Evidence of an active role of dreaming in emotional memory processing shows that we dream to forget.

Dreaming is a universal human behavior that has inspired searches for meaning across many disciplines including art, psychology, religion, and politics, yet its function remains poorly understood. Given the suggested role of sleep in emotional memory processing, we investigated whether reported overnight dreaming and dream content are associated with sleep-dependent changes in emotional memory and reactivity, and whether dreaming plays an active or passive role. Participants completed an emotional picture task before and after a full night of sleep and they recorded the presence and content of their dreams upon waking in the morning. The results replicated the emotional memory trade-off (negative images maintained at the cost of neutral memories), but only in those who reported dreaming (Dream-Recallers), and not in Non-Dream-Recallers. Results also replicated sleep-dependent reductions in emotional reactivity, but only in Dream-Recallers, not in Non-Dream-Recallers. Additionally, the more positive the dream report, the more positive the next-day emotional reactivity is compared to the night before. These findings implicate an active role for dreaming in overnight emotional memory processing and suggest a mechanistic framework whereby dreaming may enhance salient emotional experiences via the forgetting of less relevant information.

Cerebrovascular pathology mediates associations between hypoxemia during rapid eye movement sleep and medial temporal lobe structure and function in older adults.

Obstructive sleep apnea (OSA) is common in older adults and is associated with medial temporal lobe (MTL) degeneration and memory decline in aging and Alzheimer's disease (AD). However, the underlying mechanisms linking OSA to MTL degeneration and impaired memory remains unclear. By combining magnetic resonance imaging (MRI) assessments of cerebrovascular pathology and MTL structure with clinical polysomnography and assessment of overnight emotional memory retention in older adults at risk for AD, cerebrovascular pathology in fronto-parietal brain regions was shown to statistically mediate the relationship between OSA-related hypoxemia, particularly during rapid eye movement (REM) sleep, and entorhinal cortical thickness. Reduced entorhinal cortical thickness was, in turn, associated with impaired overnight retention in mnemonic discrimination ability across emotional valences for high similarity lures. These findings identify cerebrovascular pathology as a contributing mechanism linking hypoxemia to MTL degeneration and impaired sleep-dependent memory in older adults.

Medial temporal lobe functional network architecture supports sleep-related emotional memory processing in older adults.

Memory consolidation occurs via reactivation of a hippocampal index during non-rapid eye movement slow-wave sleep (NREM SWS) which binds attributes of an experience existing within cortical modules. For memories containing emotional content, hippocampal-amygdala dynamics facilitate consolidation over a sleep bout. This study tested if modularity and centrality-graph theoretical measures that index the level of segregation/integration in a system and the relative import of its nodes-map onto central tenets of memory consolidation theory and sleep-related processing. Findings indicate that greater network integration is tied to overnight emotional memory retention via NREM SWS expression. Greater hippocampal and amygdala influence over network organization supports emotional memory retention, and hippocampal or amygdala control over information flow are differentially associated with distinct stages of memory processing. These centrality measures are also tied to the local expression and coupling of key sleep oscillations tied to sleep-dependent memory consolidation. These findings suggest that measures of intrinsic network connectivity may predict the capacity of brain functional networks to acquire, consolidate, and retrieve emotional memories.

Good sleep is a mood buffer for young women during menses.

