Age-Dependent Modulations of Resting State Connectivity Following Motor Practice

Aging, brain plasticity, and motor learning

Motor skill learning, the process of acquiring new motor skills, is critically important across the lifespan, from early development through adulthood and into older age, as well as in pathological conditions (i.e., rehabilitation). Extensive research has demonstrated that motor skill acquisition in young adults is accompanied by significant neuroplastic changes, including alterations in brain structure (gray and white matter), function (i.e., activity and connectivity), and neurochemistry (i.e., levels of neurotransmitters). In the aging population, motor performance typically declines, characterized by slower and less accurate movements. However, despite these age-related changes, older adults maintain the capacity for skill improvement through training. In this review, we explore the extent to which the aging brain retains the ability to adapt in response to motor learning, specifically whether skill acquisition is accompanied by neural changes. Furthermore, we discuss the associations between inter-individual variability in brain structure and function and the potential for future learning in older adults. Finally, we consider the use of non-invasive brain stimulation techniques aimed at optimizing motor learning in this population. Our review provides insights into the neurobiological underpinnings of motor learning in older adults and emphasizes strategies to enhance their motor skill acquisition.

Sensorimotor Network Segregation Predicts Long-Term Learning of Writing Skills in Parkinson's Disease

The prediction of motor learning in Parkinson's disease (PD) is vastly understudied. Here, we investigated which clinical and neural factors predict better long-term gains after an intensive 6-week motor learning program to ameliorate micrographia. We computed a composite score of learning through principal component analysis, reflecting better writing accuracy on a tablet in single and dual task conditions. Three endpoints were studied-acquisition (pre- to post-training), retention (post-training to 6-week follow-up), and overall learning (acquisition plus retention). Baseline writing, clinical characteristics, as well as resting-state network segregation were used as predictors. We included 28 patients with PD (13 freezers and 15 non-freezers), with an average disease duration of 7 (±3.9) years. We found that worse baseline writing accuracy predicted larger gains for acquisition and overall learning. After correcting for baseline writing accuracy, we found female sex to predict better acquisition, and shorter disease duration to help retention. Additionally, absence of FOG, less severe motor symptoms, female sex, better unimanual dexterity, and better sensorimotor network segregation impacted overall learning positively. Importantly, three factors were retained in a multivariable model predicting overall learning, namely baseline accuracy, female sex, and sensorimotor network segregation. Besides the room to improve and female sex, sensorimotor network segregation seems to be a valuable measure to predict long-term motor learning potential in PD.

Frontoparietal function and underlying structure reflect capacity for motor skill acquisition during healthy aging

While capacity for motor skill acquisition changes with healthy aging, there has been little consideration of how age-related changes in brain function or baseline brain structure support motor skill acquisition. We examined: (1) age-dependent changes in functional reorganization related to frontoparietal regions during motor skill acquisition, and (2) whether capacity for motor skill acquisition relates to baseline white matter microstructure in frontoparietal tracts. Healthy older and younger adults engaged in 4 weeks of skilled motor practice. Resting-state functional connectivity (rsFC) assessed functional reorganization before and after practice. Diffusion tensor imaging indexed microstructure of a frontoparietal tract at baseline, generated by rsFC seeds. Motor skill acquisition was associated with decreases in rsFC in healthy older adults and increases in rsFC in healthy younger adults. Frontoparietal tract microstructure was lower in healthy older versus younger adults, yet it was negatively associated with rate of skill acquisition regardless of group. Findings indicate that age-dependent alterations in frontoparietal function and baseline structure of a frontoparietal tract reflect capacity for motor skill acquisition.

A randomized controlled trial of changes in resting-state functional connectivity associated with short-term motor learning of chopstick use with the non-dominant hand

INTRODUCTION

This study identified the offline brain networks associated with motor learning of non-dominant hand chopstick use within-session.

METHODS

40 healthy right-handed adults were randomly assigned to the practice and control groups (20 each). The performance, resting-state functional connectivity (RSFC), and their correlation were compared within and between groups. Both groups repeated 9 cycles of 30 s task and rest. During the task, the practice group performed the chopstick-use practice with their left hand, while the control group held chopsticks without acquiring any skills. During the rest, both groups fixated their gaze on a fixation point. The number of times candies were moved using chopsticks with the left hand in 30 s was used to evaluate the performance. RSFC was obtained by resting-state fMRI scanning and extracting Z-scores between the right primary motor cortex and all other brain regions.

