Motor Learning Promotes the Coupling between Fast Spindles and Slow Oscillations Locally over the Contralateral Motor Network

Slow oscillation-sleep spindle coupling is associated with fear extinction retention in trauma-exposed individuals

Posttraumatic stress disorder (PTSD) can be characterized as a disorder of fear learning and memory, in which there is a failure to retain memory for the extinction of conditioned fear. Sleep has been implicated in successful extinction retention. The coupling of sleep spindles to slow oscillations (SOs) during non-rapid eye movement sleep has been shown to broadly underpin sleep's beneficial effect on memory consolidation. However, the role of this oscillatory coupling in the retention of extinction memories is unknown. In a large sample of 124 trauma-exposed individuals, we investigated SO-spindle coupling in relation to fear extinction memory. We found that participants with a PTSD diagnosis, relative to trauma-exposed controls, showed significantly altered SO-spindle timing, such that PTSD participants exhibited spindle coupling further away from the peak of the SO. Across participants, the amount of coupling significantly predicted extinction retention, with coupled spindles uniquely predicting successful extinction retention compared to uncoupled spindles. These results suggest that SO-spindle coupling is critical for successful retention of extinguished fear, and that SO-spindle coupling dynamics are altered in PTSD. These alterations in the mechanics of sleep may have substantial clinical implications, meriting further investigation.

Slow Oscillation-Spindle Coupling Predicts Sequence-Based Language Learning

Sentence comprehension involves the decoding of both semantic and grammatical information, a process fundamental to communication. As with other complex cognitive processes, language comprehension relies, in part, on long-term memory. However, the electrophysiological mechanisms underpinning the encoding and generalization of higher-order linguistic knowledge remain elusive, particularly from a sleep-based consolidation perspective. One candidate mechanism that may support the consolidation of higher-order language is the coordination of slow oscillations (SO) and sleep spindles during nonrapid eye movement sleep (NREM). To examine this hypothesis, we analyzed electroencephalographic (EEG) data recorded from 35 participants (M age = 25.4; SD = 7.10; 16 males) during an artificial language learning task, contrasting performance between individuals who were given an 8 h nocturnal sleep period or an equivalent period of wake. We found that sleep relative to wake was associated with superior performance for sequence-based word order rules. Postsleep sequence-based word order processing was further associated with less task-related theta desynchronization, an electrophysiological signature of successful memory consolidation, as well as cognitive control and working memory. Frontal NREM SO-spindle coupling was also positively associated with behavioral sensitivity to sequence-based word order rules, as well as with task-related theta power. As such, theta activity during retrieval of previously learned information correlates with SO-spindle coupling, thus linking neural activity in the sleeping and waking brain. Taken together, this study presents converging behavioral and neurophysiological evidence for a role of NREM SO-spindle coupling and task-related theta activity as signatures of memory consolidation and retrieval in the context of higher-order language learning.

Sleep oscillations and their relations with sleep-dependent memory consolidation in early course psychosis and first-degree relatives

Sleep spindles mediate sleep-dependent memory consolidation, particularly when coupled to neocortical slow oscillations (SOs). Schizophrenia is characterized by a deficit in sleep spindles that correlates with reduced overnight memory consolidation. Here, we examined sleep spindle activity, SO-spindle coupling, and both motor procedural and verbal declarative memory consolidation in early course, minimally medicated psychosis patients and non-psychotic first-degree relatives. Using a four-night experimental procedure, we observed significant deficits in spindle density and amplitude in patients relative to controls that were driven by individuals with schizophrenia. Schizophrenia patients also showed reduced sleep-dependent consolidation of motor procedural memory, which correlated with lower spindle density. Contrary to expectations, there were no group differences in the consolidation of declarative memory on a word pairs task. Nor did the relatives of patients differ in spindle activity or memory consolidation compared with controls, however increased consistency in the timing of SO-spindle coupling were seen in both patients and relatives. Our results extend prior work by demonstrating correlated deficits in sleep spindles and sleep-dependent motor procedural memory consolidation in early course, minimally medicated patients with schizophrenia, but not in first-degree relatives. This is consistent with other work in suggesting that impaired sleep-dependent memory consolidation has some specificity for schizophrenia and is a core feature rather than reflecting the effects of medication or chronicity.

