NREM2 and Sleep Spindles Are Instrumental to the Consolidation of Motor Sequence Memories

Although numerous studies have convincingly demonstrated that sleep plays a critical role in motor sequence learning (MSL) consolidation, the specific contribution of the different sleep stages in this type of memory consolidation is still contentious. To probe the role of stage 2 non-REM sleep (NREM2) in this process, we used a conditioning protocol in three different groups of participants who either received an odor during initial training on a motor sequence learning task and were re-exposed to this odor during different sleep stages of the post-training night (i.e., NREM2 sleep [Cond-NREM2], REM sleep [Cond-REM], or were not conditioned during learning but exposed to the odor during NREM2 [NoCond]). Results show that the Cond-NREM2 group had significantly higher gains in performance at retest than both the Cond-REM and NoCond groups. Also, only the Cond-NREM2 group yielded significant changes in sleep spindle characteristics during cueing. Finally, we found that a change in frequency of sleep spindles during cued-memory reactivation mediated the relationship between the experimental groups and gains in performance the next day. These findings strongly suggest that cued-memory reactivation during NREM2 sleep triggers an increase in sleep spindle activity that is then related to the consolidation of motor sequence memories.     

Evidence for the re-enactment of a recently learned behavior during sleepwalking

Animal studies have shown that sequenced patterns of neuronal activity may be replayed during sleep. However, the existence of such replay in humans has not yet been directly demonstrated. Here we studied patients who exhibit overt behaviors during sleep to test whether sequences of movements trained during the day may be spontaneously reenacted by the patients during sleep. We recruited 19 sleepwalkers (who displayed complex and purposeful behaviors emerging from non REM sleep), 20 patients with REM sleep behavior disorder (who enacted their dreams in REM sleep) and 18 healthy controls. Continuous video sleep recordings were performed during sleep following intensive training on a sequence of large movements (learned during a variant of the serial reaction time task). Both patient groups showed learning of the intensively trained motor sequence after sleep. We report the re-enactment of a fragment of the recently trained motor behavior during one sleepwalking episode. This study provides, to our knowledge, the first evidence of a temporally-structured replay of a learned behavior during sleep in humans. Our observation also suggests that the study of such sleep disorders may provide unique and critical information about cognitive functions operating during sleep.     

Daytime Sleep Enhances Consolidation of the Spatial but Not Motoric Representation of Motor Sequence Memory

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

Interaction between Hippocampal and Striatal Systems Predicts Subsequent Consolidation of Motor Sequence Memory

The development of fast and reproducible motor behavior is a crucial human capacity. The aim of the present study was to address the relationship between the implementation of consistent behavior during initial training on a sequential motor task (the Finger Tapping Task) and subsequent sleep-dependent motor sequence memory consolidation, using functional magnetic resonance imaging (fMRI) and total sleep deprivation protocol. Our behavioral results indicated significant offline gains in performance speed after sleep whereas performance was only stabilized, but not enhanced, after sleep deprivation. At the cerebral level, we previously showed that responses in the caudate nucleus increase, in parallel to a decrease in its functional connectivity with frontal areas, as performance became more consistent. Here, the strength of the competitive interaction, assessed through functional connectivity analyses, between the caudate nucleus and hippocampo-frontal areas during initial training, predicted delayed gains in performance at retest in sleepers but not in sleep-deprived subjects. Moreover, during retest, responses increased in the hippocampus and medial prefrontal cortex in sleepers whereas in sleep-deprived subjects, responses increased in the putamen and cingulate cortex. Our results suggest that the strength of the competitive interplay between the striatum and the hippocampus, participating in the implementation of consistent motor behavior during initial training, conditions subsequent motor sequence memory consolidation. The latter process appears to be supported by a reorganisation of cerebral activity in hippocampo-neocortical networks after sleep.     

