Higher handgrip strength is linked to higher salience ventral attention functional network segregation in older adults.

Converging evidence suggests that handgrip strength is linked to cognition in older adults, and this may be subserved by shared age-related changes in brain function and structure. However, the interplay among handgrip strength, brain functional connectivity, and cognitive function remains poorly elucidated. Hence, our study sought to examine these relationships in 148 community-dwelling older adults. Specifically, we examined functional segregation, a measure of functional brain organization sensitive to ageing and cognitive decline, and its associations with handgrip strength and cognitive function. We showed that higher handgrip strength was related to better processing speed, attention, and global cognition. Further, higher handgrip strength was associated with higher segregation of the salience/ventral attention network, driven particularly by higher salience/ventral attention intra-network functional connectivity of the right anterior insula to the left posterior insula/frontal operculum and right midcingulate/medial parietal cortex. Importantly, these handgrip strength-related inter-individual differences in salience/ventral attention network functional connectivity were linked to cognitive function, as revealed by functional decoding and brain-cognition association analyses. Our findings thus highlight the importance of the salience/ventral attention network in handgrip strength and cognition, and suggest that inter-individual differences in salience/ventral attention network segregation and intra-network connectivity could underpin the handgrip strength-cognition relationship in older adults.

Advantage conferred by overnight sleep on schema-related memory may last only a day.

Study Objectives: Sleep contributes to declarative memory consolidation. Independently, schemas benefit memory. Here we investigated how sleep compared with active wake benefits schema consolidation 12 and 24 hours after initial learning. Methods: Fifty-three adolescents (age: 15-19 years) randomly assigned into sleep and active wake groups participated in a schema-learning protocol based on transitive inference (i.e. If B > C and C > D then B > D). Participants were tested immediately after learning and following 12-, and 24-hour intervals of wake or sleep for both the adjacent (e.g. B-C, C-D; relational memory) and inference pairs: (e.g.: B-D, B-E, and C-E). Memory performance following the respective 12- and 24-hour intervals were analyzed using a mixed ANOVA with schema (schema, no-schema) as the within-participant factor, and condition (sleep, wake) as the between-participant factor. Results: Twelve hours after learning, there were significant main effects of condition (sleep, wake) and schema, as well as a significant interaction, whereby schema-related memory was significantly better in the sleep condition compared to wake. Higher sleep spindle density was most consistently associated with greater overnight schema-related memory benefit. After 24 hours, the memory advantage of initial sleep was diminished. Conclusions: Overnight sleep preferentially benefits schema-related memory consolidation following initial learning compared with active wake, but this advantage may be eroded after a subsequent night of sleep. This is possibly due to delayed consolidation that might occur during subsequent sleep opportunities in the wake group. Clinical Trial Information: Name: Investigating Preferred Nap Schedules for Adolescents (NFS5) URL: https://clinicaltrials.gov/ct2/show/NCT04044885. Registration: NCT04044885.

Influence of mid-afternoon nap duration and sleep parameters on memory encoding, mood, processing speed, and vigilance.

STUDY OBJECTIVES: To determine how mid-afternoon naps of differing durations benefit memory encoding, vigilance, speed of processing (SOP), mood, and sleepiness; to evaluate if these benefits extend past 3 hr post-awakening and to examine how sleep macrostructure during naps modulate these benefits. METHODS: Following short habitual sleep, 32 young adults underwent four experimental conditions in randomized order: wake; naps of 10 min, 30 min, and 60 min duration verified with polysomnography. A 10-min test battery was delivered at a pre-nap baseline, and at 5 min, 30 min, 60 min, and 240 min post-nap. Participants encoded pictures 90 min post-nap and were tested for recognition 210 min later. RESULTS: Naps ranging from 10 to 60 min increased positive mood and alleviated self-reported sleepiness up to 240 min post-nap. Compared to waking, only naps of 30 min improved memory encoding. Improvements in vigilance were moderate, and benefits for SOP were not observed. Sleep inertia was observed for the 30 min to 60 min naps but was resolved within 30 min after waking. We found no significant associations between sleep macrostructure and memory benefits. CONCLUSIONS: With short habitual sleep, naps ranging from 10 to 60 min had clear and lasting benefits for positive mood and self-reported sleepiness/alertness. Cognitive improvements were moderate, with only the 30 min nap showing benefits for memory encoding. While there is no clear "winning" nap duration, a 30 min nap appears to have the best trade-off between practicability and benefit. CLINICAL TRIAL ID: Effects of Varying Duration of Naps on Cognitive Performance and Memory Encoding, https://www.clinicaltrials.gov/ct2/show/NCT04984824, NCT04984824.

