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Learning-dependent changes in sleep spindles and Stage 2 sleep
Abstract
It has become increasingly clear that sleep is necessary for efficient memory consolidation. Recently, it has been found that Stage 2 sleep disruption impairs procedural memory performance, and that memory performance is correlated with the duration of Stage 2 sleep; but the mechanisms involved in synaptic plasticity for procedural memory during sleep have not been identified. The present study examined the learning-dependent changes in sleep, including Stage 2 sleep spindles. Following an intense period of simple motor procedural learning, the duration of Stage 2 sleep and spindle density increased. There were no changes observed in the duration of any other stage of sleep or in the density of rapid eye movements. These findings support the hypothesis that sleep spindles are involved in the off-line reprocessing of simple motor procedural memory during Stage 2 sleep.
... Until now, only a few studies have investigated how learning a sports motor skill influences the architecture of the following night's sleep [5][6][7][8]. Using a multitask research strategy (pursuit rotor, simple tracing task, ball-and-cup game, and the operation game), Fogel and Smith [6] found learning-dependent changes in stage 2 sleep duration and sleep spindles during stage 2 sleep for the experimental but not for the control group while no other changes in sleep architecture were observed [6]. ...
... Until now, only a few studies have investigated how learning a sports motor skill influences the architecture of the following night's sleep [5][6][7][8]. Using a multitask research strategy (pursuit rotor, simple tracing task, ball-and-cup game, and the operation game), Fogel and Smith [6] found learning-dependent changes in stage 2 sleep duration and sleep spindles during stage 2 sleep for the experimental but not for the control group while no other changes in sleep architecture were observed [6]. However, since a multiple task strategy was used, it is impossible to dissect the influence of the different tasks used in Life 2024, 14, 203 2 of 10 this study. ...
... Until now, only a few studies have investigated how learning a sports motor skill influences the architecture of the following night's sleep [5][6][7][8]. Using a multitask research strategy (pursuit rotor, simple tracing task, ball-and-cup game, and the operation game), Fogel and Smith [6] found learning-dependent changes in stage 2 sleep duration and sleep spindles during stage 2 sleep for the experimental but not for the control group while no other changes in sleep architecture were observed [6]. However, since a multiple task strategy was used, it is impossible to dissect the influence of the different tasks used in Life 2024, 14, 203 2 of 10 this study. ...
Previous research has shown that learning procedural tasks enhances REM sleep the following night. Here, we investigate whether complex motor learning affects sleep architecture. An experiment in which twenty-two subjects either learned a motor task (trampolining) or engaged in a control task (ergometer) was carried out in a balanced within-group design. After an initial laboratory adaptation night, two experimental nights were consecutive. The results indicate that learning a motor task had an effect on REM sleep parameters and, therefore, support the hypothesis that learning a procedural skill is related to an increase in REM sleep parameters. However, the statistical effect on REM sleep is smaller than found in previous studies. One might speculate that the motor learning was not intense enough compared to other studies. For sports practice, the results suggest that REM sleep, which is particularly rich in the morning, plays an important role in motor memory consolidation. Thus, this phase should not be interrupted after complex motor skill learning sessions. In future studies, other motor tasks should be applied.
... Accumulating evidence suggests that sleep does not merely passively protect memories from interference and decay, but actively fosters their consolidation. Thus, longer sleep times lead to greater memory benefits (Diekelmann et al., 2012;Schönauer et al., 2014), the occurrence of sleep-specific brain oscillatory activity has been linked with memory consolidation (Fogel and Smith, 2006;Gais et al., 2002;Girardeau et al., 2009;Marshall et al., 2006;Perrault et al., 2019;Schmidt et al., 2006), and it has been discovered that learning-related brain activity is reactivated during non-rapid eye movement (NREM) sleep (Peigneux et al., 2003;Schönauer et al., 2017;Schreiner et al., 2021;Wilson and McNaughton, 1994). Sleep-dependent memory reactivation, in particular, is a promising candidate mechanism to underlie behavioral benefits of sleep on memory performance (Antony et al., 2012;Rasch et al., 2007;Rudoy et al., 2009). ...
... For instance, several studies showed that sleep spindles strengthen memory for a broad range of declarative tasks including wordlist and vocabulary learning (Blaskovich et al., 2017;Gais et al., 2002;Schabus et al., 2004;Schmidt et al., 2006;Studte et al., 2015;Tamminen et al., 2010), but also visual memory for pictures (Cox et al., 2012;Ward et al., 2014), and visuospatial tasks (Clemens et al., 2006;Wilhelm et al., 2011). Likewise, spindles have been shown to facilitate procedural memory, such as finger tapping, motor sequential learning, and motor adaptation (Barakat et al., 2011a;Boutin et al., 2018;Fogel and Smith, 2006;Nishida and Walker, 2007;Simor et al., 2019;Thürer et al., 2018) and mirror tracing (Holz et al., 2012;Tamaki et al., 2008;van Schalkwijk et al., 2019). However, recent findings and reviews have started to question the robustness, replicability, and generalizability of some of these findings (Ackermann et al., 2015;Cordi and Rasch, 2021). ...
... As a second control analysis, we excluded studies with the largest sample size (Ackermann et al., 2015) and the smallest sample size (Fogel and Smith, 2006) and also on studies that reported a substantially larger number of estimates than the average (Blaskovich et al., 2017;Thürer et al., 2018) and repeated the meta-analysis for the association between sleep spindles and memory consolidation. ...
Accumulating evidence suggests a central role for sleep spindles in the consolidation of new memories. However, no meta-analysis of the association between sleep spindles and memory performance has been conducted so far. Here, we report meta-analytical evidence for spindle-memory associations and investigate how multiple factors, including memory type, spindle type, spindle characteristics, and EEG topography affect this relationship. The literature search yielded 53 studies reporting 1427 effect sizes, resulting in a small to moderate effect for the average association. We further found that spindle-memory associations were significantly stronger for procedural memory than for declarative memory. Neither spindle types nor EEG scalp topography had an impact on the strength of the spindle-memory relation, but we observed a distinct functional role of global and fast sleep spindles, especially for procedural memory. We also found a moderation effect of spindle characteristics, with power showing the largest effect sizes. Collectively, our findings suggest that sleep spindles are involved in learning, thereby representing a general physiological mechanism for memory consolidation.
... Il existe une variété d'habiletés motrices découlant de l'apprentissage moteur. Ainsi, une multitude de tâches sont utilisées, en laboratoire, pour caractériser ces habiletés et étudier les différents aspects de l'apprentissage moteur : i) des tâches sensorimotrices ( Figure 1A), dans le cas spécifique de l'adaptation motrice, comme par exemple un mouvement de pointage avec déviation visuelle de la trajectoire (Taylor et al., 2014), ii) des tâches balistiques ( Figure 1B), comprenant un unique mouvement discret comme une simple adduction du pouce (Ruffino et al., 2019), iii) des tâches de mouvement continu ( Figure 1C), comme la poursuite d'une cible en mouvement avec un stylet (Fogel and Smith, 2006), iv) des tâches de séquence motrice ( Figure 1D), constituées d'un enchaînement d'actions discrètes formant un ensemble d'actions unifiées (Hikosaka et al., 1999). Ces dernières, qui constituent des habiletés de type 'sériel', sont au coeur de la plupart des comportements moteurs quotidiens comme l'utilisation d'un ordinateur, le fait de faire ses lacets ou encore passer une vitesse en voiture. ...
... Bien que l'analyse du sommeil se réalise par polysomnographie, permettant l'enregistrement de l'activité cérébrale, musculaire et oculaire, la qualité et la durée du sommeil peuvent être également évaluées subjectivement avec des questionnaires autoadministrés comme le Pittsburgh Sleep Quality Index (Buysse et al., 1989). De nombreuses études ont rapporté que le sommeil NREM stade 2 contribue à la consolidation des performances (Kuriyama et al., 2004;Fogel and Smith, 2006;Laventure et al., 2016), montrant une corrélation de la durée de ce stade avec la quantité d'amélioration 'sans pratique'. De plus, l'apprentissage moteur augmente la densité et la durée des fuseaux de sommeil (spindles en anglais) qui composent la phase NREM stade 2 lors du sommeil qui suit la pratique. ...
While the time of day significantly affects motor and mental performance, its influence on motor learning has not yet been elucidated. In this thesis, we conducted a series of experiments using a finger-tapping task to investigate the effects of time of day on two processes of motor learning: acquisition (i.e. skill improvement immediately after a training-session) and consolidation (i.e. skill retention after the passage of time and/or a night of sleep).
In the 1rt study, we showed that the time of day influenced the consolidation, but not the acquisition. Specifically, while we observed deterioration and stabilization of skill 24 hours after morning and afternoon training, respectively, we found a better consolidation 24 hours after evening training with a subsequent improvement in skill. These results highlight the crucial role of sleep in consolidating motor skills acquired beforehand.
In the 2nd study, comprising four experiments, we explored the question of the fragility of memory after morning training. Our initial results showed that memory was more fragile in the morning than in the afternoon, with deterioration occurring within 5 hours of practice only during morning training. In the subsequent two experiments, we investigated two types of interference, motor and cognitive, and found that memory was more susceptible to motor interference in the morning. Furthermore, the deterioration in performance seemed to arise from a conflict between the declarative and procedural memory systems required for our task. Additionally, we provided neurophysiological evidence for these different consolidations by demonstrating a different modulation of corticospinal excitability immediately post-practice, which varied depending on the time of day.
In the 3rd study, we emphasized the importance of daily activity in consolidation. We observed that engaging in motor activity before morning practice prevented performance deterioration during the day, whereas remaining inactive until afternoon practice resulted in worsened performance. We suggested that, while sleep is advantageous for the consolidation of previously acquired skills, it may hinder the consolidation of subsequent learning due to the inactivity it promotes.
In our final 4th study, we showed that the time of day also influenced consolidation following a mental practice. Although the acquisition and consolidation processes differ between physical and mental practice, we found that consolidation was also better in the afternoon than in the morning.
