Long-term effects of motor training on resting-state networks and underlying brain structure

Long-term motor training enhances functional connectivity between semantic and motor regions in an effector-specific manner: evidence from elite female football athletes

The relation between the action verb semantic processing and sensorimotor experience remains controversial. In this study, we examined whether plasticity changes in brain are specifically related to semantic processing of foot action verbs when long-term motor training is mainly aimed at the foot. To address this question, we acquired resting-state functional magnetic resonance imaging scans and behavioral data from a verb two-choice task from female expertise football players and football novices. We compared the resting-state functional connectivity (rsFC) differences between experts and novices using motor execution regions and general semantic regions (left anterior temporal lobe, lATL) as seed, and explored the neural correlates of behavioral performance. Here, the drift rate (v) parameter of the drift diffusion model (DDM) was used to capture the semantic processing capability. We found experts showed increased correlation between lATL subregions and important brain regions for motor processing, including supplementary motor area (SMA), bilateral paracentral lobule (PL), superior parietal lobule and inferior parietal lobule, in contrast to novices. Further predictive model analysis showed the FC found in rsFC analysis can significantly predict drift rate of foot action verb in both experts and novices, but not drift rate of hand action verb. Our findings therefore establish a connection between effector-related semantic processing and the plasticity changes in brain functional connectivity, attributable to long-term foot-related motor training. This provides evidence supporting the view that semantic processing is fundamentally rooted in the sensorimotor system.

Higher surface folding of the human premotor cortex is associated with better long-term learning capability

The capacity to learn enabled the human species to adapt to various challenging environmental conditions and pass important achievements on to the next generation. A growing body of research suggests links between neocortical folding properties and numerous aspects of human behavior, but their impact on enhanced human learning capacity remains unexplored. Here we leverage three training cohorts to demonstrate that higher levels of premotor cortical folding reliably predict individual long-term learning gains in a challenging new motor task, above and beyond initial performance differences. Individual folding-related predisposition to motor learning was found to be independent of cortical thickness and intracortical microstructure, but dependent on larger cortical surface area in premotor regions. We further show that learning-relevant features of cortical folding occurred in close spatial proximity to practice-induced structural brain plasticity. Our results suggest a link between neocortical surface folding and human behavioral adaptability.

Encoding Manual Dexterity through Modulation of Intrinsic α Band Connectivity

The human hand possesses both consolidated motor skills and remarkable flexibility in adapting to ongoing task demands. However, the underlying mechanisms by which the brain balances stability and flexibility remain unknown. In the absence of external input or behavior, spontaneous (intrinsic) brain connectivity is thought to represent a prior of stored memories. In this study, we investigated how manual dexterity modulates spontaneous functional connectivity in the motor cortex during hand movement. Using magnetoencephalography, in 47 human participants (both sexes), we examined connectivity modulations in the α and β frequency bands at rest and during two motor tasks (i.e., finger tapping or toe squeezing). The flexibility and stability of such modulations allowed us to identify two groups of participants with different levels of performance (high and low performers) on the nine-hole peg test, a test of manual dexterity. In the α band, participants with higher manual dexterity showed distributed decreases of connectivity, specifically in the motor cortex, increased segregation, and reduced nodal centrality. Participants with lower manual dexterity showed an opposite pattern. Notably, these patterns from the brain to behavior are mirrored by results from behavior to the brain. Indeed, when participants were divided using the median split of the dexterity score, we found the same connectivity patterns. In summary, this experiment shows that a long-term motor skill-manual dexterity-influences the way the motor systems respond during movements.

A longitudinal study of the effect of visuomotor learning on functional brain connectivity

Neural adaptation in the frontoparietal and motor cortex-sensorimotor circuits is crucial for acquiring visuomotor skills. However, the specific nature of highly dynamic neural connectivity in these circuits during the acquisition of visuomotor skills remains unclear. To achieve a more comprehensive understanding of the relationship between acquisition of visuomotor skills and neural connectivity, we used electroencephalographic coherence to capture highly dynamic nature of neural connectivity. We recruited 60 male novices who were randomly assigned to either the experimental group (EG) or the control group (CG). Participants in EG were asked to engage in repeated putting practice, but CG did not engage in golf practice. In addition, we analyzed the connectivity by using 8-13 Hz imaginary inter-site phase coherence in the frontoparietal networks (Fz-P3 and Fz-P4) and the motor cortex-sensorimotor networks (Cz-C3 and Cz-C4) during a golf putting task. To gain a deeper understanding of the dynamic nature of learning trajectories, we compared data at three time points: baseline (T1), 50% improvement from baseline (T2), and 100% improvement from baseline (T3). The results primarily focused on EG, an inverted U-shaped coherence curve was observed in the connectivity of the left motor cortex-sensorimotor circuit, whereas an increase in the connectivity of the right frontoparietal circuit from T2 to T3 was revealed. These results imply that the dynamics of cortico-cortical communication, particularly involving the left motor cortex-sensorimotor and frontal-left parietal circuits. In addition, our findings partially support Hikosaka et al.'s model and provide additional insight into the specific role of these circuits in visuomotor learning.

Microbiota-gut-brain axis: the mediator of exercise and brain health

The brain controls the nerve system, allowing complex emotional and cognitive activities. The microbiota-gut-brain axis is a bidirectional neural, hormonal, and immune signaling pathway that could link the gastrointestinal tract to the brain. Over the past few decades, gut microbiota has been demonstrated to be an essential component of the gastrointestinal tract that plays a crucial role in regulating most functions of various body organs. The effects of the microbiota on the brain occur through the production of neurotransmitters, hormones, and metabolites, regulation of host-produced metabolites, or through the synthesis of metabolites by the microbiota themselves. This affects the host's behavior, mood, attention state, and the brain's food reward system. Meanwhile, there is an intimate association between the gut microbiota and exercise. Exercise can change gut microbiota numerically and qualitatively, which may be partially responsible for the widespread benefits of regular physical activity on human health. Functional magnetic resonance imaging (fMRI) is a non-invasive method to show areas of brain activity enabling the delineation of specific brain regions involved in neurocognitive disorders. Through combining exercise tasks and fMRI techniques, researchers can observe the effects of exercise on higher brain functions. However, exercise's effects on brain health via gut microbiota have been little studied. This article reviews and highlights the connections between these three interactions, which will help us to further understand the positive effects of exercise on brain health and provide new strategies and approaches for the prevention and treatment of brain diseases.

Effects of square dance exercise on cognitive function in elderly individuals with mild cognitive impairment: the mediating role of balance ability and executive function

BACKGROUND

Square dancing is a kind of aerobic fitness exercise without environmental restrictions that yields many benefits for physical and mental health; this exercise is popular among middle-aged and elderly people in China and in these populations in other countries. This study aimed to evaluate the effects of square dance exercise on the overall cognitive function of elderly individuals with mild cognitive impairment (MCI) and to research its mechanisms.

METHODS

A total of 60 elderly people with MCI (60-69 years old) without square dance experience were selected and randomly divided into an experimental group (n = 30) and a control group (n = 30). The experimental group participated in square dance exercise for 12 weeks, while the control group maintained their original lifestyle habits. One week before and after the intervention period, the overall cognitive function, physical fitness, and executive function of both groups were measured.

RESULTS

According to the results, square dance exercise directly improved the overall cognitive function of elderly individuals with MCI and indirectly affected overall cognitive function through the mediating effects of balance ability and executive function.

CONCLUSIONS

Square dance exercise represents a nonpharmacological intervention for the prevention and treatment of MCI. Importantly, it is best to combine this exercise with other forms of physical exercise and comprehensive treatment programs such as cognitive training, social interaction, and psychological intervention to realize its maximum effect.