Associations between objectively measured sleep parameters and cognition in healthy older adults: A meta-analysis.

Multiple studies have examined associations between sleep and cognition in older adults, but a majority of these depend on self-reports on sleep and utilize cognitive tests that assess overall cognitive function. The current meta-analysis involved 72 independent studies and sought to quantify associations between objectively measured sleep parameters and cognitive performance in healthy older adults. Both sleep macrostructure (e.g., sleep duration, continuity, and stages) and microstructure (e.g., slow wave activity and spindle activity) were evaluated. For macrostructure, lower restlessness at night was associated with better memory performance (r = 0.43, p = 0.02), while lower sleep onset latency was associated with better executive functioning (r = 0.28, p = 0.03). Greater relative amount of N2 and REM sleep, but not N3, positively correlated with cognitive performance. The association between microstructure and cognition in older adults was marginally significant. This relationship was moderated by age (z = 0.07, p < 0.01), education (z = 0.26, p = 0.03), and percentage of female participants (z = 0.01, p < 0.01). The current meta-analysis emphasizes the importance of considering objective sleep measures to understand the relationship between sleep and cognition in healthy older adults. These results also form a base from which researchers using wearable sleep technology and measuring behavior through computerized testing tools can evaluate their findings.

Understanding the Need for Sleep to Improve Cognition.

The restorative function of sleep is shaped by its duration, timing, continuity, subjective quality, and efficiency. Current sleep recommendations specify only nocturnal duration and have been largely derived from sleep self-reports that can be imprecise and miss relevant details. Sleep duration, preferred timing, and ability to withstand sleep deprivation are heritable traits whose expression may change with age and affect the optimal sleep prescription for an individual. Prevailing societal norms and circumstances related to work and relationships interact to influence sleep opportunity and quality. The value of allocating time for sleep is revealed by the impact of its restriction on behavior, functional brain imaging, sleep macrostructure, and late-life cognition. Augmentation of sleep slow oscillations and spindles have been proposed for enhancing sleep quality, but they inconsistently achieve their goal. Crafting bespoke sleep recommendations could benefit from large-scale, longitudinal collection of objective sleep data integrated with behavioral and self-reported data.

Bedtime procrastination and chronotype differentially predict adolescent sleep on school nights and non-school nights.

OBJECTIVES: Bedtime procrastination (BTP) refers to the tendency to delay sleep beyond an intended bedtime, in favor of continuing evening activities. BTP has been associated with negative sleep outcomes (later timing, shorter duration, poorer quality), and is viewed as a problem of exercising self-control. BTP could be particularly challenging in adolescents, given the combined effects of increasing bedtime autonomy, later chronotype, and a still developing self-control capacity. Thus far, research on BTP has only been based on self-report measures. Here we examined the influence of BTP on adolescent sleep, using objective measures of sleep. METHODS: About 121 adolescents aged 14-19 years completed a survey on BTP, sleep quality, chronotype, and mental health. Subsequently, habitual sleep was actigraphically monitored for up to 2 weeks, and participants completed a temporal discounting task (a proxy for impulsivity). Associations between BTP, chronotype, and actigraphy-measured sleep were examined for school nights and non-school nights separately. RESULTS: Greater BTP was associated with poorer subjective sleep, eveningness chronotype, and higher daytime fatigue, as well as higher anxiety/depression scores. Measured using actigraphy, greater BTP predicted later bedtimes and shorter sleep duration on school nights, even when controlling for chronotype. On non-school nights, eveningness chronotype, but not BTP, predicted later bedtimes and wake-up times. BTP was not correlated with temporal discounting. CONCLUSIONS: Bedtime procrastination exerts significant influence on subjective and objective sleep measures in adolescents. Its effects are most prominent on school nights and can be separated from the effects of chronotype, which has stronger effects on sleep timing on non-school nights.

