 (2017). · DOI
  54. Lustenberger, C. et al. Auditory deep sleep stimulation in older adults at home: a randomized crossover trial. Commun. Med. 2, 30 (2022). · DOI
  55. Weigenand, A., Mölle, M., Werner, F., Martinetz, T. & Marshall, L. Timing matters: open-loop stimulation does not improve overnight consolidation of word pairs in humans. Eur. J. Neurosci. 44, 2357–2368 (2016). · DOI
  56. Grimaldi, D. et al. Strengthening sleep-autonomic interaction via acoustic enhancement of slow oscillations. Sleep. 1–11. https://doi.org/10.1093/sleep/zsz036 (2019). · DOI
  57. Bellesi, M., Riedner, B. A., Garcia-Molina, G. N., Cirelli, C. & Tononi, G. Enhancement of sleep slow waves: underlying mechanisms and practical consequences. Front. Syst. Neurosci. 8, 1–17 (2014). · DOI · Paper page
  58. Colrain, I. M. The K-complex: a 7-decade history review. Sleep 28, 255 (2005). · DOI
  59. Neves, R. M., van Keulen, S., Yang, M., Logothetis, N. K. & Eschenko, O. Locus coeruleus phasic discharge is essential for stimulus-induced gamma oscillations in the prefrontal cortex. J. Neurophysiol. 119, 904–920 (2017). · DOI
  60. Kokkinos, V. & Kostopoulos, G. K. Human non-rapid eye movement stage II sleep spindles are blocked upon spontaneous K-complex coincidence and resume as higher frequency spindles afterwards. J. Sleep. Res. 20, 57–72 (2011). · DOI
  61. Lustenberger, C. et al. Auditory deep sleep stimulation in older adults at home: a randomized crossover trial. Commun. Med. 2, 1–16 (2022). · DOI
  62. Van Egroo, M., Koshmanova, E., Vandewalle, G. & Jacobs, H. I. L. Importance of the locus coeruleus-norepinephrine system in sleep-wake regulation: Implications for aging and Alzheimer’s disease. Sleep. Med. Rev. 62, 101592 (2022). · DOI
  63. Van Someren, E. J. W. Brain mechanisms of insomnia: new perspectives on causes and consequences. Physiol. Rev. 101, 995–1046 (2021). · DOI
  64. McCall, J. G. et al. CRH engagement of the locus coeruleus noradrenergic system mediates stress-induced anxiety. Neuron 87, 605–620 (2015). · DOI · Paper page
  65. Wood, C. S., Valentino, R. J. & Wood, S. K. Individual differences in the locus coeruleus-norepinephrine system: relevance to stress-induced cardiovascular vulnerability. Physiol. Behav. 172, 40–48 (2017). · DOI
  66. Ben Barak-Dror, O. et al. Touchless short-wave infrared imaging for dynamic rapid pupillometry and gaze estimation in closed eyes. Commun. Med. 4, 157 (2024). · DOI
  67. Schiffman, R. M., Christianson, M. D., Jacobsen, G., Hirsch, J. D. & Reis, B. L. Reliability and validity of the Ocular Surface Disease Index. Arch. Ophthalmol. 118, 615–621 (2000). · DOI
  68. Delorme, A. & Makeig, S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods 134, 9–21 (2004). · DOI · Paper page
  69. Vallat, R., Walker MP, P. & Walker, M. An open-source, high-performance tool for automated sleep staging. Elife 10, 1–24 (2021). · DOI
  70. Hill, S. L. et al. Visbrain: a multi-purpose GPU-accelerated open-source suite for multimodal brain data visualization. Front. Neuroinformat. | www.frontiersin.org. 1:14. https://doi.org/10.3389/fninf.2019.00014 (2019). · DOI
  71. Lustenberger, C., Wehrle, F., Tüshaus, L., Achermann, P. & Huber, R. The multidimensional aspects of sleep spindles and their relationship to word-pair memory consolidation. Sleep 38, 1093–1103 (2015). · DOI
  72. Prerau, M. J., Brown, R. E., Bianchi, M. T., Ellenbogen, J. M. & Purdon, P. L. Sleep neurophysiological dynamics through the lens of multitaper spectral analysis. Physiology 32, 60–92 (2017). · DOI
  73. Donoghue, T. et al. Parameterizing neural power spectra into periodic and aperiodic components. Nat. Neurosci. 23, 1655–1665 (2020). · DOI
  74. Lacourse, K., Yetton B., Mednick S. C. & Warby S. Massive online data annotation, crowdsourcing to generate high quality sleep spindle annotations from EEG data. Sci. Data 7, 190 (2020). · DOI
  75. Lacourse, K., Delfrate J., Beaudry J., Peppard P. & Warby S. C. A sleep spindle detection algorithm that emulates human expert spindle scoring. Published online. https://doi.org/10.1016/j.jneumeth.2018.08.014 (2018). · DOI
  76. Fernández-Varela I., Alvarez-Estevez D., Hernández-Pereira E. & Moret-Bonillo V. A simple and robust method for the automatic scoring of EEG arousals in polysomnographic recordings. https://doi.org/10.1016/j.compbiomed.2017.05.011 (2017). · DOI
  77. Alvarez-Estevez, D. & Fernández-Varela, I. Large-scale validation of an automatic EEG arousal detection algorithm using different heterogeneous databases. Published online. https://doi.org/10.1016/j.sleep.2019.01.025 (2019). · DOI
  78. Kret, M. E. & Sjak-Shie, E. E. Preprocessing pupil size data: guidelines and code. Behav. Res Methods 51, 1336–1342 (2019). · DOI
  79. Behar, J. A. et al. PhysioZoo: a novel open access platform for heart rate variability analysis of mammalian electrocardiographic data. Front. Physiol. 9, 01390 (2018) · DOI
  80. Ferster, M. L. et al. Benchmarking real-time algorithms for in-phase auditory stimulation of low amplitude slow waves with wearable EEG devices during sleep. IEEE Trans. Biomed. Eng. 69, 2916–2925 (2022). · DOI
  81. Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using {lme4}. J. Stat. Softw. 67, 1–48 (2015). · DOI · Paper page
  82. Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. {lmerTest} Package: tests in linear mixed effects models. J. Stat. Softw. 82, 1–26 (2017). · DOI · Paper page
  83. Bakdash, J. Z. & Marusich, L. R. Package ‘rmcorr’. Front. Psychol. 8, 456 (2017). · DOI
  84. Wickham H. Ggplot2: Elegant Graphics for Data Analysis. (Springer-Verlag, New York, 2016). · DOI

Cited by

Sorted by citations

See all 41

Metadata

Authors
Carro-Domínguez, M., Huwiler, S., Oberlin, S., Oesch, T. L., Badii, G., Lüthi, A., Wenderoth, N., Meissner, S. N., & Lustenberger, C.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2025-02-28
Volume
16
Issue
1
ISSN
2041-1723
DOI
10.1038/s41467-025-57289-5
PMC
PMC11871316
Cited by
41
References
10
Language
en
Licence

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 ›

Are you an author, or do you see a problem with this page? Request a review