Sleep spindle maturity promotes slow oscillation-spindle coupling across child and adolescent development

  1. Ann-Kathrin Joechner
  2. Michael A Hahn
  3. Georg Gruber
  4. Kerstin Hoedlmoser
  5. Markus Werkle-Bergner

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    eLife assessment

    This is an important analysis of two sleep datasets in children and adolescents that contributes to our understanding of sleep spindle and slow oscillation dynamics during development and is expected to be of interest to interdisciplinary fields including development and sleep. The analyses are solid and adequately complex to capture the changes in sleep spindle to slow oscillation coupling between the age groups. However, the paper would be strengthened by performing the same analyses in an adult sample to sufficiently characterize the maturation of sleep spindles and their coupling to slow oscillations.

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Abstract

The synchronization of canonical fast sleep spindle activity (12.5–16 Hz, adult-like) precisely during the slow oscillation (0.5–1 Hz) up peak is considered an essential feature of adult non-rapid eye movement sleep. However, there is little knowledge on how this well-known coalescence between slow oscillations and sleep spindles develops. Leveraging individualized detection of single events, we first provide a detailed cross-sectional characterization of age-specific patterns of slow and fast sleep spindles, slow oscillations, and their coupling in children and adolescents aged 5–6, 8–11, and 14–18 years, and an adult sample of 20- to 26-year-olds. Critically, based on this, we then investigated how spindle and slow oscillation maturity substantiate age-related differences in their precise orchestration. While the predominant type of fast spindles was development-specific in that it was still nested in a frequency range below the canonical fast spindle range for the majority of children, the well-known slow oscillation-spindle coupling pattern was evident for sleep spindles in the adult-like canonical fast spindle range in all four age groups—but notably less precise in children. To corroborate these findings, we linked personalized measures of fast spindle maturity, which indicate the similarity between the prevailing development-specific and adult-like canonical fast spindles, and slow oscillation maturity, which reflects the extent to which slow oscillations show frontal dominance, with individual slow oscillation-spindle coupling patterns. Importantly, we found that fast spindle maturity was uniquely associated with enhanced slow oscillation-spindle coupling strength and temporal precision across the four age groups. Taken together, our results suggest that the increasing ability to generate adult-like canonical fast sleep spindles actuates precise slow oscillation-spindle coupling patterns from childhood through adolescence and into young adulthood.

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  1. Version published to 10.7554/elife.83565 on eLife
  2. eLife

    eLife assessment

    This is an important analysis of two sleep datasets in children and adolescents that contributes to our understanding of sleep spindle and slow oscillation dynamics during development and is expected to be of interest to interdisciplinary fields including development and sleep. The analyses are solid and adequately complex to capture the changes in sleep spindle to slow oscillation coupling between the age groups. However, the paper would be strengthened by performing the same analyses in an adult sample to sufficiently characterize the maturation of sleep spindles and their coupling to slow oscillations.

  3. eLife

    Reviewer #1 (Public Review):

    During NonREM sleep, two major oscillations, the slow oscillation (SO) and the sleep spindle, have been shown to interact, putatively to support memory consolidation. These oscillations and their interrelation have been shown to change during development. The authors reanalyse two datasets in children and adolescents. One is longitudinal, assessed at 8-11 years and 14-18 years, the other is cross-sectional, assessed at 5-6 years. The manuscript reports several interesting findings. They identify three types of spindles, canonical slow and fast spindles as well as "age adjusted" fast spindles. They show that fast spindles are modulated by the slow oscillation more in the older children and relate this improved modulation to a sleep-spindle maturation index. The authors use many highly complex data analysis tools and apply them to different transformations of the data, which they explain in great detail. The manuscript is written clearly although it is at times very technical. The findings could be highly interesting to the field of sleep research, as they nicely examine the developmental trajectory of spindles and their coupling to the SO. Although the manuscript makes use of two adequate samples of children and adolescents, they do not compare their findings to adults. In addition, the maturation index is not well justified and the authors could do more to show that the "age adjusted" fast spindles actually develop into fast spindles. The analysis also does not take sex into account, which could be affecting findings in puberty. In general, there are some analyses that could be added to make the findings clearer. For example, it would be great to show averages of the detected spindles to show how they may or may not differ. More descriptive data in form of figures would also help readers understand the complex analyses that are reported (i.e., spectrogram and SO phase locked activity in the spindle bands). Finally, children have been reported to have superior declarative memory consolidation, which itself has been closely linked to spindle-SO coupling. It would be great to have a more broad discussion, how the current findings are related to other developmental changes in the field of sleep (and memory).

