Targeted memory reactivation during post-learning sleep does not enhance motor memory consolidation in older adults.

Targeted memory reactivation (TMR) during sleep enhances memory consolidation in young adults by modulating electrophysiological markers of neuroplasticity. Interestingly, older adults exhibit deficits in motor memory consolidation, an impairment that has been linked to age-related degradations in the same sleep features sensitive to TMR. We hypothesised that TMR would enhance consolidation in older adults via the modulation of these markers. A total of 17 older participants were trained on a motor task involving two auditory-cued sequences. During a post-learning nap, two auditory cues were played: one associated to a learned (i.e., reactivated) sequence and one control. Performance during two delayed re-tests did not differ between reactivated and non-reactivated sequences. Moreover, both associated and control sounds modulated brain responses, yet there were no consistent differences between the auditory cue types. Our results collectively demonstrate that older adults do not benefit from specific reactivation of a motor memory trace by an associated auditory cue during post-learning sleep. Based on previous research, it is possible that auditory stimulation during post-learning sleep could have boosted motor memory consolidation in a non-specific manner.

Frequency-dependent connectivity in large-scale resting-state brain networks during sleep.

Functional connectivity (FC) during sleep has been shown to break down as non-rapid eye movement (NREM) sleep deepens before returning to a state closer to wakefulness during rapid eye movement (REM) sleep. However, the specific spatial and temporal signatures of these fluctuations in connectivity patterns remain poorly understood. This study aimed to investigate how frequency-dependent network-level FC fluctuates during nocturnal sleep in healthy young adults using high-density electroencephalography (hdEEG). Specifically, we examined source-localized FC in resting-state networks during NREM2, NREM3 and REM sleep (sleep stages scored using a semi-automatic procedure) in the first three sleep cycles of 29 participants. Our results showed that FC within and between all resting-state networks decreased from NREM2 to NREM3 sleep in multiple frequency bands and all sleep cycles. The data also highlighted a complex modulation of connectivity patterns during the transition to REM sleep whereby delta and sigma bands hosted a persistence of the connectivity breakdown in all networks. In contrast, a reconnection occurred in the default mode and the attentional networks in frequency bands characterizing their organization during wake (i.e., alpha and beta bands, respectively). Finally, all network pairs (except the visual network) showed higher gamma-band FC during REM sleep in cycle three compared to earlier sleep cycles. Altogether, our results unravel the spatial and temporal characteristics of the well-known breakdown in connectivity observed as NREM sleep deepens. They also illustrate a complex pattern of connectivity during REM sleep that is consistent with network- and frequency-specific breakdown and reconnection processes.

Prefrontal stimulation as a tool to disrupt hippocampal and striatal reactivations underlying fast motor memory consolidation.

BACKGROUND: Recent evidence suggests that hippocampal replay in humans support rapid motor memory consolidation during epochs of wakefulness interleaved with task practice. OBJECTIVES/HYPOTHESES: The goal of this study was to test whether such reactivation patterns can be modulated with experimental interventions and in turn influence fast consolidation. We hypothesized that non-invasive brain stimulation targeting hippocampal and striatal networks via the prefrontal cortex would influence brain reactivation and the rapid form of motor memory consolidation. METHODS: Theta-burst stimulation was applied to a prefrontal cluster functionally connected to both the hippocampus and striatum of young healthy participants before they learned a motor sequence task in a functional magnetic resonance imaging (fMRI) scanner. Neuroimaging data acquired during task practice and the interleaved rest epochs were analyzed to comprehensively characterize the effect of stimulation on the neural processes supporting fast motor memory consolidation. RESULTS: Our results collectively show that active, as compared to control, theta-burst stimulation of the prefrontal cortex hindered fast motor memory consolidation. Converging evidence from both univariate and multivariate analyses of fMRI data indicate that active stimulation disrupted hippocampal and caudate responses during inter-practice rest, presumably altering the reactivation of learning-related patterns during the micro-offline consolidation episodes. Last, stimulation altered the link between the brain and the behavioral markers of the fast consolidation process. CONCLUSION: These results suggest that stimulation targeting deep brain regions via the prefrontal cortex can be used to modulate hippocampal and striatal reactivations in the human brain and influence motor memory consolidation.