Systematic review and meta-analyses on the effects of afternoon napping on cognition.

Naps are increasingly considered a means to boost cognitive performance. We quantified the cognitive effects of napping in 60 samples from 54 studies. 52 samples evaluated memory. We first evaluated effect sizes for all tests together, before separately assessing their effects on memory, vigilance, speed of processing and executive function. We next examined whether nap effects were moderated by study features of age, nap length, nap start time, habituality and prior sleep restriction. Naps showed significant benefits for the total aggregate of cognitive tests (Cohen's d = 0.379, CI95 = 0.296-0.462). Significant domain specific effects were present for declarative (Cohen's d = 0.376, CI95 = 0.269-0.482) and procedural memory (Cohen's d = 0.494, CI95 = 0.301-0.686), vigilance (Cohen's d = 0.610, CI95 = 0.291-0.929) and speed of processing (Cohen's d = 0.211, CI95 = 0.052-0.369). There were no significant moderation effects of any of the study features. Nap effects were of comparable magnitude across subgroups of each of the 5 moderators (Q values = 0.009 to 8.572, p values > 0.116). Afternoon naps have a small to medium benefit over multiple cognitive tests. These effects transcend age, nap duration and tentatively, habituality and prior nocturnal sleep.

Multi-Night at-Home Evaluation of Improved Sleep Detection and Classification with a Memory-Enhanced Consumer Sleep Tracker.

Purpose: To evaluate the benefits of applying an improved sleep detection and staging algorithm on minimally processed multi-sensor wearable data collected from older generation hardware. Patients and Methods: 58 healthy, East Asian adults aged 23-69 years (M = 37.10, SD = 13.03, 32 males), each underwent 3 nights of PSG at home, wearing 2nd Generation Oura Rings equipped with additional memory to store raw data from accelerometer, infra-red photoplethysmography and temperature sensors. 2-stage and 4-stage sleep classifications using a new machine-learning algorithm (Gen3) trained on a diverse and independent dataset were compared to the existing consumer algorithm (Gen2) for whole-night and epoch-by-epoch metrics. Results: Gen 3 outperformed its predecessor with a mean (SD) accuracy of 92.6% (0.04), sensitivity of 94.9% (0.03), and specificity of 78.5% (0.11); corresponding to a 3%, 2.8% and 6.2% improvement from Gen2 across the three nights, with Cohen's d values >0.39, t values >2.69, and p values <0.01. Notably, Gen 3 showed robust performance comparable to PSG in its assessment of sleep latency, light sleep, rapid eye movement (REM), and wake after sleep onset (WASO) duration. Participants <40 years of age benefited more from the upgrade with less measurement bias for total sleep time (TST), WASO, light sleep and sleep efficiency compared to those ≥40 years. Males showed greater improvements on TST and REM sleep measurement bias compared to females, while females benefitted more for deep sleep measures compared to males. Conclusion: These results affirm the benefits of applying machine learning and a diverse training dataset to improve sleep measurement of a consumer wearable device. Importantly, collecting raw data with appropriate hardware allows for future advancements in algorithm development or sleep physiology to be retrospectively applied to enhance the value of longitudinal sleep studies.

A sleep schedule incorporating naps benefits the transformation of hierarchical knowledge.