Examining the association between posttraumatic stress disorder and disruptions in cortical networks identified using data-driven methods

Posttraumatic stress disorder (PTSD) is associated with lower cortical thickness (CT) in prefrontal, cingulate, and insular cortices in diverse trauma-affected samples. However, some studies have failed to detect differences between PTSD patients and healthy controls or reported that PTSD is associated with greater CT. Using data-driven dimensionality reduction, we sought to conduct a well-powered study to identify vulnerable networks without regard to neuroanatomic boundaries. Moreover, this approach enabled us to avoid the excessive burden of multiple comparison correction that plagues vertex-wise methods. We derived structural covariance networks (SCNs) by applying non-negative matrix factorization (NMF) to CT data from 961 PTSD patients and 1124 trauma-exposed controls without PTSD. We used regression analyses to investigate associations between CT within SCNs and PTSD diagnosis (with and without accounting for the potential confounding effect of trauma type) and symptom severity in the full sample. We performed additional regression analyses in subsets of the data to examine associations between SCNs and comorbid depression, childhood trauma severity, and alcohol abuse. NMF identified 20 unbiased SCNs, which aligned closely with functionally defined brain networks. PTSD diagnosis was most strongly associated with diminished CT in SCNs that encompassed the bilateral superior frontal cortex, motor cortex, insular cortex, orbitofrontal cortex, medial occipital cortex, anterior cingulate cortex, and posterior cingulate cortex. CT in these networks was significantly negatively correlated with PTSD symptom severity. Collectively, these findings suggest that PTSD diagnosis is associated with widespread reductions in CT, particularly within prefrontal regulatory regions and broader emotion and sensory processing cortical regions.

Neural Correlates of Balance Skill Learning in Young and Older Individuals: A Systematic Review and Meta-analysis

BACKGROUND

Despite the increasing number of research studies examining the effects of age on the control of posture, the number of annual fall-related injuries and deaths continues to increase. A better understanding of how old age affects the neural mechanisms of postural control and how countermeasures such as balance training could improve the neural control of posture to reduce falls in older individuals is therefore necessary. The aim of this review is to determine the effects of age on the neural correlates of balance skill learning measured during static (standing) and dynamic (walking) balance tasks in healthy individuals.

METHODS

We determined the effects of acute (1-3 sessions) and chronic (> 3 sessions) balance skill training on balance in the trained and in untrained, transfer balance tasks through a systematic review and quantified these effects by robust variance estimation meta-analysis in combination with meta-regression. We systematically searched PubMed, Web of Science, and Cochrane databases. Balance performance and neural plasticity outcomes were extracted and included in the systematic synthesis and meta-analysis.

RESULTS

Forty-two studies (n = 622 young, n = 699 older individuals) were included in the systematic synthesis. Seventeen studies with 508 in-analysis participants were eligible for a meta-analysis. The overall analysis revealed that acute and chronic balance training had a large effect on the neural correlates of balance skill learning in the two age groups combined (g = 0.79, p < 0.01). Both age groups similarly improved balance skill performance in 1-3 training sessions and showed little further improvements with additional sessions. Improvements in balance performance mainly occurred in the trained and less so in the non-trained (i.e., transfer) balance tasks. The systematic synthesis and meta-analysis suggested little correspondence between improved balance skills and changes in spinal, cortical, and corticospinal excitability measures in the two age groups and between the time courses of changes in balance skills and neural correlates.

CONCLUSIONS

Balance skill learning and the accompanying neural adaptations occur rapidly and independently of age with little to no training dose-dependence or correspondence between behavioral and neural adaptations. Of the five types of neural correlates examined, changes in only spinal excitability seemed to differ between age groups. However, age or training dose in terms of duration did not moderate the effects of balance training on the changes in any of the neural correlates. The behavioral and neural mechanisms of strong task-specificity and the time course of skill retention remain unclear and require further studies in young and older individuals.

REGISTRATION

PROSPERO registration number: CRD42022349573.

Microstructural dynamics of motor learning and sleep-dependent consolidation: A diffusion imaging study

Memory consolidation can benefit from post-learning sleep, eventually leading to long-term microstructural brain modifications to accommodate new memory representations. Non-invasive diffusion-weighted magnetic resonance imaging (DWI) allows the observation of (micro)structural brain remodeling after time-limited motor learning. Here, we combine conventional diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) that allows modeling dendritic and axonal complexity in gray matter to investigate with improved specificity the microstructural brain mechanisms underlying time- and sleep-dependent motor memory consolidation dynamics. Sixty-one young healthy adults underwent four DWI sessions, two sequential motor trainings, and a night of total sleep deprivation or regular sleep distributed over five days. We observed rapid-motor-learning-related remodeling in occipitoparietal, temporal, and motor-related subcortical regions, reflecting temporary dynamics in learning-related neuronal brain plasticity processes. Sleep-related consolidation seems not to exert a detectable impact on diffusion parameters, at least on the timescale of a few days.

Visual stimulation by extensive visual media consumption can be beneficial for motor learning

In this randomized controlled intervention trial, we investigated whether intense visual stimulation through television watching can enhance visual information processing and motor learning performance. 74 healthy young adults were trained in a motor skill with visual information processing demands while being accommodated in a controlled environment for five days. The experimental manipulation (n = 37) consisted of prolonged television watching (i.e., 8 h/day, + 62.5% on average) to induce intense exposure to visual stimulation. The control group (n = 37) did not consume visual media. The groups were compared by motor learning performance throughout the study as well as pre/post visual attention parameters and resting-state network connectivity in functional MRI. We found that the intervention group performed significantly better in the motor learning task (+ 8.21% (95%-CI[12.04, 4.31], t(70) = 4.23, p < 0.001) while showing an increased capacity of visual short-term memory (+ 0.254, t(58) = - 3.19, p = 0.002) and increased connectivity between visual and motor-learning associated resting-state networks. Our findings suggest that the human brain might enter a state of accentuated visuomotor integration to support the implementation of motor learning with visual information processing demands if challenged by ample input of visual stimulation. Further investigation is needed to evaluate the persistence of this effect regarding participants exposed to accustomed amounts of visual media consumption.Clinical Trials Registration: This trial was registered in the German Clinical Trials Register/Deutsches Register klinischer Studien (DRKS): DRKS00019955.

When mechanical engineering inspired from physiology improves postural-related somatosensory processes

Despite numerous studies uncovering the neural signature of tactile processing, tactile afferent inputs relating to the contact surface has not been studied so far. Foot tactile receptors being the first stimulated by the relative movement of the foot skin and the underneath moving support play an important role in the sensorimotor transformation giving rise to a postural reaction. A biomimetic surface, i.e., complying with the skin dermatoglyphs and tactile receptors characteristics should facilitate the cortical processes. Participants (n = 15) stood either on a biomimetic surface or on two control surfaces, when a sudden acceleration of the supporting surface was triggered (experiment 1). A larger intensity and shorter somatosensory response (i.e., SEP) was evoked by the biomimetic surface motion. This result and the associated decrease of theta activity (5-7 Hz) over the posterior parietal cortex suggest that increasing the amount of sensory input processing could make the balance task less challenging when standing on a biomimetic surface. This key point was confirmed by a second experiment (n = 21) where a cognitive task was added, hence decreasing the attentional resources devoted to the balance motor task. Greater efficiency of the postural reaction was observed while standing on the biomimetic than on the control surfaces.