Exogenous Ketosis Improves Sleep Efficiency and Counteracts the Decline in REM Sleep after Strenuous Exercise.

INTRODUCTION: Available evidence indicates that ketone bodies may improve sleep quality. Therefore, we determined whether ketone ester (KE) intake could counteract sleep disruptions induced by strenuous exercise. METHODS: Ten well-trained cyclists with good sleep quality participated in a randomized crossover design consisting of two experimental sessions each involving a morning endurance training and an evening high-intensity interval training ending 1 h before sleep, after which polysomnography was performed overnight. Postexercise and 30 min before sleeping time, subjects received either 25 g of KE (EX KE ) or a placebo drink (EX CON ). A third session without exercise but with placebo supplements (R CON ) was added to evaluate the effect of exercise per se on sleep. RESULTS: Blood d -ß-hydroxybutyrate concentrations transiently increased to ~3 mM postexercise and during the first part of the night in EX KE but not in EX CON or R CON . Exercise significantly reduced rapid eye movement sleep by 26% ( P = 0.001 vs R CON ) and increased wakefulness after sleep onset by 95% ( P = 0.004 vs R CON ). Interestingly, KE improved sleep efficiency by 3% ( P = 0.040 vs EX CON ) and counteracted the exercise-induced decrease in rapid eye movement sleep ( P = 0.011 vs EX CON ) and the increase in wakefulness after sleep onset ( P = 0.009 vs EX CON ). This was accompanied by a KE-induced increase in dopamine excretion ( P = 0.033 vs EX CON ), which plays a pivotal role in sleep regulation. In addition, exercise increased sleep spindle density by 36% ( P = 0.005 vs R CON ), suggesting an effect on neural plasticity processes during sleep. CONCLUSIONS: These data indicate that KE ingestion improves sleep efficiency and quality after high-intensity exercise. We provide preliminary evidence that this might result from KE-induced increases in dopamine signaling.

Sleep does not influence schema-facilitated motor memory consolidation.

STUDY OBJECTIVES: Novel information is rapidly learned when it is compatible with previous knowledge. This "schema" effect, initially described for declarative memories, was recently extended to the motor memory domain. Importantly, this beneficial effect was only observed 24 hours-but not immediately-following motor schema acquisition. Given the established role of sleep in memory consolidation, we hypothesized that sleep following the initial learning of a schema is necessary for the subsequent rapid integration of novel motor information. METHODS: Two experiments were conducted to investigate the effect of diurnal and nocturnal sleep on schema-mediated motor sequence memory consolidation. In Experiment 1, participants first learned an 8-element motor sequence through repeated practice (Session 1). They were then afforded a 90-minute nap opportunity (N = 25) or remained awake (N = 25) before learning a second motor sequence (Session 2) which was highly compatible with that learned prior to the sleep/wake interval. Experiment 2 was similar; however, Sessions 1 and 2 were separated by a 12-hour interval that included nocturnal sleep (N = 28) or only wakefulness (N = 29). RESULTS: For both experiments, we found no group differences in motor sequence performance (reaction time and accuracy) following the sleep/wake interval. Furthermore, in Experiment 1, we found no correlation between sleep features (non-REM sleep duration, spindle and slow wave activity) and post-sleep behavioral performance. CONCLUSIONS: The results of this research suggest that integration of novel motor information into a cognitive-motor schema does not specifically benefit from post-learning sleep.

Somatosensory targeted memory reactivation enhances motor performance via hippocampal-mediated plasticity.

Increasing evidence suggests that reactivation of newly acquired memory traces during postlearning wakefulness plays an important role in memory consolidation. Here, we sought to boost the reactivation of a motor memory trace during postlearning wakefulness (quiet rest) immediately following learning using somatosensory targeted memory reactivation (TMR). Using functional magnetic resonance imaging, we examined the neural correlates of the reactivation process as well as the effect of the TMR intervention on brain responses elicited by task practice on 24 healthy young adults. Behavioral data of the post-TMR retest session showed a faster learning rate for the motor sequence that was reactivated as compared to the not-reactivated sequence. Brain imaging data revealed that motor, parietal, frontal, and cerebellar brain regions, which were recruited during initial motor learning, were specifically reactivated during the TMR episode and that hippocampo-frontal connectivity was modulated by the reactivation process. Importantly, the TMR-induced behavioral advantage was paralleled by dynamical changes in hippocampal activity and hippocampo-motor connectivity during task practice. Altogether, the present results suggest that somatosensory TMR during postlearning quiet rest can enhance motor performance via the modulation of hippocampo-cortical responses.

