Predictive coding, multisensory integration, and attentional control: A multicomponent framework for lucid dreaming.

Lucid dreaming (LD) is a mental state in which we realize not being awake but are dreaming while asleep. It often involves vivid, perceptually intense dream images as well as peculiar kinesthetic sensations, such as flying, levitating, or out-of-body experiences. LD is in the cross-spotlight of cognitive neuroscience and sleep research as a particular case to study consciousness, cognition, and the neural background of dream experiences. Here, we present a multicomponent framework for the study and understanding of neurocognitive mechanisms and phenomenological aspects of LD. We propose that LD is associated with prediction error signals arising during sleep and occurring at higher or lower levels of the processing hierarchy. Prediction errors are resolved by generating a superordinate self-model able to integrate ambiguous stimuli arriving from sensory periphery and higher-order cortical regions. While multisensory integration enables lucidity maintenance and contributes to peculiar kinesthetic experiences, attentional control facilitates multisensory integration by dynamically regulating the balance between the influence of top-down mental models and the precision weighting of bottom-up sensory inputs. Our novel framework aims to link neural correlates of LD with current concepts of sleep and arousal regulation and provide testable predictions on interindividual differences in LD as well as neurocognitive mechanisms inducing lucid dreams.

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.

Sleep-dependent structural neuroplasticity after a spatial navigation task: A diffusion imaging study.

Evidence for sleep-dependent changes in microstructural neuroplasticity remains scarce, despite the fact that it is a mandatory correlate of the reorganization of learning-related functional networks. We investigated the effects of post-training sleep on structural neuroplasticity markers measuring standard diffusion tensor imaging (DTI), mean diffusivity (MD), and the revised biophysical neurite orientation dispersion and density imaging (NODDI), free water fraction (FWF), and neurite density (NDI) parameters that enable disentangling whether MD changes result from modifications in neurites or in other cellular components (e.g., glial cells). Thirty-four healthy young adults were scanned using diffusion-weighted imaging (DWI) on Day1 before and after 40-min route learning (navigation) in a virtual environment, then were sleep deprived (SD) or slept normally (RS) for the night. After recovery sleep for 2 nights, they were scanned again (Day4) before and after 40-min route learning (navigation) in an extended environment. Sleep-related microstructural changes were computed on DTI (MD) and NODDI (NDI and FWF) parameters in the cortical ribbon and subcortical hippocampal and striatal regions of interest (ROIs). Results disclosed navigation learning-related decreased DWI parameters in the cortical ribbon (MD, FWF) and subcortical (MD, FWF, NDI) areas. Post-learning sleep-related changes were found at Day4 in the extended learning session (pre- to post-relearning percentage changes), suggesting a rapid sleep-related remodeling of neurites and glial cells subtending learning and memory processes in basal ganglia and hippocampal structures.

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.

Partially Preserved Processing of Musical Rhythms in REM but Not in NREM Sleep.

The extent of high-level perceptual processing during sleep remains controversial. In wakefulness, perception of periodicities supports the emergence of high-order representations such as the pulse-like meter perceived while listening to music. Electroencephalography (EEG) frequency-tagged responses elicited at envelope frequencies of musical rhythms have been shown to provide a neural representation of rhythm processing. Specifically, responses at frequencies corresponding to the perceived meter are enhanced over responses at meter-unrelated frequencies. This selective enhancement must rely on higher-level perceptual processes, as it occurs even in irregular (i.e., syncopated) rhythms where meter frequencies are not prominent input features, thus ruling out acoustic confounds. We recorded EEG while presenting a regular (unsyncopated) and an irregular (syncopated) rhythm across sleep stages and wakefulness. Our results show that frequency-tagged responses at meter-related frequencies of the rhythms were selectively enhanced during wakefulness but attenuated across sleep states. Most importantly, this selective attenuation occurred even in response to the irregular rhythm, where meter-related frequencies were not prominent in the stimulus, thus suggesting that neural processes selectively enhancing meter-related frequencies during wakefulness are weakened during rapid eye movement (REM) and further suppressed in non-rapid eye movement (NREM) sleep. These results indicate preserved processing of low-level acoustic properties but limited higher-order processing of auditory rhythms during sleep.

