Examining the optimal timing for closed-loop auditory stimulation of slow-wave sleep in young and older adults
Miguel Navarrete, Jules Schneider, Hong-Viet V Ngo, Mario Valderrama, Alexander J Casson, Penelope A Lewis, Miguel Navarrete, Jules Schneider, Hong-Viet V Ngo, Mario Valderrama, Alexander J Casson, Penelope A Lewis
Abstract
Study objectives: Closed-loop auditory stimulation (CLAS) is a method for enhancing slow oscillations (SOs) through the presentation of auditory clicks during sleep. CLAS boosts SOs amplitude and sleep spindle power, but the optimal timing for click delivery remains unclear. Here, we determine the optimal time to present auditory clicks to maximize the enhancement of SO amplitude and spindle likelihood.
Methods: We examined the main factors predicting SO amplitude and sleep spindles in a dataset of 21 young and 17 older subjects. The participants received CLAS during slow-wave-sleep in two experimental conditions: sham and auditory stimulation. Post-stimulus SOs and spindles were evaluated according to the click phase on the SOs and compared between and within conditions.
Results: We revealed that auditory clicks applied anywhere on the positive portion of the SO increased SO amplitudes and spindle likelihood, although the interval of opportunity was shorter in the older group. For both groups, analyses showed that the optimal timing for click delivery is close to the SO peak phase. Click phase on the SO wave was the main factor determining the impact of auditory stimulation on spindle likelihood for young subjects, whereas for older participants, the temporal lag since the last spindle was a better predictor of spindle likelihood.
Conclusions: Our data suggest that CLAS can more effectively boost SOs during specific phase windows, and these differ between young and older participants. It is possible that this is due to the fluctuation of sensory inputs modulated by the thalamocortical networks during the SO.
Keywords: age; closed-loop auditory stimulation; memory; sleep; slow oscillation.
© Sleep Research Society 2019. Published by Oxford University Press on behalf of the Sleep Research Society.
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References
- Iber C, et al. .. The AASM Manual for the Scoring of Sleep and Associated Events: Rules Terminology and Technical Specifications, 1st ed. Westchester, IL: American Academy of Sleep Medicine; 2007:59.
- Rasch B, et al. . About sleep’s role in memory. Physiol Rev. 2013;93(2):681–766.
- Besedovsky L, et al. . Auditory closed-loop stimulation of EEG slow oscillations strengthens sleep and signs of its immune-supportive function. Nat Commun. 2017;8(1):1984.
- Xie L, et al. .. Sleep drives metabolite clearance from the adult brain. Science. 2013;342(6156):373–377.
- Ohayon MM, et al. . Meta-Analysis of quantitative sleep parameters from childhood to old age in healthy individuals: developing normative sleep values across the human lifespan. Sleep. 2004;27(7):1255–1273.
- Mander BA, et al. . Sleep and human aging. Neuron. 2017;94(1):19–36.
- Scullin MK, et al. . Sleep, cognition, and normal aging: integrating a half century of multidisciplinary research. Perspect Psychol Sci. 2015;10(1):97–137.
- Scullin MK. Sleep, memory, and aging: the link between slow-wave sleep and episodic memory changes from younger to older adults. Psychol Aging. 2013;28(1):105–114.
- Mander BA, et al. . White matter structure in older adults moderates the benefit of sleep spindles on motor memory consolidation. J Neurosci. 2017;37(48):11675–11687.
- Massimini M, et al. . Triggering sleep slow waves by transcranial magnetic stimulation. Proc Natl Acad Sci U S A. 2007;104(20):8496–8501.
- Marshall L, et al. . Transcranial direct current stimulation during sleep improves declarative memory. J Neurosci. 2004;24(44):9985–9992.
- Ketz N, et al. . Closed-Loop slow-wave tacs improves sleep-dependent long-term memory generalization by modulating endogenous oscillations. J Neurosci. 2018;38(33):7314–7326.
- Ngo HV, et al. . Auditory closed-loop stimulation of the sleep slow oscillation enhances memory. Neuron. 2013;78(3):545–553.
- Ngo HV, et al. . Driving sleep slow oscillations by auditory closed-loop stimulation-a self-limiting process. J Neurosci. 2015;35(17):6630–6638.
- Papalambros NA, et al. . Acoustic enhancement of sleep slow oscillations and concomitant memory improvement in older adults. Front Hum Neurosci. 2017;11:109.
- Ong JL, et al. . Auditory stimulation of sleep slow oscillations modulates subsequent memory encoding through altered hippocampal function. Sleep. 2019;42(2). doi:10.1093/sleep/zsy240.
- Grimaldi D, et al. . Strengthening sleep–autonomic interaction via acoustic enhancement of slow oscillations. Sleep. 2019;42(5). doi:10.1093/sleep/zsz036
- Leminen M, et al. . Enhanced memory consolidation via automatic sound stimulation during non-rem sleep. Sleep. 2017;40(3). doi:10.1093/sleep/zsx003
- Santostasi G, et al. . Phase-locked loop for precisely timed acoustic stimulation during sleep. J Neurosci Methods. 2016;259:101–114.
- Schabus M, et al. . The fate of incoming stimuli during nrem sleep is determined by spindles and the phase of the slow oscillation. Front Neurol. 2012;3:40.