Rapid neural changes during novel speech-sound learning: An fMRI and DTI study

While the functional and microstructural changes that occur when we learn new language skills are well documented, relatively little is known about the time course of these changes. Here a combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) study that tracks neural change over three days of learning Arabic phonetic categorization as a new language (L-training) is presented. Twenty adult native English-speaking (L-native) participants are scanned before and after training to perceive and produce L-training phonetic contrasts for one hour on three consecutive days. A third (Chinese) language is used as a control language (L-control). Behavioral results show significant performance improvement for L-training in both learnt tasks; the perception and production task. Imaging analysis reveals that, training-related hemodynamic fMRI signal and fractional anisotropy (FA) value increasing can be observed, in the left inferior frontal gyrus (LIFG) and positively correlated with behavioral improvement. Moreover, post training functional connectivity findings show a significant increasing between LIFG and left inferior parietal lobule for L-training. These results indicate that three hours of phonetic categorization learning causes functional and microstructural changes that are typically associated with much more long-term learning.

The optimal method for improving postural balance in healthy young and older people: specific training for postural tasks encountered in personal physical practice

It is well known that regular exercise or physical activity (training) improves postural balance in healthy young and older subjects, but the optimal exercise or physical activity (i.e., likely to induce the greatest postural improvements) and the context in which it is carried out remain to be explored and determined for each population. The most beneficial adaptations would depend, in particular, on gestural conditions (body position, movement and gesture practiced) and material conditions (nature of the ground surface, sports equipment used, type of environment - stable or changing). In fact, the global postural adaptations induced by training do not result from the transfer between different trained and untrained postural tasks, but are the sum of the adaptations related to each trained postural task in healthy young and older subjects. Based on current knowledge, optimal training programs should include the full range of postural tasks encountered in personal physical practice for each population. To date, the method of implementing progressive postural balance tasks with different degrees of difficulty and instability has been used as the effective method to improve postural balance, but it should not be considered as the reference method. Instead, it should be considered as a complementary method to the one based on specific postural tasks. An intervention strategy is proposed for young and older adults consisting of three different steps (general, oriented and specific/ecologic training). However, some parameters still need to be explored and possibly reconsidered in future studies to improve postural balance in an optimal way.

Cortico-cortical paired associative stimulation (ccPAS) over premotor-motor areas affects local circuitries in the human motor cortex via Hebbian plasticity

Transcranial magnetic stimulation (TMS) studies have shown that cortico-cortical paired associative stimulation (ccPAS) can strengthen connectivity between the ventral premotor cortex (PMv) and the primary motor cortex (M1) by modulating convergent input over M1 via Hebbian spike-timing-dependent plasticity (STDP). However, whether ccPAS locally affects M1 activity remains unclear. We tested 60 right-handed young healthy humans in two studies, using a combination of dual coil TMS and ccPAS over the left PMv and M1 to probe and manipulate PMv-to-M1 connectivity, and single- and paired-pulse TMS to assess neural activity within M1. We provide convergent evidence that ccPAS, relying on repeated activations of excitatory PMv-to-M1 connections, acts locally over M1. During ccPAS, motor-evoked potentials (MEPs) induced by paired PMv-M1 stimulation gradually increased. Following ccPAS, the threshold for inducing MEPs of different amplitudes decreased, and the input-output curve (IO) slope increased, highlighting increased M1 corticospinal excitability. Moreover, ccPAS reduced the magnitude of short-interval intracortical inhibition (SICI), reflecting suppression of GABA-ergic interneuronal mechanisms within M1, without affecting intracortical facilitation (ICF). These changes were specific to ccPAS Hebbian strengthening of PMv-to-M1 connectivity, as no modulations were observed when reversing the order of the PMv-M1 stimulation during a control ccPAS protocol. These findings expand prior ccPAS research that focused on the malleability of cortico-cortical connectivity at the network-level, and highlight local changes in the area of convergent activation (i.e., M1) during plasticity induction. These findings provide new mechanistic insights into the physiological basis of ccPAS that are relevant for protocol optimization.

Short-term balance consolidation relies on the primary motor cortex: a rTMS study

Structural and functional adaptations occur in the primary motor cortex (M1) after only a few balance learning sessions. Nevertheless, the role of M1 in consolidating balance tasks remains to be discussed, as direct evidence is missing due to the fact that it is unclear whether adaptations in M1 are indeed the driving force for balance improvements or merely the consequence of improved balance. The aim of the present study was to investigate whether the primary motor cortex is involved in the learning and consolidation of balance tasks. Thirty participants were randomly allocated into a repetitive transcranial magnetic stimulation (rTMS) or sham-rTMS group. The experimental design included a single balance acquisition phase, followed by either 15 min of low-frequency rTMS (1 Hz at 115% of resting motor threshold to disrupt the involvement of M1) or sham-rTMS, and finally a retention test 24 h later. During the acquisition phase, no differences in balance improvements were observed between the two groups. However, significant differences between the rTMS and the sham-rTMS group were found from the end of the acquisition phase to the retention test. While the rTMS group had a performance loss, the sham-rTMS group displayed significant off-line gains (p = 0.001). For the first time, this finding may propose a causal relationship between the involvement of M1 and the acquisition and consolidation of a balance task.

Microstructural and neurochemical plasticity mechanisms interact to enhance human perceptual decision-making

Experience and training are known to boost our skills and mold the brain's organization and function. Yet, structural plasticity and functional neurotransmission are typically studied at different scales (large-scale networks, local circuits), limiting our understanding of the adaptive interactions that support learning of complex cognitive skills in the adult brain. Here, we employ multimodal brain imaging to investigate the link between microstructural (myelination) and neurochemical (GABAergic) plasticity for decision-making. We test (in males, due to potential confounding menstrual cycle effects on GABA measurements in females) for changes in MRI-measured myelin, GABA, and functional connectivity before versus after training on a perceptual decision task that involves identifying targets in clutter. We demonstrate that training alters subcortical (pulvinar, hippocampus) myelination and its functional connectivity to visual cortex and relates to decreased visual cortex GABAergic inhibition. Modeling interactions between MRI measures of myelin, GABA, and functional connectivity indicates that pulvinar myelin plasticity interacts-through thalamocortical connectivity-with GABAergic inhibition in visual cortex to support learning. Our findings propose a dynamic interplay of adaptive microstructural and neurochemical plasticity in subcortico-cortical circuits that supports learning for optimized decision-making in the adult human brain.

Early sleep after action observation and motor imagery training boosts improvements in manual dexterity

The systematic observation and imagination of actions promotes acquisition of motor skills. Furthermore, studies demonstrated that early sleep after practice enhances motor learning through an offline stabilization process. Here, we investigated behavioral effects and neurodynamical correlates of early sleep after action observation and motor imagery training (AO + MI-training) on motor learning in terms of manual dexterity. Forty-five healthy participants were randomized into three groups receiving a 3 week intervention consisting of AO + MI-training immediately before sleeping or AO + MI-training at least 12 h before sleeping or a control stimulation. AO + MI-training implied the observation and motor imagery of transitive manual dexterity tasks, whereas the control stimulation consisted of landscape video-clips observation. Manual dexterity was assessed using functional tests, kinematic and neurophysiological outcomes before and after the training and at 1-month follow-up. AO + MI-training improved manual dexterity, but subjects performing AO + MI-training followed by early sleep had significantly larger improvements than those undergoing the same training at least 12 h before sleeping. Behavioral findings were supported by neurodynamical correlates during motor performance and additional sleep-dependent benefits were also detected at 1 month follow-up. These findings introduce a new approach to enhance the acquisition of new motor skills or facilitate recovery in patients with motor impairments.