STUDY OBJECTIVES: We sought to elucidate the interaction between sleep and mood considering menstrual cycle phase (menses and non-menses portions of the cycle) in 72 healthy young women (18-33 years) with natural, regular menstrual cycles and without menstrual-associated disorders. This work fills a gap in literature of examining mood in context of sleep and menstrual cycle jointly, rather than individually. METHODS: Daily subjective measures of sleep and mood, and date of menses were remotely, digitally collected over a 2-month period. Each morning, participants rated their sleep on the previous night, and each evening participants rated the extent of positive and negative mood for that day. Objective sleep was tracked with a wearable (OURA ring) during month 2 of the study. Time-lag cross-correlation and mixed linear models were used to analyze the significance and directionality of the sleep-mood relationship, and how the interaction between menstrual cycle status and sleep impacted mood levels. RESULTS: We found that menstrual status alone did not impact mood. However, subjective sleep quality and menstrual status interacted to impact positive mood (p < .05). After a night of perceived poor sleep quality, participants reported lower positive mood during menses compared to non-menses portions of the cycle, while after a night of perceived good sleep quality participants reported equivalent levels of positive mood across the cycle. CONCLUSIONS: We suggest that the perception of good sleep quality acts as a mood equalizer, with good sleep providing a protective buffer to positive mood across the menstrual cycle.

The Role of Working Memory in Age-Related Emotional Memory Bias.

Aging is accompanied by deterioration in both working memory (WM) and long-term memory (LTM), yet whether these changes are related is not understood. Sleep plays a role in the formation of LTM in young adults, but the findings in older adults are not as clear. The types of memories we store also shift with age as young adults preserve a higher proportion of negative experiences when compared to older adults. The reason for this age-related change in emotional memory bias is also not clear; however, some studies have suggested that WM changes across aging may be an important factor. In the current study, we examined performance in WM and emotional LTM in younger and older adults. We added a daytime nap in half the subjects to examine a possible role of sleep on emotional LTM. In the morning, 93 younger (18-39) and 121 older (60-85) adults completed a WM task. Subjects also encoded neutral or negative word pairs and provided valence and arousal ratings for each pair. After half the subjects took a daytime nap, LTM was examined, and valence and arousal ratings were reassessed. Results indicate that older adults showed worse recognition for negative word pairs compared with neutral, as well as decreased negative valence ratings in the afternoon. This decrease in emotional reactivity was correlated with better LTM performance. In contrast, younger adults performed better on the negative compared to neutral word pairs, with no change in emotional reactivity and no association between emotional reactivity and LTM. In addition, WM was positively related to LTM in younger, but not in older adults. Lastly, no differences were shown across sleep, regardless of age. Our findings suggest that the emotional memory bias may be associated with the emotional saliency of the information in older adults, and with WM capacity in younger adults. Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-022-00134-5.

Sleep facilitates spatial memory but not navigation using the Minecraft Memory and Navigation task.

Sleep facilitates hippocampal-dependent memories, supporting the acquisition and maintenance of internal representation of spatial relations within an environment. In humans, however, findings have been mixed regarding sleep's contribution to spatial memory and navigation, which may be due to task designs or outcome measurements. We developed the Minecraft Memory and Navigation (MMN) task for the purpose of disentangling how spatial memory accuracy and navigation change over time, and to study sleep's independent contributions to each. In the MMN task, participants learned the locations of objects through free exploration of an open field computerized environment. At test, they were teleported to random positions around the environment and required to navigate to the remembered location of each object. In study 1, we developed and validated four unique MMN environments with the goal of equating baseline learning and immediate test performance. A total of 86 participants were administered the training phases and immediate test. Participants' baseline performance was equivalent across all four environments, supporting the use of the MMN task. In study 2, 29 participants were trained, tested immediately, and again 12 h later after a period of sleep or wake. We found that the metric accuracy of object locations, i.e., spatial memory, was maintained over a night of sleep, while after wake, metric accuracy declined. In contrast, spatial navigation improved over both sleep and wake delays. Our findings support the role of sleep in retaining the precise spatial relationships within a cognitive map; however, they do not support a specific role of sleep in navigation.

Autonomic central coupling during daytime sleep differs between older and younger people.