Motor learning promotes regionally-specific spindle-slow wave coupled cerebral memory reactivation

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.

Sleep Consolidation Potentiates Sensorimotor Adaptation

Contrary to its well-established role in declarative learning, the impact of sleep on motor memory consolidation remains a subject of debate. Current literature suggests that while motor skill learning benefits from sleep, consolidation of sensorimotor adaptation (SMA) depends solely on the passage of time. This has led to the proposal that SMA may be an exception to other types of memories. Here, we addressed this ongoing controversy in humans through three comprehensive experiments using the visuomotor adaptation paradigm (N = 290, 150 females). In Experiment 1, we investigated the impact of sleep on memory retention when the temporal gap between training and sleep was not controlled. In line with the previous literature, we found that memory consolidates with the passage of time. In Experiment 2, we used an anterograde interference protocol to determine the time window during which SMA memory is most fragile and, thus, potentially most sensitive to sleep intervention. Our results show that memory is most vulnerable during the initial hour post-training. Building on this insight, in Experiment 3, we investigated the impact of sleep when it coincided with the critical first hour of memory consolidation. This manipulation unveiled a benefit of sleep (30% memory enhancement) alongside an increase in spindle density and spindle-SO coupling during NREM sleep, two well-established neural markers of sleep consolidation. Our findings reconcile seemingly conflicting perspectives on the active role of sleep in motor learning and point to common mechanisms at the basis of memory formation.

Post-training sleep modulates motor adaptation and task-related beta oscillations

Motor adaptation reflects the ability of the brain's sensorimotor system to flexibly deal with environmental changes to generate effective motor behaviour. Whether sleep contributes to the consolidation of motor adaptation remains controversial. In this study, we investigated the impact of sleep on motor adaptation and its neurophysiological correlates in a novel motor adaptation task that leverages a highly automatised motor skill, that is, typing. We hypothesised that sleep-associated memory consolidation would benefit motor adaptation and induce modulations in task-related beta band (13-30 Hz) activity during adaptation. Healthy young male experts in typing on the regular computer keyboard were trained to type on a vertically mirrored keyboard while brain activity was recorded using electroencephalography. Typing performance was assessed either after a full night of sleep with polysomnography or a similar period of daytime wakefulness. Results showed improved motor adaptation performance after nocturnal sleep but not after daytime wakefulness, and decreased beta power: (a) during mirrored typing as compared with regular typing; and (b) in the post-sleep versus the pre-sleep mirrored typing sessions. Furthermore, the slope of the electroencephalography signal, a measure of aperiodic brain activity, decreased during mirrored as compared with regular typing. Changes in the electroencephalography spectral slope from pre- to post-sleep mirrored typing sessions were correlated with changes in task performance. Finally, increased fast sleep spindle density (13-15 Hz) during the night following motor adaptation training was predictive of successful motor adaptation. These findings suggest that post-training sleep modulates neural activity supporting adaptive motor functions.

Spindle-slow wave coupling and problem-solving skills: impact of 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 non-rapid eye movement 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 the 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.

Motor learning- and consolidation-related resting state fast and slow brain dynamics across wake and sleep

Motor skills dynamically evolve during practice and after training. Using magnetoencephalography, we investigated the neural dynamics underpinning motor learning and its consolidation in relation to sleep during resting-state periods after the end of learning (boost window, within 30 min) and at delayed time scales (silent 4 h and next day 24 h windows) with intermediate daytime sleep or wakefulness. Resting-state neural dynamics were investigated at fast (sub-second) and slower (supra-second) timescales using Hidden Markov modelling (HMM) and functional connectivity (FC), respectively, and their relationship to motor performance. HMM results show that fast dynamic activities in a Temporal/Sensorimotor state network predict individual motor performance, suggesting a trait-like association between rapidly recurrent neural patterns and motor behaviour. Short, post-training task re-exposure modulated neural network characteristics during the boost but not the silent window. Re-exposure-related induction effects were observed on the next day, to a lesser extent than during the boost window. Daytime naps did not modulate memory consolidation at the behavioural and neural levels. These results emphasise the critical role of the transient boost window in motor learning and memory consolidation and provide further insights into the relationship between the multiscale neural dynamics of brain networks, motor learning, and consolidation.