Visuo-motor transformations in the intraparietal sulcus mediate the acquisition of endovascular medical skill

Performing endovascular medical interventions safely and efficiently requires a diverse set of skills that need to be practised in dedicated training sessions. Here, we used multimodal magnetic resonance (MR) imaging to determine the structural and functional plasticity and core skills associated with skill acquisition. A training group learned to perform a simulator-based endovascular procedure, while a control group performed a simplified version of the task; multimodal MR images were acquired before and after training. Using a well-controlled interaction design, we found strong multimodal evidence for the role of the intraparietal sulcus (IPS) in endovascular skill acquisition that is in line with previous work implicating the structure in visuospatial transformations including simple visuo-motor and mental rotation tasks. Our results provide a unique window into the multimodal nature of rapid structural and functional plasticity of the human brain while learning a multifaceted and complex clinical skill. Further, our results provide a detailed description of the plasticity process associated with endovascular skill acquisition and highlight specific facets of skills that could enhance current medical pedagogy and be useful to explicitly target during clinical resident training.

Choice of Voxel-based Morphometry processing pipeline drives variability in the location of neuroanatomical brain markers

Fundamental and clinical neuroscience has benefited tremendously from the development of automated computational analyses. In excess of 600 human neuroimaging papers using Voxel-based Morphometry (VBM) are now published every year and a number of different automated processing pipelines are used, although it remains to be systematically assessed whether they come up with the same answers. Here we examined variability between four commonly used VBM pipelines in two large brain structural datasets. Spatial similarity and between-pipeline reproducibility of the processed gray matter brain maps were generally low between pipelines. Examination of sex-differences and age-related changes revealed considerable differences between the pipelines in terms of the specific regions identified. Machine learning-based multivariate analyses allowed accurate predictions of sex and age, however accuracy differed between pipelines. Our findings suggest that the choice of pipeline alone leads to considerable variability in brain structural markers which poses a serious challenge for reproducibility and interpretation.

Four common processing pipelines tested on two Voxel-based Morphometry (VBM) datasets yield considerable variations in results, raising issues on the interpretability and robustness of VBM results.

Combination of structural and functional connectivity explains unique variation in specific domains of cognitive function

The relationship between structural and functional brain networks has been characterised as complex: the two networks mirror each other and show mutual influence but they also diverge in their organisation. This work explored whether a combination of structural and functional connectivity can improve the fit of regression models of cognitive performance. Principal Component Analysis (PCA) was first applied to cognitive data from the Human Connectome Project to identify latent cognitive components: Executive Function, Self-regulation, Language, Encoding and Sequence Processing. A Principal Component Regression approach with embedded Step-Wise Regression (SWR-PCR) was then used to fit regression models of each cognitive domain based on structural (SC), functional (FC) or combined structural-functional (CC) connectivity. Executive Function was best explained by the CC model. Self-regulation was equally well explained by SC and FC. Language was equally well explained by CC and FC models. Encoding and Sequence Processing were best explained by SC. Evaluation of out-of-sample models' skill via cross-validation showed that SC, FC and CC produced generalisable models of Language performance. SC models performed most effectively at predicting Language performance in unseen sample. Executive Function was most effectively predicted by SC models, followed only by CC models. Self-regulation was only effectively predicted by CC models and Sequence Processing was only effectively predicted by FC models. The present study demonstrates that integrating structural and functional connectivity can help explaining cognitive performance, but that the added explanatory value (in sample) may be domain-specific and can come at the expense of reduced generalisation performance (out-of-sample).

Modulation of network centrality and gray matter microstructure using multi-session brain stimulation and memory training

Neural mechanisms of behavioral improvement induced by repeated transcranial direct current stimulation (tDCS) combined with cognitive training are yet unclear. Previously, we reported behavioral effects of a 3-day visuospatial memory training with concurrent anodal tDCS over the right temporoparietal cortex in older adults. To investigate intervention-induced neural alterations we here used functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) datasets available from 35 participants of this previous study, acquired before and after the intervention. To delineate changes in whole-brain functional network architecture, we employed eigenvector centrality mapping. Gray matter alterations were analyzed using DTI-derived mean diffusivity (MD). Network centrality in the bilateral posterior temporooccipital cortex was reduced after anodal compared to sham stimulation. This focal effect is indicative of decreased functional connectivity of the brain region underneath the anodal electrode and its left-hemispheric homolog with other "relevant" (i.e., highly connected) brain regions, thereby providing evidence for reorganizational processes within the brain's network architecture. Examining local MD changes in these clusters, an interaction between stimulation condition and training success indicated a decrease of MD in the right (stimulated) temporooccipital cluster in individuals who showed superior behavioral training benefits. Using a data-driven whole-brain network approach, we provide evidence for targeted neuromodulatory effects of a combined tDCS-and-training intervention. We show for the first time that gray matter alterations of microstructure (assessed by DTI-derived MD) may be involved in tDCS-enhanced cognitive training. Increased knowledge on how combined interventions modulate neural networks in older adults, will help the development of specific therapeutic interventions against age-associated cognitive decline.

Impact of Metacognitive and Psychological Factors in Learning-Induced Plasticity of Resting State Networks

Simple Summary

Connections within the brain can reshape themselves to rapidly adapt to new learning. We aimed to demonstrate that these reconfigurations do not only reflect a memory trace but a more global response to other processes involved in learning. Furthermore, we investigated why individuals do not present the same ability both in learning and in connection plasticity. Present results indicate that brain rapid reconfiguration is not only linked to learning abilities but also to the process of confidence in learning. Factors such as age, education, and anxiety also appear to influence the brain’s response to learning and explain part of the variability observed between subjects. This study revealed important links between brain and psychological functioning and how they influence each other which highlights the need for considering psychological factors both in education and in psychiatric disorders.

Abstract

While resting-state networks are able to rapidly adapt to experiences and stimuli, it is currently unknown whether metacognitive processes such as confidence in learning and psychological temperament may influence this process. We explore the neural traces of confidence in learning and their variability by: (1) targeting rs-networks in which functional connectivity (FC) modifications induced by a learning task were associated either with the participant’s performance or confidence in learning; and (2) investigating the links between FC changes and psychological temperament. Thirty healthy individuals underwent neuropsychological and psychometric evaluations as well as rs-fMRI scans before and after a visuomotor associative learning task. Confidence in learning was positively associated with the degree of FC changes in 11 connections including the cerebellar, frontal, parietal, and subcortical areas. Variability in FC changes was linked to the individual’s level of anxiety sensitivity. The present findings indicate that reconfigurations of resting state networks linked to confidence in learning differ from those linked to learning accuracy. In addition, certain temperament characteristics appear to influence these reconfigurations.

Resting state networks mediate the association between both cardiovascular fitness and gross motor skills with neurocognitive functioning

Recent evidence suggests that cardiovascular fitness and gross motor skill performance are related to neurocognitive functioning by influencing brain structure and functioning. This study investigates the role of resting‐state networks (RSNs) in the relation of cardiovascular fitness and gross motor skills with neurocognitive functioning in healthy 8‐ to 11‐year‐old children (n = 90, 45 girls, 10% migration background). Cardiovascular fitness and gross motor skills were related to brain activity in RSNs. Furthermore, brain activity in RSNs mediated the relation of both cardiovascular fitness (Frontoparietal network and Somatomotor network) and gross motor skills (Somatomotor network) with neurocognitive functioning. The results indicate that brain functioning may contribute to the relation between both cardiovascular fitness and gross motor skills with neurocognitive functioning.

Associations between resting-state functional connectivity changes and prolonged benefits of writing training in Parkinson's disease

BACKGROUND

Our earlier work showed that automaticity and retention of writing skills improved with intensive writing training in Parkinson's disease (PD). However, whether this training changed the resting-state networks in the brain and how these changes underlie retention of motor learning is currently unknown.