Persistence of hippocampal and striatal multivoxel patterns during awake rest after motor sequence learning.

Memory consolidation, the process by which newly encoded and fragile memories become more robust, is thought to be supported by the reactivation of brain regions - including the hippocampus - during post-learning rest. While hippocampal reactivations have been demonstrated in humans in the declarative memory domain, it remains unknown whether such a process takes place after motor learning. Using multivariate analyses of task-related and resting state fMRI data, here we show that patterns of brain activity within both the hippocampus and striatum elicited during motor learning persist into post-learning rest, indicative of the reactivation of learning-related neural activity patterns. Moreover, results indicate that hippocampal reactivation reflects the spatial representation of the learned motor sequence. These results thus provide insights into the functional significance of neural reactivation after motor sequence learning.

Sigma oscillations protect or reinstate motor memory depending on their temporal coordination with slow waves.

Targeted memory reactivation (TMR) during post-learning sleep is known to enhance motor memory consolidation but the underlying neurophysiological processes remain unclear. Here, we confirm the beneficial effect of auditory TMR on motor performance. At the neural level, TMR enhanced slow wave (SW) characteristics. Additionally, greater TMR-related phase-amplitude coupling between slow (0.5-2 Hz) and sigma (12-16 Hz) oscillations after the SW peak was related to higher TMR effect on performance. Importantly, sounds that were not associated to learning strengthened SW-sigma coupling at the SW trough. Moreover, the increase in sigma power nested in the trough of the potential evoked by the unassociated sounds was related to the TMR benefit. Altogether, our data suggest that, depending on their precise temporal coordination during post learning sleep, slow and sigma oscillations play a crucial role in either memory reinstatement or protection against irrelevant information; two processes that critically contribute to motor memory consolidation.

Connectivity in Large-Scale Resting-State Brain Networks Is Related to Motor Learning: A High-Density EEG Study.

Previous research has shown that resting-state functional connectivity (rsFC) between different brain regions (seeds) is related to motor learning and motor memory consolidation. Using high-density electroencephalography (hdEEG), we addressed this question from a brain network perspective. Specifically, we examined frequency-dependent functional connectivity in resting-state networks from twenty-nine young healthy participants before and after they were trained on a motor sequence learning task. Consolidation was assessed with an overnight retest on the motor task. Our results showed training-related decreases in gamma-band connectivity within the motor network, and between the motor and functionally distinct resting-state networks including the attentional network. Brain-behavior correlation analyses revealed that baseline beta, delta, and theta rsFC were related to subsequent motor learning and memory consolidation such that lower connectivity within the motor network and between the motor and several distinct resting-state networks was correlated with better learning and overnight consolidation. Lastly, training-related increases in beta-band connectivity between the motor and the visual networks were related to greater consolidation. Altogether, our results indicate that connectivity in large-scale resting-state brain networks is related to-and modulated by-motor learning and memory consolidation processes. These finding corroborate previous seed-based connectivity research and provide evidence that frequency-dependent functional connectivity in resting-state networks is critically linked to motor learning and memory consolidation.

Differential Effects of a Nap on Motor Sequence Learning-Related Functional Connectivity Between Young and Older Adults.