RESULTS

Both the groups improved in the post-task performance; the practice group improved more. The RSFC of the two networks increased in the practice group. One network was the RSFC between the right M1 and the right cerebellar Crus I, positively correlated with performance in the post-task. Another was the RSFC between the right M1 and the left cerebellar Crus II, positively correlated with skills in the amount of change pre- and post-task.

CONCLUSION

Offline enhancement of RSFC in these networks was shown to contribute to early chopstick-use motor learning with the left hand. These results serve as a basis for future studies on compensatory networks in individuals with stroke.

The correlation between upper body grip strength and resting-state EEG network

Current research in the field of neuroscience primarily focuses on the analysis of electroencephalogram (EEG) activities associated with movement within the central nervous system. However, there is a dearth of studies investigating the impact of prolonged individual strength training on the resting state of the brain. Therefore, it is crucial to examine the correlation between upper body grip strength and resting-state EEG networks. In this study, coherence analysis was utilized to construct resting-state EEG networks using the available datasets. A multiple linear regression model was established to examine the correlation between the brain network properties of individuals and their maximum voluntary contraction (MVC) during gripping tasks. The model was used to predict individual MVC. The beta and gamma frequency bands showed significant correlation between RSN connectivity and MVC (p < 0.05), particularly in left hemisphere frontoparietal and fronto-occipital connectivity. RSN properties were consistently correlated with MVC in both bands, with correlation coefficients greater than 0.60 (p < 0.01). Additionally, predicted MVC positively correlated with actual MVC, with a coefficient of 0.70 and root mean square error of 5.67 (p < 0.01). The results show that the resting-state EEG network is closely related to upper body grip strength, which can indirectly reflect an individual's muscle strength through the resting brain network.

Bimanual motor impairments in older adults: an updated systematic review and meta-analysis

This updated systematic review and meta-analysis further examined potential effects of aging on bimanual movements. Forty-seven qualified studies that compared bimanual motor performances between elderly and younger adults were included in this meta-analysis. Moderator variable analyses additionally determined whether altered bimanual motor performances in older adults were different based on the task types (i.e., symmetry vs. asymmetry vs. complex) or outcome measures (i.e., accuracy vs. variability vs. movement time). The random effects model meta-analysis on 80 comparisons from 47 included studies revealed significant negative overall effects indicating more bimanual movement impairments in the elderly adults than younger adults. Moderator variable analyses found that older adults showed more deficits in asymmetrical bimanual movement tasks than symmetrical and complex tasks, and the bimanual movement impairments in the elderly adults included less accurate, more variable, and greater movement execution time than younger adults. These findings suggest that rehabilitation programs for improving motor actions in older adults are necessary to focus on functional recovery of interlimb motor control including advanced motor performances as well coordination.

Modality of Practice Modulates Resting State Connectivity During Motor Learning

When bookending skilled motor practice, changes in resting state functional magnetic resonance imaging (rs-fMRI; used to characterise synchronized patterns of activity when the brain is at rest) reflect functional reorganization that supports motor memory consolidation and learning. Despite its use in practice in numerous domains, the neural mechanisms underlying motor memory consolidation and learning that result from motor imagery practice (MIP) relative to physical practice are not well understood. The current study examined how rs-fMRI is modulated by skilled motor practice that results through either MIP or physical practice. Two groups of participants engaged in five days of MIP or physical practice of a dart throwing task. Performance and rs-fMRI were captured before and after training. Relative to physical practice, where focal changes in rs-fMRI within a cerebellar-cortical network were observed, MIP stimulated widespread changes in rs-fMRI within a frontoparietal network encompassing bilateral regions. Findings indicate that functional reorganization that supports motor memory consolidation and learning is not equivalent across practice modality. Ultimately, this work provides new information regarding the unique neural underpinnings MIP relies on to drive motor memory consolidation and learning.

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.