Recent advances in memory consolidation and information processing during sleep.

Increasingly studied in a systematic manner since the 1970s, the cognitive processes of the brain taking place during sleeping periods remain an important object of scrutiny in the scientific community. In particular, sleep has been demonstrated to play a significant role for learning and memory consolidation processes, and sleep scientists have started unravelling its underlying neurophysiological mechanisms. However, sleep remains a multidimensional phenomenon, and many questions remain left open for future research. In this selective review article, we address recent advances in particular domains in which sleep research has further progressed in the past decade. We highlight the developmental trajectory of sleep-dependent learning and memory consolidation processes, from their development in childhood to their potential impairments in ageing, and the nature and extent of our capabilities for information processing, learning, and memory reinforcement during sleep.

Localization accuracy of a common beamformer for the comparison of two conditions.

The linearly constrained minimum variance beamformer is frequently used to reconstruct sources underpinning neuromagnetic recordings. When reconstructions must be compared across conditions, it is considered good practice to use a single, "common" beamformer estimated from all the data at once. This is to ensure that differences between conditions are not ascribable to differences in beamformer weights. Here, we investigate the localization accuracy of such a common beamformer. Based on theoretical derivations, we first show that the common beamformer leads to localization errors in source reconstruction. We then turn to simulations in which we attempt to reconstruct a (genuine) source in a first condition, while considering a second condition in which there is an (interfering) source elsewhere in the brain. We estimate maps of mislocalization and assess statistically the difference between "standard" and "common" beamformers. We complement our findings with an application to experimental MEG data. The results show that the common beamformer may yield significant mislocalization. Specifically, the common beamformer may force the genuine source to be reconstructed closer to the interfering source than it really is. As the same applies to the reconstruction of the interfering source, both sources are pulled closer together than they are. This observation was further illustrated in experimental data. Thus, although the common beamformer allows for the comparison of conditions, in some circumstances it introduces localization inaccuracies. We recommend alternative approaches to the general problem of comparing conditions.

Sleep medicine catalogue of knowledge and skills - Revision.

The 'catalogue of knowledge and skills' for sleep medicine presents the blueprint for a curriculum, a textbook, and an examination on sleep medicine. The first catalogue of knowledge and skills was presented by the European Sleep Research Society in 2014. It was developed following a formal Delphi procedure. A revised version was needed in order to incorporate changes that have occurred in the meantime in the International Classification of Sleep Disorders, updates in the manual for scoring sleep and associated events, and, most important, new knowledge in sleep physiology and pathophysiology. In addition, another major change can be observed in sleep medicine: a paradigm shift in sleep medicine has taken place. Sleep medicine is no longer a small interdisciplinary field in medicine. Sleep medicine has increased in terms of recognition and importance in medical care. Consequently, major medical fields (e.g. pneumology, cardiology, neurology, psychiatry, otorhinolaryngology, paediatrics) recognise that sleep disorders become a necessity for education and for diagnostic assessment in their discipline. This paradigm change is considered in the catalogue of knowledge and skills revision by the addition of new chapters.

Is an irritable ADHD profile traceable using personality dimensions? Replicability, stability, and predictive value over time of data-driven profiles.

Pediatric attention deficit/hyperactivity disorder (ADHD) is a heterogeneous condition. In particular, children with ADHD display varying profiles of dispositional traits, as assessed through temperament and personality questionnaires. Previous data-driven community detection analyses based on temperament dimensions identified an irritable profile of patients with ADHD, uniquely characterized by elevated emotional dysregulation symptoms. Belonging to this profile increased the risk of developing comorbid disorders. Here, we investigated whether we could replicate this profile in a sample of 178 children with ADHD, using community detection based on personality dimensions. Stability of the identified profiles, of individual classifications, and clinical prediction were longitudinally assessed over a 1-year interval. Three personality profiles were detected: The first two profiles had high levels of neuroticism, with the first displaying higher ADHD severity and lower openness to experience (profile 1; N = 38), and the second lower agreeableness (profile 2; N = 73). The third profile displayed scores closer to the normative range on all five factors (profile 3; N = 67). The identified profiles did only partially replicate the temperament-based profiles previously reported, as higher levels of neuroticism were found in two of the three detected profiles. Nonetheless, despite changes in individual classifications, the profiles themselves were highly stable over time and of clinical predictive value. Whereas children belonging to profiles 1 and 2 benefited from starting medication, children in profile 3 did not. Hence, belonging to an emotionally dysregulated profile at baseline predicted the effect of medication at follow-up over and above initial ADHD symptom severity. This finding suggests that personality profiles could play a role in predicting treatment response in ADHD.