STUDY OBJECTIVES: The learning brain establishes schemas (knowledge structures) that benefit subsequent learning. We investigated how sleep and having a schema might benefit initial learning followed by rearranged and expanded memoranda. We concurrently examined the contributions of sleep spindles and slow-wave sleep to learning outcomes. METHODS: Fifty-three adolescents were randomly assigned to an 8 h Nap schedule (6.5 h nocturnal sleep with a 90-minute daytime nap) or an 8 h No-Nap, nocturnal-only sleep schedule. The study spanned 14 nights, simulating successive school weeks. We utilized a transitive inference task involving hierarchically ordered faces. Initial learning to set up the schema was followed by rearrangement of the hierarchy (accommodation) and hierarchy expansion (assimilation). The expanded sequence was restudied. Recall of hierarchical knowledge was tested after initial learning and at multiple points for all subsequent phases. As a control, both groups underwent a No-schema condition where the hierarchy was introduced and modified without opportunity to set up a schema. Electroencephalography accompanied the multiple sleep opportunities. RESULTS: There were main effects of Nap schedule and Schema condition evidenced by superior recall of initial learning, reordered and expanded memoranda. Improved recall was consistently associated with higher fast spindle density but not slow-wave measures. This was true for both nocturnal sleep and daytime naps. CONCLUSION: A sleep schedule incorporating regular nap opportunities compared to one that only had nocturnal sleep benefited building of robust and flexible schemas, facilitating recall of the subsequently rearranged and expanded structured knowledge. These benefits appear to be strongly associated with fast spindles. CLINICAL TRIAL REGISTRATION: NCT04044885 (https://clinicaltrials.gov/ct2/show/NCT04044885).

Cortical thinning and sleep slow wave activity reductions mediate age-related improvements in cognition during mid-late adolescence.

STUDY OBJECTIVES: Gains in cognitive test performance that occur during adolescence are associated with brain maturation. Cortical thinning and reduced sleep slow wave activity (SWA) are markers of such developmental changes. Here we investigate whether they mediate age-related improvements in cognition. METHODS: 109 adolescents aged 15-19 years (49 males) underwent magnetic resonance imaging, polysomnography (PSG), and a battery of cognitive tasks within a 2-month time window. Cognitive tasks assessed nonverbal intelligence, sustained attention, speed of processing and working memory and executive function. To minimize the effect of sleep history on SWA and cognitive performance, PSG and test batteries were administered only after at least 8 nights of 9-h time-in-bed (TIB) sleep opportunity. RESULTS: Age-related improvements in speed of processing (r = 0.33, p = 0.001) and nonverbal intelligence (r = 0.24, p = 0.01) domains were observed. These cognitive changes were associated with reduced cortical thickness, particularly in bilateral temporoparietal regions (rs = -0.21 to -0.45, ps < 0.05), as well as SWA (r = -0.35, p < 0.001). Serial mediation models found that ROIs in the middle/superior temporal cortices, together with SWA mediated the age-related improvement observed on cognition. CONCLUSIONS: During adolescence, age-related improvements in cognition are mediated by reductions in cortical thickness and sleep SWA.

Sleep-dependent prospective memory consolidation is impaired with aging.

STUDY OBJECTIVES: Existing literature suggests that sleep-dependent memory consolidation is impaired in older adults but may be preserved for personally relevant information. Prospective memory (PM) involves remembering to execute future intentions in a timely manner and has behavioral importance. As previous work suggests that N3 sleep is important for PM in young adults, we investigated if the role of N3 sleep in PM consolidation would be maintained in older adults. METHODS: Forty-nine young adults (mean age ± SD: 21.8 ± 1.61 years) and 49 healthy older adults (mean age ± SD: 65.7 ± 6.30 years) were randomized into sleep and wake groups. After a semantic categorization task, participants encoded intentions comprising four related and four unrelated cue-action pairs. They were instructed to remember to perform these actions in response to cue words presented during a second semantic categorization task 12 h later that encompassed either daytime wake (09:00 am-21:00 pm) or overnight sleep with polysomnography (21:00 pm-09:00 am). RESULTS: The significant condition × age group × relatedness interaction suggested that the sleep benefit on PM intentions varied according to age group and relatedness (p = 0.01). For related intentions, sleep relative to wake benefitted young adults' performance (p < 0.001) but not older adults (p = 0.30). For unrelated intentions, sleep did not improve PM for either age group. While post-encoding N3 was significantly associated with related intentions' execution in young adults (r = 0.43, p = 0.02), this relationship was not found for older adults (r = -0.07, p = 0.763). CONCLUSIONS: The age-related impairment of sleep-dependent memory consolidation extends to PM. Our findings add to an existing body of work suggesting that the link between sleep and memory is functionally weakened in older adulthood.

