Sleepers track informative speech in a multitalker environment


Sleep is a vital need, forcing us to spend a large portion of our life unable to interact with the external world. Current models interpret such extreme vulnerability as the price to pay for optimal learning. Sleep would limit external interferences on memory consolidation1,2,3 and allow neural systems to reset through synaptic downscaling4. Yet, the sleeping brain continues generating neural responses to external events5,6, revealing the preservation of cognitive processes ranging from the recognition of familiar stimuli to the formation of new memory representations7,8,9,10,11,12,13,14,15. Why would sleepers continue processing external events and yet remain unresponsive? Here we hypothesized that sleepers enter a ‘standby mode’ in which they continue tracking relevant signals, finely balancing the need to stay inward for memory consolidation with the ability to rapidly awake when necessary. Using electroencephalography to reconstruct competing streams in a multitalker environment16, we demonstrate that the sleeping brain amplifies meaningful speech compared to irrelevant signals. However, the amplification of relevant stimuli was transient and vanished during deep sleep. The effect of sleep depth could be traced back to specific oscillations, with K-complexes promoting relevant information in light sleep, whereas slow waves actively suppress relevant signals in deep sleep. Thus, the selection of relevant stimuli continues to operate during sleep but is strongly modulated by specific brain rhythms.

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Fig. 1: Experimental procedure.
Fig. 2: Reconstruction score and decoding performance across wake and NREM sleep.
Fig. 3: Spatiotemporal integration of acoustic information.
Fig. 4: Effect of sleep spindles, K-complexes and slow waves on stimulus reconstruction.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.


  1. 1.

    Rasch, B. & Born, J. About sleep’s role in memory. Physiol. Rev. 93, 681–766 (2013).

    CAS  Article  Google Scholar 

  2. 2.

    Diekelmann, S. & Born, J. The memory function of sleep. Nat. Rev. Neurosci. 11, 114–126 (2010).

    CAS  Article  Google Scholar 

  3. 3.

    Peigneux, P., Laureys, S., Delbeuck, X. & Maquet, P. Sleeping brain, learning brain the role of sleep for memory systems. Neuroreport 12, A111–A124 (2001).

    CAS  Article  Google Scholar 

  4. 4.

    Tononi, G. & Cirelli, C. Sleep and the price of plasticity: from synaptic and cellular homeostasis to memory consolidation and integration. Neuron 81, 12–34 (2014).

    CAS  Article  Google Scholar 

  5. 5.

    Issa, E. B. & Wang, X. Sensory responses during sleep in primate primary and secondary auditory cortex. J. Neurosci. 28, 14467–14480 (2008).

    CAS  Article  Google Scholar 

  6. 6.

    Nir, Y., Vyazovskiy, V. V., Cirelli, C., Banks, M. I. & Tononi, G. Auditory responses and stimulus-specific adaptation in rat auditory cortex are preserved across NREM and REM sleep. Cereb. Cortex 25, 1362–1378 (2015).

    Article  Google Scholar 

  7. 7.

    Perrin, F., Garcı́a-Larrea, L., Mauguière, F. & Bastuji, H. A differential brain response to the subject’s own name persists during sleep. Clin. Neurophysiol. 110, 2153–2164 (1999).

    CAS  Article  Google Scholar 

  8. 8.

    Ibáñez, A., López, V. & Cornejo, C. ERPs and contextual semantic discrimination: degrees of congruence in wakefulness and sleep. Brain Lang. 98, 264–275 (2006).

    Article  Google Scholar 

  9. 9.

    Bastuji, H., Perrin, F. & Garcia-Larrea, L. Semantic analysis of auditory input during sleep: studies with event related potentials. Int. J. Psychophysiol. 46, 243–255 (2002).

    Article  Google Scholar 

  10. 10.

    Brualla, J., Romero, M. F., Serrano, M. & Valdizán, J. R. Auditory event-related potentials to semantic priming during sleep. Electroencephalogr. Clin. Neurophysiol. 108, 283–290 (1998).

    CAS  Article  Google Scholar 

  11. 11.

    Ruby, P., Caclin, A., Boulet, S., Delpuech, C. & Morlet, D. Odd sound processing in the sleeping brain. J. Cogn. Neurosci. 20, 296–311 (2007).

    Article  Google Scholar 

  12. 12.

    Strauss, M. et al. Disruption of hierarchical predictive coding during sleep. Proc. Natl Acad. Sci. USA 112, E1353–E1362 (2015).

    CAS  Article  Google Scholar 

  13. 13.

    Arzi, A. et al. Humans can learn new information during sleep. Nat. Neurosci. 15, 1460–1465 (2012).

    CAS  Article  Google Scholar 

  14. 14.

    de Lavilléon, G., Lacroix, M. M., Rondi-Reig, L. & Benchenane, K. Explicit memory creation during sleep demonstrates a causal role of place cells in navigation. Nat. Neurosci. 18, 493–495 (2015).