Sleep deprivation increases threat beliefs in human fear conditioning.

Sleep disturbances and anxiety disorders exhibit high comorbidity levels, but it remains unclear whether sleep problems are causes or consequences of increased anxiety. To experimentally probe the aetiological role of sleep disturbances in anxiety, we investigated in healthy participants how total sleep deprivation influences fear expression in a conditioning paradigm. In a fear conditioning procedure, one face stimulus (conditioned stimulus [CS+]) was paired with electric shock, whereas another face stimulus was not (unpaired stimulus [CS-]). Fear expression was tested the next morning using the two face stimuli from the training phase and a generalization stimulus (i.e. a morph between the CS+ and CS- stimuli). Between fear conditioning and test, participants were either kept awake in the laboratory for 12 hr (n = 20) or had a night of sleep at home (n = 20). Irrespective of stimulus type, subjective threat expectancies, but not skin conductance responses, were enhanced after sleep deprivation, relative to regular sleep. These results suggest that sleep disturbances may play a role in anxiety disorders by increasing perceived threat.

Do the posterior midline cortices belong to the electrophysiological default-mode network?

The default-mode network (DMN) and its principal core hubs in the posterior midline cortices (PMC), i.e., the precuneus and the posterior cingulate cortex, play a critical role in the human brain structural and functional architecture. Because of their centrality, they are affected by a wide spectrum of brain disorders, e.g., Alzheimer's disease. Non-invasive electrophysiological techniques such as magnetoencephalography (MEG) are crucial to the investigation of the neurophysiology of the DMN and its alteration by brain disorders. However, MEG studies relying on band-limited power envelope correlation diverge in their ability to identify the PMC as a part of the DMN in healthy subjects at rest. Since these works were based on different MEG recording systems and different source reconstruction pipelines, we compared DMN functional connectivity estimated with two distinct MEG systems (Elekta, now MEGIN, and CTF) and two widely used reconstruction algorithms (Minimum Norm Estimation and linearly constrained minimum variance Beamformer). Our results identified the reconstruction method as the critical factor influencing PMC functional connectivity, which was significantly dampened by the Beamformer. On this basis, we recommend that future electrophysiological studies on the DMN should rely on Minimum Norm Estimation (or close variants) rather than on the classical Beamformer. Crucially, based on analytic knowledge about these two reconstruction algorithms, we demonstrated with simulations that this empirical observation could be explained by the existence of a spontaneous linear, approximately zero-lag synchronization structure between areas of the DMN or among multiple sources within the PMC. This finding highlights a novel property of the neural dynamics and functional architecture of a core human brain network at rest.

Synchrony, metastability, dynamic integration, and competition in the spontaneous functional connectivity of the human brain.

The human brain is functionally organized into large-scale neural networks that are dynamically interconnected. Multiple short-lived states of resting-state functional connectivity (rsFC) identified transiently synchronized networks and cross-network integration. However, little is known about the way brain couplings covary as rsFC states wax and wane. In this magnetoencephalography study, we explore the synchronization structure among the spontaneous interactions of well-known resting-state networks (RSNs). To do so, we extracted modes of dynamic coupling that reflect rsFC synchrony and analyzed their spatio-temporal features. These modes identified transient, sporadic rsFC changes characterized by the widespread integration of RSNs across the brain, most prominently in the ß band. This is in line with the metastable rsFC state model of resting-state dynamics, wherein our modes fit as state transition processes. Furthermore, the default-mode network (DMN) stood out as being structured into competitive cross-network couplings with widespread DMN-RSN interactions, especially among the ß-band modes. These results substantiate the theory that the DMN is a core network enabling dynamic global brain integration in the ß band.