Sleep Promotes the Extraction of Grammatical Rules

Grammar acquisition is a high level cognitive function that requires the extraction of complex rules. While it has been proposed that offline time might benefit this type of rule extraction, this remains to be tested. Here, we addressed this question using an artificial grammar learning paradigm. During a short-term memory cover task, eighty-one human participants were exposed to letter sequences generated according to an unknown artificial grammar. Following a time delay of 15 min, 12 h (wake or sleep) or 24 h, participants classified novel test sequences as Grammatical or Non-Grammatical. Previous behavioral and functional neuroimaging work has shown that classification can be guided by two distinct underlying processes: (1) the holistic abstraction of the underlying grammar rules and (2) the detection of sequence chunks that appear at varying frequencies during exposure. Here, we show that classification performance improved after sleep. Moreover, this improvement was due to an enhancement of rule abstraction, while the effect of chunk frequency was unaltered by sleep. These findings suggest that sleep plays a critical role in extracting complex structure from separate but related items during integrative memory processing. Our findings stress the importance of alternating periods of learning with sleep in settings in which complex information must be acquired.     

Cortical control of motor sequences

The neural substrate of sequence learning is well known. However, we lack a clear understanding of the detailed functional properties of many of the areas involved. The reason for this discrepancy lies, in part, in the fact that two types of processes, implicit and explicit, subserve motor sequence learning, and these often interact with each other. The most significant recent advances have been the elucidation of the very complex relationships between medial motor areas and the temporal and ordinal control of sequences, and the demonstration that motor cortex is an important site for sequence storage and production. The challenge for the future will be to develop a coherent and internally consistent theory of sequence control.     

Simultaneous Brain–Cervical Cord fMRI Reveals Intrinsic Spinal Cord Plasticity during Motor Sequence Learning

The spinal cord participates in the execution of skilled movements by translating high-level cerebral motor representations into musculotopic commands. Yet, the extent to which motor skill acquisition relies on intrinsic spinal cord processes remains unknown. To date, attempts to address this question were limited by difficulties in separating spinal local effects from supraspinal influences through traditional electrophysiological and neuroimaging methods. Here, for the first time, we provide evidence for local learning-induced plasticity in intact human spinal cord through simultaneous functional magnetic resonance imaging of the brain and spinal cord during motor sequence learning. Specifically, we show learning-related modulation of activity in the C6–C8 spinal region, which is independent from that of related supraspinal sensorimotor structures. Moreover, a brain–spinal cord functional connectivity analysis demonstrates that the initial linear relationship between the spinal cord and sensorimotor cortex gradually fades away over the course of motor sequence learning, while the connectivity between spinal activity and cerebellum gains strength. These data suggest that the spinal cord not only constitutes an active functional component of the human motor learning network but also contributes distinctively from the brain to the learning process. The present findings open new avenues for rehabilitation of patients with spinal cord injuries, as they demonstrate that this part of the central nervous system is much more plastic than assumed before. Yet, the neurophysiological mechanisms underlying this intrinsic functional plasticity in the spinal cord warrant further investigations.     

Motor imagery—Anatomical representation and electrophysiological characteristics

Experience and results of neuropsychological studies have shown that motor imagery can improve motor performance and enhance motor learning. In recent years several electro-physiological and functional imaging studies have investigated the physiological basis for this observation. In the present essay we review two of our recent studies, in which we compared motor imagery with motor preparation and motor execution. In the first we used positron emission tomography to describe their functional anatomy and in the second we employed electromyography, H-reflexes and transcranial magnetic stimulation to delineate their electrophysiological characteristics. Both studies demonstrated that motor imagery shares some characteristics with motor preparation and other, additional ones with motor execution. Thus it can be seen as a special form of motor behaviour, similar but distinct from both motor preparation and execution. This combination of mutual and distinct characteristics may be the key to its successful role in motor learning. Special issue dedicated to Dr. Herman Bachelard.     