Splitting sleep between the night and a daytime nap reduces homeostatic sleep pressure and enhances long-term memory.

Daytime naps have been linked with enhanced memory encoding and consolidation. It remains unclear how a daily napping schedule impacts learning throughout the day, and whether these effects are the same for well-rested and sleep restricted individuals. We compared memory in 112 adolescents who underwent two simulated school weeks containing 8 or 6.5 h sleep opportunities each day. Sleep episodes were nocturnal or split between nocturnal sleep and a 90-min afternoon nap, creating four experimental groups: 8 h-continuous, 8 h-split, 6.5 h-continuous and 6.5 h-split. Declarative memory was assessed with picture encoding and an educationally realistic factual knowledge task. Splitting sleep significantly enhanced afternoon picture encoding and factual knowledge under both 6.5 h and 8 h durations. Splitting sleep also significantly reduced slow-wave energy during nocturnal sleep, suggesting lower homeostatic sleep pressure during the day. There was no negative impact of the split sleep schedule on morning performance, despite a reduction in nocturnal sleep. These findings suggest that naps could be incorporated into a daily sleep schedule that provides sufficient sleep and benefits learning.

Schema-driven memory benefits boost transitive inference in older adults.

Age-related cognitive deficits may be diminished by tapping into prior knowledge structures. We investigated age-related differences in the formation and updating of schemas and examined whether the memory benefits of recently acquired schemas would be preserved in older adults. Data were collected from 60 older adults (M = 66.2, SD = 9.3 years) and 59 adolescents recruited from Singapore's top schools (M = 16.6, SD = 0.9 years) who learnt the age hierarchy of six galaxies to criterion by viewing neighboring pairs one at a time, for example A-B, D-E, C-D, enabling the formation of a schema via transitive inference (i.e., if B > C and C > D then B > D). Once learning reached criterion, two new sets of galaxies were presented: one comprising four galaxies from the schema intercalated with four new galaxies (schema condition) and the other comprising eight unfamiliar galaxies (no schema condition). Participants were then tested on both neighboring pairs (noninference) and inference pairs: (B-D, B-E, C-E). Compared with adolescents, older adults required a significantly higher number of learning blocks to successfully form a schema. Nonetheless, the acquired schema significantly aided relational memory and facilitated the making of novel inferences in older adults. This schema benefit was particularly pronounced in supporting novel inferences, boosting performance in older adults to levels comparable with adolescents (59% vs. 61%). These results suggest that older adults can effectively form new schemas with extended practice. Schema-driven memory benefits are preserved with aging and appear to mitigate age-related memory deficits, optimizing cognitive performance in making novel inferences. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Multi-Night Validation of a Sleep Tracking Ring in Adolescents Compared with a Research Actigraph and Polysomnography.

BACKGROUND: Wearable devices have tremendous potential for large-scale longitudinal measurement of sleep, but their accuracy needs to be validated. We compared the performance of the multisensor Oura ring (Oura Health Oy, Oulu, Finland) to polysomnography (PSG) and a research actigraph in healthy adolescents. METHODS: Fifty-three adolescents (28 females; aged 15-19 years) underwent overnight PSG monitoring while wearing both an Oura ring and Actiwatch 2 (Philips Respironics, USA). Measurements were made over multiple nights and across three levels of sleep opportunity (5 nights with either 6.5 or 8h, and 3 nights with 9h). Actiwatch data at two sensitivity settings were analyzed. Discrepancies in estimated sleep measures as well as sleep-wake, and sleep stage agreements were evaluated using Bland-Altman plots and epoch-by-epoch (EBE) analyses. RESULTS: Compared with PSG, Oura consistently underestimated TST by an average of 32.8 to 47.3 minutes (Ps < 0.001) across the different TIB conditions; Actiwatch 2 at its default setting underestimated TST by 25.8 to 33.9 minutes. Oura significantly overestimated WASO by an average of 30.7 to 46.3 minutes. It was comparable to Actiwatch 2 at default sensitivity in the 6.5, and 8h TIB conditions. Relative to PSG, Oura significantly underestimated REM sleep (12.8 to 19.5 minutes) and light sleep (51.1 to 81.2 minutes) but overestimated N3 by 31.5 to 46.8 minutes (Ps < 0.01). EBE analyses demonstrated excellent sleep-wake accuracies, specificities, and sensitivities - between 0.88 and 0.89 across all TIBs. CONCLUSION: The Oura ring yielded comparable sleep measurement to research grade actigraphy at the latter's default settings. Sleep staging needs improvement. However, the device appears adequate for characterizing the effect of sleep duration manipulation on adolescent sleep macro-architecture.