Subjectively-defined optimal/non-optimal time of day modulates controlled but not automatic retrieval processes in verbal memory.

Performance for controlled, resource-demanding retrieval in episodic memory has been consistently found to be better at an optimal compared with non-optimal time of the day, evidencing a synchrony effect. However, performance in memory tasks in which retrieval is mostly based on automatic processes was inconclusively found either to be better at a non-optimal time of day or independent of synchrony effects. A caveat in most prior studies is that optimal/non-optimal time of day is based on morningness-eveningness composite scores derived from chronotype questionnaires, which might not efficiently predict subjectively-defined cognitive efficiency periods. An additional caveat is that separate tasks are used to assess explicit and implicit retrieval in verbal memory. Indeed, no task is process-pure, and both controlled and automatic retrieval processes may potentially contribute to retrieval scores in different types of memory tasks. In the present study, we investigated the impact of individually defined subjective optimal/non-optimal time of day on verbal memory retrieval, using an adaptation of the Process-Dissociation Procedure that allows estimating the respective contributions of automatic and controlled memory retrieval processes within the same memory task. Our results disclose a higher involvement of controlled processes at subjectively optimal compared with non-optimal time of day, but no differences for automatic processes. Synchrony effects and subjectively-defined peaks and troughs of performance for controlled components of memory retrieval should be considered in the evaluation of episodic memory.

Developmental changes of sleep spindles and their impact on sleep-dependent memory consolidation and general cognitive abilities: A longitudinal approach.

Sleep spindles are related to sleep-dependent memory consolidation and general cognitive abilities. However, they undergo drastic maturational changes during adolescence. Here we used a longitudinal approach (across 7 years) to explore whether developmental changes in sleep spindle density can explain individual differences in sleep-dependent memory consolidation and general cognitive abilities. Ambulatory polysomnography was recorded during four nights in 34 healthy subjects (24 female) with two nights (baseline and experimental) at initial recording (age range 8-11 years) and two nights at follow-up recording (age range 14-18 years). For declarative learning, participants encoded word pairs with a subsequent recall before and after sleep. General cognitive abilities were measured by the Wechsler Intelligence Scale. Higher slow (11-13 Hz) than fast (13-15 Hz) spindle density at frontal, central, and parietal sites during initial recordings, followed by a shift to higher fast than slow spindle density at central and parietal sites during follow-up recordings, suggest that mature spindle topography develops throughout adolescence. Fast spindle density increases from baseline to experimental night were positively related to sleep-dependent memory consolidation. In addition, we found that the development of fast spindles predicted the improvement in memory consolidation across the two longitudinal measurements, a finding that underlines a crucial role for mature fast spindles for sleep-dependent memory consolidation. Furthermore, slow spindle changes across adolescence were related to general cognitive abilities, a relationship that could indicate the maturation of frontal networks relevant for efficient cognitive processing. A video abstract of this article can be viewed at: https://www.youtube.com/watch?v=7NXJzm8HbIw and https://www.youtube.com/watch?v=iuMQY1OIJ0s.

Applications of Functional Near-Infrared Spectroscopy in Fatigue, Sleep Deprivation, and Social Cognition.

Functional near-infrared spectroscopy (fNIRS) is an optical diffusion technique that allows the non-invasive imaging of cortical activity. During the last two decades, rapid technical and methodological advances have made fNIRS a powerful tool to investigate the cerebral correlates of human performance and cognitive functions, including fatigue, sleep deprivation and social cognition. Despite intrinsic limitations such as restricted brain depth and spatial resolution, its applicability, low cost, ecological validity, and tolerance to movements make fNIRS advantageous for scientific research and clinical applications. It can be viewed as a valid and promising brain imaging approach to investigate applied societal problems (e.g., safety, children development, sport science) and complement other neuroimaging techniques. The intrinsic power of fNIRS measurements for the study of social cognition is magnified when applied to the hyperscanning paradigm (i.e., measuring activity in two or more brains simultaneously). Besides consolidating existing findings, future fNIRS research should focus on methodological advances (e.g., artefacts correction, connectivity approaches) and standardization of analysis pipelines, and expand currently used paradigms in more naturalistic but controlled settings.