In older adults, motor sequence learning (MSL) is largely intact. However, consolidation of newly learned motor sequences is impaired compared to younger adults, and there is evidence that brain areas supporting enhanced consolidation via sleep degrade with age. It is known that brain activity in hippocampal-cortical-striatal areas is important for sleep-dependent, off-line consolidation of motor-sequences. Yet, the intricacies of how both age and sleep alter communication within this network of brain areas, which facilitate consolidation, are not known. In this study, 37 young (age 20-35) and 49 older individuals (age 55-75) underwent resting state functional magnetic resonance imaging (fMRI) before and after training on a MSL task as well as after either a nap or a period of awake rest. Young participants who napped showed strengthening of functional connectivity (FC) between motor, striatal, and hippocampal areas, compared to older subjects regardless of sleep condition. Follow-up analyses revealed this effect was driven by younger participants who showed an increase in FC between striatum and motor cortices, as well as older participants who showed decreased FC between the hippocampus, striatum, and precuneus. Therefore, different effects of sleep were observed in younger vs. older participants, where young participants primarily showed increased communication in the striatal-motor areas, while older participants showed decreases in key nodes of the default mode network and striatum. Performance gains correlated with FC changes in young adults, and this association was much greater in participants who napped compared to those who stayed awake. Performance gains also correlated with FC changes in older adults, but only in those who napped. This study reveals that, while there is no evidence of time-dependent forgetting/deterioration of performance, older adults exhibit a completely different pattern of FC changes during consolidation compared to younger adults, and lose the benefit that sleep affords to memory consolidation.

Prefrontal stimulation prior to motor sequence learning alters multivoxel patterns in the striatum and the hippocampus.

Motor sequence learning (MSL) is supported by dynamical interactions between hippocampal and striatal networks that are thought to be orchestrated by the prefrontal cortex. In the present study, we tested whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex (DLPFC) prior to MSL can modulate multivoxel response patterns in the stimulated cortical area, the hippocampus and the striatum. Response patterns were assessed with multivoxel correlation structure analyses of functional magnetic resonance imaging data acquired during task practice and during resting-state scans before and after learning/stimulation. Results revealed that, across stimulation conditions, MSL induced greater modulation of task-related DLPFC multivoxel patterns than random practice. A similar learning-related modulatory effect was observed on sensorimotor putamen patterns under inhibitory stimulation. Furthermore, MSL as well as inhibitory stimulation affected (posterior) hippocampal multivoxel patterns at post-intervention rest. Exploratory analyses showed that MSL-related brain patterns in the posterior hippocampus persisted into post-learning rest preferentially after inhibitory stimulation. These results collectively show that prefrontal stimulation can alter multivoxel brain patterns in deep brain regions that are critical for the MSL process. They also suggest that stimulation influenced early offline consolidation processes as evidenced by a stimulation-induced modulation of the reinstatement of task pattern into post-learning wakeful rest.

A role for GABA in the modulation of striatal and hippocampal systems under stress.

Previous research has demonstrated that stress modulates the competitive interaction between the hippocampus and striatum, two structures known to be critically involved in motor sequence learning. These earlier investigations, however, have largely focused on blood oxygen-level dependent (BOLD) responses. No study to date has examined the link between stress, motor learning and levels of striatal and hippocampal gamma-aminobutyric acid (GABA). This knowledge gap is surprising given the known role of GABA in neuroplasticity subserving learning and memory. The current study thus examined: a) the effects of motor learning and stress on striatal and hippocampal GABA levels; and b) how learning- and stress-induced changes in GABA relate to the neural correlates of learning. To do so, fifty-three healthy young adults were exposed to a stressful or non-stressful control intervention before motor sequence learning. Striatal and hippocampal GABA levels were assessed at baseline and post-intervention/learning using magnetic resonance spectroscopy. Regression analyses indicated that stress modulated the link between striatal GABA levels and functional plasticity in both the hippocampus and striatum during learning as measured with fMRI. This study provides evidence for a role of GABA in the stress-induced modulation of striatal and hippocampal systems.

Hippocampal and striatal responses during motor learning are modulated by prefrontal cortex stimulation.

While it is widely accepted that motor sequence learning (MSL) is supported by a prefrontal-mediated interaction between hippocampal and striatal networks, it remains unknown whether the functional responses of these networks can be modulated in humans with targeted experimental interventions. The present proof-of-concept study employed a multimodal neuroimaging approach, including functional magnetic resonance (MR) imaging and MR spectroscopy, to investigate whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex can modulate responses in the hippocampus and the basal ganglia during motor learning. Our results indicate that while stimulation did not modulate motor performance nor task-related brain activity, it influenced connectivity patterns within hippocampo-frontal and striatal networks. Stimulation also altered the relationship between the levels of gamma-aminobutyric acid (GABA) in the stimulated prefrontal cortex and learning-related changes in both activity and connectivity in fronto-striato-hippocampal networks. This study provides the first experimental evidence, to the best of our knowledge, that brain stimulation can alter motor learning-related functional responses in the striatum and hippocampus.