Overall, the results of this thesis underscore the importance of considering the time of day and the activities undertaken before learning when designing optimal training programs and rehabilitation protocols.
... With increasing age, spindle density, duration and amplitude are significantly reduced [13][14][15] . There is growing consensus that non-rapid eye movement (NREM) sleep 16 and spindles in particular, are necessary for the optimal consolidation of procedural memory [17][18][19][20][21][22][23][24][25] . ...
... However, recent studies have found that older adults do not derive the same benefit from sleep for procedural memory consolidation as compared to young adults, despite a normal rate of initial learning 4,8,9,[43][44][45][46] . Furthermore, learning-related increases in density, duration and amplitude of spindles are observed following intense periods of procedural motor skills learning, with the change in several of these spindle characteristics being correlated with offline gains in memory performance [17][18][19]21,23,24,47 . Two recent studies have shown that spindles may also be related to the consolidation of procedural skills that involve cognitively complex problem-solving 30,31 , however, evidence is very limited and it is not known how this relationship may be impacted by age. ...
We examined how aging affects the role of sleep in the consolidation of newly learned cognitive strategies. Forty healthy young adults (20-35 years) and 30 healthy older adults (60-85 years) were included. Participants were trained on the Tower of Hanoi (ToH) task, then, half of each age group were assigned to either the 90-minute nap condition, or stayed awake, before retesting. The temporal co-occurrence between slow-waves (SW) and sleep spindles (SP) during NREM sleep was examined as a function of age in relation to memory consolidation of problem-solving skills. We found that despite intact learning, older adults derived a reduced benefit of sleep for problem-solving skills relative to younger adults. As expected, the percentage of coupled spindles was lower in older compared to younger individuals from control to testing sessions. Furthermore, coupled spindles in young adults were more strongly coupled to the SW upstate compared to older individuals. Coupled spindles in older individuals were lower in amplitude (mean area under curve; μV) compared to the young group. Lastly, there was a significant relationship between offline gains in accuracy on the ToH and percent change of spindles coupled to the upstate of the slow wave in older, but not younger adults. Multiple regression revealed that age accounted for differences in offline gains in accuracy, as did spindle coupling during the upstate. These results suggest that with aging, spindle-slow wave coupling decreases. However, the degree of the preservation of coupling with age correlates with the extent of problem-solving skill consolidation during sleep.
... Sleep spindles, one of the hallmarks of N2 sleep, are transient waxing and waning oscillations, classified into posteriorly distributed fast spindles (13)(14)(15) and anteriorly distributed slow spindles (11)(12)(13) Hz; [13][14][15][16]). The functional role of sleep spindles involves sleep-related memory consolidation and sleep-protection mechanisms [17][18][19]-on the one hand, sleep spindles facilitate memory consolidation and are associated with improved memory performance [20][21][22]; on the other hand, individuals with higher spindle density were less susceptible to interference from sounds or other types of environmental stimuli [7,23], as spindles hinder the transmission of external stimuli from the thalamus to the cortex [24]. ...
... Most of these previous studies investigating the relationship between sleep and cognitive activity have focused on a specific cognitive domain, usually memory, such as declarative memory [1] or procedural memory [21,25]. The present study employed an integrated cognitive activity consisting of several cognitive domains (i.e., working memory, inhibition control, cognitive flexibility and associative memory), which enhanced the ecological validity of the tasks. ...
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.
... In addition, a sleep-dependance of motor learning has been documented by neuronal activity patterns occurring in specific sleep phases, such as sleep spindles during the non-Rapid Eye Movement (REM) sleep (stage 2) and Slow Wave Sleep 22 . These electrophysiological events have been considered as associated with sleep-dependent motor memory consolidation 23,24 . ...
... Sleep-dependent gains in motor performance after a training have been reported to occur through an offline replay of neural activity, able to induce a memory consolidation of newly acquired movement patterns 21 . This reactivation process is documented by specific EEG markers (e.g., sleep spindles) and involves the cortico-striato-cerebellar network, where the degree of reactivation seems to be related to ameliorations in terms of motor performance 23 . Previous studies demonstrated benefits induced by AO/AO + MI in terms of manual dexterity 13,15,27,28 . ...
The systematic observation and imagination of actions promotes acquisition of motor skills. Furthermore, studies demonstrated that early sleep after practice enhances motor learning through an offline stabilization process. Here, we investigated behavioral effects and neurodynamical correlates of early sleep after action observation and motor imagery training (AO + MI-training) on motor learning in terms of manual dexterity. Forty-five healthy participants were randomized into three groups receiving a 3 week intervention consisting of AO + MI-training immediately before sleeping or AO + MI-training at least 12 h before sleeping or a control stimulation. AO + MI-training implied the observation and motor imagery of transitive manual dexterity tasks, whereas the control stimulation consisted of landscape video-clips observation. Manual dexterity was assessed using functional tests, kinematic and neurophysiological outcomes before and after the training and at 1-month follow-up. AO + MI-training improved manual dexterity, but subjects performing AO + MI-training followed by early sleep had significantly larger improvements than those undergoing the same training at least 12 h before sleeping. Behavioral findings were supported by neurodynamical correlates during motor performance and additional sleep-dependent benefits were also detected at 1 month follow-up. These findings introduce a new approach to enhance the acquisition of new motor skills or facilitate recovery in patients with motor impairments.
... Beyond being markers of NREM sleep, SSs seem to be fundamental in determining sleep architecture (Fernandez and Lüthi, 2020;Purcell et al., 2017). In addition, the systems consolidation theory implies an active role of NREM sleep in the consolidation of both declarative and non-declarative memory including also the pivotal role of SSs in that mechanism Fogel and Smith, 2006;Gais et al., 2002;Genzel et al., 2009;Morin et al., 2008). Furthermore, several studies support the hypothesis that sleep spindle amplitude and/or density index correlate with general cognitive ability/intelligence in healthy human subjects (Bódizs et al., 2005;Ujma et al., 2020). ...
... The role of NREM sleep, particularly slow-wave sleep in declarative memory reactivation and consolidation has already been confirmed (Rasch and Born, 2013). In addition, the correlation between SS activity and both declarative and non-declarative memory processes (including learning and general cognitive abilities) has also been evidenced Fogel and Smith, 2006;Gais et al., 2002;Genzel et al., 2009;Morin et al., 2008). The function of SS is not fully understood, while it seems essential in cognition and NREM sleep microstructure (Fernandez and Lüthi, 2020;Purcell et al., 2017). ...
Study objectives
Sleep disturbances and altered sleep macrostructure are common in Parkinson's disease (PD). Few studies have addressed the changes in sleep spindle (SS) properties in this movement disorder so far. SS seem to be fundamental of both sleep architecture and memory consolidation. The aim of our comparative study was to investigate the changes of SS characteristics in PD, and reveal the relationship between SS properties and cognitive function.
Methods
We investigated 20 PD patients and 18 age-matched controls. All participants underwent a 24-hour-long polygraphic EEG recording after extensive clinical investigation. We detected slow and fast SS properties automatically using individual adjusting method (IAM). The data were statistically evaluated.
Results
We found significantly lower fast spindle amplitude in PD comparing with controls. We did not find significant differences in SS densities, duration and oscillatory frequency between the groups. We detected significant positive correlation between fast SS amplitude and memory in PD, and between fast SS density and retrograde memory in controls. The total Addenbrooke's cognitive score correlated negatively with slow SS density and duration in controls.
Conclusions
By the time clinical diagnosis of PD is established, the pathological process is already spreading. Changes in sleep macrostructure and SS properties might become a useful biomarker of the neurodegenerative process in PD. In addition, decreased fast SS amplitude might predict further cognitive deterioration and indicate early involvement of corresponding cortical area. Our study results strengthen the importance of EEG examination in PD, and the use of IAM method in SS analysis.
... This study was not designed to distinguish the directionality of the relationship between the learning episode itself and interindividual characteristics in sleep physiology. On the one hand, learning manipulations can induce changes in sleep spindles and slow oscillations (SOs) [61][62][63] . On the other hand, the Baycrest Tour was-by design-just one event in the participants' day before sleep. ...
Sleep is thought to play a critical role in the retention of memory for past experiences (episodic memory), reducing the rate of forgetting compared with wakefulness. Yet it remains unclear whether and how sleep actively transforms the way we remember multidimensional real-world experiences, and how such memory transformation unfolds over the days, months and years that follow. In an exception to the law of forgetting, we show that sleep actively and selectively improves the accuracy of memory for a one-time, real-world experience (an art tour)—specifically boosting memory for the order of tour items (sequential associations) versus perceptual details from the tour (featural associations). This above-baseline boost in sequence memory was not evident after a matched period of wakefulness. Moreover, the preferential retention of sequence relative to featural memory observed after a night’s sleep grew over time up to 1 year post-encoding. Finally, overnight polysomnography showed that sleep-related memory enhancement was associated with the duration and neurophysiological hallmarks of slow-wave sleep previously linked to sequential neural replay, particularly spindle–slow wave coupling. These results suggest that sleep serves a crucial and selective role in enhancing sequential organization in our memory for past events at the expense of perceptual details, linking sleep-related neural mechanisms to the days-to-years-long transformation of memory for complex real-life experiences.
... myös esim. Fogel & Smith, 2006). Sensomotorisen tehtävän oppiminen taas johti lisääntyneeseen hidasaaltouneen sekä unisukkuloiden suurempaan amplitudiin (Yordanova, Kolev, Bruns, Kirov & Verleger, 2017) verrattuna aiemmin mitattuun yöuneen, jota ei edeltänyt oppiminen. ...