Decreased functioning in the elderly is mirrored by independent changes in central and autonomic nervous systems. Additionally, recent work suggests that the coupling of these systems may also serve an important role. In young adults, Autonomic and Central Events (ACEs), measured in the temporal coincidence of heart rate bursts (HRBs) and increased slow-wave-activity (SWA, 0.5-1 Hz) and sigma activity (12-15 Hz), followed by parasympathetic surge (RRHF) during non-rapid eye movement (NREM) sleep, predicted cognitive improvements. However, ACEs have not been examined in the elderly. Thus, the current study compared ACEs during wake and daytime sleep in older and younger adults and examined associations with working memory improvement before and after a nap. Compared to youngers, older adults showed lower amplitude of ACEs during NREM sleep, but not during wake. Furthermore, while younger adults demonstrated a parasympathetic surge after HRBs, older adults showed an earlier rise and longer maintenance of the RRHF. Taken together, our results demonstrate that autonomic-central coupling declines with age. Pathological aging implicates independent roles for decreased autonomic and central nervous system functioning, the current findings suggest that the coupling of these systems may also deserve attention.

Tracking Sleep, Temperature, Heart Rate, and Daily Symptoms Across the Menstrual Cycle with the Oura Ring in Healthy Women.

Background and Objective: The ovulatory menstrual cycle is characterized by hormonal fluctuations that influence physiological systems and functioning. Multi-sensor wearable devices can be sensitive tools capturing cycle-related physiological features pertinent to women's health research. This study used the Oura ring to track changes in sleep and related physiological features, and also tracked self-reported daily functioning and symptoms across the regular, healthy menstrual cycle. Methods: Twenty-six healthy women (age, mean (SD): 24.4 (1.1 years)) with regular, ovulatory cycles (length, mean (SD): 28.57 (3.8 days)) were monitored across a complete menstrual cycle. Four menstrual cycle phases, reflecting different hormone milieus, were selected for analysis: menses, ovulation, mid-luteal, and late-luteal. Objective measures of sleep, sleep distal skin temperature, heart rate (HR) and vagal-mediated heart rate variability (HRV, rMSSD), derived from the Oura ring, and subjective daily diary measures (eg sleep quality, readiness) were compared across phases. Results: Wearable-based measures of sleep continuity and sleep stages did not vary across the menstrual cycle. Women reported no menstrual cycle-related changes in perceived sleep quality or readiness and only marginally poorer mood in the midluteal phase. However, they reported moderately more physical symptoms during menses (p < 0.001). Distal skin temperature and HR, measured during sleep, showed a biphasic pattern across the menstrual cycle, with increased HR (p < 0.03) and body temperature (p < 0.001) in the mid- and late-luteal phases relative to menses and ovulation. Correspondingly, rMSSD HRV tended to be lower in the luteal phase. Further, distal skin temperature was lower during ovulation relative to menses (p = 0.05). Conclusion: The menstrual cycle was not accompanied by significant fluctuations in objective and perceived measures of sleep or in mood, in healthy women with regular, ovulatory menstrual cycles. However, other physiological changes in skin temperature and HR were evident and may be longitudinally tracked with the Oura ring in women over multiple cycles in a natural setting.

Age-related losses in cardiac autonomic activity during a daytime nap.

In healthy, young individuals, a reduction in cardiovascular output and a shift from sympathetic to parasympathetic (vagal) dominance is observed from wake into stages of nocturnal and daytime sleep. This cardiac autonomic profile, measured by heart rate variability (HRV), has been associated with significant benefits for cardiovascular health. Aging is associated with decreased nighttime sleep quality and lower parasympathetic activity during both sleep and resting. However, it is not known whether age-related dampening of HRV extends to daytime sleep, diminishing the cardiovascular benefits of naps in the elderly. Here, we investigated this question by comparing the autonomic activity profile between young and older healthy adults during a daytime nap and a similar period of wakefulness (quiet wake; QW). For each condition, from the electrocardiogram (ECG), we obtained beat-to-beat HRV intervals (RR), root mean square of successive differences between adjacent heart-beat-intervals (RMSSD), high-frequency (HF), low-frequency (LF) power, and total power (TP), HF normalized units (HFnu ), and the LF/HF ratio. As previously reported, young subjects showed a parasympathetic dominance during NREM, compared with REM, prenap rest, and WASO. Moreover, older, compared to younger, adults showed significantly lower vagally mediated HRV (measured by RMSSD, HF, HFnu ) during NREM. Interestingly, however, no age-related differences were detected during prenap rest or QW. Altogether, our findings suggest a sleep-specific reduction in parasympathetic modulation that is unique to NREM sleep in older adults.