Age-Related Changes in Functional Connectivity during the Sensorimotor Integration Detected by Artificial Neural Network

Large-scale functional connectivity is an important indicator of the brain’s normal functioning. The abnormalities in the connectivity pattern can be used as a diagnostic tool to detect various neurological disorders. The present paper describes the functional connectivity assessment based on artificial intelligence to reveal age-related changes in neural response in a simple motor execution task. Twenty subjects of two age groups performed repetitive motor tasks on command, while the whole-scalp EEG was recorded. We applied the model based on the feed-forward multilayer perceptron to detect functional relationships between five groups of sensors located over the frontal, parietal, left, right, and middle motor cortex. Functional dependence was evaluated with the predicted and original time series coefficient of determination. Then, we applied statistical analysis to highlight the significant features of the functional connectivity network assessed by our model. Our findings revealed the connectivity pattern is consistent with modern ideas of the healthy aging effect on neural activation. Elderly adults demonstrate a pronounced activation of the whole-brain theta-band network and decreased activation of frontal–parietal and motor areas of the mu-band. Between-subject analysis revealed a strengthening of inter-areal task-relevant links in elderly adults. These findings can be interpreted as an increased cognitive demand in elderly adults to perform simple motor tasks with the dominant hand, induced by age-related working memory decline.

Additive and interaction effects of working memory and motor sequence training on brain functional connectivity

Although shared behavioral and neural mechanisms between working memory (WM) and motor sequence learning (MSL) have been suggested, the additive and interactive effects of training have not been studied. This study aimed at investigating changes in brain functional connectivity (FC) induced by sequential (WM + MSL and MSL + WM) and combined (WM × MSL) training programs. 54 healthy subjects (27 women; mean age: 30.2 ± 8.6 years) allocated to three training groups underwent twenty-four 40-min training sessions over 6 weeks and four cognitive assessments including functional MRI. A double-baseline approach was applied to account for practice effects. Test performances were compared using linear mixed-effects models and t-tests. Resting state fMRI data were analysed using FSL. Processing speed, verbal WM and manual dexterity increased following training in all groups. MSL + WM training led to additive effects in processing speed and verbal WM. Increased FC was found after training in a network including the right angular gyrus, left superior temporal sulcus, right superior parietal gyrus, bilateral middle temporal gyri and left precentral gyrus. No difference in FC was found between double baselines. Results indicate distinct patterns of resting state FC modulation related to sequential and combined WM and MSL training suggesting a relevance of the order of training performance. These observations could provide new insight for the planning of effective training/rehabilitation.

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

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

Resting State Connectivity Is Modulated by Motor Learning in Individuals After Stroke

Objective

Activity patterns across brain regions that can be characterized at rest (ie, resting-state functional connectivity [rsFC]) are disrupted after stroke and linked to impairments in motor function. While changes in rsFC are associated with motor recovery, it is not clear how rsFC is modulated by skilled motor practice used to promote recovery. The current study examined how rsFC is modulated by skilled motor practice after stroke and how changes in rsFC are linked to motor learning.

Methods

Two groups of participants (individuals with stroke and age-matched controls) engaged in 4 weeks of skilled motor practice of a complex, gamified reaching task. Clinical assessments of motor function and impairment, and brain activity (via functional magnetic resonance imaging) were obtained before and after training.

Results

While no differences in rsFC were observed in the control group, increased connectivity was observed in the sensorimotor network, linked to learning in the stroke group. Relative to healthy controls, a decrease in network efficiency was observed in the stroke group following training.

Conclusions

Findings indicate that rsFC patterns related to learning observed after stroke reflect a shift toward a compensatory network configuration characterized by decreased network efficiency.

Brain sources' activity in resting state before a visuo-motor task

Objective In modern neuroscience, the underlying mechanisms of the elaboration and reaction to different kinds of stimuli of the brain hemispheres remain still very challenging to understand, together with the possibility to anticipate certain behaviors to improve the performance. Approach The purpose of the present study was to investigate the brain rhythms characteristics of EEG recordings and in particular, their interhemispheric differences in resting state condition before a visuo-motor task in a population of healthy adults. During the task, subjects were asked to react to a sequence of visual cues as quick as possible. The reaction times (RTs) to the task were measured, collected and correlated with the EEG signals recorded in a resting state condition immediately preceding the task. The EEG data were analyzed in the space of cortical sources of EEG rhythms by the computation of the Global Spectra Power Density (GSPD) in the left and in the right hemisphere, and of an index of brain Laterality L. Main results The results showed a negative correlation between the RTs and the GSPD in the central areas in the left and in the right hemisphere in both eyes open and eyes closed conditions. A close to significant and negative correlation was found in the parietal areas. Furthermore, RTs negatively correlated with L in the central areas in eyes closed condition. The results showed a negative correlation between the RTs and the GSPD in the central areas in the left and in the right hemisphere in both eyes open and eyes closed conditions. Significance The correlations between the brain activity before a task and the RTs to the task can represent an interesting tool for exploring the brain state characterization for the upcoming tasks performance.