OBJECTIVE

To examine changes in resting-state functional connectivity (rs-FC) and their relation to behavioral changes immediately after writing training and at 6 week follow-up.

METHODS

Twenty-five PD patients underwent resting-state fMRI (ON medication) before and after 6 weeks writing training. Motor learning was evaluated with a dual task paradigm pre- and post-training and at follow-up. Next, pre-post within-network changes in rs-FC were identified by an independent component analysis. Significant clusters were used as seeds in ROI-to-ROI analyses and rs-FC changes were correlated with changes in behavioral performance over time.

RESULTS

Similar to our larger cohort findings, writing accuracy in single and dual task conditions improved post-training and this was maintained at follow-up. Connectivity within the dorsal attentional network (DAN) increased pre-post training, particularly with the right superior and middle temporal gyrus (rS/MTG). This cluster also proved more strongly connected to parietal and frontal areas and to cerebellar regions. Behavioral improvements from pre- to post-training and follow-up correlated with increased rs-FC between rS/MTG and the cerebellum.

CONCLUSIONS

Training-driven improvements in dual task writing led to functional reorganization within the DAN and increased connectivity with cerebellar areas. These changes were associated with the retention of writing gains and could signify task-specific neural changes or an inability to segregate neural networks.

Priming cardiovascular exercise improves complex motor skill learning by affecting the trajectory of learning-related brain plasticity

In recent years, mounting evidence from animal models and studies in humans has accumulated for the role of cardiovascular exercise (CE) in improving motor performance and learning. Both CE and motor learning may induce highly dynamic structural and functional brain changes, but how both processes interact to boost learning is presently unclear. Here, we hypothesized that subjects receiving CE would show a different pattern of learning-related brain plasticity compared to non-CE controls, which in turn associates with improved motor learning. To address this issue, we paired CE and motor learning sequentially in a randomized controlled trial with healthy human participants. Specifically, we compared the effects of a 2-week CE intervention against a non-CE control group on subsequent learning of a challenging dynamic balancing task (DBT) over 6 consecutive weeks. Structural and functional MRI measurements were conducted at regular 2-week time intervals to investigate dynamic brain changes during the experiment. The trajectory of learning-related changes in white matter microstructure beneath parieto-occipital and primary sensorimotor areas of the right hemisphere differed between the CE vs. non-CE groups, and these changes correlated with improved learning of the CE group. While group differences in sensorimotor white matter were already present immediately after CE and persisted during DBT learning, parieto-occipital effects gradually emerged during motor learning. Finally, we found that spontaneous neural activity at rest in gray matter spatially adjacent to white matter findings was also altered, therefore indicating a meaningful link between structural and functional plasticity. Collectively, these findings may lead to a better understanding of the neural mechanisms mediating the CE-learning link within the brain.

Exploration of the Mechanism Underlying the Association of Incident Microinfarct and Motor Deficit: A Preliminary Functional MRI Study

BACKGROUND

Cerebral microinfarcts (CMIs) might cause measurable disruption to brain connections and are associated with cognitive decline, but the association between CMIs and motor impairment is still unclear.

OBJECTIVE

To assess the CMIs effect on motor function in vivo and explore the potential neuropathological mechanism based on graph-based network method.

METHODS

We identified 133 non-demented middle-aged and elderly participants who underwent MRI scanning, cognitive, and motor assessment. The short physical performance battery (SPPB) assessed motor function, including balance, walking speed, and chair stand. We grouped participants into 34 incident CMIs carriers and 99 non-CMIs carriers as controls, depending on diffusion-weighted imaging. Then we assessed the independent CMIs effects on motor function and explored neural mechanisms of CMIs on motor impairment via mapping of degree centrality (DC) and eigenvector centrality (EC).

RESULTS

CMIs carriers had worse motor function than non-carriers. Linear regression analyses showed that CMIs independently contributed to motor function. CMIs carriers had decreased EC in the precuneus, while increased DC and EC in the middle temporal gyrus and increased DC in the inferior frontal gyrus compared to controls (p < 0.05, corrected). Correlation analyses showed that EC of precuneus was related to SPPB (r = 0.25) and balance (r = 0.27); however, DC (r = -0.25) and EC (r = -0.25) of middle temporal gyrus was related with SPPB in all participants (p < 0.05, corrected).

CONCLUSION

CMIs represent an independent risk factor for motor dysfunction. The relationship between CMIs and motor function may be attributed to suppression of functional hub region and compensatory activation of motor-related regions.

Individual Discriminative Ability of Resting Functional Brain Connectivity is Susceptible to the Time Span of MRI Scans

Recent studies have suggested that resting-state brain functional connectivity (RSFC) has the potential to discriminate among individuals in a population. These studies mostly utilized a pattern of RSFC obtained from one scan to identify a given individual from the set of patterns obtained from the second scan. However, it remains unclear whether the discriminative ability would change with the extension of the time span between the two brain scans. This study explores the variations in the discriminative ability of RSFC on eight time spans, including 6 hours, 12 hours, 1 day, 1 month, 3-6 months, 7-12 months, 1-2 years and 2-3 years. We first searched for a set of the most discriminative RSFCs using the data of 200 healthy adult subjects from the Human Connectome Project dataset, and we then utilized this set of RSFCs to identify individuals from a population. The variations in the discriminative accuracies over different time spans were evaluated on datasets from a total of 682 unseen adult subjects acquired from four different sites. We found that although the accuracies were detectable at above-chance levels, the discriminative accuracies showed a significant decrease (F = 17.87, p < 0.01) along with the extension of brain imaging time span, from over 90% within one month to 66% at 2-3 years. Furthermore, the decreasing trend was robust and not dependent on the training set or analysis method. Therefore, we suggest that the discriminative ability of RSFC in identifying individuals should be susceptible to the length of time between brain scans.

Dynamics of task-induced modulation of spontaneous brain activity and functional connectivity in the triple resting-state networks assessed using the visual oddball paradigm

The default mode network (DMN), the salience network (SN), and the central executive network (CEN) are considered as the core resting-state brain networks (RSN) due to their involvement in a wide range of cognitive tasks. Despite the large body of knowledge related to their regional spontaneous activity (RSA) and functional connectivity (FC) of these networks, less is known about the dynamics of the task-associated modulation on these parameters and the task-induced interaction between these three networks. We have investigated the effects of the visual-oddball paradigm on three fMRI measures (amplitude of low-frequency fluctuations for RSA, regional homogeneity for local FC, and degree centrality for global FC) in these three core RSN. A rest-task-rest paradigm was used and the RSNs were identified using independent component analysis (ICA) on the resting-state data. The observed patterns of change differed noticeably between the networks and were tightly associated with the task-related brain activity and the distinct involvement of the networks in the performance of the single subtasks. Furthermore, the inter-network analysis showed an increased synchronization of CEN with the DMN and the SN immediately after the task, but not between the DMN and SN. Higher pre-task inter-network synchronization between the DMN and the CEN was associated with shorter reaction times and thus better performance. Our results provide some additional insights into the dynamics within and between the triple RSN. Further investigations are required in order to understand better their functional importance and interplay.