Tässä katsauksessa perehdytään unen rooliin oppimisessa ja muistissa keskittyen erityisesti muistijälkien lujittamiseen. Ihmisen ja useiden muiden nisäkkäiden vireystila vaihtelee valon säätelemää vuorokausirytmiä noudattaen. Ihmisellä yöunen aikana univaiheet toistuvat jaksoittaisesti siten, että perusuni painottuu alkuyöhön ja vilkeuni loppuyöhön. Verrattuna valveeseen, uni parantaa juuri opitun muistiin painamista. Perusunen aikana aivoissa kertautuvat valveen aikana muodostuneet hermostolliset aktivaatiokaavat. Tämän prosessin on tulkittu heijastavan tiedon tallentamista pitkäkestoiseen muistiin aivokuoren ja alempien aivorakenteiden, kuten talamuksen ja hippokampuksen, muodostamiin hajautettuihin hermostollisiin verkostoihin. Vilkeunen roolista aivorakenteiden muodostamien verkostojen tasolla tapahtuvan muistiinpainamisen mekanismissa ei ole vielä selvyyttä. Vaikuttaa kuitenkin siltä, että myös vilkeuni on tärkeää oppimiselle, sillä sen määrä ja suhteellinen osuus unesta kasvaa oppimistilanteiden jälkeen, mikä heijastuu seuraavan valvetilan aikana mitattuihin muistisuorituksiin. Uni vahvistaa sekä taitoja että tietoja ja tapahtumia koskevien muistijälkien lujittumista. On myös mahdollista, että unen aikana esitetyistä ulkoisista ärsykkeistä voi oppia uutta ja unen aikana esitetyt muistutukset valveen aikana opitusta vahvistavat muistiin painamista. Unen merkitys oppimiselle ja muistille on siis ensiarvoisen tärkeä ja sitä voidaan hyödyntää oppimisen tehostamisessa.
... Spindle-density and the length of phase 2 NREM sleep increased after learning, evidencing the involvement of those oscillations in the memory-process. The increase of spindling correlated with after-sleep performance and spindling was shown to be participating in the protection of engrams during memory-consolidation. [29][30][31] Evidence linking MTLE with the mediotemporal-hippocampal network. ...
We aimed to provide a comprehensive review of the system epilepsy concept and adapt its principles to major epilepsy syndromes. We present our views on epileptogenesis: NREM sleep and especially sleep homeostatic plasticity are essential contributors of the epileptic transformation, upgrading and derailing normal brain networks. We follow the common process and specific features epileptic transformation in major epilepsies.
... One of the key sleep features involved in the consolidation of memories, and in particular memory for motor skills, is the sleep spindle; brief bursts of oscillatory activity (~11-16 Hz) that characterize and predominate non-rapid eye movement (NREM) sleep. In fact, several studies have demonstrated learning-dependent increases in sleep spindle activity following motor skill learning (MSL) [10][11][12][13] . Spindles have also been found to be correlated with both behavioral improvements 14 and sleep-dependent changes of activity in brain structures which support motor skills 15,16 . ...
Sleep is essential for the optimal consolidation of newly acquired memories. This study examines the neurophysiological processes underlying memory consolidation during sleep, via reactivation. Here, we investigated the impact of slow wave - spindle (SW-SP) coupling on regionally-task-specific brain reactivations following motor sequence learning. Utilizing simultaneous EEG-fMRI during sleep, our findings revealed that memory reactivation occured time-locked to coupled SW-SP complexes, and specifically in areas critical for motor sequence learning. Notably, these reactivations were confined to the hemisphere actively involved in learning the task. This regional specificity highlights a precise and targeted neural mechanism, underscoring the crucial role of SW-SP coupling. In addition, we observed double-dissociation whereby primary sensory areas were recruited time-locked to uncoupled spindles; suggesting a role for uncoupled spindles in sleep maintenance. These findings advance our understanding the functional significance of SW-SP coupling for enhancing memory in a regionally-specific manner, that is functionally dissociable from uncoupled spindles.
... There is consistent evidence for the involvement of NREM2 sleep spindles in motor (Fogel, Smith, 2006;Nishida, Walker, 2007) and declarative (Genzel et al., 2009) learning. It is also known that sensory stimulation during NREM sleep can trigger sleep spindles (Sato et al., 2007;Andrillon et al., 2017), leading to an increase in their density (Landsness et al., 2009) and suggesting a possible stimulatory rather than inhibitory effect on memory consolidation of such sleep interference. ...
Establishing well-defined relationships between sleep features and memory consolidation is essential in comprehending the pathophysiology of cognitive decline commonly seen in patients with insomnia, depression, and other sleep-disrupting conditions.
Twenty-eight volunteers participated in two experimental sessions: a session with selective SWS suppression during one night and a session with undisturbed night sleep (as a control condition). Fifteen of them also participated in a third session with REM suppression. Suppression was achieved by presenting an acoustic tone. In the evening and the morning, the participants completed procedural and declarative memory tasks and the Psychomotor vigilance task (PVT). Heart rate variability analysis and salivary cortisol were used to control possible stress reactions on sleep interference.
SWS and REM suppression led to more than 50 percent reduction in amount of these stages. Neither vigilance nor memory consolidation was impaired after SWS or REM suppression. Unexpectedly, a beneficial effect of selective SWS suppression on PVT performance was found. Similarly, after a night with SWS suppression, the overnight improvement in procedural skills was higher than after a night with REM suppression and after a night with undisturbed sleep.
Our data brings into question the extent to which SWS and REM are truly necessary for effective memory consolidation to proceed. Moreover, SWS suppression may even improve the performance of some tasks, possibly by reducing sleep inertia associated with undisturbed sleep.
Highlights
Our data brings into question the extent to which SWS and REM are truly necessary for effective memory consolidation to proceed.
Provided that sleep disturbances do not cause stress, half the usual amount of SWS or REM is sufficient for procedural and declarative memory consolidation.
Moreover, SWS suppression may even improve the performance of psychomotor vigilance task and finger sequence tapping task, possibly by reducing sleep inertia associated with undisturbed night sleep.
... Certain features of sleep seem to be highly correlated with trait-like individual differences in cognitive abilities 144 . For example, particularly strong relationships have been identified between the density of fast frontal sleep spindles and general mental ability 150 , the amplitude of fast parietal spindles and reasoning abilities 151,152 , and the duration of stage 2 sleep and spindle density following procedural learning 153 . These cognitive abilities are partly intertwined with learning and memory functions. ...
Understanding the complex relationship between sleep and memory consolidation is a major challenge in cognitive neuroscience and psychology. Many studies suggest that sleep triggers off-line memory processes, resulting in less forgetting of declarative memory and performance stabilization in non-declarative memory. However, the role of sleep in human memory consolidation is still under considerable debate, and numerous contradictory and non-replicable findings have been reported. Methodological issues related to experimental designs, task characteristics and measurements, and data-analysis practices all influence the effects that are observed and their interpretation. In this Perspective, we review methodological issues in sleep and memory studies and suggest constructive solutions to address them. We believe that implementing these solutions in future sleep and memory research will substantially advance the field and improve understanding of the specific role of sleep in memory consolidation. Sections
... Hz (Werth et al., 1997). Sleep spindles are important for memory consolidation (for a review, see (Fogel and Smith, 2011;Rasch and Born, 2013) and more global intellectual abilities (Bódizs et al., 2005(Bódizs et al., , 2008Fogel et al., 2007;Fogel and Smith, 2006;Lafortune et al., 2014;Smith, 2001, 2003). Spindles are also important for sleep maintenance and protection (Cote et al., 2000;Dang-Vu et al., 2010;Elton et al., 1997;Schabus et al., 2012;Vyazovskiy et al., 2004). ...
... Sleep spindles are bursts of rhythmic 10-16 Hz activity lasting 0.5-2 s that are the hallmark of stage 2 or "non-Rapid Eye Movement stage 2" (NREM2) sleep [16]. Spindles are thought to play a role in memory consolidation [17][18][19][20][21] and appear to be altered in a wide variety of neuropsychiatric conditions including autism [22], schizophrenia [23][24][25] and neurodegenerative diseases [26][27][28]. Given the importance of these graphoelements, much work has been invested in developing tools for spindle detection and characterization [29]. ...
Background
Sleep spindle activity is commonly estimated by measuring sigma power during stage 2 non-rapid eye movement (NREM2) sleep. However, spindles account for little of the total NREM2 interval and therefore sigma power over the entire interval may be misleading. This study compares derived spindle measures from direct automated spindle detection with those from gross power spectral analyses for the purposes of clinical trial design.
Methods
We estimated spindle activity in a set of 8,440 overnight electroencephalogram (EEG) recordings from 5,793 patients from the Sleep Heart Health Study using both sigma power and direct automated spindle detection. Performance of the two methods was evaluated by determining the sample size required to detect decline in age-related spindle coherence with each method in a simulated clinical trial.
Results
In a simulated clinical trial, sigma power required a sample size of 115 to achieve 95% power to identify age-related changes in sigma coherence, while automated spindle detection required a sample size of only 60.
Conclusions
Measurements of spindle activity utilizing automated spindle detection outperformed conventional sigma power analysis by a wide margin, suggesting that many studies would benefit from incorporation of automated spindle detection. These results further suggest that some previous studies which have failed to detect changes in sigma power or coherence may have failed simply because they were underpowered.
... Our methodology has proved to be a reliable source of EEG data and a basis for meaningful comparisons with other species as demonstrated by a line of different experiments conducted in dogs. For example, it has been shown in dogs that their sleep spectral feautres are predictive of their memory performances 70 and that sleep spindles are associated with better learning 20,71 , similarly to humans 72,73 and rats 74,75 . Different types of learning tasks have also been successfully carried out with wolves in comparative studies (e.g. ...