GABA levels are differentially associated with bimanual motor performance in older as compared to young adults

Although gamma aminobutyric acid (GABA) is of particular importance for efficient motor functioning, very little is known about the relationship between regional GABA levels and motor performance. Some studies suggest this relation to be subject to age-related differences even though literature is scarce. To clarify this matter, we employed a comprehensive approach and investigated GABA levels within young and older adults across multiple motor tasks as well as multiple brain regions. Specifically, 30 young and 30 older adults completed a task battery of three different bimanual tasks. Furthermore, GABA levels were obtained within bilateral primary sensorimotor cortex (SM1), bilateral dorsal premotor cortex, the supplementary motor area and bilateral dorsolateral prefrontal cortex (DLPFC) using magnetic resonance spectroscopy. Results indicated that older adults, as compared to their younger counterparts, performed worse on all bimanual tasks and exhibited lower GABA levels in bilateral SM1 only. Moreover, GABA levels across the motor network and DLPFC were differentially associated with performance in young as opposed to older adults on a manual dexterity and bimanual coordination task but not a finger tapping task. Specifically, whereas higher GABA levels related to better manual dexterity within older adults, higher GABA levels predicted poorer bimanual coordination performance in young adults. By determining a task-specific and age-dependent association between GABA levels across the cortical motor network and performance on distinct bimanual tasks, the current study advances insights in the role of GABA for motor performance in the context of aging.

Motor Skill Learning-Induced Functional Plasticity in the Primary Somatosensory Cortex: A Comparison Between Young and Older Adults

While in young adults (YAs) the underlying neural mechanisms of motor learning are well-studied, studies on the involvement of the somatosensory system during motor skill learning in older adults (OAs) remain sparse. Therefore, the aim of the present study was to investigate motor learning-induced neuroplasticity in the primary somatosensory cortex (S1) in YAs and OAs. Somatosensory evoked potentials (SEPs) were used to quantify somatosensory activation prior and immediately after motor skill learning in 20 right-handed healthy YAs (age range: 19–35 years) and OAs (age range: 57–76 years). Participants underwent a single session of a 30-min co-contraction task of the abductor pollicis brevis (APB) and deltoid muscle. To assess the effect of motor learning, muscle onset asynchrony (MOA) between the onsets of the contractions of both muscles was measured using electromyography monitoring. In both groups, MOA shortened significantly during motor learning, with YAs showing bigger reductions. No changes were found in SEP amplitudes after motor learning in both groups. However, a correlation analysis revealed an association between baseline SEP amplitudes of the N20/P25 and N30 SEP component and the motor learning slope in YAs such that higher amplitudes are related to higher learning. Hence, the present findings suggest that SEP amplitudes might serve as a predictor of individual motor learning success, at least in YAs. Additionally, our results suggest that OAs are still capable of learning complex motor tasks, showing the importance of motor training in higher age to remain an active part of our society as a prevention for care dependency.

Regression Networks for Neurophysiological Indicator Evaluation in Practicing Motor Imagery Tasks

Motor Imagery (MI) promotes motor learning in activities, like developing professional motor skills, sports gestures, and patient rehabilitation. However, up to 30% of users may not develop enough coordination skills after training sessions because of inter and intra-subject variability. Here, we develop a data-driven estimator, termed Deep Regression Network (DRN), which jointly extracts and performs the regression analysis in order to assess the efficiency of the individual brain networks in practicing MI tasks. The proposed double-stage estimator initially learns a pool of deep patterns, extracted from the input data, in order to feed a neural regression model, allowing for infering the distinctiveness between subject assemblies having similar variability. The results, which were obtained on real-world MI data, prove that the DRN estimator fosters pre-training neural desynchronization and initial training synchronization to predict the bi-class accuracy response, thus providing a better understanding of the Brain-Computer Interface inefficiency of subjects.

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).