Altered dynamics of functional connectivity density associated with early and advanced stages of motor training in tennis and table tennis athletes

Until now, knowledge about the effects of motor training on the temporal dynamics of the brain functional organization is still limited. Here we combined dynamic functional connectivity density (dFCD) mapping and k-means clustering analyses to explore how early and advanced stages of motor training affected the brain dynamic FC architecture and dynamic states in little-ball athletes using resting-state functional magnetic resonance imaging (fMRI) data of student-athletes (SA), elite athletes (EA) and non-athlete healthy controls (NC). The ANOVA analysis demonstrated the levels of dFCD variability in the EA group had the trend to regress to the NC group levels in all statistically significant regions. Specifically, the brain regions responsible for the basic motor and sensory innervations showed more stabilized dFCD variability in EA and NC compared with SA. The results supported the idea of a stronger efficiency of functional networks and an automation process of new motor skills in EA. Furthermore, EA and NC had the increased dFCD variability in brain regions responsible for top-down visual-motor control compared with SA; while EA exhibited more flexible alterations in FCD status levels and the equilibrium probability in the long run compared with SA and NC. This suggested that regions involved in higher functions of visual-motor control exhibited more flexibility in functional regulation with other brain networks in EA. Our findings suggested the diversity and specialization of fluctuating dynamic brain adaption induced by motor training in different training stages, and highlighted the effect of motor training stages on brain functional adaption.

Neurobiological and behavioural outcomes of biofeedback-based training in autism: a randomized controlled trial

The human brain has demonstrated the power to structurally change as a result of movement-based interventions. However, it is unclear whether these structural brain changes differ in autistic individuals compared to non-autistic individuals. The purpose of the present study was to pilot a randomized controlled trial to investigate brain, balance, autism symptom severity and daily living skill changes that result from a biofeedback-based balance intervention in autistic adolescents (13-17 years old). Thirty-four autistic participants and 28 age-matched non-autistic participants underwent diagnostic testing and pre-training assessment (neuroimaging, cognitive, autism symptom severity and motor assessments) and were then randomly assigned to 6 weeks of a balance-training intervention or a sedentary-control condition. After the 6 weeks, neuroimaging, symptom severity and motor assessments were repeated. Results found that both the autistic and non-autistic participants demonstrated similar and significant increases in balance times with training. Furthermore, individuals in the balance-training condition showed significantly greater improvements in postural sway and reductions in autism symptom severity compared to individuals in the control condition. Daily living scores did not change with training, nor did we observe hypothesized changes to the microstructural properties of the corticospinal tract. However, follow-up voxel-based analyses found a wide range of balance-related structures that showed changes across the brain. Many of these brain changes were specific to the autistic participants compared to the non-autistic participants, suggesting distinct structural neuroplasticity in response to balance training in autistic participants. Altogether, these findings suggest that biofeedback-based balance training may target postural stability challenges, reduce core autism symptoms and influence neurobiological change. Future research is encouraged to examine the superior cerebellar peduncle in response to balance training and symptom severity changes in autistic individuals, as the current study produced overlapping findings in this brain region.

The impact of early musical training on striatal functional connectivity

Evidence from language, visual and sensorimotor learning suggests that training early in life is more effective. The present work explores the hypothesis that learning during sensitive periods involves distinct brain networks in addition to those involved when learning later in life. Expert pianists were tested who started their musical training early (<7 years of age; n = 21) or late (n = 15), but were matched for total lifetime practice. Motor timing expertise was assessed using a musical scale playing task. Brain activity at rest was measured using fMRI and compared with a control group of nonmusicians (n = 17). Functional connectivity from seeds in the striatum revealed a striatal-cortical-sensorimotor network that was observed only in the early-onset group. In this network, higher connectivity correlated with greater motor timing expertise, which resulted from early/late group differences in motor timing expertise. By contrast, networks that differentiated musicians and nonmusicians, namely a striatal-occipital-frontal-cerebellar network in which connectivity was higher in musicians, tended to not show differences between early and late musicians and not be correlated with motor timing expertise. These results parcel musical sensorimotor neuroplasticity into a set of musicianship-related networks and a distinct set of predominantly early-onset networks. The findings lend support to the possibility that we can learn skills more easily early in development because during sensitive periods we recruit distinct brain networks that are no longer implicated in learning later in life.

Childhood exercise predicts response inhibition in later life via changes in brain connectivity and structure

Participation in exercise during early life (i.e., childhood through adolescence) enhances response inhibition; however, it is unclear whether participation in exercise during early life positively predicts response inhibition in later life. This historical cohort study was designed to clarify whether participation in exercise (e.g., structured sports participation) during early life predicts response inhibition in adulthood and if so, to reveal the brain connectivity and cortical structures contributing to this association. We analyzed data derived from 214 participants (women = 104, men = 110; age: 26‒69 years). Results indicated that participation in exercise during childhood (before entering junior high school; ≤ 12 years old) significantly predicted better response inhibition. No such association was found if exercise participation took place in early adolescence or later (junior high school or high school; ≥ 12 years old). The positive association of exercise participation during childhood with response inhibition was moderated by decreased structural and functional connectivity in the frontoparietal (FPN), cingulo-opercular (CON), and default mode networks (DMN), and increased inter-hemispheric structural networks. Greater cortical thickness and lower levels of dendritic arborization and density in the FPN, CON, and DMN also moderated this positive association. Our results suggest that participation in exercise during childhood positively predicts response inhibition later in life and that this association can be moderated by changes in neuronal circuitry, such as increased cortical thickness and efficiency, and strengthened inter-hemispheric connectivity.

Enriching activities during childhood are associated with variations in functional connectivity patterns later in life

Enriching early life experiences (e.g., sport, art, music, volunteering, language learning) during a critical period of brain development may promote structural and functional brain changes that are still present decades later (>60 years). We assessed whether a greater variety of enriching early life activities (EELA) before age 13 years were associated with individual differences in cortical and subcortical (hippocampus and amygdala) structure and function later in life (older adults aged 60-80 years). Results indicated no association between EELA and amygdala and hippocampus volumes, but higher functional connectivity between the amygdala and the insula was associated with more variety of EELA. EELA was not associated with cortical thickness controlling for sex, but sex-specific associations with the right pars opercularis were found. EELA was further associated with variations in functional connectivity patterns of the orbitofrontal cortex, driven by connecitivty to regions within the visual, somatosensory and limbic networks. Early life enriching activities appear to contribute to potential mechanisms of cognitive reserve (functional processes) more so than brain reserve (structure) later in life.

Using high-definition transcranial direct current stimulation to investigate the role of the dorsolateral prefrontal cortex in explicit sequence learning

Though we have a general understanding of the brain areas involved in motor sequence learning, there is more to discover about the neural mechanisms underlying skill acquisition. Skill acquisition may be subserved, in part, by interactions between the cerebellum and prefrontal cortex through a cerebello-thalamo-prefrontal network. In prior work, we investigated this network by targeting the cerebellum; here, we explored the consequence of stimulating the dorsolateral prefrontal cortex using high-definition transcranial direct current stimulation (HD-tDCS) before administering an explicit motor sequence learning paradigm. Using a mixed within- and between- subjects design, we employed anodal (n = 24) and cathodal (n = 25) HD-tDCS (relative to sham) to temporarily alter brain function and examine effects on skill acquisition. The results indicate that both anodal and cathodal prefrontal stimulation impedes motor sequence learning, relative to sham. These findings suggest an overall negative influence of active prefrontal stimulation on the acquisition of a sequential pattern of finger movements. Collectively, this provides novel insight on the role of the dorsolateral prefrontal cortex in initial skill acquisition, when cognitive processes such as working memory are used. Exploring methods that may improve motor learning is important in developing therapeutic strategies for motor-related diseases and rehabilitation.