Memory performance following napping in habitual and non-habitual nappers.

STUDY OBJECTIVES: Afternoon naps benefit memory but this may depend on whether one is a habitual napper (HN; ≥1 nap/week) or non-habitual napper (NN). Here, we investigated whether a nap would benefit HN and NN differently, as well as whether HN would be more adversely affected by nap restriction compared to NN. METHODS: Forty-six participants in the nap condition (HN-nap: n = 25, NN-nap: n = 21) took a 90-min nap (14:00-15:30 pm) on experimental days while 46 participants in the Wake condition (HN-wake: n = 24, NN-wake: n = 22) remained awake in the afternoon. Memory tasks were administered after the nap to assess short-term topographical memory and long-term memory in the form of picture encoding and factual knowledge learning respectively. RESULTS: An afternoon nap boosted picture encoding and factual knowledge learning irrespective of whether one habitually napped (main effects of condition (nap/wake): ps < 0.037). However, we found a significant interaction for the hippocampal-dependent topographical memory task (p = 0.039) wherein a nap, relative to wake, benefitted habitual nappers (HN-nap vs HN-wake: p = 0.003) compared to non-habitual nappers (NN-nap vs. NN-wake: p = 0.918). Notably for this task, habitual nappers' performance significantly declined if they were not allowed to nap (HN-wake vs NN-wake: p = 0.037). CONCLUSIONS: Contrary to concerns that napping may be disadvantageous for non-habitual nappers, we found that an afternoon nap was beneficial for long-term memory tasks even if one did not habitually nap. Naps were especially beneficial for habitual nappers performing a short-term topographical memory task, as it restored the decline that would otherwise have been incurred without a nap. CLINICAL TRIAL INFORMATION: NCT04044885.

Cognitive effects of split and continuous sleep schedules in adolescents differ according to total sleep opportunity.

STUDY OBJECTIVES: We compared the basic cognitive functions of adolescents undergoing split (nocturnal sleep + daytime nap) and continuous nocturnal sleep schedules when total sleep opportunity was either below or within the recommended range (i.e. 6.5 or 8 h). METHODS: Adolescent participants (age: 15-19 year) in the 8-h split (n = 24) and continuous (n = 29) sleep groups were compared with 6.5-h split and continuous sleep groups from a previous study (n = 58). These protocols involved two baseline nights (9-h time-in-bed [TIB]), 5 nights of sleep manipulation, 2 recovery nights (9-h TIB), followed by a second cycle of sleep manipulation (3 nights) and recovery (2 nights). Cognitive performance, subjective sleepiness, and mood were evaluated daily; sleep was assessed using polysomnography. RESULTS: Splitting 6.5 h of sleep with a mid-afternoon nap offered a boost to cognitive function compared to continuous nocturnal sleep. However, when total TIB across 24 h increased to 8 h, the split and continuous sleep groups performed comparably in tests evaluating vigilance, working memory, executive function, processing speed, subjective sleepiness, and mood. CONCLUSIONS: In adolescents, the effects of split sleep on basic cognitive functions vary by the amount of total sleep obtained. As long as the total sleep opportunity across 24 h is within the recommended range, students may fulfill sleep requirements by adopting a split sleep schedule consisting of a shorter period of nocturnal sleep combined with a mid-afternoon nap, without significant impact on basic cognitive functions. CLINICAL TRIAL REGISTRATION: NCT04044885.

The effects of sleep on prospective memory: A systematic review and meta-analysis.