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

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

Age-Related Changes in Pain Perception Are Associated With Altered Functional Connectivity During Resting State

Aging affects pain experience and brain functioning. However, how aging leads to changes in pain perception and brain functional connectivity has not yet been completely understood. To investigate resting-state and pain perception changes in old and young participants, this study employed region of interest (ROI) to ROI resting-state functional connectivity (rsFC) analysis of imaging data by using regions implicated in sensory and affective dimensions of pain, descending pain modulation, and the default-mode networks (DMNs). Thirty-seven older (66.86 ± 4.04 years; 16 males) and 38 younger healthy participants (20.74 ± 4.15 years; 19 males) underwent 10 min’ eyes-closed resting-state scanning. We examined the relationship between rsFC parameters with pressure pain thresholds. Older participants showed higher pain thresholds than younger. Regarding rsFC, older adults displayed increased connectivity of pain-related sensory brain regions in comparison to younger participants: increased rsFC between bilateral primary somatosensory area (SI) and anterior cingulate cortex (ACC), and between SI(L) and secondary somatosensory area (SII)-(R) and dorsolateral prefrontal cortex (PFC). Moreover, decreased connectivity in the older compared to the younger group was found among descending pain modulatory regions: between the amygdala(R) and bilateral insula(R), thalamus(R), ACC, and amygdala(L); between the amygdala(L) and insula(R) and bilateral thalamus; between ACC and bilateral insula, and between periaqueductal gray (PAG) and bilateral thalamus. Regarding the DMN, the posterior parietal cortex and lateral parietal (LP; R) were more strongly connected in the older group than in the younger group. Correlational analyses also showed that SI(L)-SII(R) rsFC was positively associated with pressure pain thresholds in older participants. In conclusion, these findings suggest a compensatory mechanism for the sensory changes that typically accompanies aging. Furthermore, older participants showed reduced functional connectivity between key nodes of the descending pain inhibitory pathway.

Reduced Modulation of Task-Related Connectivity Mediates Age-Related Declines in Bimanual Performance

Aging is accompanied by marked changes in motor behavior and its neural correlates. At the behavioral level, age-related declines in motor performance manifest, for example, as a reduced capacity to inhibit interference between hands during bimanual movements, particularly when task complexity increases. At the neural level, aging is associated with reduced differentiation between distinct functional systems. Functional connectivity (FC) dedifferentiation is characterized by more homogeneous connectivity patterns across various tasks or task conditions, reflecting a reduced ability of the aging adult to modulate brain activity according to changing task demands. It is currently unknown, however, how whole-brain dedifferentiation interacts with increasing task complexity. In the present study, we investigated age- and task-related FC in a group of 96 human adults across a wide age range (19.9-74.5 years of age) during the performance of a bimanual coordination task of varying complexity. Our findings indicated stronger task complexity-related differentiation between visuomotor- and nonvisuomotor-related networks, though modulation capability decreased with increasing age. Decreased FC modulation mediated larger complexity-related increases in between-hand interference, reflective of worse bimanual coordination. Thus, the ability to maintain high motor performance levels in older adults is related to the capability to properly segregate and modulate functional networks.

Impaired motor skills and atypical functional connectivity of the sensorimotor system in 40- to 65-year-old adults with autism spectrum disorders

Impairments in fine and gross motor function, coordination, and balance in early development are common in autism spectrum disorders (ASDs). It is unclear whether these deficits persist into adulthood and whether they may be exacerbated by additional motor problems that often emerge in typical aging. We assessed motor skills and used resting-state functional magnetic resonance imaging to study intrinsic functional connectivity of the sensorimotor network in 40- to 65-year-old adults with ASDs (n = 17) and typically developing matched adults (n = 19). Adults with ASDs scored significantly lower on assessments of motor skills compared with an age-matched group of typical control adults. In addition, functional connectivity of the sensorimotor system was reduced and the pattern of connectivity was more heterogeneous in adults with ASDs. A negative correlation between functional connectivity of the motor system and motor skills, however, was only found in the typical control group. Findings suggest behavioral impairment and atypical brain organization of the motor system in middle-age adults with ASDs, accompanied by pronounced heterogeneity.