Slacklining: An explanatory multi-dimensional model considering classical mechanics, biopsychosocial health and time

This paper aims to overcome slacklining's limited formulated explanatory models. Slacklining is an activity with increasing recreational use, but also has progressive adoption into prehabilitation and rehabilitation. Slacklining is achieved through self-learned strategies that optimize energy expenditure without conceding dynamic stability, during the neuromechanical action of balance retention on a tightened band. Evolved from rope-walking or 'Funambulus', slacklining has an extensive history, yet limited and only recent published research, particularly for clinical interventions and in-depth hypothesized multi-dimensional models describing the neuromechanical control strategies. These 'knowledge-gaps' can be overcome by providing an, explanatory model, that evolves and progresses existing standards, and explains the broader circumstances of slacklining's use. This model details the individual's capacity to employ control strategies that achieve stability, functional movement and progressive technical ability. The model considers contributing entities derived from: Self-learned control of movement patterns; subjected to classical mechanical forces governed by Newton's physical laws; influenced by biopsychosocial health factors; and within time's multi-faceted perspectives, including as a quantified unit and as a spatial and cortical experience. Consequently, specific patient and situational uses may be initiated within the framework of evidence based medicine that ensures a multi-tiered context of slacklining applications in movement, balance and stability. Further research is required to investigate and mathematically define this proposed model and potentially enable an improved understanding of human functional movement. This will include its application in other diverse constructed and mechanical applications in varied environments, automation levels, robotics, mechatronics and artificial-intelligence factors, including machine learning related to movement phenotypes and applications.

BCI learning induces core-periphery reorganization in M/EEG multiplex brain networks

Brain-computer interfaces (BCIs) constitute a promising tool for communication and control. However, mastering non-invasive closed-loop systems remains a learned skill that is difficult to develop for a non-negligible proportion of users. The involved learning process induces neural changes associated with a brain network reorganization that remains poorly understood. To address this inter-subject variability, we adopted a multilayer approach to integrate brain network properties from electroencephalographic (EEG) and magnetoencephalographic (MEG) data resulting from a four-session BCI training program followed by a group of healthy subjects. Our method gives access to the contribution of each layer to multilayer network that tends to be equal with time. We show that regardless the chosen modality, a progressive increase in the integration of somatosensory areas in the α band was paralleled by a decrease of the integration of visual processing and working memory areas in the β band. Notably, only brain network properties in multilayer network correlated with future BCI scores in the α2 band: positively in somatosensory and decision-making related areas and negatively in associative areas. Our findings cast new light on neural processes underlying BCI training. Integrating multimodal brain network properties provides new information that correlates with behavioral performance and could be considered as a potential marker of BCI learning.

Up-regulation of proactive control is associated with beneficial effects of a childhood gymnastics program on response preparation and working memory

The current study focused on the effects of an 8-week motor skill-based physical activity (i.e., gymnastics) program on the contingent negative variation derived from event-related brain potentials (CNV-ERP) during a working memory task in children. Children aged 7-10 years old were assigned to a gymnastics group (n = 26) or a wait-list control group (n = 24). The gymnastics group engaged in a gymnastics program whereas children in the control group were asked to maintain their typical routine during the intervention period. Working memory performance was measured by a delayed-matching working memory task, accompanied by CNV-ERP collection. The results revealed significant improvement of response accuracy from pre-test to post-test in the gymnastic group regardless of memory demands. Moreover, significant increase from pre-test to post-test in the initial CNV was observed in the gymnastic group regardless of memory demands. Bivariate correlations further indicated that, in the gymnastic group, increases in response accuracy from pre-test to post-test were correlated with increases in initial CNV from pre-test to post-test in task conditions with lower and higher memory loads. Overall, the current findings suggest that up-regulation of proactive control may characterize the beneficial effects of childhood motor skill-based physical activity on working memory.

Post-learning micro- and macro-structural neuroplasticity changes with time and sleep

Neuroplasticity refers to the fact that our brain can partially modify both structure and function to adequately respond to novel environmental stimulations. Neuroplasticity mechanisms are not only operating during the acquisition of novel information (i.e., online) but also during the offline periods that take place after the end of the actual learning episode. Structural brain changes as a consequence of learning have been consistently demonstrated on the long term using non-invasive neuroimaging methods, but short-term changes remained more elusive. Fortunately, the swift development of advanced MR methods over the last decade now allows tracking fine-grained cerebral changes on short timescales beyond gross volumetric modifications stretching over several days or weeks. Besides a mere effect of time, post-learning sleep mechanisms have been shown to play an important role in memory consolidation and promote long-lasting changes in neural networks. Sleep was shown to contribute to structural modifications over weeks of prolonged training, but studies evidencing more rapid post-training sleep structural effects linked to memory consolidation are still scarce in human. On the other hand, animal studies convincingly show how sleep might modulate synaptic microstructure. We aim here at reviewing the literature establishing a link between different types of training/learning and the resulting structural changes, with an emphasis on the role of post-training sleep and time in tuning these modifications. Open questions are raised such as the role of post-learning sleep in macrostructural changes, the links between different MR structural measurement-related modifications and the underlying microstructural brain processes, and bidirectional influences between structural and functional brain changes.

Automatic Estimation of Laryngeal Vestibule Closure Duration Using High- Resolution Cervical Auscultation Signals

Purpose

Safe swallowing requires adequate protection of the airway to prevent swallowed materials from entering the trachea or lungs (i.e., aspiration). Laryngeal vestibule closure (LVC) is the first line of defense against swallowed materials entering the airway. Absent LVC or mistimed/ shortened closure duration can lead to aspiration, adverse medical consequences, and even death. LVC mechanisms can be judged commonly through the videofluoroscopic swallowing study; however, this type of instrumentation exposes patients to radiation and is not available or acceptable to all patients. There is growing interest in noninvasive methods to assess/monitor swallow physiology. In this study, we hypothesized that our noninvasive sensor- based system, which has been shown to accurately track hyoid displacement and upper esophageal sphincter opening duration during swallowing, could predict laryngeal vestibule status, including the onset of LVC and the onset of laryngeal vestibule reopening, in real time and estimate the closure duration with a comparable degree of accuracy as trained human raters.

Method

The sensor-based system used in this study is high-resolution cervical auscultation (HRCA). Advanced machine learning techniques enable HRCA signal analysis through feature extraction and complex algorithms. A deep learning model was developed with a data set of 588 swallows from 120 patients with suspected dysphagia and further tested on 45 swallows from 16 healthy participants.

Results

The new technique achieved an overall mean accuracy of 74.90% and 75.48% for the two data sets, respectively, in distinguishing LVC status. Closure duration ratios between automated and gold-standard human judgment of LVC duration were 1.13 for the patient data set and 0.93 for the healthy participant data set.

Conclusions

This study found that HRCA signal analysis using advanced machine learning techniques can effectively predict laryngeal vestibule status (closure or opening) and further estimate LVC duration. HRCA is potentially a noninvasive tool to estimate LVC duration for diagnostic and biofeedback purposes without X-ray imaging.

Network-based brain computer interfaces: principles and applications

Brain-computer interfaces (BCIs) make possible to interact with the external environment by decoding the mental intention of individuals. BCIs can therefore be used to address basic neuroscience questions but also to unlock a variety of applications from exoskeleton control to neurofeedback (NFB) rehabilitation. In general, BCI usability critically depends on the ability to comprehensively characterize brain functioning and correctly identify the user's mental state. To this end, much of the efforts have focused on improving the classification algorithms taking into account localized brain activities as input features. Despite considerable improvement BCI performance is still unstable and, as a matter of fact, current features represent oversimplified descriptors of brain functioning. In the last decade, growing evidence has shown that the brain works as a networked system composed of multiple specialized and spatially distributed areas that dynamically integrate information. While more complex, looking at how remote brain regions functionally interact represents a grounded alternative to better describe brain functioning. Thanks to recent advances in network science, i.e. a modern field that draws on graph theory, statistical mechanics, data mining and inferential modelling, scientists have now powerful means to characterize complex brain networks derived from neuroimaging data. Notably, summary features can be extracted from these networks to quantitatively measure specific organizational properties across a variety of topological scales. In this topical review, we aim to provide the state-of-the-art supporting the development of a network theoretic approach as a promising tool for understanding BCIs and improve usability.