Sleep research greatly benefits from comparative studies to understand the underlying physiological and environmental factors affecting the different features of sleep, also informing us about the possible evolutionary changes shaping them. Recently, the domestic dog became an exceedingly valuable model species in sleep studies, as the use of non-invasive polysomnography methodologies enables direct comparison with human sleep data. In this study, we applied the same polysomnography protocol to record the sleep of dog’s closest wild relative, the wolf. We measured the sleep of seven captive (six young and one senior), extensively socialized wolves using a fully non-invasive sleep EEG methodology, originally developed for family dogs. We provide the first descriptive analysis of the sleep macrostructure and NREM spectral power density of wolves using a completely non-invasive methodology. For (non-statistical) comparison, we included the same sleep data of similarly aged dogs. Although our sample size was inadequate to perform statistical analyses, we suggest that it may form the basis of an international, multi-site collection of similar samples using our methodology, allowing for generalizable, unbiased conclusions. As we managed to register both macrostructural and spectral sleep data, our procedure appears to be suitable for collecting valid data in other species too, increasing the comparability of non-invasive sleep studies.
... As one of the markers of the second stage of NREM sleep, the sleep spindle, is one of the most important sleep events in the sleep microstructure, and is commonly generated in the thalamus cortex system [2,3]. The density, number and amplitude of spindle activity have been shown to be related to general cognitive ability, sleep disorders, learning and memory [4][5][6][7][8]. Furthermore, spindle activity can be used as one of the indicators to identify patients with a disorder of consciousness (DOC), that is, to identify patients with a minimal consciousness state and an unresponsive syndrome [9]. ...
Sleep spindles are an electroencephalogram (EEG) biomarker of non-rapid eye movement (NREM) sleep and have important implications for clinical diagnosis and prognosis. However, it is challenging to accurately detect sleep spindles due to the complexity of the human brain and the uncertainty of neural mechanisms. To improve the reliability and objectivity of sleep spindle detection and to compensate for the limitations of manual annotation, this study proposes a new automatic detection algorithm based on Matching Pursuit (MP) and Least Squares Boosting (LSBoost), where the automatic sleep spindle detection algorithm can help reduce the visual annotation workload of sleep clinicians. Specifically, MP is a time-frequency analysis method suitable for extracting spindle wave characteristics, which can accurately locate spindle waves on a time-frequency plane. LSBoost is an ensemble learning classification method to deal with unbalanced data. Initially, the MP method is used to search for EEG segments that are possible spindle waves from the filtered raw EEG data. Then, the designed feature segments are thrown into the LSBoost classifier to further identify the real spindles from all candidates and output the final results. The proposed method is verified on the common public dataset DREAMS. The experiment results show that the sensitivity and F1-scores based on the sample-based assessments achieve 68.2% and 55.4%, respectively. Furthermore, the Recall and F1-score based on the event assessments are 83.8% and 70.8%, respectively. These results show that the proposed algorithm is robust to the subject changes in the DREAMS dataset. In addition, it improves the quality of sleep spindle detection, which is expected to assist the manual marking of experts.
... Certain features of sleep (e.g., sleep spindles) appear to be highly correlated with trait-like individual differences in cognitive abilities. Particularly strong relationships have been identified for cognitive abilities related to reasoning, problem-solving, the ability to identify complex patterns and relationships, and the use of logic (i.e., 'fluid intelligence') [141][142][143][144][145] . Since these cognitive abilities are associated with certain features of sleep and with memory functions, they may confound the associations revealed between sleep and memory consolidation. ...
Understanding the complex relationship between sleep and memory is a major challenge in neuroscience. Many studies on memory consolidation in humans suggest that sleep triggers offline memory processes, resulting in less forgetting of declarative memory and performance stabilization in non-declarative memory. However, issues related to non-optimal experimental designs, task characteristics and measurements, and inappropriate data analysis practices can significantly affect the interpretation of the effect of sleep on memory. In this article, we discuss these issues and suggest constructive solutions to address them. We believe that implementing these solutions in future sleep and memory research will significantly advance this field by improving the understanding of the specific role of sleep in memory consolidation.
... A consolidation period of sleep (as compared to wakefulness) after learning new procedural skills, and in particular, skills that require the acquisition of new rules and cognitive strategies, results in performance boosts in speed, accuracy, and insight [1][2][3][4][5][6][7][8][9][10]. This post-learning period of sleep is marked by changes to sleep architecture (e.g. ...
The hallmark eye movement (EM) bursts that occur during Rapid Eye Movement (REM) sleep are markers of consolidation for procedural memory involving novel cognitive strategies and problem-solving skills. Examination of the brain activity associated with EMs during REM sleep might elucidate the processes involved in memory consolidation, and may uncover the functional significance of REM sleep and EMs themselves. Participants performed a REM-dependent, novel procedural problem-solving task (i.e., the Tower of Hanoi; ToH) before and after intervals of either overnight sleep (n=20) or a daytime 8-hour wake period (n=20). In addition, event-related spectral perturbation (ERSP) of the electroencephalogram (EEG) time-locked to EMs occurring either in bursts (i.e., phasic REM), or in isolation (i.e., tonic REM), were compared to sleep on a non-learning control night. ToH improvement was greater following sleep compared to wakefulness. During sleep, frontal-central theta (~2-8 Hz) and central-parietal-occipital sensorimotor rhythm (SMR) activity (~8-16 Hz) time-locked to EMs, were greater on the ToH night vs. control night, and during phasic REM sleep, were both positively correlated with overnight memory improvements. Furthermore, SMR power during tonic REM increased significantly from the control night to ToH night, but was relatively stable from night-to-night during phasic REM. These results suggest that EMs are markers of learning-related increases in theta and SMR during phasic and tonic REM sleep. Phasic and tonic REM sleep may be functionally distinct in terms of their contribution to procedural memory consolidation.
... Certain features of sleep (e.g., sleep spindles) appear to be highly correlated with trait-like individual differences in cognitive abilities. Particularly strong relationships have been identified for cognitive abilities related to reasoning, problem solving, the ability to identify complex patterns and relationships, and the use of logic (i.e., 'fluid intelligence') [161][162][163][164][165] . Since these cognitive abilities are associated with certain features of sleep and with memory functions, they may confound the associations revealed between sleep and memory consolidation. ...
Understanding the complex relationship between sleep and memory is a major challenge in neuroscience. Many studies on memory consolidation in humans suggest that sleep triggers offline memory processes, resulting in less forgetting of declarative memory and performance stabilization in non-declarative memory. However, an increasing number of contradictory findings reveal potential issues with how research is conducted in this field and call into question the reliability and interpretation of the results. All scientific disciplines face similar challenges. In this regard, research on the relationship between sleep and memory is still very fortunate. Yet, there is a constant need to fine-tune the methodology. In this article, we describe four behavioral methodological issues in human sleep and memory research that should be improved: non-optimal experimental designs, task complexity, fatigue effects in repetitive tasks, and inappropriate data analysis practices. We then offer solutions to each of these issues. We believe that implementing these solutions in future sleep and memory research will lead to more reliable results and significantly advance our understanding in this field.
... Several spindle parameters (e.g. number, density, and activity) increase overnight after learning a new task and have been associated with consolidation in declarative [5][6][7][8] and procedural [9,10] memory. Sleep spindles may promote the reactivation of memories [11,12] and the reorganization of memory traces within neural networks [13,14]. ...
Sleep plays a crucial role in memory consolidation. Recent data in rodents and young adults revealed that fast spindle band power fluctuates at a 0.02-Hz infraslow scale during non-rapid eye movement (NREM) sleep. These fluctuations result from a periodic temporal clustering of spindles and may modulate sleep maintenance and memory consolidation. With age, sleep undergoes substantial changes but age-related changes in spindle clustering have never been investigated. Polysomnography data were collected in 147 older (mean age ± SD: 69.3 ± 4.1 years) and 32 young-middle aged (34.5 ± 10.9 years) adults. Sleep-dependent memory consolidation was assessed in a subsample of 57 older adults using a visuospatial memory task. We analyzed power fluctuations in fast spindle frequency band, detected fast spindles and quantified their clustering during the night separating encoding and retrieval. Fast spindle band power fluctuated at a 0.02-Hz infraslow scale in young-middle aged and older adults. However, the proportion of clustered fast spindles decreased non-linearly with age (p < 0.001). This effect was not mediated by NREM sleep fragmentation. The clustering level of fast spindles modulated their characteristics (p < 0.001). Finally, the mean size of spindle clusters was positively associated with memory consolidation (p = 0.036) and negatively with NREM sleep micro-arousals density (p = 0.033). These results suggest that clusters of fast spindles may constitute stable sleep periods promoting off-line processes such as memory consolidation. We emphasize the relevance of considering spindle dynamics, obviously impaired during ageing, to understand the impact of age-related sleep changes on memory.
... The motor system must learn to generate complex, skilled movements, but the old adage of practice makes perfect has in recent decades been updated to practice with sleep makes perfect (Walker et al., 2002;Walker and Stickgold, 2005;Fogel and Smith, 2006;Fogel et al., 2009;Menicucci et al., 2020). The cerebellum has long been implicated in the process of motor learning (De Zeeuw, 2021), but surprisingly the possible involvement of the cerebellum in sleep-dependent consolidation and overnight performance improvements has been largely ignored (Canto et al., 2017). ...
Despite the importance of the cerebellum for motor learning, and the recognised role of sleep in motor memory consolidation, surprisingly little is known about neural activity in the sleeping cerebro-cerebellar system. Here we used wireless recording from M1 and the cerebellum in three female monkeys to examine the relationship between patterns of single-unit spiking activity observed during waking behaviour and in natural sleep. Across the population of recorded units, we observed similarities in the timing of firing relative to local field potential features associated with both movements during waking and up-states during sleep. We also observed a consistent pattern of asymmetry in pair-wise cross-correlograms, indicative of preserved sequential firing in both wake and sleep at low frequencies. Despite the overall similarity in population dynamics between wake and sleep, there was a global change in the timing of cerebellar activity relative to motor cortex, from contemporaneous in the awake state, to motor cortex preceding the cerebellum in sleep. We speculate that similar population dynamics in waking and sleep may imply that cerebellar internal models are activated in both states, despite the absence of movement when asleep. Moreover, spindle frequency coherence between the cerebellum and motor cortex may provide a mechanism for cerebellar computations to influence sleep-dependent learning processes in the motor cortex.SIGNIFICANCE STATEMENT:It is well known that sleep can lead to improved motor performance. One possibility is that off-line learning results from neural activity during sleep in brain areas responsible for the control of movement. In this study we show for the first time that neuronal patterns in the cerebro-cerebellar system are conserved during both movements and sleep up-states, albeit with a shift in the relative timing between areas. Additionally, we show the presence of simultaneous M1-cerebellar spike coherence at spindle frequencies associated with up-state replay and postulate that this is a mechanism whereby a cerebellar internal models can shape plasticity in neocortical circuits during sleep.