Learning-driven cerebellar intrinsic functional connectivity changes in men

Learning involves distributed but coordinated activity among the widespread connected brain areas. Increase in areas connections' strength may be established offline, that is, aside from the task itself, in a resting-state. The resulting functional connectivity may hence constitute a neural trace of the learning episode. The present study examined whether a conditional visuomotor learning task previously shown to activate the cerebellum would modify cerebellar intrinsic connectivity in groups of young and older male subjects. In the group of young subjects, resting-state connectivity within several cerebellar networks (fronto-cerebellar, temporo-cerebellar, cerebello-cerebellar) was modified following the task. In most cases, modulation resulted in increased anticorrelations between cerebellar and cortical areas and the amplitude of changes was correlated with learning efficacy. The group of older subjects drastically differed, with sparser modifications of resting-state functional connectivity and no cerebellar networks involved. The findings of this exploratory study indicate that associative learning modifies the strength of intrinsic connectivity in young subjects but to a lesser degree in older subjects. They further suggest that functional connectivity within cerebellar networks may play an operative role in this kind of learning.

Visuomotor task acquisition is reduced by priming paired associative stimulation in older adults

Transcranial magnetic stimulation may represent an effective means for improving motor function in the elderly. The aim of this study was therefore to investigate the effects of paired associative stimulation (PAS; a plasticity-inducing transcranial magnetic stimulation paradigm) on acquisition of a novel visuomotor task in young and older adults. Fourteen young (20.4 ± 0.6 years) and 13 older (69.0 ± 1.6 years) adults participated in 3 experimental sessions during which training was preceded (primed) by PAS. Within each session, the interstimulus interval used for PAS was set at either the N20 latency plus 5 ms (PAS_LTP), the N20 latency minus 10 ms (PAS_LTD), or a constant 100 ms (PAS_Control). After training, the level of motor skill was not different between PAS conditions in young subjects (all p-values > 0.2), but was reduced by both PAS_LTP (p = 0.02) and PAS_LTD (p = 0.0001) in older subjects. Consequently, priming PAS was detrimental to skill acquisition in older adults, possibly suggesting a need for interventions that are optimized for use in elderly populations.

Towards understanding neural network signatures of motor skill learning in Parkinson's disease and healthy aging

In the past decade, neurorehabilitation has been shown to be an effective therapeutic supplement for patients with Parkinson's disease (PD). However, patients still experience severe problems with the consolidation of learned motor skills. Knowledge on the neural correlates underlying this process is thus essential to optimize rehabilitation for PD. This review investigates the existing studies on neural network connectivity changes in relation to motor learning in healthy aging and PD and critically evaluates the imaging methods used from a methodological point of view. The results indicate that despite neurodegeneration there is still potential to modify connectivity within and between motor and cognitive networks in response to motor training, although these alterations largely bypass the most affected regions in PD. However, so far training-related changes are inferred and possible relationships are not substantiated by brain-behavior correlations. Furthermore, the studies included suffer from many methodological drawbacks. This review also highlights the potential for using neural network measures as predictors for the response to rehabilitation, mainly based on work in young healthy adults. We speculate that future approaches, including graph theory and multimodal neuroimaging, may be more sensitive than brain activation patterns and model-based connectivity maps to capture the effects of motor learning. Overall, this review suggests that methodological developments in neuroimaging will eventually provide more detailed knowledge on how neural networks are modified by training, thereby paving the way for optimized neurorehabilitation for patients.

Aging Modulates the Resting Brain after a Memory Task: A Validation Study from Multivariate Models

Recent work has demonstrated that aging modulates the resting brain. However, the study of these modulations after cognitive practice, resulting from a memory task, has been scarce. This work aims at examining age-related changes in the functional reorganization of the resting brain after cognitive training, namely, neuroplasticity, by means of the most innovative tools for data analysis. To this end, electroencephalographic activity was recorded in 34 young and 38 older participants. Different methods for data analyses, including frequency, time-frequency and machine learning-based prediction models were conducted. Results showed reductions in Alpha power in old compared to young adults in electrodes placed over posterior and anterior areas of the brain. Moreover, young participants showed Alpha power increases after task performance, while their older counterparts exhibited a more invariant pattern of results. These results were significant in the 140-160 s time window in electrodes placed over anterior regions of the brain. Machine learning analyses were able to accurately classify participants by age, but failed to predict whether resting state scans took place before or after the memory task. These findings greatly contribute to the development of multivariate tools for electroencephalogram (EEG) data analysis and improve our understanding of age-related changes in the functional reorganization of the resting brain.