Somatosensory Targeted Memory Reactivation Modulates Oscillatory Brain Activity but not Motor Memory Consolidation.

Previous research has shown that targeted memory reactivation (TMR) protocols using acoustic or olfactory stimuli can boost motor memory consolidation. While somatosensory information is crucial for motor control and learning, the effects of somatosensory TMR on motor memory consolidation remain elusive. Here, healthy young adults (n = 28) were trained on a sequential serial reaction time task and received, during the offline consolidation period that followed, sequential electrical stimulation of the fingers involved in the task. This somatosensory TMR procedure was applied during either a 90-minute diurnal sleep (NAP) or wake (NONAP) interval that was monitored with electroencephalography. Consolidation was assessed with a retest following the NAP/NONAP episode. Behavioral results revealed no effect of TMR on motor performance in either of the groups. At the brain level, somatosensory stimulation elicited changes in oscillatory activity in both groups. Specifically, TMR induced an increase in power in the mu band in the NONAP group and in the beta band in both the NAP and NONAP groups. Additionally, TMR elicited an increase in sigma power and a decrease in delta oscillations in the NAP group. None of these TMR-induced modulations of oscillatory activity, however, were correlated with measures of motor memory consolidation. The present results collectively suggest that while somatosensory TMR modulates oscillatory brain activity during post-learning sleep and wakefulness, it does not influence motor performance in an immediate retest.

Movement errors during skilled motor performance engage distinct prediction error mechanisms.

The brain detects deviations from intended behaviors by estimating the mismatch between predicted and actual outcomes. Axiomatic to these computations are salience and valence prediction error signals, which alert the brain to the occurrence and value of unexpected events. Despite the theoretical assertion of these prediction error signals, it is unknown whether and how brain mechanisms underlying their computations support error processing during skilled motor behavior. Here we demonstrate, with functional magnetic resonance imaging, that internal detection, i.e., without externally-provided feedback, of self-generated movement errors evokes instantaneous activity increases within the salience network and delayed lingering decreases within the nucleus accumbens - a key structure in the reward valuation pathway. A widespread suppression within the sensorimotor network was also observed. Our findings suggest that neural computations of salience and valence prediction errors during skilled motor behaviors operate on different time-scales and, therefore, may contribute differentially to immediate and longer-term adaptive processes.

Lateralized effects of post-learning transcranial direct current stimulation on motor memory consolidation in older adults: An fMRI investigation.

Previous research has consistently demonstrated that older adults have difficulties transforming recently learned movements into robust, long-lasting memories (i.e., motor memory consolidation). One potential avenue to enhance consolidation in older individuals is the administration of transcranial direct current stimulation (tDCS) to task-relevant brain regions after initial learning. Although this approach has shown promise, the underlying cerebral correlates have yet to be revealed. Moreover, it is unknown whether the effects of tDCS are lateralized, an open question with implications for rehabilitative approaches following predominantly unilateral neurological injuries. In this research, healthy older adults completed a sequential motor task before and 6 h after receiving anodal or sham stimulation to right or left primary motor cortex (M1) while functional magnetic resonance images were acquired. Unexpectedly, anodal stimulation to right M1 following left-hand sequence learning significantly hindered consolidation as compared to a sham control, whereas no differences were observed with left M1 stimulation following right-hand learning. Impaired performance following right M1 stimulation was paralleled by sustained engagement of regions known to be critical for early learning stages, including the caudate nucleus and the premotor and parietal cortices. Thus, post-learning tDCS in older adults not only exerts heterogenous effects across the two hemispheres but can also disrupt ongoing memory processing.

Baseline sensorimotor GABA levels shape neuroplastic processes induced by motor learning in older adults.

