Laura B. Ray

Changes in the density of stage 2 sleep spindles following motor learning in young and older adults

The purpose of this study was to compare the changes that occur in sleep architecture following the acquisition of a simple motor learning task in young and older adults. Subjects included 14 young (range = 17–24 years) and 14 older (range = 62–79 years) adults, all of whom were in good health. Using in‐home recording systems, sleep architecture (sleep stages and the density of Stage 2 sleep spindles) was examined before and after learning the pursuit rotor. To control for possible age differences in baseline motor performance and spindle density, both absolute and relative (percent change) measures were examined. Both groups improved significantly on the pursuit rotor task at Retest (1 week later); however, the magnitude of absolute improvement was larger in the young group than in the older group. There was no group difference when a relative measure of improvement (percent increase across sessions) was used. The density of Stage 2 sleep spindles increased significantly following task Acquisition in the young group but not in the older group. These age differences failed to reach significance when change was measured as a percentage of baseline level of spindle density. The increase in spindle density was correlated with performance level during acquisition in the young group but not the older group. The results of the present study are largely consistent with previous studies on sleep and memory in young adults and suggest that more detailed examination of this relationship in older adults is warranted.

Daytime sleep enhances consolidation of the spatial but not motoric representation of motor sequence memory.

Motor sequence learning is known to rely on more than a single process. As the skill develops with practice, two different representations of the sequence are formed: a goal representation built under spatial allocentric coordinates and a movement representation mediated through egocentric motor coordinates. This study aimed to explore the influence of daytime sleep (nap) on consolidation of these two representations. Through the manipulation of an explicit finger sequence learning task and a transfer protocol, we show that both allocentric (spatial) and egocentric (motor) representations of the sequence can be isolated after initial training. Our results also demonstrate that nap favors the emergence of offline gains in performance for the allocentric, but not the egocentric representation, even after accounting for fatigue effects. Furthermore, sleep-dependent gains in performance observed for the allocentric representation are correlated with spindle density during non-rapid eye movement (NREM) sleep of the post-training nap. In contrast, performance on the egocentric representation is only maintained, but not improved, regardless of the sleep/wake condition. These results suggest that motor sequence memory acquisition and consolidation involve distinct mechanisms that rely on sleep (and specifically, spindle) or simple passage of time, depending respectively on whether the sequence is performed under allocentric or egocentric coordinates.

Validating an automated sleep spindle detection algorithm using an individualized approach.

The goal of the current investigation was to develop a systematic method to validate the accuracy of an automated method of sleep spindle detection that takes into consideration individual differences in spindle amplitude. The benchmarking approach used here could be employed more generally to validate automated spindle scoring from other detection algorithms. In a sample of Stage 2 sleep from 10 healthy young subjects, spindles were identified both manually and automatically. The minimum amplitude threshold used by the prana® (PhiTools, Strasbourg, France) software spindle detection algorithm to identify a spindle was subject‐specific and determined based upon each subject’s mean peak spindle amplitude. Overall sensitivity and specificity values were 98.96 and 88.49%, respectively, when compared to manual scoring. Selecting individual amplitude thresholds for spindle detection based on systematic benchmarking data may validate automated spindle detection methods and improve reproducibility of experimental results. Given that interindividual differences are accounted for, we feel that automatic spindle detection provides an accurate and efficient alternative approach for detecting sleep spindles.

Age Differences in the Variability and Distribution of Sleep Spindle and Rapid Eye Movement Densities

The present study had two main objectives. The first objective was to compare the sleep architecture of young and older adults, with an emphasis on sleep spindle density and REM density. The second objective was to examine two aspects of age differences that have not been considered in previous studies: age differences in the variability of sleep measures as well as the magnitude of age differences in phasic events across the distribution of values (i.e., at each decile rather than a single measure of location such as the mean or median. A total of 24 young (mean age = 20.75±1.78 years) and 24 older (mean age = 71.17±6.15 years) adults underwent in-home polysomnography. Whole-night spindle density was significantly higher in young adults than older adults. The two age groups did not differ significantly in whole-night REM density, although significant increases in REM density across the night were observed in both age groups. These results suggest that spindle density is more affected by age than REM density. Although age differences were observed in the degree of absolute variability (older adults had significantly larger variances than young adults for sleep efficiency and time spent awake after sleep onset), a similar pattern was also observed within the two age groups: the four sleep measures with the lowest degrees of relative variability were the same and included time spent in REM and Stage 2 sleep, total sleep time, and sleep efficiency. The distributional analysis of age differences in sleep spindle density revealed that the largest age differences were initially observed in the middle of the distributions, but as the night progressed, they were seen at the upper end of the distributions. The results reported here have potential implications for the causes and functional implications of age-related changes in sleep architecture.