... Each subtest was then weighted according to the factor loadings from Hampshire et al. (2012). Finally, the respective subtests were averaged to create the Reasoning, STM, and Verbal subscales and transformed to standard scores, so that test scores were readily comparable with results from similar studies that employed test batteries tapping into Reasoning and Verbal abilities, such as the Multidimensional Aptitude Battery-II (Fogel and Smith 2006;Fogel et al. 2007) and other commonly used batteries of cognitive abilities such as the Wechsler Adult Intelligence Scale (Wechsler 1981). The descriptive statistics of each subtest are shown in Table 1. ...
Sleep spindles (SP) are one of the few known electrophysiological neuronal biomarkers of interindividual differences in cognitive abilities and aptitudes. Recent simultaneous electroencephalography with functional magnetic resonance imaging (EEG-fMRI) studies suggest that the magnitude of the activation of brain regions recruited during spontaneous spindle events is specifically related to Reasoning abilities. However, it is not known if the relationship with cognitive abilities differs between uncoupled spindles, uncoupled slow waves (SW), and coupled SW–SP complexes, nor have the functional-neuroanatomical substrates that support this relationship been identified. Here, we investigated the functional significance of activation of brain areas recruited during SW-coupled spindles, uncoupled spindles, and uncoupled slow waves. We hypothesize that brain activations time locked to SW-coupled spindle complexes will be primarily associated to Reasoning abilities, especially in subcortical areas. Our results provide direct evidence that the relationship between Reasoning abilities and sleep spindles depends on spindle coupling status. Specifically, we found that the putamen and thalamus, recruited during coupled SW–SP events were positively correlated with Reasoning abilities. In addition, we found a negative association between Reasoning abilities and hippocampal activation time-locked to uncoupled SWs that might reflect a refractory mechanism in the absence of new, intensive hippocampal-dependent memory processing.
... Interestingly, the time window that coincides with spindle activity overlaps with the TMR process (Cairney et al., 2018). This fact, together with the positive correlation between spindle density and cognitive performance (Fogel & Smith, 2011), procedural memory (Fogel & Smith, 2006), or IQ (Fang et al., 2017), highlights the role of sleep spindles in the service of memory consolidation. ...
A growing number of studies have shown the strong relationship between sleep and different cognitive processes, especially those that involve memory consolidation. Traditionally, these processes were attributed to mechanisms related to the macroarchitecture of sleep, as sleep cycles or the duration of specific stages, such as the REM stage. More recently, the relationship between different cognitive traits and specific waves (sleep spindles or slow oscillations) has been studied. We here present the most important physiological processes induced by sleep, with particular focus on brain electrophysiology. In addition, recent and classical literature were reviewed to cover the gap between sleep and cognition, while illustrating this relationship by means of clinical examples. Finally, we propose that future studies may focus not only on analyzing specific waves, but also on the relationship between their characteristics as potential bio-markers for multiple diseases.
... Older adults displayed an increase in the number of minutes of slow-wave sleep (SWS) and SWS percentage after learning. 12,15,23 Studies have shown that pre-sleep learning improves subsequent sleep quality in older individuals, in the areas of continuity, stability, and organization. 24 Two studies to date have investigated the beneficial effects of prolonged cognitive training over an 8-week session on the sleep quality of 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.
... Sleep spindles are bursts of rhythmic 10-15 Hz activity lasting 0.5-2 seconds that are the hallmark of stage 2 or "non-REM stage 2" (NREM2) sleep [16]. Spindles are thought to play a role in memory consolidation [17][18][19][20][21] and appear to be altered in a wide variety of neuropsychiatric conditions including autism [22], schizophrenia [23][24][25] and neurodegenerative diseases [26][27][28]. Given the importance of these graphoelements, much work has been invested in developing tools for spindle detection and characterization [29]. ...
Study Objectives
Sleep spindle activity is commonly estimated by measuring sigma power during stage 2 non-rapid eye movement (NREM2) sleep. However, spindles account for little of the total NREM2 interval and therefore sigma power over the entire interval may be misleading. This study compares derived spindle measures from direct automated spindle detection with those from gross power spectral analyses for the purposes of clinical trial design.
Methods
We estimated spindle activity in a set of 8,440 overnight electroencephalogram (EEG) recordings from 5,793 patients from the Sleep Heart Health Study using both sigma power and direct automated spindle detection. Performance of the two methods was evaluated by ability to distinguish NREM2 from other NREM sleep stages and by determining the sample size required to detect decline in age-related spindle coherence with each method in a simulated clinical trial.
Results
Mean sigma power in NREM2 was indistinguishable from other NREM states in 25% of recordings, vs only 7% for direct spindle measurement (P < 0.001). These percentages were 34% and 14% respectively for sigma coherence comparisons. In a simulated clinical trial, sigma power required a sample size of 115 to achieve 95% power to identify age-related changes in sigma coherence, while automated spindle detection required a sample size of only 60.
Conclusions
Measurements of spindle activity utilizing automated spindle detection outperformed conventional sigma power analysis by a wide margin, suggesting that many studies would benefit from incorporation of automated spindle detection. These results further suggest that some previous studies which have failed to detect changes in sigma power or coherence may have failed simply because they were underpowered.
... Sleep spindles are transient oscillations observed in both lighter and deeper non-rapid eye movement (NREM) sleep (i.e., sleep stages 2 and 3). Their role in memory consolidation is supported by increases in spindle density following learning (e.g., [21]), and the observation that age-related changes in sleep spindles are correlated with differences in overnight performance gains (e.g., [22,23]; see [24] for a review of spindle mechanisms and functions). ...
Closed-loop brain stimulation refers to capturing neurophysiological measures such as electroencephalography (EEG), quickly identifying neural events of interest, and producing auditory, magnetic or electrical stimulation so as to interact with brain processes precisely. It is a promising new method for fundamental neuroscience and perhaps for clinical applications such as restoring degraded memory function; however, existing tools are expensive, cumbersome, and offer limited experimental flexibility. In this article, we propose the Portiloop, a deep learning-based, portable and low-cost closed-loop stimulation system able to target specific brain oscillations. We first document open-hardware implementations that can be constructed from commercially available components. We also provide a fast, lightweight neural network model and an exploration algorithm that automatically optimizes the model hyperparameters to the desired brain oscillation. Finally, we validate the technology on a challenging test case of real-time sleep spindle detection, with results comparable to off-line expert performance on the Massive Online Data Annotation spindle dataset (MODA; group consensus). Software and plans are available to the community as an open science initiative to encourage further development and advance closed-loop neuroscience research [https://github.com/Portiloop].
... Sleep spindles are bursts of rhythmic 10-15 Hz activity lasting 0.5-2 seconds that are the hallmark of stage 2 or "non-REM stage 2" (NREM2) sleep (16). Spindles are thought to play a role in memory consolidation (17)(18)(19)(20)(21) and appear to be altered in a wide variety of neuropsychiatric conditions including autism (22), schizophrenia (23)(24)(25) and neurodegenerative diseases (26-28). Given the importance of these graphoelements, much work has been invested in developing tools for spindle detection and characterization (29). ...
Background. Sleep spindle activity is commonly estimated by measuring sigma power during stage 2 non-rapid eye movement (NREM2) sleep. However, spindles account for little of the total NREM2 interval and therefore sigma power over the entire interval may be misleading. This study compares derived spindle measures from direct automated spindle detection with those from gross power spectral analyses for the purposes of clinical trial design.
Methods. We estimated spindle activity in a set of 8,440 overnight electroencephalogram (EEG) recordings from 5,793 patients from the Sleep Heart Health Study using both sigma power and direct automated spindle detection. Performance of the two methods was evaluated by ability to distinguish NREM2 from other NREM sleep stages and by determining the sample size required to detect decline in age-related spindle coherence with each method in a simulated clinical trial.
Results. Mean sigma power in NREM2 was indistinguishable from other NREM states in 25% of recordings, vs only 7% for direct spindle measurement (P < 0.001). These percentages were 34% and 14% respectively for sigma coherence comparisons. In a simulated clinical trial, sigma power required a sample size of 115 to achieve 95% power to identify age-related changes in sigma coherence, while automated spindle detection required a sample size of only 60.
Conclusions. Measurements of spindle activity utilizing automated spindle detection outperformed conventional sigma power analysis by a wide margin, suggesting that many studies would benefit from incorporation of automated spindle detection. These results further suggest that some previous studies which have failed to detect changes in sigma power or coherence may have failed simply because they were underpowered.
... As a second control analysis, we excluded studies with the largest sample size (Ackermann et al., 2015) and the smallest sample size (Fogel and Smith, 2006) and also on studies that reported a substantially larger number of estimates than the average (Blaskovich et al., 2017; Thürer et al., 2018; k > 130) and repeated the meta-analysis for the association between sleep spindles and memory consolidation. ...