Previous research in young adults has demonstrated that both motor learning and transcranial direct current stimulation (tDCS) trigger decreases in the levels of gamma-aminobutyric acid (GABA) in the sensorimotor cortex, and these decreases are linked to greater learning. Less is known about the role of GABA in motor learning in healthy older adults, a knowledge gap that is surprising given the established aging-related reductions in sensorimotor GABA. Here, we examined the effects of motor learning and subsequent tDCS on sensorimotor GABA levels and resting-state functional connectivity in the brains of healthy older participants. Thirty-six older men and women completed a motor sequence learning task before receiving anodal or sham tDCS to the sensorimotor cortex. GABA-edited magnetic resonance spectroscopy of the sensorimotor cortex and resting-state (RS) functional magnetic resonance imaging data were acquired before and after learning/stimulation. At the group level, neither learning nor anodal tDCS significantly modulated GABA levels or RS connectivity among task-relevant regions. However, changes in GABA levels from the baseline to post-learning session were significantly related to motor learning magnitude, age, and baseline GABA. Moreover, the change in functional connectivity between task-relevant regions, including bilateral motor cortices, was correlated with baseline GABA levels. These data collectively indicate that motor learning-related decreases in sensorimotor GABA levels and increases in functional connectivity are limited to those older adults with higher baseline GABA levels and who learn the most. Post-learning tDCS exerted no influence on GABA levels, functional connectivity or the relationships among these variables in older adults.

The role of the PMd in task complexity: functional connectivity is modulated by motor learning and age.

The dorsal premotor cortex (PMd) plays a key role in the control and learning of motor tasks, especially when task complexity is high. This study sought to investigate the effect of task complexity on PMd-seeded functional connectivity in the context of aging using psychophysiological interaction analyses. Young and older participants were enrolled in a 3-day training protocol whereby task-related functional magnetic resonance imaging data were acquired. During training, movement was either internally generated or externally generated in the absence or presence of online visual feedback, respectively. Behavioral results indicated that older adults tended to have more difficulties with the complex task variants as compared with young adults. On a neural level, older adults demonstrated difficulties in flexibly adjusting their neural resources dependent on the feedback provided. Furthermore, PMd-seeded connectivity was related to a behavioral task complexity index in both age groups, albeit mediated by age. Together, these results highlight the importance of PMd in adaptability to task complexity and its age-related effects.

Weaker Inter-hemispheric and Local Functional Connectivity of the Somatomotor Cortex During a Motor Skill Acquisition Is Associated With Better Learning.

Recently, an increasing interest in investigating interactions between brain regions using functional connectivity (FC) methods has shifted the initial focus of cognitive neuroimaging research from localizing functional circuits based on task activation to mapping brain networks based on intrinsic FC dynamics. Leveraging the advantages of the latter approach, it has been shown that despite primarily invariant intrinsic organization of the large-scale functional networks, interactions between and within these networks significantly differ between various behavioral and cognitive states. These differences presumably indicate transient reconfiguration of functional connections-an instantaneous process that flexibly mediates and calibrates human behavior according to momentary demands of the environment. Nevertheless, the specificity of these reconfigured FC patterns to the task at hand and their relevance to adaptive processes during learning remain elusive. To address this knowledge gap, we investigated (1) to what extent FC within the somatomotor network is reconfigured during motor skill practice, and (2) how these changes are related to learning. We applied a seed-driven FC approach to data collected during a continuous task-free condition, so-called resting state, and during a motor sequence learning task using functional magnetic resonance imaging. During the task, participants repeatedly performed a short five-element sequence with their non-dominant (left) hand. As predicted, such unimanual sequence production was associated with lateralized activation of the right somatomotor cortex (SMC). Using this "active" region as a seed, here we show that unimanual performance of the motor sequence relies on functional segregation between the two SMC and selective integration between the "active" SMC and supplementary motor area. Whereas, greater segregation between the two SMC was associated with gains in performance rate, greater segregation within the "active" SMC itself was associated with more consistent performance by the end of training. Nether the resting-state FC patterns within the somatomotor network nor their relative modulation by the task state predicted these behavioral benefits of learning. Our results suggest that task-induced FC changes reflect reconfiguration of the connectivity patterns within the somatomotor network rather than a simple amplification or silencing of its intrinsic dynamics. Such reconfiguration not only supports motor behavior but may also predict learning.