Expert and crowd-sourced validation of an individualized sleep spindle detection method employing complex demodulation and individualized normalization

A spindle detection method was developed that: (1) extracts the signal of interest (i.e., spindle-related phasic changes in sigma) relative to ongoing “background” sigma activity using complex demodulation, (2) accounts for variations of spindle characteristics across the night, scalp derivations and between individuals, and (3) employs a minimum number of sometimes arbitrary, user-defined parameters. Complex demodulation was used to extract instantaneous power in the spindle band. To account for intra- and inter-individual differences, the signal was z-score transformed using a 60 s sliding window, per channel, over the course of the recording. Spindle events were detected with a z-score threshold corresponding to a low probability (e.g., 99th percentile). Spindle characteristics, such as amplitude, duration and oscillatory frequency, were derived for each individual spindle following detection, which permits spindles to be subsequently and flexibly categorized as slow or fast spindles from a single detection pass. Spindles were automatically detected in 15 young healthy subjects. Two experts manually identified spindles from C3 during Stage 2 sleep, from each recording; one employing conventional guidelines, and the other, identifying spindles with the aid of a sigma (11–16 Hz) filtered channel. These spindles were then compared between raters and to the automated detection to identify the presence of true positives, true negatives, false positives and false negatives. This method of automated spindle detection resolves or avoids many of the limitations that complicate automated spindle detection, and performs well compared to a group of non-experts, and importantly, has good external validity with respect to the extant literature in terms of the characteristics of automatically detected spindles.

Sleep spindles and intellectual ability: Epiphenomenon or directly related?

Sleep spindles—short, phasic, oscillatory bursts of activity that characterize non-rapid eye movement sleep—are one of the only electrophysiological oscillations identified as a biological marker of human intelligence (e.g., cognitive abilities commonly assessed using intelligence quotient tests). However, spindles are also important for sleep maintenance and are modulated by circadian factors. Thus, the possibility remains that the relationship between spindles and intelligence quotient may be an epiphenomenon of a putative relationship between good quality sleep and cognitive ability or perhaps modulated by circadian factors such as morningness–eveningness tendencies. We sought to ascertain whether spindles are directly or indirectly related to cognitive abilities using mediation analysis. Here, we show that fast (13.5–16 Hz) parietal but not slow (11–13.5 Hz) frontal spindles in both non-rapid eye movement stage 2 sleep and slow wave sleep are directly related to reasoning abilities (i.e., cognitive abilities that support “fluid intelligence,” such as the capacity to identify complex patterns and relationships and the use of logic to solve novel problems) but not verbal abilities (i.e., cognitive abilities that support “crystalized intelligence”; accumulated knowledge and experience) or cognitive abilities that support STM (i.e., the capacity to briefly maintain information in an available state). The relationship between fast spindles and reasoning abilities is independent of the indicators of sleep maintenance and circadian chronotype, thus suggesting that spindles are indeed a biological marker of cognitive abilities and can serve as a window to further explore the physiological and biological substrates that give rise to human intelligence.

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Sleep facilitates the consolidation (i.e., enhancement) of simple, explicit (i.e., conscious) motor sequence learning (MSL). MSL can be dissociated into egocentric (i.e., motor) or allocentric (i.e., spatial) frames of reference. The consolidation of the allocentric memory representation is sleep-dependent, whereas the egocentric consolidation process is independent of sleep or wake for explicit MSL. However, it remains unclear the extent to which sleep contributes to the consolidation of implicit (i.e., unconscious) MSL, nor is it known what aspects of the memory representation (egocentric, allocentric) are consolidated by sleep. Here, we investigated the extent to which sleep is involved in consolidating implicit MSL, specifically, whether the egocentric or the allocentric cognitive representations of a learned sequence are enhanced by sleep, and whether these changes support the development of explicit sequence knowledge across sleep but not wake. Our results indicate that egocentric and allocentric representations can be behaviorally dissociated for implicit MSL. Neither representation was preferentially enhanced across sleep nor were developments of explicit awareness observed. However, after a 1-wk interval performance enhancement was observed in the egocentric representation. Taken together, these results suggest that like explicit MSL, implicit MSL has dissociable allocentric and egocentric representations, but unlike explicit sequence learning, implicit egocentric and allocentric memory consolidation is independent of sleep, and the time-course of consolidation differs significantly.

Does sleep facilitate the consolidation of allocentric or egocentric representations of implicitly learned visual-motor sequence learning?