Sleep-behaviour relationship in children with autism spectrum disorder: methodological pitfalls and insights from cognition and sensory processing.

Sleep disturbances are frequent and varied in autism spectrum disorder (ASD). Growing evidence suggests that sleep problems in children with ASD are driven by their clinical characteristics and psychiatric comorbidities. Therefore, the wide range of reported sleep disturbances reflects the marked heterogeneity of clinical pictures in ASD. Whether sleep disturbances and their various forms may, in turn, account for at least part of the phenotypical variability of ASD is a crucial question discussed in this review. We first outline studies both validating and challenging a bidirectional theoretical framework for sleep disorders in children with ASD. We then propose to extend this model by including cognition and sensory processing as key factors in the vicious circle linking sleep disorders and autistic symptoms. WHAT THIS PAPER ADDS: There is a bidirectional interplay between autism symptoms and sleep disturbances. Sleep influence on daytime cognitive and sensory skills should be further investigated.

RELACIÓN ENTRE EL SUEÑO Y LA CONDUCTA EN NIÑOS CON TRASTORNO DEL ESPECTRO AUTISTA: DIFICULTADES METODOLÓGICAS Y CONOCIMIENTOS DE LA COGNICIÓN Y EL PROCESAMIENTO SENSORIAL: Los trastornos del sueño son frecuentes y variados en el trastorno del espectro autista (TEA). La creciente evidencia sugiere que los problemas del sueño en niños con TEA se deben a sus características clínicas y comorbilidades psiquiátricas. Por lo tanto, la amplia gama de trastornos del sueño reportados refleja la marcada heterogeneidad de los cuadros clínicos en TEA. En esta revisión se analiza si las alteraciones del sueño y sus diversas formas pueden, a su vez, explicar al menos parte de la variabilidad fenotípica del TEA. Primero, resumimos los estudios que validan y desafían un marco teórico bidireccional para los trastornos del sueño en niños con TEA. Luego, proponemos extender este modelo incluyendo la cognición y el procesamiento sensorial como factores clave en el círculo vicioso que vincula los trastornos del sueño y los síntomas presentes en el TEA.

RELAÇÃO ENTRE SONO E COMPORTAMENTO EM CRIANÇAS COM TRANSTORNO DO ESPECTRO AUTISTA: DESAFIOS METODOLÓGICOS E DESCOBERTAS A PARTIR DO PROCESSAMENTO SENSORIAL E COGNIÇÃO: Distúrbios do sono são frequentes e variados no transtorno do espectro autista (TEA). Crescente evidência sugere que problemas de sono em crianças com TEA são causados por características clínicas e comorbidades psiquiátricas. Portanto, a ampla variedade de distúrbios do sono reportados refletem a notável heterogeneidade dos quadros clínicos em TEA. Se os distúrbios do sono podem, por sua vez, responder por pelo menos uma parte da variabilidade fenotípica do TEA é uma questão crucial a ser discutida nesta revisão. Primeiro, nós delineamos estudos que validam e outros que desafiam uma abordagem teórica bidirectional para os distúrbios do sono em crianças com TEA. Então, propomos uma extensão deste modelo, incluindo a cognição e o processamento sensorial como fatores chave no ciclo vicioso que liga desordens do sono e sintomas autísticos.

The impact of sleep deprivation on visual perspective taking.

Total sleep deprivation (TSD) is known to alter cognitive processes. Surprisingly little attention has been paid to its impact on social cognition. Here, we investigated whether TSD alters levels-1 and -2 visual perspective-taking abilities, i.e. the capacity to infer (a) what can be seen and (b) how it is seen from another person's visual perspective, respectively. Participants completed levels-1 and -2 visual perspective-taking tasks after a night of sleep and after a night of TSD. In these tasks, participants had to take their own (self trials) or someone else's (other trials) visual perspective in trials where both perspectives were either the same (consistent trials) or different (inconsistent trials). An instruction preceding each trial indicated the perspective to take (i.e. the relevant perspective). Results show that TSD globally deteriorates social performance. In the level-1 task, TSD affects the selection of relevant over irrelevant perspectives. In the level-2 task, the effect of TSD cannot be unequivocally explained. This implies that visual perspective taking should be viewed as partially state-dependent, rather than a wholly static trait-like characteristic.

