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  • Importantly we observed that there is variability of

    2018-10-29

    Importantly, we observed that there is variability of sleep concordance across dyads. This variability indicates that not all adolescents are necessarily tuned with their parents. That is, sleep and neural connectivity patterns developed in adolescents are not based solely on the sleep and neural connectivity patterns of their parents. Adolescence is a period of social attention shifting beyond family (Nelson et al., 2005) with decreased closeness to their parents (Tsai et al., 2013). Moreover, parental influence on their children’s sleep declines during adolescence, and adolescents tend to take more control over their own sleep schedule. Thus, understanding such variability will be important for future research. Given that concordance in sleep behavior and DMN connectivity is associated with more optimal sleep quality, interventions aimed at promoting better sleep should move beyond variables centered on the individual adolescent (e.g., reducing technology use) to a more family-focused approach. By identifying which adolescents are more in-tuned with their parents will be one direction for understanding which youth may benefit most from such a family-focused approach. Indeed, prior work has found that retinoid x receptor reporting more closeness tend to show greater similarity in their sleep patterns (e.g., Kalak et al., 2012). Whatever the possible source may be, the current variability indicates that dyadic concordance is a mutual process between parents and children that may vary depending on the context of the family (e.g., high closeness). Future research should unpack what other factors, such as quality of adolescent-parent interactions, are involved in the reconfiguration of neural and behavioral dynamics and how dyadic concordance can change across development by adopting a longitudinal design. In the current study, we focused on how the DMN is wired to other intrinsic networks. This is because previous studies have indicated that the DMN is significantly involved in wakefulness regulation (Basner et al., 2013; Horovitz et al., 2009; McKenna and Eyler, 2012; Picchioni et al., 2013) by changing its connectivity with other networks to initialize and terminate sleep (Larson-Prior et al., 2011; Laufs et al., 2003; Picchioni et al., 2013; Sämann et al., 2010). However, in the current study, we did not collect resting state while our participants were asleep. Therefore wiring patterns of the DMN we observed are more likely to be a reflection of intrinsic regulatory processes playing a role in internally and externally directed cognitive processes (Buckner et al., 2008; Fox et al., 2005) rather than capturing ongoing functional dynamics in active sleep regulation. Future studies should examine similarity in functional dynamic changes in the DMN as well as other intrinsic functional networks in parent-child dyads during their actual sleep. Also, given previous evidence highlighting the major role of DMN in sleep, we focused on DMN’s between network connectivity. Therefore, we cannot make claims about the specificity of the DMN’s connectivity profile in being related to our construct of interest. Thus, it would be informative to observe neural circuit similarity at the global level of the connectome to see how large-scale brain architecture is harmoniously involved in dyadic concordance and shared interpersonal processing (e.g., Lee et al., 2017). Finally, we focused on global measures of sleep quality using the Pittsburgh Sleep Quality Index (PSQI; Buysse et al., 1989). This is a widely used measure that captures clinical levels of poor sleep (i.e., those scoring above 16). While our focus was on global sleep quality, future research should examine multiple aspects of sleep, including insomnia, as well as use more objective measures of sleep with actigraphy. It is possible that different domains of sleep are associated with different neural network connectivity patterns. For example, the degree of anti-correlation in DMN connectivity with other networks (e.g., right frontoparietal network) is related to insomnia (e.g., De Havas et al., 2012). Therefore, future investigation focusing on subcomponents of sleep quality will increase our understanding of the neurobiological basis of sleep. Finally, given the novelty of our approach, and the small sample size, it is important for future research to replicate these effects in larger samples.