Neural reactivation during human sleep

Sleep promotes memory consolidation: the process by which newly acquired memories are stabilised, strengthened, and integrated into long-term storage. Pioneering research in rodents has revealed that memory reactivation in sleep is a primary mechanism underpinning sleep's beneficial effect on memory. In this review, we consider evidence for memory reactivation processes occurring in human sleep. Converging lines of research support the view that memory reactivation occurs during human sleep, and is functionally relevant for consolidation. Electrophysiology studies have shown that memory reactivation is tightly coupled to the cardinal neural oscillations of non-rapid eye movement sleep, namely slow oscillation-spindle events. In addition, functional imaging studies have found that brain regions recruited during learning become reactivated during post-learning sleep. In sum, the current evidence paints a strong case for a mechanistic role of neural reactivation in promoting memory consolidation during human sleep.

Dusk2Dawn: an EEGLAB plugin for automatic cleaning of whole-night sleep electroencephalogram using Artifact Subspace Reconstruction

Whole-night sleep electroencephalogram (EEG) is plagued by several types of large-amplitude artifacts. Common approaches to remove them are fraught with issues: channel interpolation, rejection of noisy intervals, and independent component analysis are time-consuming, rely on subjective user decisions, and result in signal loss. Artifact Subspace Reconstruction (ASR) is an increasingly popular approach to rapidly and automatically clean wake EEG data. Indeed, ASR adaptively removes large-amplitude artifacts regardless of their scalp topography or consistency throughout the recording. This makes ASR, at least in theory, a highly-promising tool to clean whole-night EEG. However, ASR crucially relies on calibration against a subset of relatively clean "baseline" data. This is problematic when the baseline changes substantially over time, as in whole-night EEG data. Here we tackled this issue and, for the first time, validated ASR for cleaning sleep EEG. We demonstrate that ASR applied out-of-the-box, with the parameters recommended for wake EEG, results in the dramatic removal of slow waves. We also provide an appropriate procedure to use ASR for automatic and rapid cleaning of whole-night sleep EEG data or any long EEG recording. Our procedure is freely available in Dusk2Dawn, an open-source plugin for EEGLAB.

NREM sleep oscillations and their relations with sleep-dependent memory consolidation in early course psychosis and first-degree relatives

Sleep spindles are believed to mediate sleep-dependent memory consolidation, particularly when coupled to neocortical slow oscillations. Schizophrenia is characterized by a deficit in sleep spindles that correlates with reduced overnight memory consolidation. Here, we examined sleep spindle activity, slow oscillation-spindle coupling, and both motor procedural and verbal declarative memory consolidation in early course, minimally medicated psychosis patients and non-psychotic first-degree relatives. Using a four-night experimental procedure, we observed significant deficits in spindle density and amplitude in patients relative to controls that were driven by individuals with schizophrenia. Schizophrenia patients also showed reduced sleep-dependent consolidation of motor procedural memory, which correlated with spindle density. Contrary to expectations, there were no group differences in the consolidation of declarative memory on a word pairs task. Nor did the relatives of patients differ in spindle activity or memory consolidation compared with controls, however increased consistency in the timing of SO-spindle coupling were seen in both patient and relatives. Our results extend prior work by demonstrating correlated deficits in sleep spindles and sleep-dependent motor procedural memory consolidation in early course, minimally medicated patients with schizophrenia, but not in first-degree relatives. This is consistent with other work in suggesting that impaired sleep-dependent memory consolidation has some specificity for schizophrenia and is a core feature rather than reflecting the effects of medication or chronicity.

The effects of closed-loop auditory stimulation on sleep oscillatory dynamics in relation to motor procedural memory consolidation

STUDY OBJECTIVES

Healthy aging and many disorders show reduced sleep-dependent memory consolidation and corresponding alterations in non-rapid eye movement sleep oscillations. Yet sleep physiology remains a relatively neglected target for improving memory. We evaluated the effects of closed-loop auditory stimulation during sleep (CLASS) on slow oscillations (SOs), sleep spindles, and their coupling, all in relation to motor procedural memory consolidation.

METHODS

Twenty healthy young adults had two afternoon naps: one with auditory stimulation during SO upstates and another with no stimulation. Twelve returned for a third nap with stimulation at variable times in relation to SO upstates. In all sessions, participants trained on the motor sequence task prior to napping and were tested afterward.

