The Effect of Cognitive Activity on Sleep Maintenance in a Subsequent Daytime Nap

The influence of cognitive activity on subsequent daytime nap: A deep neural network model based on sleep spindles

OBJECTIVES

Understanding the influence of cognitive activity on subsequent sleep has both theoretical and applied implications. This study aims to investigate the effect of pre-sleep cognitive activity, in the context of avoiding emotional interference, on macro-sleep and sleep spindles.

METHODS

In a within-subjects design, participants' sleep electroencephalography was collected in both the with and without pre-sleep cognitive activity conditions. Subsequent macro-sleep (i.e., sleep stage distribution and sleep parameters) and spindle characteristics (i.e., density, amplitude, duration, and frequency) were analyzed. In addition, a novel machine learning framework (i.e., deep neural network, DNN) was used to discriminate between cognitive activity and control conditions.

RESULTS

There were no significant differences in macro-sleep and sleep spindles between the cognitive activity and control conditions. Spindles-based DNN models achieved over 96% accuracy in differentiating between the two conditions, with fast spindles performing better than full-range and slow spindles.

CONCLUSIONS

These results suggest a weak but positive effect of pre-sleep cognitive activity on subsequent sleep. It sheds light on a possible low-cost and easily accessible sleep intervention strategy for clinical and educational purposes.

Habitual Videogame Playing Does Not Compromise Subjective Sleep Quality and Is Associated with Improved Daytime Functioning

Research on the effects of videogames (VGs) on health has produced mixed results. Here, we assess the relationships of VG playing with sleep; chronotype; sleepiness; and levels of depression, anxiety, and stress; and how they are modulated by the level of exposure to VGs. Four hundred-and two adult participants (age = 26.2 ± 7.84; 227 F) completed an online survey including questions on VG use and a set of standardized questionnaires. The sample was divided into three groups: habitual gamers (HGs, 42.2%), nonhabitual gamers (NHGs, 36.5%), and non-gamers (NGs, 21.3%). No between-group differences emerged in sleepiness (Epworth Sleepiness Scale) or Pittsburgh Sleep Quality Index measures except the sleep disturbances subscore, which was higher in NHGs. HGs showed delayed bed- and risetimes and higher eveningness (reduced Morningness-Eveningness Questionnaire). HGs and NHGs showed higher depression subscores (Depression Anxiety Stress Scale) but remained in the subclinical range. Moreover, hours/week of VG playing predicted delayed sleep timing, lower daytime dysfunction, and lower sleepiness. Our data suggest that VG playing does not necessarily compromise sleep quality and may even benefit daytime functioning, underlining the need to reconsider the relationships between VG use and health by taking into account possible modulating factors such as habitual VG exposure.

Sleep Continuity, Stability and Cyclic Organization Are Impaired in Insomniacs: A Case-Control Study

The possibility of distinguishing insomniacs from good sleepers based on polysomnography (PSG) remains an open question. While these groups show modest differences in traditional PSG parameters, some studies suggest that finer measures may be more useful. Here we assess differences between good sleepers (GS), poor sleepers (PS) and insomniacs (IN) in classical PSG measures as well as in sleep continuity, stability and cyclic organization. PSG-monitored sleep (two nights) of 17 IN (diagnosed through a standard clinical interview; Pittsburgh Sleep Quality Index (PSQI) ≥ 5, Insomnia Severity Index (ISI) > 14) was compared to that of 33 GS (PSQI < 5) and 20 PS (PSQI ≥ 5, ISI ≤ 14). Compared to GS, IN were impaired in sleep macrostructure (sleep latency, sleep efficiency, WASO%) and in continuity, stability and organization, whereas PS only showed disrupted continuity and stability. Spindle parameters were comparable between IN and GS, but the former displayed enhanced power in fast frequency bands. Our findings support the hypothesis of a continuum between individuals with self-reported poor sleep and insomniacs. Further, they add to extant data on impaired sleep continuity, stability and organization in poor sleepers and elderly individuals, underlining the utility of including these measures in standard sleep assessments.