Accumulating evidence suggests a central role for sleep spindles in the consolidation of new memories. However, no metaanalysis of the association between sleep spindles and memory performance has been conducted so far. Here, we report meta-analytical evidence for spindle-memory associations and investigate how multiple factors, including memory type, spindle type, spindle characteristics, and EEG topography affect this relationship. The literature search yielded 53 studies reporting 1424 effect sizes, resulting in a small to moderate effect for the average association. We further found that spindle-memory relationships were significantly stronger for procedural memory than for declarative memory. Neither spindle types nor EEG scalp topography had an impact on the strength of the spindlememory relation, but we observed a distinct functional role of global and fast sleep spindles, especially for procedural memory. We also found a moderation effect of spindle characteristics, with spindle frequency and power showing the largest effect sizes. Collectively, our findings suggest that sleep spindles are involved in learning and plasticity, thereby representing a general physiological mechanism for memory consolidation.
Highlights
Spindle measures showed a small to medium-sized association with memory performance.
This relationship was stronger for procedural memory than declarative memory.
No moderation effects of spindle type and EEG scalp topography have been observed.
Spindle frequency and power emerged as the strongest predictors.
Naps showed similar spindle-related consolidation mechanisms to whole-night sleep.
Multiple studies suggest that the various stages of sleep affect the effectiveness of taking a nap. For this reason, the purpose of this study is to develop a model that may be used to classify the first and second stages of short sleep or the awake state. We employ sleep recordings obtained from the open-access dataset. To enhance the quality of recorded EEG signals, we implement a Notch Filter to reduce power line noise and a 0.5–70 Hz bandpass (Butterworth) filter to isolate the pertinent EEG signals. Two classifiers, Support Vector Machine (SVM) and Random Forest (RF), are used to assess and compare the performance of classification. In addition, the mRmR (minimal Redundancy Maximum Relevance) feature selection approach is employed to improve the model efficiency. The outcomes of our study reveal that both classifiers for each subject have an accuracy rate approaching 80%, differentiating between wakefulness and phases 1 and 2 of short sleep. This study emphasizes the efficacy of these strategies in offering essential instruments for comprehending and enhancing nap efficiency.
The recurrent hormonal fluctuations within reproductive cycles impact sleep-wake behavior in women and in rats and mice used in preclinical models of sleep research. Strides have been made in sleep-related clinical trials to include equal numbers of women; however, the inclusion of female rodents in neuroscience and sleep research is lacking. Female animals are commonly omitted from studies over concerns of the effect of estrus cycle hormones on measured outcomes. This review highlights the estrous cycle’s broad effects on sleep-wake behavior: from changes in sleep macroarchitecture to regionally specific alterations in neural oscillations. These changes are largely driven by cycle-dependent ovarian hormonal fluctuations occurring during proestrus and estrus that modulate neural circuits regulating sleep-wake behavior. Removal of estrous cycle influence by ovariectomy ablates characteristic sleep changes. Further, sex differences in sleep are present between gonadally intact females and males. Removal of reproductive hormones via gonadectomy in both sexes mitigates some, but not all sex differences. We examine the extent to which reproductive hormones and sex chromosomes contribute to sex differences in sleep-wake behavior. Finally, this review addresses the limitations in our understanding of the estrous cycle’s impact on sleep-wake behavior, gaps in female sleep research that are well studied in males, and the implications that ignoring the estrous cycle has on studies of sleep-related processes.
Sleep spindles appear to play an important role in learning new motor skills. Motor skill learning engages several brain regions with two important areas being the motor cortex (M1) and the cerebellum (CB). However, the neurophysiological processes in these areas during sleep, especially how spindle oscillations affect local and cross-region spiking, are not fully understood. We recorded an activity from the M1 and cerebellar cortex in eight rats during spontaneous activity to investigate how sleep spindles in these regions are related to local spiking as well as cross-region spiking. We found that M1 firing was significantly changed during both M1 and CB spindles, and this spiking occurred at a preferred phase of the spindle. On average, M1 and CB neurons showed most spiking at the M1 or CB spindle peaks. These neurons also developed a preferential phase locking to local or cross-area spindles with the greatest phase-locking value at spindle peaks; however, this preferential phase locking was not significant for cerebellar neurons when compared with CB spindles. Additionally, we found that the percentage of task-modulated cells in the M1 and CB that fired with nonuniform spike phase distribution during M1/CB spindle peaks were greater in the rats that learned a reach-to-grasp motor task robustly. Finally, we found that spindle band LFP coherence (for M1 and CB LFPs) showed a positive correlation with success rate in the motor task. These findings support the idea that sleep spindles in both the M1 and CB recruit neurons that participate in the awake task to support motor memory consolidation.
Sleep spindles are critical for memory consolidation and strongly linked to neurological disease and aging. Despite their significance, the relative influences of factors like sleep depth, cortical up/down states, and spindle temporal patterns on individual spindle production remain poorly understood. Moreover, spindle temporal patterns are typically ignored in favor of an average spindle rate. Here, we analyze spindle dynamics in 1008 participants from the Multi-Ethnic Study of Atherosclerosis using a point process framework. Results reveal fingerprint-like temporal patterns, characterized by a refractory period followed by a period of increased spindle activity, which are highly individualized yet consistent night-to-night. We observe increased timing variability with age and distinct gender/age differences. Strikingly, and in contrast to the prevailing notion, individualized spindle patterns are the dominant determinant of spindle timing, accounting for over 70% of the statistical deviance explained by all of the factors we assessed, surpassing the contribution of slow oscillation (SO) phase (~14%) and sleep depth (~16%). Furthermore, we show spindle/SO coupling dynamics with sleep depth are preserved across age, with a global negative shift towards the SO rising slope. These findings offer novel mechanistic insights into spindle dynamics with direct experimental implications and applications to individualized electroencephalography biomarker identification.
Understanding the complex relationship between sleep and memory consolidation is a major challenge in cognitive neuroscience and psychology. Many studies suggest that sleep triggers off-line memory processes, resulting in less forgetting of declarative memory and performance stabilization in non-declarative memory. However, the role of sleep in human memory consolidation is still under considerable debate, and numerous contradictory and non-replicable findings have been reported. Methodological issues related to experimental designs, task characteristics and measurements, and data-analysis practices all influence the effects that are observed and their interpretation. In this Perspective, we review methodological issues in sleep and memory studies and suggest constructive solutions to address them. We believe that implementing these solutions in future sleep and memory research will substantially advance the field and improve understanding of the specific role of sleep in memory consolidation.
Purpose
Many studies have investigated the cognitive, emotional, and other impairments caused by sleep restriction. However, few studies have explored the relationship between cognitive performance and changes in sleep structure and electroencephalography (EEG) during sleep. The present study aimed to examine whether changes in sleep structure and EEG can account for cognitive impairment caused by sleep restriction.
Patients and Methods
Sixteen young adults spent five consecutive nights (adaptation 9h, baseline 8h, 1st restriction 6h, 2nd restriction 6h, and recovery 10h) in a sleep laboratory, with polysomnography recordings taken during sleep. Throughout waking periods in each condition, participants completed the psychomotor vigilance test (PVT), which measures vigilant attention, and the Go/No-Go task, which measures inhibition control.
Results
The results showed that sleep restriction significantly decreased the proportion of N1 and N2 sleep, increased the proportion of N3 sleep, and reduced the time spent awake after sleep onset (WASO) and sleep onset latency. Poorer performance on the PVT and Go/No Go task was associated with longer WASO, a larger proportion of N3 sleep, and a smaller proportion of N2 sleep. Additionally, the power spectral density of delta waves significantly increased after sleep restriction, and this increase predicted a decrease in vigilance and inhibition control the next day.
Conclusion
These findings suggest that sleep architecture and EEG signatures may partially explain cognitive impairment caused by sleep restriction.
Sleep benefits the consolidation of motor skills learned by physical practice, mainly through periodic thalamocortical sleep spindle activity. However, motor skills can be learned without overt movement through motor imagery or action observation. Here, we investigated whether sleep spindle activity also supports the consolidation of non-physically learned movements. Forty-five electroencephalographic sleep recordings were collected during a daytime nap after motor sequence learning by physical practice, motor imagery, or action observation. Our findings reveal that a temporal cluster-based organization of sleep spindles underlies motor memory consolidation in all groups, albeit with distinct behavioral outcomes. A daytime nap offers an early sleep window promoting the retention of motor skills learned by physical practice and motor imagery, and its generalizability toward the inter-manual transfer of skill after action observation. Findings may further have practical impacts with the development of non-physical rehabilitation interventions for patients having to remaster skills following peripherical or brain injury.
Conventional obstructive sleep apnea (OSA) and sleep macroarchitecture may be associated with cognitive function. However, the evidence comes from clinical or select cohort studies, with generalisability of the findings to the broader population uncertain. Furthermore, sleep quantitative electroencephalography (qEEG) sleep microarchitecture may be a useful brain-specific marker of cognitive function. However, the evidence is limited and largely comes from small studies.
This thesis investigates cross-sectional and longitudinal associations of OSA and sleep macro and microarchitecture with cognitive function in a sample of unselected community-dwelling middle-aged and older men from the Men Androgen Inflammation Lifestyle Environment and Stress (MAILES) Study, one of the most comprehensive and longest-running longitudinal cohort studies of male health and wellbeing in Australia. Findings confirmed that cross-sectional and longitudinal associations exist between some measures of OSA and sleep macroarchitecture and cognitive function. However, sleep qEEG markers were not associated with cognitive function examined 8-10 years later.
The activities and role of the cerebellum in sleep have, until recently, been largely ignored by both the sleep and cerebellum fields. Human sleep studies often neglect the cerebellum because it is at a position in the skull that is inaccessible to EEG electrodes. Animal neurophysiology sleep studies have focussed mainly on the neocortex, thalamus and the hippocampus. However, recent neurophysiological studies have shown that not only does the cerebellum participate in the sleep cycle, but it may also be implicated in off-line memory consolidation. Here we review the literature on cerebellar activity during sleep and the role it plays in off-line motor learning, and introduce a hypothesis whereby the cerebellum continues to compute internal models during sleep that train the neocortex.