Sleep-Dependent Reactivation of Ensembles in Motor Cortex Promotes Skill Consolidation

Despite many prior studies demonstrating offline behavioral gains in motor skills after sleep, the underlying neural mechanisms remain poorly understood. To investigate the neurophysiological basis for offline gains, we performed single-unit recordings in motor cortex as rats learned a skilled upper-limb task. We found that sleep improved movement speed with preservation of accuracy. These offline improvements were linked to both replay of task-related ensembles during non-rapid eye movement (NREM) sleep and temporal shifts that more tightly bound motor cortical ensembles to movements; such offline gains and temporal shifts were not evident with sleep restriction. Interestingly, replay was linked to the coincidence of slow-wave events and bursts of spindle activity. Neurons that experienced the most consistent replay also underwent the most significant temporal shift and binding to the motor task. Significantly, replay and the associated performance gains after sleep only occurred when animals first learned the skill; continued practice during later stages of learning (i.e., after motor kinematics had stabilized) did not show evidence of replay. Our results highlight how replay of synchronous neural activity during sleep mediates large-scale neural plasticity and stabilizes kinematics during early motor learning.     

Striatal and Hippocampal Involvement in Motor Sequence Chunking Depends on the Learning Strategy

Motor sequences can be learned using an incremental approach by starting with a few elements and then adding more as training evolves (e.g., learning a piano piece); conversely, one can use a global approach and practice the whole sequence in every training session (e.g., shifting gears in an automobile). Yet, the neural correlates associated with such learning strategies in motor sequence learning remain largely unexplored to date. Here we used functional magnetic resonance imaging to measure the cerebral activity of individuals executing the same 8-element sequence after they completed a 4-days training regimen (2 sessions each day) following either a global or incremental strategy. A network comprised of striatal and fronto-parietal regions was engaged significantly regardless of the learning strategy, whereas the global training regimen led to additional cerebellar and temporal lobe recruitment. Analysis of chunking/grouping of sequence elements revealed a common prefrontal network in both conditions during the chunk initiation phase, whereas execution of chunk cores led to higher mediotemporal activity (involving the hippocampus) after global than incremental training. The novelty of our results relate to the recruitment of mediotemporal regions conditional of the learning strategy. Thus, the present findings may have clinical implications suggesting that the ability of patients with lesions to the medial temporal lobe to learn and consolidate new motor sequences may benefit from using an incremental strategy.     

The Consolidation of Implicit Sequence Memory in Obstructive Sleep Apnea

Obstructive Sleep Apnea (OSA) Syndrome is a relatively frequent sleep disorder characterized by disrupted sleep patterns. It is a well-established fact that sleep has beneficial effect on memory consolidation by enhancing neural plasticity. Implicit sequence learning is a prominent component of skill learning. However, the formation and consolidation of this fundamental learning mechanism remains poorly understood in OSA. In the present study we examined the consolidation of different aspects of implicit sequence learning in patients with OSA. We used the Alternating Serial Reaction Time task to measure general skill learning and sequence-specific learning. There were two sessions: a learning phase and a testing phase, separated by a 10-hour offline period with sleep. Our data showed differences in offline changes of general skill learning between the OSA and control group. The control group demonstrated offline improvement from evening to morning, while the OSA group did not. In contrast, we did not observe differences between the groups in offline changes in sequence-specific learning. Our findings suggest that disrupted sleep in OSA differently affects neural circuits involved in the consolidation of sequence learning.     

Sleep-dependent consolidation of contextual learning

Memory consolidation is facilitated by sleep. Specifying the functional domain of sleep-dependent consolidation (SDC) is important for identifying the neural mechanisms underlying this phenomenon. Previous work indicates that SDC may be limited to conditions in which learning is explicit. In the present study, we tested the hypothesis that SDC may also occur with implicit learning when learning benefits from the formation of contextual associations, a function associated with the hippocampus. Three versions of the serial-reaction-time task (SRTT) were examined, and SDC was assessed by comparing performance after 12 hr breaks that included or did not include sleep. SDC was observed in the Explicit condition. Two implicit conditions were compared. In the Implicit Noncontextual condition, participants performed a concurrent tone-counting task with the pitch of each tone selected at random, precluding cross-dimensional associations. In the Implicit Contextual condition, participants responded to the color of the cues while the spatial location of the cues followed a correlated sequence. Whereas learning was observed in both implicit conditions, SDC was restricted to the contextual condition. Given that the formation of contextual associations is dependent on the hippocampus, we suggest that SDC is a hippocampus-mediated process.     