The effects of napping on night‐time sleep in healthy young adults

The discrepancies in the effects of napping on sleep quality may be due to differences in methodologies, napping behaviours, and daytime activity levels across studies. We determined whether napping behaviours and daytime activity levels are associated with night-time sleep fragmentation and sleep quality in young adults. A total of 62 healthy adults (mean [SD] age 23.5 [4.2] years) completed screening questionnaires for sleep habits, physical activity, medical and psychological history. Actigraphy was used to record sleep including naps. The fragmentation algorithm (K_RA ) was applied to the actigraphic data to measure night-time sleep fragmentation. We classified participants' nap frequency as "non-nappers" (0 naps/8 days), "moderate nappers" (1-2 naps/8 days) or "frequent nappers" (≥3 naps/8 days) naps. Nap duration was defined as "short" (≤60 min) or "long" (>60 min). Naps' proximity to the night sleep episode was defined as "early" (≥7 h) and "late" (<7 h) naps. Outcome variables were night-time K_RA and actigraphic sleep variables. Frequent nappers had a significantly higher K_RA than moderate nappers (p < 0.01) and non-nappers (p < 0.02). Late naps were associated with poorer measures of night sleep quality versus early naps (all p ≤ 0.02). Nap duration and daytime activity were not associated with significant differences in the outcome variables (all p > 0.05). K_RA correlated with sleep duration, sleep efficiency, and awakenings (r = -0.32, -0.32, and 0.53, respectively; all p < 0.05). Frequent napping and late naps may be associated with increased sleep fragmentation and poorer sleep quality, reflected in longer sleep onsets and increased awakenings. These findings have implications for public health sleep hygiene recommendations.

Variation in Gut Microbiota Composition is Associated with Sleep Quality and Cognitive Performance in Older Adults with Insomnia

PURPOSE

Insomnia, a chronic condition affecting 50% of older adults, is often accompanied by cognitive decline. The mechanism underlying this comorbidity is not fully understood. A growing literature suggests the importance of gut microbiota for brain function. We tested associations between sleep quality and cognitive performance with gut microbiota in older adults with insomnia.

PATIENTS AND METHODS

Seventy-two older adults with insomnia (age 73.2 ± 5.73 years, 56 females) provided stool samples for gut microbial sequencing. Microbiota profile was determined using the DADA2 bioinformatics pipeline. Cognition was assessed with the Cambridge Neuropsychological Test Automated Battery. Objective sleep quality was monitored by a two-week actigraphic recording, and participants completed the Insomnia Severity Index (ISI). We used partial canonical correspondence analysis (pCCA) to examine the relative contribution of insomnia, based on actigraphic sleep efficiency (SE) and ISI, and of cognitive status, based on the Multitasking test of Median Reaction Latency (MTTLMD) and the Spatial Working Memory Between Errors (SWMBE), to variance in microbiota composition. We used Pearson correlations to correlate insomnia and cognitive status parameters with microbiota amplicon sequence variants, genera, and families.

RESULTS

The pCCA revealed that sleep quality and cognitive performance explained a variation of 7.5-7.9% in gut microbiota composition in older adults with insomnia. Correlation analysis demonstrated that Lachnoclostridium (genus) correlates positively with SE (r=0.42; P=0.05) and negatively with MTTLMD (r=-0.29; P=0.03), whereas Blautia (genus) correlates negatively with MTTLMD (r=-0.31; P=0.01).

CONCLUSION

Findings demonstrate the associations of sleep quality and cognitive performance with variance in gut microbiota composition and with specific genus abundance in older adults with insomnia. Further studies should validate the findings, determine causal relationships, and evaluate potential interventions for the comorbidity of insomnia and cognitive impairment in older adults with insomnia.

Learning Monologues at Bedtime Improves Sleep Quality in Actors and Non-Actors

Several studies show that pre-sleep learning determines changes in subsequent sleep, including improvements of sleep quality. Our aims were to confirm this finding using a more ecological task (learning a theatrical monologue) and to investigate whether the effect is modulated by expertise. Using a mixed design, we compared polysomnographic recordings of baseline sleep (BL, 9-h TIB) to those of post-training sleep (TR, with the same TIB but preceded by the training session), in one group of actors (N = 11) and one of non-actors (N = 11). In both groups, TR appears reorganized and re-compacted by the learning session, as shown, among others, by a significant decrease of WASO%, awakenings, arousals, and state transitions and by a trend towards an increased number of complete cycles and total cycle time. Concerning memory performance, the number of synonyms produced was significantly higher in the morning relative to immediate recall. No between-groups differences emerged either for sleep or memory variables. Our data confirm pre-sleep learning's beneficial effect on sleep quality in an ecological context. While expertise appears not to influence memory-related sleep mechanisms, results on morning recall support the recent view that sleep's role in memory processes consists in trace "transformation" for adaptive purposes, rather than rote consolidation.

Sleep and psychological characteristics in habitual self-awakeners and forced awakeners

Previous studies described the modifications of physiological and behavioural variables associated with self-awakening, while only few studies assessed subjective sleep quality and psychological characteristics in habitual self-awakeners. Here we investigated self-reported sleep habits and features, as well as psychological variables of habitual self-awakeners and forced-awakeners, with special regard to subjective sleep quality, personality characteristics, anxiety and depression symptoms. In our sample, the prevalence of habitual self-awakeners was 15.1%. Compared to forced-awakeners, habitual self-awakeners showed more regular sleep/wake schedules and were more frequently morning types. Moreover, habitual self-awakeners referred to be more satisfied about their sleep, to wake up more easily in the morning, to need less time to get out of bed and to feel more refreshed upon awakening than forced-awakeners. We also observed an association between the habit of self-awakening and the "ability" to set the awakening to an unusual time. Concerning psychological features, habitual self-awakeners showed higher scores in Conscientiousness and Openness and lower scores in Extraversion compared to forced-awakeners, whereas no differences between groups emerged for anxiety and depression levels. In conclusion, our findings point to an association between the habit of self-awakening and good subjective sleep quality. In this perspective, future research should objectively test in detail the effects of the self-awakening habit on sleep structure and organization, taking into account also microstructural sleep features.