Purpose
Interictal epileptic discharges (IEDs) are known to affect cognitive function in patients with epilepsy, but the mechanism has not been elucidated. Sleep spindles appearing in synchronization with IEDs were recently demonstrated to impair memory consolidation in rat, but this has not been investigated in humans. On the other hand, the increase of sleep spindles at night after learning is positively correlated with amplified learning effects during sleep for motor sequence learning. In this study, we examined the effects of IEDs and IED-coupled spindles on motor sequence learning in patients with epilepsy, and clarified their pathological significance.
Materials and methods
Patients undergoing long-term video-electroencephalography (LT-VEEG) at our hospital from June 2019 to November 2021 and age-matched healthy subjects were recruited. Motor sequence learning consisting of a finger-tapping task was performed before bedtime and the next morning, and the improvement rate of performance was defined as the sleep-dependent learning effect. We searched for factors associated with the changes in learning effect observed between the periods of when antiseizure medications (ASMs) were withdrawn for LT-VEEG and when they were returned to usual doses after LT-VEEG.
Results
Excluding six patients who had epileptic seizures at night after learning, nine patients and 11 healthy subjects were included in the study. In the patient group, there was no significant learning effect when ASMs were withdrawn. The changes in learning effect of the patient group during ASM withdrawal were not correlated with changes in sleep duration or IED density; however, they were significantly negatively correlated with changes in IED-coupled spindle density.
Conclusion
We found that the increase of IED-coupled spindles correlated with the decrease of sleep-dependent learning effects of procedural memory. Pathological IED-coupled sleep spindles could hinder memory consolidation, that is dependent on physiological sleep spindles, resulting in cognitive dysfunction in patients with epilepsy.
The interplay between the medial prefrontal cortex and hippocampus during non‐REM (NREM) sleep contributes to the consolidation of contextual memories. To assess the role of the thalamic nucleus reuniens (Nre) in this interaction, we investigated the coupling of neuro‐oscillatory activities between prelimbic cortex, Nre, and hippocampus across sleep states and their role in the consolidation of contextual memories using multi‐site electrophysiological recordings and optogenetic manipulations. We showed that ripples are time‐locked to the Up state of cortical slow waves, the transition from Up to Down state in thalamic slow waves, the troughs of cortical spindles, and the peaks of thalamic spindles during spontaneous sleep, rebound sleep, and sleep following a fear conditioning task. In addition, spiking activity in Nre increased before hippocampal ripples and the phase‐locking of hippocampal ripples and thalamic spindles during NREM sleep was stronger after acquisition of a fear memory. We showed that optogenetic inhibition of Nre neurons reduced phase‐locking of ripples to cortical slow waves in the ventral hippocampus while their activation altered the preferred phase of ripples to slow waves in ventral and dorsal hippocampi. However, none of these optogenetic manipulations of Nre during sleep after acquisition of fear conditioning did alter sleep‐dependent memory consolidation. Collectively, these results showed that Nre is central in modulating hippocampus and cortical rhythms during NREM sleep.
Behavioral pediatrics is a multidisciplinary field that involves many healthcare specialists
revolving around the practicing pediatrician and primary care clinician; also, various additional, associated fields of training have developed such as developmental-behavioral pediatrics, neurodevelopmental pediatrics, pediatric psychodermatology and medical care for those of all ages with developmental disabilities (1-16). Experts in psychiatry and psychology work closely with pediatric clinicians in a variety of professional relationships, including co-located and non-co-located mental health settings (17-24). Pediatricians can provide a wide variety of care to children and adolescents with complex disorders, depending on their training as well as interests, and this book seeks to provide au courant perspectives in behavioral pediatrics (25-29). Behavioral health screening remains an important task of pediatricians and behavioral pediatricians as they evaluate their pediatric patients (30-40).
Adolescence is commonly accepted as a challenging time for sleep, with multiple factors contributing to sleep deficiency in adolescents. These include physiologic changes with shifts in their circadian rhythm; medical sleep disorders; and social, cultural, and environmental factors. Early school start times negatively affect sleep in adolescents as well, with poorer outcomes in their overall health, wellbeing, and performance. This article highlights the different contributing factors for sleep deficiency in adolescents and the consequences of sleep deficiency. In addition, the authors discuss the impact of delayed school start times in improving adolescents' sleep and overall function.
Posttraining rapid eye movement (REM) sleep has been reported to be important for efficient memory consolidation. The present results demonstrate increases in the intensity of REM sleep during the night of sleep following cognitive procedural/implicit task acquisition. These REM increases manifest as increases in total number of rapid eye movements (REMs) and REM densities, whereas the actual time spent in REM sleep did not change. Further, the participants with the higher intelligence (IQ) scores showed superior task acquisition scores as well as larger posttraining increases in number of REMs and REM density. No other sleep state changes were observed. None of the pretraining baseline measures of REM sleep were correlated with either measured IQ or task performance. Posttraining increases in REM sleep intensity implicate REM sleep mechanisms in further off-line memory processing, and provide a biological marker of learning potential.
Repeated, daily tetanization of the corpus callosum induces lasting changes in sensorimotor cortex field potential responses, but the synaptic populations that mediate these responses and support long-term potentiation (LTP) have not been characterized. Current source density analyses of field responses were compared between control animals and those in which LTP was induced by 10 daily series of tetanizations. Tetanization and paired-pulse stimulation (100 ms interval) enhanced the duration of initial (∼3 ms onset) deep-negative population spike activity generated by a current sink in layer V that peaked repeatedly at a frequency of ∼400 Hz. The early (∼10 ms to peak) surface-negative component of field responses was generated by a current sink in upper layer V and a source in layer VI. This monosynaptic component followed high stimulation frequencies, recovered quickly from the effects of anaesthesia, and was enhanced by both tetanization and paired-pulse stimulation. The late (∼20 ms to peak) surface-negative component was generated by a sink in upper layer V and a source deep in layer V, and was greatly enhanced by tetanization and paired-pulse stimulation. The late component did not follow high-frequency stimulation and recovered slowly from anaesthesia, suggesting that it is driven polysynaptically. Potentiation of monosynaptic thalamic and cortico-cortical afferents probably mediates enhancements of the early component and population spikes, while potentiation of polysynaptic afferents to layer V may contribute to growth in the late component.
It is now clear that states of sleep are involved with the off-line memory reprocessing or consolidation of a variety of tasks. The large majority of these sleep sensitive tasks has been of the procedural type, tasks that are usually learned implicitly. It is still unclear which states of sleep are most important. For motor skills tasks, Stage 2 sleep has sometimes been implicated, while at other times the important sleep state appears to be rapid eye movement (REM). This paper is an attempt to more clearly identify the characteristics that differentiate REM-dependent from Stage 2-dependent motor tasks and to examine the nature of the brain state differences between the two stages at the neurophysiological and neurochemical levels. We have developed a model to explain how motor skills tasks involving REM and Stage 2 sleep might be dependent on two separate, but overlapping, neural systems. (PsycINFO Database Record (c) 2007 APA ) (journal abstract)
It has recently been reported that selective REM sleep deprivation (REMD) in college students results in memory impairment of the application of a set of rules in a logic task, but not recall of a paired associate task. The present experiments were designed to examine the effects of Total Sleep Deprivation (TSD) and (REMD) following acquisition of a pure motor task, the pursuit rotor. In Experiment 1, subjects (N = 90) were exposed to TSD for one of several nights following training. Results showed that TSD on the same night as training resulted in poorer performance on retest one week later. In Experiment 2, subjects (N = 42) were exposed to various kinds of sleep deprivation on the night of task acquisition. One group was subjected to REMD. Other groups included a non-REM awakening control group (NREMA), a TSD group, a normally rested Control group and a group allowed the first 4 h of sleep in the night before being subjected to TSD (LH - TSD) for the rest of the night. Results showed the REMD and Control groups to have excellent memory for this task while the TSD and LH - TSD subjects had significantly poorer memory for the task. The NREMA group showed a slight, but not significant deficit. It was concluded that Stage 2 sleep, rather than REM sleep was the important stage of sleep for efficient memory processing of the pursuit rotor task.
Evidence for the involvement of rapid eye movement (REM) sleep or paradoxical sleep (PS) with memory processing continues to accumulate. In animals, there is continuing evidence of relatively small, vulnerable paradoxical sleep windows (PSWs) following successful acquisition. These PSWs, which manifest as increases in PS over normal levels, appear to exhibit shorter latencies to onset when the amount of material presented during acquisition is increased. Prevention of the PSW results in memory deficits. In humans, there is now evidence that different types of tasks are differentially sensitive to rapid eye movement sleep deprivation (REMD). Memory for declarative or explicit types of tasks appear not to be affected by REM sleep loss, while memory for cognitive procedural or implicit types of material are impaired by REMD. Using post training auditory stimulation during REM sleep, memory enhancement of the procedural material is also possible. The memory for a fine motor task appears to be sensitive to post training stage 2 sleep loss. The important neural structures are generally not yet identifiable, although the hippocampus would appear to be important for place learning in the Morris water maze.
Repeated, daily tetanization of the corpus callosum induces lasting changes in sensorimotor cortex field potential responses, but the synaptic populations that mediate these responses and support long-term potentiation (LTP) have not been characterized. Current source density analyses of field responses were compared between control animals and those in which LTP was induced by 10 daily series of tetanizations. Tetanization and paired-pulse stimulation (100 ms interval) enhanced the duration of initial (approximately 3 ms onset) deep-negative population spike activity generated by a current sink in layer V that peaked repeatedly at a frequency of approximately 400 Hz. The early (approximately 10 ms to peak) surface-negative component of field responses was generated by a current sink in upper layer V and a source in layer VI. This monosynaptic component followed high stimulation frequencies, recovered quickly from the effects of anaesthesia, and was enhanced by both tetanization and paired-pulse stimulation. The late (approximately 20 ms to peak) surface-negative component was generated by a sink in upper layer V and a source deep in layer V, and was greatly enhanced by tetanization and paired-pulse stimulation. The late component did not follow high-frequency stimulation and recovered slowly from anaesthesia, suggesting that it is driven polysynaptically. Potentiation of monosynaptic thalamic and cortico-cortical afferents probably mediates enhancements of the early component and population spikes, while potentiation of polysynaptic afferents to layer V may contribute to growth in the late component.