Functional and effective reorganization of the aging brain during unimanual and bimanual hand movements

Motor performance decline observed during aging is linked to changes in brain structure and function, however, the precise neural reorganization associated with these changes remains largely unknown. We investigated the neurophysiological correlates of this reorganization by quantifying functional and effective brain network connectivity in elderly individuals (n = 11; mean age = 67.5 years), compared to young adults (n = 12; mean age = 23.7 years), while they performed visually-guided unimanual and bimanual handgrips inside the magnetoencephalography (MEG) scanner. Through a combination of principal component analysis and Granger causality, we observed age-related increases in functional and effective connectivity in whole-brain, task-related motor networks. Specifically, elderly individuals demonstrated (i) greater information flow from contralateral parietal and ipsilateral secondary motor regions to the left primary motor cortex during the unimanual task and (ii) decreased interhemispheric temporo-frontal communication during the bimanual task. Maintenance of motor performance and task accuracy in elderly was achieved by hyperactivation of the task-specific motor networks, reflecting a possible mechanism by which the aging brain recruits additional resources to counteract known myelo- and cytoarchitectural changes. Furthermore, resting-state sessions acquired before and after each motor task revealed that both older and younger adults maintain the capacity to adapt to task demands via network-wide increases in functional connectivity. Collectively, our study consolidates functional connectivity and directionality of information flow in systems-level cortical networks during aging and furthers our understanding of neuronal flexibility in motor processes.

Age-related differences in network flexibility and segregation at rest and during motor performance

Brain networks undergo widespread changes in older age. A large body of knowledge gathered about those changes evidenced an increase of functional connectivity between brain networks. Previous work focused mainly on cortical networks during the resting state. Subcortical structures, however, are of critical importance during the performance of motor tasks. In this study, we investigated age-related changes in cortical, striatal and cerebellar functional connectivity at rest and its modulation by motor task execution. To that end, functional MRI from twenty-five young (mean age 21.5 years) and eighteen older adults (mean age 68.6 years) were analysed during rest and while performing a bimanual tracking task practiced over a two-week period. We found that inter-network connectivity among cortical structures was more positive in older adults both during rest and task performance. Functional connectivity within striatal structures decreased with age during rest and task execution. Network flexibility, the changes in network composition from rest to task, was also reduced in older adults, but only in networks with an age-related increase in connectivity. Finally, flexibility of areas in the prefrontal cortex were associated with lower error scores during task execution, especially in older adults. In conclusion, our findings indicate an age-related reduction in the ability to suppress irrelevant network communication, leading to less segregated and less flexible cortical networks. At the same time, striatal connectivity is impaired in older adults, while cerebellar connectivity shows heterogeneous age-related effects during rest and task execution. Future research is needed to clarify how cortical and subcortical connectivity changes relate to one another.

fMRI data processing in MRTOOL: to what extent does anatomical registration affect the reliability of functional results?

Spatial registration is an essential step in the analysis of fMRI data because it enables between-subject analyses of brain activity, measured either during task performance or in the resting state. In this study, we investigated how anatomical registration with MRTOOL affects the reliability of task-related fMRI activity. We used as a benchmark the results from two other spatial registration methods implemented in SPM12: the Unified Segmentation algorithm and the DARTEL toolbox. Structural alignment accuracy and the impact on functional activation maps were assessed with high-resolution T1-weighted images and a set of task-related functional volumes acquired in 10 healthy volunteers. Our findings confirmed that anatomical registration is a crucial step in fMRI data processing, contributing significantly to the total inter-subject variance of the activation maps. MRTOOL and DARTEL provided greater registration accuracy than Unified Segmentation. Although DARTEL had superior gray matter and white matter tissue alignment than MRTOOL, there were no significant differences between DARTEL and MRTOOL in test-retest reliability. Likewise, we found only limited differences in BOLD activation morphology between MRTOOL and DARTEL. The test-retest reliability of task-related responses was comparable between MRTOOL and DARTEL, and both proved superior to Unified Segmentation. We conclude that MRTOOL, which is suitable for single-subject processing of structural and functional MR images, is a valid alternative to other SPM12-based approaches that are intended for group analysis. MRTOOL now includes a normalization module for fMRI data and is freely available to the scientific community.