The Effects of the COVID19-Related Lockdown Are Modulated by Age: An Italian Study in Toddlers and Pre-Schoolers

Although the issue has been repeatedly explored, data on the impact of the COVID-19 pandemic on children’s sleep quality are inconsistent. To clarify these discrepancies, here we investigate possible age-related differences. During the lockdown, 112 parents of toddlers (0–3 years, N = 61) and pre-schoolers (4–5 years, n = 51) completed an online survey including the Children’s Sleep Habits Questionnaire (CSHQ). Sleep-related items required an additional retrospective judgment, referring to the pre-pandemic period. During the lockdown, sleep schedules were delayed in both age groups whereas sleep quality (CSHQ total scores) improved in pre-schoolers but not in toddlers. Between-groups comparisons revealed that, prior to the lockdown, pre-schoolers showed worse sleep quality than toddlers, whereas this difference disappeared during home confinement. Also, pre-schoolers’ sleep timing was advanced before the lockdown and delayed during the lockdown relative to toddlers’. Our data highlight a significant modulation of age on the impact of the pandemic crisis on sleep, with pre-schoolers experiencing greater effects than toddlers. This profile suggests that factors affecting sleep features have different weights at different ages: sleep patterns would be mainly determined by developmental factors (i.e., biological drive) in younger children, whereas environmental factors (e.g., major lifestyle changes) would have a stronger effect on older ones.

Sleep continuity, stability and organization in good and bad sleepers

The relationship between objective and subjective sleep quality is still debated. Here, we investigate differences in objective sleep parameters in habitual subjective good sleepers and bad sleepers with the aim of evaluating sleep continuity, stability and organization as possible determinants of subjective sleep quality. In total, 38 subjects (good sleepers, N = 18; bad sleepers, N = 20) underwent two nights of sleep recording. Traditional sleep parameters displayed no between-groups differences. Conversely, bad sleepers showed lower sleep continuity (awakenings frequency), stability (e.g. arousals and state transitions frequency) and organization (e.g. number of sleep cycles and time spent in cycles). Our findings point to the involvement of these measures in determining habitual sleep quality perception and suggest the possibility to include them in standard sleep assessments.

The effect of complex cognitive training on subsequent night sleep

Using a nap design, we have recently shown that training at a complex cognitive task at bedtime improves objective sleep quality by reducing sleep fragmentation. In order to extend our findings to nighttime sleep, here we assess the impact of a multi-componential cognitive task at bedtime on the subsequent sleep episode of subjects reporting habitual bad sleep, allegedly characterized by high sleep fragmentation. In a within-subjects design, 20 subjective bad sleepers underwent polysomnographic recording in three conditions: (a) baseline sleep (BL); (b) post-training sleep (TR), preceded by a complex ecological task, i.e. a modified version of the word game Ruzzle; (c) post-active control sleep (AC), preceded by a control task. Sleep in TR was more organized (higher number of cycles and longer time spent in cycles) and showed lower microarousal frequency than in AC and BL. As for sleep continuity (total and brief awakening frequency) and other stability measures (state transition and functional uncertainty period frequency, time in functional uncertainty), both TR and AC showed significant improvements compared with BL. Arousal frequency was also reduced in TR relative to BL. Our results show a clear impact of cognitive training on subsequent night sleep, basically consisting of an increase in sleep continuity, stability and organization. In our sample of bad sleepers, these post-training changes end up representing a notable sleep improvement, also consistently reflected in subjective sleep quality perception. Therefore, ecological pre-sleep cognitive training should be further studied as an easily accessible complementary approach in standard therapies for sleep-disordered populations.

Sleep changes following intensive cognitive activity

Studies over the last 40 years have mainly investigated sleep structure changes as a result of wake duration, in the frame of the classical sleep regulation theories. However, wake intervals of the same duration can profoundly differ in their intensity, which actually reflects the degree of cognitive and physical activity. Data on how sleep can be modified by wake intensity changes (initially sparse and of little consistence) have become much more substantial, especially in the frame of the intense research debate on sleep-memory relationships. Our aim is to examine the vast repertoire of sleep modifications that depend on waking cognitive manipulations, highlighting the sleep features that appear most affected. By systematically addressing this issue, we want to set the basis for future research exploring both the specific nature of the mechanisms involved and the applicative psychosocial and clinical fall-outs, in terms of possible behavioural interventions for sleep quality improvement.