Does working memory improvement benefit from sleep in older adults?

Working Memory (WM), is an important factor influencing many higher-order cognitive functions that decline with age. Repetitive training appears to increase WM, yet the mechanisms underlying this improvement are not understood. Sleep has been shown to benefit long-term memory formation and may also play a role in WM enhancement in young adults. However, considering age-related decline in sleep, it is uninvestigated whether sleep will facilitate WM in older adults. In the present work, we investigated the impact of a nap, quiet wakefulness (QW) and active wakefulness (AW) on within-day training on the Operation Span (OSPAN) task in older adults. Improvement in WM was found following a nap and QW, but not active wake. Furthermore, better WM was associated with shared electrophysiological features, including slow oscillation (SO, 0.5-1 Hz) power in both the nap and QW, and greater coupling between SO and sigma (12-15 Hz) in the nap. In summary, our data suggest that WM improvement in older adults occurs opportunistically during offline periods that afford enhancement in slow oscillation power, and that further benefits may come with cross-frequency coupling of neural oscillations during sleep.

Impact of sex steroids and reproductive stage on sleep-dependent memory consolidation in women.

Age and sex are two of the three major risk factors for Alzheimer's disease (ApoE-e4 allele is the third), with women having a twofold greater risk for Alzheimer's disease after the age of 75 years. Sex differences have been shown across a wide range of cognitive skills in young and older adults, and evidence supports a role for sex steroids, especially estradiol, in protecting against the development of cognitive decline in women. Sleep may also be a protective factor against age-related cognitive decline, since specific electrophysiological sleep events (e.g. sleep spindle/slow oscillation coupling) are critical for offline memory consolidation. Furthermore, studies in young women have shown fluctuations in sleep events and sleep-dependent memory consolidation during different phases of the menstrual cycle that are associated with the levels of sex steroids. An under-appreciated possibility is that there may be an important interaction between these two protective factors (sex steroids and sleep) that may play a role in daily fluctuations in cognitive processing, in particular memory, across a woman's lifespan. Here, we summarize the current knowledge of sex steroid-dependent influences on sleep and cognition across the lifespan in women, with special emphasis on sleep-dependent memory processing. We further indicate gaps in knowledge that require further experimental examination in order to fully appreciate the complex and changing landscape of sex steroids and cognition. Lastly, we propose a series of testable predictions for how sex steroids impact sleep events and sleep-dependent cognition across the three major reproductive stages in women (reproductive years, menopause transition, and post-menopause).

The impact of frequent napping and nap practice on sleep-dependent memory in humans.

Napping benefits long-term memory formation and is a tool many individuals use to improve daytime functioning. Despite its potential advantages, approximately 47% of people in the United States eschew napping. The goal of this study was to determine whether people who endorse napping at least once a week (nap+) show differences in nap outcomes, including nap-dependent memory consolidation, compared with people who rarely or never nap (nap-). Additionally, we tested whether four weeks of nap practice or restriction would change sleep and performance profiles. Using a perceptual learning task, we found that napping enhanced performance to a greater degree in nap+ compared with nap- individuals (at baseline). Additionally, performance change was associated with different electrophysiological sleep features in each group. In the nap+ group, spindle density was positively correlated with performance improvement, an effect specific to spindles in the hemisphere contralateral to the trained visual field. In the nap- group, slow oscillatory power (0.5-1 Hz) was correlated with performance. Surprisingly, no changes to performance or brain activity during sleep emerged after four weeks of nap practice or restriction. These results suggest that individual differences may impact the potential benefits of napping on performance and the ability to become a better napper.

The effect of sex and menstrual phase on memory formation during a nap.