Changes in striatal dopamine release associated with human motor-skill acquisition

The acquisition of new motor skills is essential throughout daily life and involves the processes of learning new motor sequence and encoding elementary aspects of new movement. Although previous animal studies have suggested a functional importance for striatal dopamine release in the learning of new motor sequence, its role in encoding elementary aspects of new movement has not yet been investigated. To elucidate this, we investigated changes in striatal dopamine levels during initial skill-training (Day 1) compared with acquired conditions (Day 2) using (11)C-raclopride positron-emission tomography. Ten volunteers learned to perform brisk contractions using their non-dominant left thumbs with the aid of visual feedback. On Day 1, the mean acceleration of each session was improved through repeated training sessions until performance neared asymptotic levels, while improved motor performance was retained from the beginning on Day 2. The (11)C-raclopride binding potential (BP) in the right putamen was reduced during initial skill-training compared with under acquired conditions. Moreover, voxel-wise analysis revealed that (11)C-raclopride BP was particularly reduced in the right antero-dorsal to the lateral part of the putamen. Based on findings from previous fMRI studies that show a gradual shift of activation within the striatum during the initial processing of motor learning, striatal dopamine may play a role in the dynamic cortico-striatal activation during encoding of new motor memory in skill acquisition.     

At the interface of the auditory and vocal motor systems: NIf and its role in vocal processing,production and learning

Communication between auditory and vocal motor nuclei is essential for vocal learning. In songbirds, the nucleus interfacialis of the nidopallium (NIf) is part of a sensorimotor loop, along with auditory nucleus avalanche (Av) and song system nucleus HVC, that links the auditory and song systems. Most of the auditory information comes through this sensorimotor loop, with the projection from NIf to HVC representing the largest single source of auditory information to the song system. In addition to providing the majority of HVC’s auditory input, NIf is also the primary driver of spontaneous activity and premotor-like bursting during sleep in HVC. Like HVC and RA, two nuclei critical for song learning and production, NIf exhibits behavioral-state dependent auditory responses and strong motor bursts that precede song output. NIf also exhibits extended periods of fast gamma oscillations following vocal production. Based on the converging evidence from studies of physiology and functional connectivity it would be reasonable to expect NIf to play an important role in the learning, maintenance, and production of song. Surprisingly, however, lesions of NIf in adult zebra finches have no effect on song production or maintenance. Only the plastic song produced by juvenile zebra finches during the sensorimotor phase of song learning is affected by NIf lesions. In this review, we carefully examine what is known about NIf at the anatomical, physiological, and behavioral levels. We reexamine conclusions drawn from previous studies in the light of our current understanding of the song system, and establish what can be said with certainty about NIf’s involvement in song learning, maintenance, and production. Finally, we review recent theories of song learning integrating possible roles for NIf within these frameworks and suggest possible parallels between NIf and sensorimotor areas that form part of the neural circuitry for speech processing in humans.     

Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State

Background

Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning.

Methodology/Principal Findings

We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN.

Conclusions/Significance

These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning.     

Interacting adaptive processes with different timescales underlie short-term motor learning

Multiple processes may contribute to motor skill acquisition, but it is thought that many of these processes require sleep or the passage of long periods of time ranging from several hours to many days or weeks. Here we demonstrate that within a timescale of minutes, two distinct fast-acting processes drive motor adaptation. One process responds weakly to error but retains information well, whereas the other responds strongly but has poor retention. This two-state learning system makes the surprising prediction of spontaneous recovery (or adaptation rebound) if error feedback is clamped at zero following an adaptation-extinction training episode. We used a novel paradigm to experimentally confirm this prediction in human motor learning of reaching, and we show that the interaction between the learning processes in this simple two-state system provides a unifying explanation for several different, apparently unrelated, phenomena in motor adaptation including savings, anterograde interference, spontaneous recovery, and rapid unlearning. Our results suggest that motor adaptation depends on at least two distinct neural systems that have different sensitivity to error and retain information at different rates.     