    Article  Google Scholar 

  15. 15.

    Andrillon, T., Pressnitzer, D., Léger, D. & Kouider, S. Formation and suppression of acoustic memories during human sleep. Nat. Commun. 8, 179 (2017).

    Article  Google Scholar 

  16. 16.

    O’Sullivan, J. A. et al. Attentional selection in a cocktail party environment can be decoded from single-trial EEG. Cereb. Cortex 25, 1697–1706 (2015).

    Article  Google Scholar 

  17. 17.

    Formby, D. Maternal recognition of infant’s cry. Dev. Med. Child Neurol. 9, 293–298 (1967).

    CAS  Article  Google Scholar 

  18. 18.

    Cherry, E. C. Some experiments on the recognition of speech, with one and with two ears. J. Acoust. Soc. Am. 25, 975–979 (1953).

    Article  Google Scholar 

  19. 19.

    Mesgarani, N., David, S. V., Fritz, J. B. & Shamma, S. A. Influence of context and behavior on stimulus reconstruction from neural activity in primary auditory cortex. J. Neurophysiol. 102, 3329–3339 (2009).

    Article  Google Scholar 

  20. 20.

    Mesgarani, N. & Chang, E. F. Selective cortical representation of attended speaker in multi-talker speech perception. Nature 485, 233–236 (2012).

    CAS  Article  Google Scholar 

  21. 21.

    Bastien, C. H., Ladouceur, C. & Campbell, K. B. EEG characteristics prior to and following the evoked K-complex. Can. J. Exp. Psychol. 54, 255–265 (2000).

    CAS  Article  Google Scholar 

  22. 22.

    Halász, P. K-complex, a reactive EEG graphoelement of NREM sleep: an old chap in a new garment. Sleep Med. Rev. 9, 391–412 (2005).

    Article  Google Scholar 

  23. 23.

    Destexhe, A., Hughes, S. W., Rudolph, M. & Crunelli, V. Are corticothalamic ‘up’ states fragments of wakefulness? Trends Neurosci. 30, 334–342 (2007).

    CAS  Article  Google Scholar 

  24. 24.

    Steriade, M. Neuronal Substrates of Sleep and Epilepsy (Cambridge Univ. Press, Cambridge, 2003).

  25. 25.

    McCormick, D. A. & Bal, T. Sensory gating mechanisms of the thalamus. Curr. Opin. Neurobiol. 4, 550–556 (1994).

    CAS  Article  Google Scholar 

  26. 26.

    Sela, Y., Vyazovskiy, V. V., Cirelli, C., Tononi, G. & Nir, Y. Responses in rat core auditory cortex are preserved during sleep spindle oscillations. Sleep 39, 1069–1082 (2016).

    Article  Google Scholar 

  27. 27.

    Andrillon, T., Poulsen, A. T., Hansen, L. K., Léger, D. & Kouider, S. Neural markers of responsiveness to the environment in human sleep. J. Neurosci. 36, 6583–6596 (2016).

    Article  Google Scholar 

  28. 28.

    Kouider, S., Andrillon, T., Barbosa, L. S., Goupil, L. & Bekinschtein, T. A. Inducing task-relevant responses to speech in the sleeping brain. Curr. Biol. 24, 2208–2214 (2014).

    CAS  Article  Google Scholar 

  29. 29.

    Hennevin, E., Huetz, C. & Edeline, J.-M. Neural representations during sleep: from sensory processing to memory traces. Neurobiol. Learn. Mem. 87, 416–440 (2007).

    Article  Google Scholar 

  30. 30.

    Tononi, G. & Massimini, M. Why does consciousness fade in early sleep? Ann. N. Y. Acad. Sci. 1129, 330–334 (2008).

    Article  Google Scholar 

  31. 31.

    De Boer, E. et al. Auditory System. Part 3: Clinical and Special Topics (Springer, Berlin–Heidelberg, 1976).

  32. 32.

    Iber, C. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications (American Academy of Sleep Medicine, 2007).

  33. 33.

    Massimini, M., Ferrarelli, F., Sarasso, S. & Tononi, G. Cortical mechanisms of loss of consciousness: insight from TMS/EEG studies. Arch. Ital. Biol. 150, 44–55 (2012).

    CAS  PubMed  Google Scholar 

  34. 34.

    Siclari, F. et al. Two distinct synchronization processes in the transition to sleep: a high-density electroencephalographic study. Sleep 37, 1621–1637 (2014).

    Article  Google Scholar 

  35. 35.

    Sara, S. J. The locus coeruleus and noradrenergic modulation of cognition. Nat. Rev. Neurosci. 10, 211–223 (2009).

    CAS  Article  Google Scholar 

  36. 36.

    Eschenko, O., Magri, C., Panzeri, S. & Sara, S. J. Noradrenergic neurons of the locus coeruleus are phase locked to cortical up-down states during sleep. Cereb. Cortex 22, 426–435 (2012).