Prospective memory (PM) enables us to execute previously conceived intentions at a later time and is used when remembering to call a friend or submitting a proposal on time. Evidence that sleep benefits PM is presently mixed. Further, when a benefit is observed, it is unclear if this is achieved through improvements in strategic monitoring (maintaining an intention in mind and searching for cues) or spontaneous retrieval (an automatic process occurring without preparatory attention). We conducted a meta-analysis of 24 independent samples (N = 165,432) to quantify the effect of sleep on PM and gain clarity regarding the retrieval process benefitted by sleep. Cohen's d with 95% confidence intervals (CI95) were derived using random-effects models. The benefit of sleep on PM was statistically significant and in the small to medium range (d = 0.41, CI95 = 0.25-0.56). Moreover, sleep did not appear to influence monitoring (d = -0.11, CI95 = -0.40-0.17). In contrast, the benefits of sleep are significantly greater when the likelihood of spontaneous retrieval is high (d = 0.94, CI95 = 0.44-1.44) versus low (d = 0.45, CI95 = -0.02-0.93), suggesting that sleep may leverage on spontaneous retrieval processes to improve PM. These findings inform theoretical models of sleep and PM that could sharpen strategies to improve memory function in vulnerable populations.

Sleep improves memory for the content but not execution of intentions in adolescents.

OBJECTIVE: Sleep benefits prospective memory in young adults probably in part due to its well-established role in enhancing declarative memory, thereby facilitating retrieval of the intention content. In prior work on adolescents, we did not detect differences in prospective memory comparing five nights of sleep restriction and adequate sleep. Here, we examined whether this might be attributed to a limited role of sleep in benefiting the declarative content in this age group, and whether a sleep benefit on prospective memory would be uncovered with a shorter retention interval. METHODS: A total of 59 adolescents (mean ± standard deviation: 16.55 ± 0.94 years) were instructed to remember to press a special key in response to two target words embedded in a semantic categorization task. Memory was tested after a 12-h retention interval, which included either overnight sleep (21:00-09:00, n = 29) or daytime wakefulness (09:00-21:00, n = 30). RESULTS: We found no significant group difference in the percentage of target words correctly responded to (mean ± standard error of the mean for the sleep group: 32.76 ± 6.69%; wake group: 41.67 ± 7.61%, t = 0.88, p = 0.38). However, participants who slept recalled more target words compared to those who stayed awake (98.28 ± 1.72% vs. 86.67 ± 5.32%, t = 2.05, p < 0.05). In addition, a significantly greater proportion of sleep participants (n = 28 of 29) compared to wake participants (n = 24 of 30) recalled both target words correctly (χ2 = 3.76, p < 0.05). CONCLUSION: These findings suggest that during adolescence, sleep plays a more prominent role in improving memory for the content as compared to the execution of intentions.

Slow wave sleep facilitates spontaneous retrieval in prospective memory.

STUDY OBJECTIVES: Previous studies have shown that sleep benefits prospective memory by facilitating spontaneous retrieval processes. Here, we investigated the sleep features supporting such a benefit. METHODS: Forty-nine young adults (mean age ± SD: 22.06 ± 1.71 years; 18 males) encoded intentions comprising four related (phone-unplug earphones) and four unrelated (mirror-close the book) cue-action pairs. They were instructed to remember to perform these actions in response to cue words presented during a semantic categorization task 12 h later. The retention interval involved either a period of wakefulness (09:30-21:30; n = 24) or overnight sleep with polysomnographic monitoring (21:30-09:30; n = 25). RESULTS: We found a significant Group × Relatedness interaction for prospective memory accuracy (F = 8.35, p < 0.01). The sleep group successfully executed a significantly higher percentage of related intentions compared to the wake group (mean ± standard error of the mean (SEM): 94.00 ± 2.61% vs 66.67 ± 6.84%, p < 0.001). This benefit for related intentions was associated with longer post-learning slow wave sleep (r = 0.46, p < 0.05). In contrast, the percentage of unrelated intentions successfully executed did not differ between groups (82.00 ± 5.10% vs 72.92 ± 6.88%, p = 0.29). CONCLUSION: Slow wave sleep after memory encoding may strengthen the preexisting associations between semantically related cues and actions, thereby facilitating subsequent spontaneous retrieval processes.