  4. eLife

    Reviewer #2 (Public Review):

    The article by Joechner et al is a reanalysis of a large cohort data-set on sleep oscillation development. By combining an analysis with fixed frequencies derived from adults with adaptive frequency ranges, they highlight that initially spindle oscillations are slower and it takes until mid adolescence for spindles to be more adult like. Further, those spindles that already have adult-like frequency ranges also show the other properties known from adults. These results are intriguing and the analysis is well-done and thorough. I only have minor comments on how the article could be improved.

    Some additional analysis that would complement the current findings: in Fig 1 it would be good to include the adult-like slow frontal spindles for comparison (similar as the inclusion for the centro parietal ones). Further, providing distributions could let the readers have some valuable insight into the events. Could the authors combine all events and show 3D scatter plots with frequency X amplitude X duration of each spindle event? And then either color code the events from different age groups or have them in separate plots. Additionally, the frequency cut-off for adult-events could be added to the plot. This would likely show nicely how the events shift in their properties over age and thus slowly reach adult-like characteristics.

    On page 2. Line 17 the authors state that spindles align ripples. While this is the case, the interaction between these oscillations are more complex. Ripples will also occur before the spindle and the ripples before spindles have been shown to be causally related to memory consolidation. Please cite Maingret et al Nat Neurosci 2016. Further, the authors should also discuss other rodent work for example Garcia et al Frontiers 2022, which also investigates the development of spindles.

  5. eLife

    Reviewer #3 (Public Review):

    Joechner and their co-authors performed an extensive analysis of two existing datasets from sleeping children aged between 5 to 18 years. By identifying discrete events of slow oscillations (SOs) and (fast) sleep spindles they examined not only the developmental changes of these distinct sleep grapho-elements. They also took a closer look at their interplay, e.g., to what extend sleep spindles are co-occurring with slow oscillation up-states, as this coupling is thought to underlie sleep-dependent memory consolidation.

    The authors found that both sleep spindles and slow oscillation undergo a change across the young age, e.g., while sleep spindles increased in frequency approaching the typical 12-16 Hz range found in adults, slow oscillation showed a shift in occurrence patterns from posterior to anterior sites. Likewise, the coupling of fast spindles within slow oscillation up-states manifested with age, which is almost non-existing in 5- to 6-year-old children. However, and most intriguingly, a coupling analysis based on the adult-like 12-16 Hz range revealed an already existing SO-spindle phase-relation across all age ranges. Altogether, this data nicely demonstrates the trajectory of sleep spindles and SOs in children and highlights the almost inherent coupling between SOs and "adult" sleep spindles. In my view, these results not only provide a good overview of a healthy development but also interesting food for thought regarding the function of SO-spindle coupling in healthy or clinical development.

    Overall, this work is well-written, and the performed analyses are well conceptualized. Hence, there are one general and a few minor aspects that could be addressed to hopefully strengthen this manuscript a bit further.

    The biggest aspect that was striking is the shear amount of data reported, e.g., a supplement with 28 tables is too extensive. The authors should consider reducing a few aspects.
    For example, the authors employ a linear mixed effects model and report coefficient etc. in the supplement. However, in the main text, the authors mainly report ANOVA-based results. Obviously, a LMM and an ANOVA are equivalent, however, focusing on one approach could streamline everything.
    Another example is the assessment of spindle frequency via the discrete events: First spindle peak frequency is derived via power spectra. Using the then individually identified peaks, discrete events are detected. Shouldn't it be obvious that these events show the same behavior with regard to their frequency?
    As a final example, the authors first report changes in fast spindle properties across age and, e.g., find an increase in frequency towards 12-16 Hz adult range. They then repeat the whole analysis in the 12-16 Hz range and examine the "distance" to the individualized results. It should again be obvious that this approach comes to the same conclusion, a smaller distance in older children. Even more obvious is the conclusion "Hence, it appears as if fast centro-parietal SPs become more dominant and adult-like in their frequency and amplitude characteristics in older children" because it describes a normal development of a healthy child. Altogether, the authors could streamline a few aspects by removing hidden redundancies and focus on the - in my view - central aspect of an inherent 12-16 Hz coupling across all ages.

  6. Version published to 10.1101/2022.09.05.506664v1 on bioRxiv