Prior cortical activity differences during an action observation plus motor imagery task related to motor adaptation performance of a coordinated multi-limb complex task

Motor adaptation is the ability to develop new motor skills that makes performing a consolidated motor task under different psychophysical conditions possible. There exists a proven relationship between prior brain activity at rest and motor adaptation. However, the brain activity at rest is highly variable both between and within subjects. Here we hypothesize that the cortical activity during the original task to be later adapted is a more reliable and stronger determinant of motor adaptation. Consequently, we present a study to find cortical areas whose activity, both at rest and during first-person virtual reality simulation of bicycle riding, characterizes the subjects who did and did not adapt to ride a reverse steering bicycle, a complex motor adaptation task involving all limbs and balance. The results showed that cortical activity differences during the simulated task were higher, more significant, spatially larger, and spectrally wider than at rest for good performers. In this sense, the activity of the left anterior insula, left dorsolateral and ventrolateral inferior prefrontal areas, and left inferior premotor cortex (action understanding hub of the mirror neuron circuit) during simulated bicycle riding are the areas with the most descriptive power for the ability of adapting the motor task. Trials registration Trial was registered with the NIH Clinical Trials Registry (clinicaltrials.gov), with the registration number NCT02999516 (21/12/2016).

Drumming Motor Sequence Training Induces Apparent Myelin Remodelling in Huntington's Disease: A Longitudinal Diffusion MRI and Quantitative Magnetization Transfer Study

Background:

Impaired myelination may contribute to Huntington’s disease (HD) pathogenesis.

Objective:

This study assessed differences in white matter (WM) microstructure between HD patients and controls, and tested whether drumming training stimulates WM remodelling in HD. Furthermore, it examined whether training-induced microstructural changes are related to improvements in motor and cognitive function.

Methods:

Participants undertook two months of drumming exercises. Working memory and executive function were assessed before and post-training. Changes in WM microstructure were investigated with diffusion tensor magnetic resonance imaging (DT-MRI)-based metrics, the restricted diffusion signal fraction (Fr) from the composite hindered and restricted model of diffusion (CHARMED) and the macromolecular proton fraction (MPF) from quantitative magnetization transfer (qMT) imaging. WM pathways linking putamen and supplementary motor areas (SMA-Putamen), and three segments of the corpus callosum (CCI, CCII, CCIII) were studied using deterministic tractography. Baseline MPF differences between patients and controls were assessed with tract-based spatial statistics.

Results:

MPF was reduced in the mid-section of the CC in HD subjects at baseline, while a significantly greater change in MPF was detected in HD patients relative to controls in the CCII, CCIII, and the right SMA-putamen post-training. Further, although patients improved their drumming and executive function performance, such improvements did not correlate with microstructural changes. Increased MPF suggests training-induced myelin changes in HD.

Conclusion:

Though only preliminary and based on a small sample size, these results suggest that tailored behavioural stimulation may lead to neural benefits in early HD, that could be exploited for delaying disease progression.

Neurodiagnostics in Sports: Investigating the Athlete's Brain to Augment Performance and Sport-Specific Skills

Enhancing performance levels of athletes during training and competition is a desired goal in sports. Quantifying training success is typically accompanied by performance diagnostics including the assessment of sports-relevant behavioral and physiological parameters. Even though optimal brain processing is a key factor for augmented motor performance and skill learning, neurodiagnostics is typically not implemented in performance diagnostics of athletes. We propose, that neurodiagnostics via non-invasive brain imaging techniques such as functional near-infrared spectroscopy (fNIRS) will offer novel perspectives to quantify training-induced neuroplasticity and its relation to motor behavior. A better understanding of such a brain-behavior relationship during the execution of sport-specific movements might help to guide training processes and to optimize training outcomes. Furthermore, targeted non-invasive brain stimulation such as transcranial direct current stimulation (tDCS) might help to further enhance training outcomes by modulating brain areas that show training-induced neuroplasticity. However, we strongly suggest that ethical aspects in the use of non-invasive brain stimulation during training and/or competition need to be addressed before neuromodulation can be considered as a performance enhancer in sports.

Colocalized White Matter Plasticity and Increased Cerebral Blood Flow Mediate the Beneficial Effect of Cardiovascular Exercise on Long-Term Motor Learning

Cardiovascular exercise (CE) is a promising intervention strategy to facilitate cognition and motor learning in healthy and diseased populations of all ages. CE elevates humoral parameters, such as growth factors, and stimulates brain changes potentially relevant for learning and behavioral adaptations. However, the causal relationship between CE-induced brain changes and human's ability to learn remains unclear. We tested the hypothesis that CE elicits a positive effect on learning via alterations in brain structure (morphological changes of gray and white matter) and function (functional connectivity and cerebral blood flow in resting state). We conducted a randomized controlled trial with healthy male and female human participants to compare the effects of a 2 week CE intervention against a non-CE control group on subsequent learning of a challenging new motor task (dynamic balancing; DBT) over 6 consecutive weeks. We used multimodal neuroimaging [T1-weighted magnetic resonance imaging (MRI), diffusion-weighted MRI, perfusion-weighted MRI, and resting state functional MRI] to investigate the neural mechanisms mediating between CE and learning. As expected, subjects receiving CE subsequently learned the DBT at a higher rate. Using a modified nonparametric combination approach along with multiple mediator analysis, we show that this learning boost was conveyed by CE-induced increases in cerebral blood flow in frontal brain regions and changes in white matter microstructure in frontotemporal fiber tracts. Our study revealed neural mechanisms for the CE-learning link within the brain, probably allowing for a higher flexibility to adapt to highly novel environmental stimuli, such as learning a complex task.SIGNIFICANCE STATEMENT It is established that cardiovascular exercise (CE) is an effective approach to promote learning and memory, yet little is known about the underlying neural transfer mechanisms through which CE acts on learning. We provide evidence that CE facilitates learning in human participants via plasticity in prefrontal white matter tracts and a colocalized increase in cerebral blood flow. Our findings are among the first to demonstrate a transfer potential of experience-induced brain plasticity. In addition to practical implications for health professionals and coaches, our work paves the way for future studies investigating effects of CE in patients suffering from prefrontal hypoperfusion or white matter diseases.

Explaining Individual Differences in Motor Behavior by Intrinsic Functional Connectivity and Corticospinal Excitability

Motor performance varies substantially between individuals. This variance is rooted in individuals' innate motor abilities, and should thus have a neural signature underlying these differences in behavior. Could these individual differences be detectable with neural measurements acquired at rest? Here, we tested the hypothesis that motor performance can be predicted by resting motor-system functional connectivity and motor-evoked-potentials (MEPs) induced by non-invasive brain stimulation. Twenty healthy right handed subjects performed structural and resting-state fMRI scans. On a separate day, MEPs were measured using transcranial magnetic stimulation (TMS) over the contrateral primary motor cortex (M1). At the end of the session, participants performed a finger-tapping task using their left non-dominant hand. Resting-state functional connectivity between the contralateral M1 and the supplementary motor area (SMA) predicted motor task performance, indicating that individuals with stronger resting M1-SMA functional connectivity exhibit better motor performance. This prediction was neither improved nor reduced by the addition of corticospinal excitability to the model. These results confirm that motor behavior can be predicted from neural measurements acquired prior to task performance, primarily relying on resting functional connectivity rather than corticospinal excitability. The ability to predict motor performance from resting neural markers, provides an opportunity to identify the extent of successful rehabilitation following neurological damage.