- Batterink LJ, et al. . Phase of spontaneous slow oscillations during sleep influences memory-related processing of auditory cues. J Neurosci. 2016;36(4):1401–1409.
- Riedner BA, et al. . Sleep homeostasis and cortical synchronization: III. A high-density EEG study of sleep slow waves in humans. Sleep. 2007;30(12):1643–1657.
- Clemens Z, et al. . Temporal coupling of parahippocampal ripples, sleep spindles and slow oscillations in humans. Brain. 2007;130(Pt 11):2868–2878.
- Warby SC, et al. . Sleep-spindle detection: crowdsourcing and evaluating performance of experts, non-experts and automated methods. Nat Methods. 2014;11(4):385–392.
- Purcell SM, et al. . Characterizing sleep spindles in 11,630 individuals from the National Sleep Research Resource. Nat Commun. 2017;8(May):15930.
- Ngo HV, et al. . Insights on auditory closed-loop stimulation targeting sleep spindles in slow oscillation up-states. J Neurosci Methods. 2019;316:117–124.
- Boashash B. Estimating and interpreting the instantaneous frequency of a signal. I. Fundamentals. Proc IEEE. 1992;80(4):540–568.
- Chavez M, et al. . Towards a proper estimation of phase synchronization from time series. J Neurosci Methods. 2006;154(1-2):149–160.
- Berens P. CircStat: a MATLAB toolbox for circular statistics. J Stat Softw. 2009;31(10):1–21.
- Benjamini Y, et al. . The control of the false discovery rate in multiple testing under dependency. Ann Stat. 2001;29(4):1165–1188.
- Antony JW, et al. . Sleep spindle refractoriness segregates periods of memory reactivation. Curr Biol. 2018;28(11):1736–1743.e4.
- Mardia KV. Linear-Circular correlation coefficients and rhythmometry. Biometrika. 1976;63(2):403.
- Mardia KV, et al. . A model for cylindrical variables with applications. J R Stat Soc Ser B. 1978;40(2):229–233.
- Jammalamadaka SR, Sengupta A.. Series on Multivariate Analysis: Volume 5 Topics in Circular Statistics, vol 5 Singapore. World Scientific Publishing Co Pte Ltd; 2001.
- Al-Daffaie K, et al. . Logistic regression for circular data. In: AIP Conference Proceedings: The 3rd ISM International Statistical Conference 2016 (ISM III). Vol 1842 2017:030022.
- Lecci S, et al. . Coordinated infraslow neural and cardiac oscillations mark fragility and offline periods in mammalian sleep. Sci Adv. 2017;3(2):e1602026.
- Colrain IM, et al. . The N550 component of the evoked K-complex: a modality non-specific response? J Sleep Res. 1999;8(4):273–280.
- Riedner BA, et al. . Temporal dynamics of cortical sources underlying spontaneous and peripherally evoked slow waves. Prog Brain Res. 2011;193:201–218.
- Massimini M. EEG slow (~1 hz) waves are associated with nonstationarity of thalamo-cortical sensory processing in the sleeping human. J Neurophysiol. 2002;89(3):1205–1213.
- Rector DM, et al. . Mechanisms underlying state dependent surface-evoked response patterns. Neuroscience. 2009;159(1):115–126.
- Haslinger R, et al. . Analysis of LFP phase predicts sensory response of barrel cortex. J Neurophysiol. 2006;96(3):1658–1663.
- Bellesi M, et al. . Enhancement of sleep slow waves: underlying mechanisms and practical consequences. Front Syst Neurosci. 2014;8:208.
- Rosanova M, et al. . Neuronal mechanisms mediating the variability of somatosensory evoked potentials during sleep oscillations in cats. J Physiol. 2005;562(Pt 2):569–582.
- Nir Y, et al. . Regional slow waves and spindles in human sleep. Neuron. 2011;70(1):153–169.
- Helfrich RF, et al. . Old brains come uncoupled in sleep: slow wave-spindle synchrony, brain atrophy, and forgetting. Neuron. 2018;97(1):221–230.e4.
- Saletin JM, et al. . Structural brain correlates of human sleep oscillations. Neuroimage. 2013;83:658–668.
- Clawson BC, et al. . Form and function of sleep spindles across the lifespan. Neural Plast. 2016;2016:6936381.
- Landolt HP, et al. . Effect of age on the sleep EEG: slow-wave activity and spindle frequency activity in young and middle-aged men. Brain Res. 1996;738(2):205–212.
- Mölle M, et al. . Fast and slow spindles during the sleep slow oscillation: disparate coalescence and engagement in memory processing. Sleep. 2011;34(10):1411–1421.
- Mak-McCully RA, et al. . Coordination of cortical and thalamic activity during non-REM sleep in humans. Nat Commun. 2017;8:15499.
- Latchoumane CFV, et al. . Thalamic spindles promote memory formation during sleep through triple phase-locking of cortical, thalamic, and hippocampal rhythms. Neuron. 2017;95(2):424–435. e6.
- Lustenberger C, et al. . High-density EEG characterization of brain responses to auditory rhythmic stimuli during wakefulness and NREM sleep. Neuroimage. 2018;169:57–68.
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