Memory formation can be influenced by sleep and sex hormones in both men and women, and by the menstrual cycle in women. Though many studies have shown that sleep benefits the consolidation of memories, it is not clear whether this effect differs between men and women in general or according to menstrual phase in women. The present study investigated the effect of sex and menstrual cycle on memory consolidation of face-name associations (FNA) following a daytime nap. Recognition memory was tested using a face-name paired associates task with a polysomnographic nap between morning and evening testing. Seventeen healthy women (age: 20.75 (1.98) years) were studied at two time points of their menstrual cycles, defined from self-report and separated by 2weeks (perimenses: -5days to +6days from the start of menses, and non-perimenses: outside of the perimenses phase), and compared with eighteen healthy men (age: 22.01 (2.91) years). Regardless of menstrual phase, women had better pre-nap performance than men. Further, menstrual phase affected post-nap memory consolidation, with women showing greater forgetting in their perimenses phase compared with their non-perimenses phase and men. Interestingly, post-nap performance correlated with electrophysiological events during sleep (slow oscillations, spindles, and temporal coupling between the two), however, these correlations differed according to menstrual phase and sex. Men's performance improvement was associated with the temporal coupling of spindles and slow oscillations (i.e., spindle/SO coincidence) as well as spindles. Women, however, showed an association with slow oscillations during non-perimenses, whereas when they were in their perimenses phase of their cycle, women appeared to show an association only with sleep spindle events for consolidation. These findings add to the growing literature demonstrating sex and menstrual phase effects on memory formation during sleep.

The Interdisciplinarity of Collaborations in Cognitive Science.

We introduce a new metric for interdisciplinarity, based on co-author publication history. A published article that has co-authors with quite different publication histories can be deemed relatively "interdisciplinary," in that the article reflects a convergence of previous research in distinct sets of publication outlets. In recent work, we have shown that this interdisciplinarity metric can predict citations. Here, we show that the journal Cognitive Science tends to contain collaborations that are relatively high on this interdisciplinarity metric, at about the 80th percentile of all journals across both social and natural sciences. Following on Goldstone and Leydesdorff (2006), we describe how scientometric tools provide a valuable means of assessing the role of cognitive science in broader scientific work, and also as a tool to investigate teamwork and distributed cognition. We describe how data-driven metrics of this kind may facilitate this exploration without relying upon rapidly changing discipline and topic keywords associated with publications.

Automatic detection of rapid eye movements (REMs): A machine learning approach.

BACKGROUND: Rapid eye movements (REMs) are a defining feature of REM sleep. The number of discrete REMs over time, or REM density, has been investigated as a marker of clinical psychopathology and memory consolidation. However, human detection of REMs is a time-consuming and subjective process. Therefore, reliable, automated REM detection software is a valuable research tool. NEW METHOD: We developed an automatic REM detection algorithm combining a novel set of extracted features and the 'AdaBoost' classification algorithm to detect the presence of REMs in Electrooculogram data collected from the right and left outer canthi (ROC/LOC). Algorithm performance measures of Recall (percentage of REMs detected) and Precision (percentage of REMs detected that are true REMs) were calculated and compared to the gold standard of human detection by three expert sleep scorers. REM detection by four non-experts were also investigated and compared to expert raters and the algorithm. RESULTS: The algorithm performance (78.1% Recall, 82.6% Precision) surpassed that of the average (expert & non-expert) single human detection performance (76% Recall, 83% Precision). Agreement between non-experts (Cronbach Alpha=0.65) is markedly lower than experts (Cronbach Alpha=0.80). COMPARISON WITH EXISTING METHOD(S): By following reported methods, we implemented all previously published LOC and ROC based detection algorithms on our dataset. Our algorithm performance exceeded all others. CONCLUSIONS: The automatic detection algorithm presented is a viable and efficient method of REM detection as it reliably matches the performance of human scorers and outperforms all other known LOC- and ROC-based detection algorithms.