Reduced susceptibility to interference in the consolidation of motor memory before adolescence

Are children superior to adults in consolidating procedural memory? This notion has been tied to "critical," early life periods of increased brain plasticity. Here, using a motor sequence learning task, we show, in experiment 1, that a) the rate of learning during a training session, b) the gains accrued, without additional practice, within a 24 hours post-training interval (delayed consolidation gains), and c) the long-term retention of these gains, were as effective in 9, 12 and 17-year-olds and comparable to those reported for adults. However, a follow-up experiment showed that the establishment of a memory trace for the trained sequence of movements was significantly more susceptible to interference by a subsequent motor learning experience (practicing a reversed movement sequence) in the 17-year-olds compared to the 9 and 12-year-olds. Unlike the 17-year-olds, the younger age-groups showed significant delayed gains even after interference training. Altogether, our results indicate the existence of an effective consolidation phase in motor learning both before and after adolescence, with no childhood advantage in the learning or retention of a motor skill. However, the ability to co-consolidate different, successive motor experiences, demonstrated in both the 9 and 12-year-olds, diminishes after puberty, suggesting that a more selective memory consolidation process takes over from the childhood one. Only the adult consolidation process is gated by a recency effect, and in situations of multiple, clashing, experiences occurring within a short time-interval, adults may less effectively establish in memory experiences superseded by newer ones.     

A neuromorphic architecture for object recognition and motion anticipation using burst-STDP

In this work we investigate the possibilities offered by a minimal framework of artificial spiking neurons to be deployed in silico. Here we introduce a hierarchical network architecture of spiking neurons which learns to recognize moving objects in a visual environment and determine the correct motor output for each object. These tasks are learned through both supervised and unsupervised spike timing dependent plasticity (STDP). STDP is responsible for the strengthening (or weakening) of synapses in relation to pre- and post-synaptic spike times and has been described as a Hebbian paradigm taking place both in vitro and in vivo. We utilize a variation of STDP learning, called burst-STDP, which is based on the notion that, since spikes are expensive in terms of energy consumption, then strong bursting activity carries more information than single (sparse) spikes. Furthermore, this learning algorithm takes advantage of homeostatic renormalization, which has been hypothesized to promote memory consolidation during NREM sleep. Using this learning rule, we design a spiking neural network architecture capable of object recognition, motion detection, attention towards important objects, and motor control outputs. We demonstrate the abilities of our design in a simple environment with distractor objects, multiple objects moving concurrently, and in the presence of noise. Most importantly, we show how this neural network is capable of performing these tasks using a simple leaky-integrate-and-fire (LIF) neuron model with binary synapses, making it fully compatible with state-of-the-art digital neuromorphic hardware designs. As such, the building blocks and learning rules presented in this paper appear promising for scalable fully neuromorphic systems to be implemented in hardware chips.     

Practice makes imperfect: restorative effects of sleep on motor learning

Emerging evidence suggests that sleep plays a key role in procedural learning, particularly in the continued development of motor skill learning following initial acquisition. We argue that a detailed examination of the time course of performance across sleep on the finger-tapping task, established as the paradigm for studying the effect of sleep on motor learning, will help distinguish a restorative role of sleep in motor skill learning from a proactive one. Healthy subjects rehearsed for 12 trials and, following a night of sleep, were tested. Early training rapidly improved speed as well as accuracy on pre-sleep training. Additional rehearsal caused a marked slow-down in further improvement or partial reversal in performance to observed levels below theoretical upper limits derived on the basis of early pre-sleep rehearsal. This decrement in learning efficacy does not occur always, but if and only if it does, overnight sleep has an effect in fully or partly restoring the efficacy and actual performance to the optimal theoretically achieveable level. Our findings re-interpret the sleep-dependent memory enhancement in motor learning reported in the literature as a restoration of fatigued circuitry specialized for the skill. In providing restitution to the fatigued brain, sleep eliminates the rehearsal-induced synaptic fatigue of the circuitry specialized for the task and restores the benefit of early pre-sleep rehearsal. The present findings lend support to the notion that latent sleep-dependent enhancement of performance is a behavioral expression of the brain's restitution in sleep.