Sleep facilitates the consolidation (i.e., enhancement) of simple, explicit (i.e., conscious) motor sequence learning (MSL). MSL can be dissociated into egocentric (i.e., motor) or allocentric (i.e., spatial) frames of reference. The consolidation of the allocentric memory representation is sleep-dependent, whereas the egocentric consolidation process is independent of sleep or wake for explicit MSL. However, it remains unclear the extent to which sleep contributes to the consolidation of implicit (i.e., unconscious) MSL, nor is it known what aspects of the memory representation (egocentric, allocentric) are consolidated by sleep. Here, we investigated the extent to which sleep is involved in consolidating implicit MSL, specifically, whether the egocentric or the allocentric cognitive representations of a learned sequence are enhanced by sleep, and whether these changes support the development of explicit sequence knowledge across sleep but not wake. Our results indicate that egocentric and allocentric representations can be behaviorally dissociated for implicit MSL. Neither representation was preferentially enhanced across sleep nor were developments of explicit awareness observed. However, after a 1-wk interval performance enhancement was observed in the egocentric representation. Taken together, these results suggest that like explicit MSL, implicit MSL has dissociable allocentric and egocentric representations, but unlike explicit sequence learning, implicit egocentric and allocentric memory consolidation is independent of sleep, and the time-course of consolidation differs significantly.

A Novel Approach to Dream Content Analysis Reveals Links Between Learning-Related Dream Incorporation and Cognitive Abilities

Can dreams reveal insight into our cognitive abilities and aptitudes (i.e., “human intelligence”)? The relationship between dream production and trait-like cognitive abilities is the foundation of several long-standing theories on the neurocognitive and cognitive-psychological basis of dreaming. However, direct experimental evidence is sparse and remains contentious. On the other hand, recent research has provided compelling evidence demonstrating a link between dream content and new learning, suggesting that dreams reflect memory processing during sleep. It remains to be investigated whether the extent of learning-related dream incorporation (i.e., the semantic similarity between waking experiences and dream content) is related to inter-individual differences in cognitive abilities. The relationship between pre–post sleep memory performance improvements and learning-related dream incorporation was investigated (N = 24) to determine if this relationship could be explained by inter-individual differences in intellectual abilities (e.g., reasoning, short term memory (STM), and verbal abilities). The extent of dream incorporation using a novel and objective method of dream content analysis, employed a computational linguistic approach to measure the semantic relatedness between verbal reports describing the experience on a spatial (e.g., maze navigation) or a motor memory task (e.g., tennis simulator) with subsequent hypnagogic reverie dream reports and waking “daydream” reports, obtained during a daytime nap opportunity. Consistent with previous studies, the extent to which something new was learned was related (r = 0.47) to how richly these novel experiences were incorporated into the content of dreams. This was significant for early (the first 4 dream reports) but not late dreams (the last 4 dream reports). Notably, here, we show for the first time that the extent of this incorporation for early dreams was related (r = 0.41) to inter-individual differences in reasoning abilities. On the other hand, late dream incorporation was related (r = 0.46) to inter-individual differences in verbal abilities. There was no relationship between performance improvements and intellectual abilities, and thus, inter-individual differences in cognitive abilities did not mediate the relationship between performance improvements and dream incorporation; suggesting a direct relationship between reasoning abilities and dream incorporation. This study provides the first evidence that learning-related dream production is related to inter-individual differences in cognitive abilities.

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Sleep facilitates the consolidation (i.e., enhancement) of simple, explicit (i.e., conscious) motor sequence learning (MSL). MSL can be dissociated into egocentric (i.e., motor) or allocentric (i.e., spatial) frames of reference. The consolidation of the allocentric memory representation is sleep-dependent, whereas the egocentric consolidation process is independent of sleep or wake for explicit MSL. However, it remains unclear the extent to which sleep contributes to the consolidation of implicit (i.e., unconscious) MSL, nor is it known what aspects of the memory representation (egocentric, allocentric) are consolidated by sleep. Here, we investigated the extent to which sleep is involved in consolidating implicit MSL, specifically, whether the egocentric or the allocentric cognitive representations of a learned sequence are enhanced by sleep, and whether these changes support the development of explicit sequence knowledge across sleep but not wake. Our results indicate that egocentric and allocentric representations can be behaviorally dissociated for implicit MSL. Neither representation was preferentially enhanced across sleep nor were developments of explicit awareness observed. However, after a 1-wk interval performance enhancement was observed in the egocentric representation. Taken together, these results suggest that like explicit MSL, implicit MSL has dissociable allocentric and egocentric representations, but unlike explicit sequence learning, implicit egocentric and allocentric memory consolidation is independent of sleep, and the time-course of consolidation differs significantly.