Resting-state Functional Connectivity is an Age-dependent Predictor of Motor Learning Abilities.

This magnetoencephalography study investigates how ageing modulates the relationship between pre-learning resting-state functional connectivity (rsFC) and subsequent learning. Neuromagnetic resting-state activity was recorded 5 min before motor sequence learning in 14 young (19-30 years) and 14 old (66-70 years) participants. We used a seed-based beta-band power envelope correlation approach to estimate rsFC maps, with the seed located in the right primary sensorimotor cortex. In each age group, the relation between individual rsFC and learning performance was investigated using Pearson's correlation analyses. Our results show that rsFC is predictive of subsequent motor sequence learning but involves different cross-network interactions in the two age groups. In young adults, decreased coupling between the sensorimotor network and the cortico-striato-cerebellar network is associated with better motor learning, whereas a similar relation is found in old adults between the sensorimotor, the dorsal-attentional and the DMNs. Additionally, age-related correlational differences were found in the dorsolateral prefrontal cortex, known to subtend attentional and controlled processes. These findings suggest that motor skill learning depends-in an age-dependent manner-on subtle interactions between resting-state networks subtending motor activity on the one hand, and controlled and attentional processes on the other hand.

Age-related differences in practice-dependent resting-state functional connectivity related to motor sequence learning.

Decreased neural plasticity is observed with healthy ageing in the primary sensorimotor (SM1) cortex thought to participate in motor learning and memory consolidation processes. In the present magnetoencephalography study, the post-training reorganization of resting-state functional connectivity (rsFC) and its relation with motor learning and early consolidation in 14 young (19-30 years) and 14 old (66-70 years) healthy participants were investigated. At the behavioral level, participants were trained on a motor sequence learning task then retested 20-30 min later for transient offline gains in performance. Using a sensorimotor seed-based approach, rsFC relying on beta band power envelope correlation was estimated immediately before and 10 min after the learning episode. Post-training changes in rsFC (from before to after learning) were correlated with motor learning performance and with the offline improvement in performance within the hour after learning. Young and old participants exhibited differential patterns of sensorimotor-related rsFC, bearing specific relationships with motor learning and consolidation. Our findings suggest that rsFC changes following learning reflect the offline processing of the new motor skill and contribute to the early memory consolidation within the hour after learning. Furthermore, differences in post-training changes in rsFC between young and old participants support the hypothesis that ageing modulates the neural circuits underlying the learning of a new motor skill and the early subsequent consolidation stages. Hum Brain Mapp 38:923-937, 2017. © 2016 Wiley Periodicals, Inc.

Auditory Magnetoencephalographic Frequency-Tagged Responses Mirror the Ongoing Segmentation Processes Underlying Statistical Learning.

Humans are highly sensitive to statistical regularities in their environment. This phenomenon, usually referred as statistical learning, is most often assessed using post-learning behavioural measures that are limited by a lack of sensibility and do not monitor the temporal dynamics of learning. In the present study, we used magnetoencephalographic frequency-tagged responses to investigate the neural sources and temporal development of the ongoing brain activity that supports the detection of regularities embedded in auditory streams. Participants passively listened to statistical streams in which tones were grouped as triplets, and to random streams in which tones were randomly presented. Results show that during exposure to statistical (vs. random) streams, tritone frequency-related responses reflecting the learning of regularities embedded in the stream increased in the left supplementary motor area and left posterior superior temporal sulcus (pSTS), whereas tone frequency-related responses decreased in the right angular gyrus and right pSTS. Tritone frequency-related responses rapidly developed to reach significance after 3 min of exposure. These results suggest that the incidental extraction of novel regularities is subtended by a gradual shift from rhythmic activity reflecting individual tone succession toward rhythmic activity synchronised with triplet presentation, and that these rhythmic processes are subtended by distinct neural sources.