    Article  Google Scholar 

  37. 37.

    Pigorini, A. et al. Bistability breaks-off deterministic responses to intracortical stimulation during non-REM sleep. Neuroimage 112, 105–113 (2015).

    Article  Google Scholar 

  38. 38.

    Massimini, M. et al. Breakdown of cortical effective connectivity during sleep. Science 309, 2228–2232 (2005).

    CAS  Article  Google Scholar 

  39. 39.

    Ding, N. & Simon, J. Z. Emergence of neural encoding of auditory objects while listening to competing speakers. Proc. Natl Acad. Sci. USA 109, 11854–11859 (2012).

    CAS  Article  Google Scholar 

  40. 40.

    Beltramo, R. et al. Layer-specific excitatory circuits differentially control recurrent network dynamics in the neocortex. Nat. Neurosci. 16, 227–234 (2013).

    CAS  Article  Google Scholar 

  41. 41.

    Maquet, P. Functional neuroimaging of normal human sleep by positron emission tomography. J. Sleep Res. 9, 207–231 (2000).

    CAS  Article  Google Scholar 

  42. 42.

    Ohayon, M. M., Carskadon, M. A., Guilleminault, C. & Vitiello, M. V. Meta-analysis of quantitative sleep parameters from childhood to old age in healthy individuals: developing normative sleep values across the human lifespan. Sleep 27, 1255–1273 (2004).

    Article  Google Scholar 

  43. 43.

    Borbély, A. A. & Achermann, P. Sleep homeostasis and models of sleep regulation. J. Biol. Rhythms 14, 559–570 (1999).

    Article  Google Scholar 

  44. 44.

    Siclari, F., LaRocque, J. J., Postle, B. R. & Tononi, G. Assessing sleep consciousness within subjects using a serial awakening paradigm. Front. Psychol. 4, 542 (2013).

    Article  Google Scholar 

  45. 45.

    Ferrand, L. et al. The French Lexicon Project: lexical decision data for 38,840 French words and 38,840 pseudowords. Behav. Res. Methods 42, 488–496 (2010).

    Article  Google Scholar 

  46. 46.

    Obin, N. MeLos: Analysis and Modelling of Speech Prosody and Speaking Style (Université Pierre et Marie Curie—Paris VI, 2011).

  47. 47.

    Dorran, D., Lawlor, R. & Coyle, E. High quality time-scale modification of speech using a peak alignment overlap-add algorithm (PAOLA). In 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP ’03) I-700–I-703 (IEEE, 2003).

  48. 48.

    Haufe, S. et al. On the interpretation of weight vectors of linear models in multivariate neuroimaging. Neuroimage 87, 96–110 (2014).

    Article  Google Scholar 

  49. 49.

    Andrillon, T. et al. Sleep spindles in humans: insights from intracranial EEG and unit recordings. J. Neurosci. 31, 17821–17834 (2011).

    CAS  Article  Google Scholar 

  50. 50.

    Nir, Y. et al. Regional slow waves and spindles in human sleep. Neuron 70, 153–169 (2011).

    CAS  Article  Google Scholar 

  51. 51.

    Riedner, B. A. et al. Sleep homeostasis and cortical synchronization: III. A high-density EEG study of sleep slow waves in humans. Sleep 30, 1643–1657 (2007).

    Article  Google Scholar 

  52. 52.

    Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).

    Article  Google Scholar 

  53. 53.

    Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest package: tests in linear mixed effects models. J. Stat. Softw. 82, 1–26 (2017).

    Article  Google Scholar 

  54. 54.

    Maris, E. & Oostenveld, R. Nonparametric statistical testing of EEG- and MEG-data. J. Neurosci. Methods 164, 177–190 (2007).

    Article  Google Scholar 

  55. 55.

    Kass, R. E. & Raftery, A. E. Bayes factors. J. Am. Stat. Assoc. 90, 773–795 (1995).

    Article  Google Scholar 

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This research was supported by ANR grants (ANR-10-LABX-0087 and ANR-10-IDEX-0001-02), by the European Research Council (ERC project METAWARE to S.K.), by the CIFAR (to S.K.), by the SFRMS and IBRO (to T.A.) and by the DGA (to M.K.). We thank S. Shamma and D. Pressnitzer for discussion, C. Girard for her assistance throughout the experiment, and N. Obin and A. Roebel for their help in constructing the stimuli. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information




S.K. and T.A. designed the study. G.L., T.A. and M.K. collected the data. T.A., G.L. and S.K. analysed and interpreted the data. S.K., T.A., G.L. and M.K. wrote the paper.

Corresponding author

Correspondence to Sid Kouider.

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Legendre, G., Andrillon, T., Koroma, M. et al. Sleepers track informative speech in a multitalker environment. Nat Hum Behav 3, 274–283 (2019).

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