RESULTS

Relative to epochs with no stimulation, upstate stimuli disrupted sleep and evoked SOs, spindles, and SO-coupled spindles. Stimuli that successfully evoked oscillations were delivered closer to the peak of the SO upstate and when spindle power was lower than stimuli that failed to evoke oscillations. Across conditions, participants showed similar significant post-nap performance improvement that correlated with the density of SO-coupled spindles.

CONCLUSIONS

Despite its strong effects on sleep physiology, CLASS failed to enhance motor procedural memory. Our findings suggest methods to overcome this failure, including better sound calibration to preserve sleep continuity and the use of real-time predictive algorithms to more precisely target SO upstates and to avoid disrupting endogenous SO-coupled spindles and their mnemonic function. They motivate continued development of CLASS as an intervention to manipulate sleep oscillatory dynamics and improve memory.

A Novel Approach to Estimating the Cortical Sources of Sleep Spindles Using Simultaneous EEG/MEG

Sleep spindles, defining oscillations of stage II non-rapid eye movement sleep (N2), mediate sleep-dependent memory consolidation. Spindles are disrupted in several neurodevelopmental, neuropsychiatric, and neurodegenerative disorders characterized by cognitive impairment. Increasing spindles can improve memory suggesting spindles as a promising physiological target for the development of cognitive enhancing therapies. This effort would benefit from more comprehensive and spatially precise methods to characterize spindles. Spindles, as detected with electroencephalography (EEG), are often widespread across electrodes. Available evidence, however, suggests that they act locally to enhance cortical plasticity in the service of memory consolidation. Here, we present a novel method to enhance the spatial specificity of cortical source estimates of spindles using combined EEG and magnetoencephalography (MEG) data constrained to the cortex based on structural MRI. To illustrate this method, we used simultaneous EEG and MEG recordings from 25 healthy adults during a daytime nap. We first validated source space spindle detection using only EEG data by demonstrating strong temporal correspondence with sensor space EEG spindle detection (gold standard). We then demonstrated that spindle source estimates using EEG alone, MEG alone and combined EEG/MEG are stable across nap sessions. EEG detected more source space spindles than MEG and each modality detected non-overlapping spindles that had distinct cortical source distributions. Source space EEG was more sensitive to spindles in medial frontal and lateral prefrontal cortex, while MEG was more sensitive to spindles in somatosensory and motor cortices. By combining EEG and MEG data this method leverages the differential spatial sensitivities of the two modalities to obtain a more comprehensive and spatially specific source estimation of spindles than possible with either modality alone.

Visuomotor Adaptation Modulates the Clustering of Sleep Spindles Into Trains

Sleep spindles are thought to promote memory consolidation. Recently, we have shown that visuomotor adaptation (VMA) learning increases the density of spindles and promotes the coupling between spindles and slow oscillations, locally, with the level of spindle-SO synchrony predicting overnight memory retention. Yet, growing evidence suggests that the rhythmicity in spindle occurrence may also influence the stabilization of declarative and procedural memories. Here, we examined if VMA learning promotes the temporal organization of sleep spindles into trains. We found that VMA increased the proportion of spindles and spindle-SO couplings in trains. In agreement with our previous work, this modulation was observed over the contralateral hemisphere to the trained hand, and predicted overnight memory retention. Interestingly, spindles grouped in a cluster showed greater amplitude and duration than isolated spindles. The fact that these features increased as a function of train length, provides evidence supporting a biological advantage of this temporal arrangement. Our work opens the possibility that the periodicity of NREM oscillations may be relevant in the stabilization of procedural memories.

Using EEG to study sensorimotor adaptation

Sensorimotor adaptation, or the capacity to flexibly adapt movements to changes in the body or the environment, is crucial to our ability to move efficiently in a dynamic world. The field of sensorimotor adaptation is replete with rigorous behavioural and computational methods, which support strong conceptual frameworks. An increasing number of studies have combined these methods with electroencephalography (EEG) to unveil insights into the neural mechanisms of adaptation. We review these studies: discussing EEG markers of adaptation in the frequency and the temporal domain, EEG predictors for successful adaptation and how EEG can be used to unmask latent processes resulting from adaptation, such as the modulation of spatial attention. With its high temporal resolution, EEG can be further exploited to deepen our understanding of sensorimotor adaptation.