Declarative memory consolidation is enhanced by sleep. In the investigation of underlying mechanisms, mainly rapid eye movement (REM) sleep and slow-wave sleep have been considered. More recently, sleep stage 2 with sleep spindles as a most prominent feature has received increasing attention. Specifically, in rats hippocampal ripples were found to occur in temporal proximity to cortical sleep spindles, indicating an information transfer between the hippocampus and neocortex, which is supposed to underlie the consolidation of declarative memories during sleep. This study in humans looks at the changes in EEG activity during nocturnal sleep after extensive training on a declarative learning task, as compared with a nonlearning control task of equal visual stimulation and subjectively rated cognitive strain. Time spent in each sleep stage, spindle density, and EEG power spectra for 28 electrode locations were determined. During sleep after training, the density of sleep spindles was significantly higher after the learning task as compared with the nonlearning control task. This effect was largest during the first 90 min of sleep (p < 0.01). Additionally, spindle density was correlated to recall performance both before and after sleep (r = 0.56; p < 0.05). Power spectra and time spent in sleep stages did not differ between learning and nonlearning conditions. Results indicate that spindle activity during non-REM sleep is sensitive to previous learning experience.
The present paper focuses on human studies attempting to relate sleep states to memory processes. These studies typically present learning material to participants and then examine their ability to recall this material after intervening post-training sleep or sleep deprivation. Most experiments utilize either sleep recording or sleep deprivation following task acquisition to reach their conclusions, although cueing and position emission tomography (PET) scan studies have also been done. Results strongly suggest that REM sleep is involved with the efficient memory processing of cognitive procedural material but not declarative material. Although there are some data to suggest that stage 3/4 or NREM sleep is necessary for declarative memory consolidation, NREM may in fact simply be occurring at the same time as another factor that is actually involved in the memory processing. Preliminary results suggest that the length of the NREM-REM sleep cycle may be important for declarative memory. Preliminary data also suggest that stage 2 sleep may be involved with the memory for motor procedural but not cognitive procedural tasks. Sleep researchers would do well to capitalize on the latest advancements in memory research by choosing tasks that represent special memory systems and examining their relationships to sleep states.
Posttraining rapid eye movement (REM) sleep has been reported to be important for efficient memory consolidation. The present results demonstrate increases in the intensity of REM sleep during the night of sleep following cognitive procedural/implicit task acquisition. These REM increases manifest as increases in total number of rapid eye movements (REMs) and REM densities, whereas the actual time spent in REM sleep did not change. Further, the participants with the higher intelligence (IQ) scores showed superior task acquisition scores as well as larger posttraining increases in number of REMs and REM density. No other sleep state changes were observed. None of the pretraining baseline measures of REM sleep were correlated with either measured IQ or task performance. Posttraining increases in REM sleep intensity implicate REM sleep mechanisms in further off-line memory processing, and provide a biological marker of learning potential.
Spindles are non-rapid eye movement (non-REM) sleep EEG rhythms (7-14 Hz) that occur independently or in association with slow oscillations (0.6-0.8 Hz). Despite their proposed function in learning and memory, their role in synaptic plasticity is essentially unknown. We studied the ability of a neuronal firing pattern underlying spindles in vivo to induce synaptic plasticity in neocortical pyramidal cells in vitro. A spindle stimulation pattern (SSP) was extracted from a slow oscillation upstate that was recorded in a cat anesthetized with ketamine-xylazine, which is known to induce a sleep-like state. To mimic the recurrence of spindles grouped by the slow oscillation, the SSP was repeated every 1.5 s (0.6 Hz). Whole-cell patch-clamp recordings were obtained from layer V pyramidal cells of rat somatosensory cortex with infrared videomicroscopy, and composite EPSPs were evoked within layers II-III. Trains of EPSPs and action potentials simultaneously triggered by the SSP induced an NMDA receptor-dependent short-term potentiation (STP) and an L-type Ca2+ channel-dependent long-term potentiation (LTP). The number of spindle sequences affected the amount of STP-LTP. In contrast, spindle trains of EPSPs alone led to long-term depression. LTP was not consistently induced by a regular firing pattern, a mirrored SSP, or a randomized SSP; however, a synthetic spindle pattern consisting of repetitive spike bursts at 10 Hz reliably induced STP-LTP. Our results show that spindle-associated spike discharges are efficient in modifying excitatory neocortical synapses according to a Hebbian rule. This is in support of a role for sleep spindles in memory consolidation.
Recall of paired-associate lists (declarative memory) and mirror-tracing skills (procedural memory) was assessed after retention intervals defined over early and late nocturnal sleep. In addition, effects of sleep on recall were compared with those of early and late retention intervals filled with wakefulness. Twenty healthy men served as subjects. Saliva cortisol concentrations were determined before and after the retention intervals to determine pituitary-adrenal secretory activity. Sleep was determined somnopolygraphically. Sleep generally enhanced recall when compared with the effects of corresponding retention intervals of wakefulness. The benefit from sleep on recall depended on the phase of sleep and on the type of memory: Recall of paired-associate lists improved more during early sleep, and recall of mirror-tracing skills improved more during late sleep. The effects may reflect different influences of slow wave sleep (SWS) and rapid eye movement (REM) sleep since time in SWS was 5 times longer during the early than late sleep retention interval, and time in REM sleep was twice as long during late than early sleep (p < 0.005). Changes in cortisol concentrations, which independently of sleep and wakefulness were lower during early retention intervals than late ones, cannot account for the effects of sleep on memory. The experiments for the first time dissociate specific effects of early and late sleep on two principal types of memory, declarative and procedural, in humans.
Neocortical preparations have proven highly resistant to the induction of long-term potentiation (LTP), and we have only recently determined the conditions sufficient for the induction of neocortical LTP in the adult, freely moving rat. The stimulation trains must be spaced and repeated over a period of days in order to reach asymptotic levels of potentiation. Here we show that, within these constraints, the neocortex is actually highly responsive. LTP could be induced with as few as one brief high frequency train per day or with extremely low-intensity stimulation trains. We also provide evidence for a critical role for N-methyl-D-aspartate (NMDA) receptor activation in LTP induction in this preparation, and demonstrate that this LTP is input-specific. Control pathways showed no potentiation effects. LTP was found in a monosynaptic and two polysynaptic components (average latencies to peak: 8.1, 15.2 and 20.0 ms) and in the superimposed population spikes. Although LTP could be induced with one train per day or with low-intensity trains, larger and longer-lasting potentiation effects could be induced by increasing the number of trains delivered per session, the number of sessions over which trains were delivered, or the pulse intensity of the trains. The LTP decayed slowly and was still evident 5 weeks later. Administration of the competitive NMDA antagonist 3-[(+/-)-2-carboxypiperazin-4-yl]-propyl-1-phosphonic acid blocked the induction of LTP in a dose-dependent fashion and appeared to unmask a depression of both the population spikes and a polysynaptic component. These results indicate that the neocortex is highly sensitive to LTP induction procedures, as long as the stimulation trains are spaced and applied over a period of days. They are also consistent with the view that the neocortex must operate with a slow learning rate to reduce interference effects in memory.
The neocortex and thalamus are a unified oscillatory machine. Different types of brain rhythms, which characterize various behavioral states, are combined within complex wave-sequences. During the stage of sleep that is associated with low-frequency and high-amplitude brain rhythms, the excitatory component of a cortically generated slow oscillation is effective in triggering thalamically generated rhythms and in increasing their spatiotemporal coherence over widespread territories. Thus, the study of coherent oscillations, as they appear naturally during states of vigilance in animals and humans, requires intact-brain preparations in which the neocortex and thalamus engage in a permanent dialog. Sleep oscillations are associated with rhythmic spike-bursts or spike-trains in thalamic and cortical neurons, which lead to persistent excitability changes consisting of increased depolarizing responses and decreased inhibitory responses. These short-term plasticity processes could be used to consolidate memory traces acquired during wakefulness, but can also lead to paroxysmal (hypersynchronous) episodes, similar to those observed in some epileptic seizures.
Improvement in motor skill performance is known to continue for at least 24 hr following training, yet the relative contributions of time spent awake and asleep are unknown. Here we provide evidence that a night of sleep results in a 20% increase in motor speed without loss of accuracy, while an equivalent period of time during wake provides no significant benefit. Furthermore, a significant correlation exists between the improved performance overnight and the amount of stage 2 NREM sleep, particularly late in the night. This finding of sleep-dependent motor skill improvement may have important implications for the efficient learning of all skilled actions in humans.
Functional significance of stage 2 sleep spindle activity for declarative memory consolidation.
Randomized, within-subject, multicenter.
Weekly sleep laboratory visits, actigraphy, and sleep diary (4 weeks).
Twenty-four healthy subjects (12 men) aged between 20 and 30 years.
Declarative memory task or nonlearning control task before sleep.
This study measured spindle activity during stage 2 sleep following a (declarative) word-pair association task as compared to a control task. Participants performed a cued recall in the evening after learning (160 word pairs) as well as in the subsequent morning after 8 hours of undisturbed sleep with full polysomnography. Overnight change in the number of recalled words, but not absolute memory performance, correlated significantly with increased spindle activity during the experimental night (r24 = .63, P < .01). Time spent in each sleep stage could not account for this relationship.
A growing body of evidence supports the active role of sleep for information reprocessing. Whereas past research focused mainly on the distinct rapid eye movement and slow-wave sleep, these results indicate that increased sleep stage 2 spindle activity is related to an increase in recall performance and, thus, may reflect memory consolidation.
A multivariate study of pursuit rotor skill development
- D Seigel
Seigel, D. A multivariate study of pursuit rotor skill development. Res.
Q. Exerc. Sport, 1990, 61: 201-205.
- Maquet P.