Motor neuroplasticity: A MEG-fMRI study of motor imagery and execution in healthy ageing

Lifespan trajectories of motor control and neural oscillations: A systematic review of magnetoencephalography insights

Motor control (MC) evolves across the human lifespan, improving during childhood and adolescence, stabilizing in early adulthood, and declining in older age. These developmental and degenerative patterns are linked to neural oscillatory activity, which can be assessed via magnetoencephalography (MEG) to gain insights into motor planning, execution, termination, and command initiation. This review systematically examined age-related changes in MC and neural oscillations, centering on movement-related beta desynchronization (MRBD), post-movement beta rebound (PMBR), and movement-related gamma synchrony (MRGS). Following PRISMA guidelines, 17 cross-sectional studies were identified. The findings revealed significant enhancements in motor efficiency from childhood to adolescence, characterized by faster movement speed, shorter movement duration, weaker MRBD, and increased PMBR and MRGS. From adolescence to early adulthood, further improvements in motor performance were noted, accompanied by strengthened MRBD, PMBR, and a slight decline in MRGS. In older adults, motor performance deteriorates, presenting as slower movement and prolonged duration, alongside heightened resting beta power, elevated MRBD, and reduced PMBR. Alterations in MRGS remain insufficiently explored. Overall, MEG proves valuable for capturing neural dynamics underlying the development and decline of motor control across the lifespan. These findings underscore potential avenues for motor rehabilitation and cognitive interventions, particularly in aging populations.

Deep Learning-Enhanced Motor Training: A Hybrid VR and Exoskeleton System for Cognitive-Motor Rehabilitation

This research explored the integration of the real-time machine learning classification of motor imagery data with a brain-machine interface, leveraging prefabricated exoskeletons and an EEG headset integrated with virtual reality (VR). By combining these technologies, the study aimed to develop practical and scalable therapeutic applications for rehabilitation and daily motor training. The project showcased an optimized system designed to assess and train cognitive-motor functions in elderly individuals. Key innovations included a motor imagery EEG acquisition protocol for data classification and a machine learning framework leveraging deep learning with a wavelet packet transform for feature extraction. Comparative analyses were conducted with traditional models such as Support Vector Machines (SVMs), Convolutional Neural Networks (CNNs), and Long Short-Term Memory (LSTM) networks. The performance was further enhanced through a random hyperparameter search, optimizing feature extraction and learning parameters to achieve high classification accuracy (89.23%). A novel VR fishing game was developed to dynamically respond to EEG outputs, enabling the performance of interactive motor imagery tasks in coordination with upper limb exoskeleton arms. While clinical testing is ongoing, the system demonstrates potential for increasing ERD/ERS polarization rates in alpha and beta waves among elderly users after several weeks of training. This integrated approach offers a tangible step forward in creating effective, user-friendly solutions for motor function rehabilitation.

Differences in motor learning-related structural plasticity of layer 2/3 parvalbumin-positive interneurons of the young and aged motor cortex

Changes to neuronal connectivity are believed to be a key factor in cognitive impairments associated with normal aging. Because of its effect on activities of daily living, deficient motor control is a critical type of cognitive decline to understand. Diminished inhibitory networks in the cortex are implicated in such motor control deficits, pointing to the connectivity of inhibitory cortical interneurons as an important area for study. Here, we used chronic two-photon microscopy to track the structural plasticity of en passant boutons (EPBs) of parvalbumin-positive interneurons in the mouse motor cortex in the first longitudinal, in vivo study of inhibitory interneuron synapses in the context of aging. Young (3-5 months) and aged (23-28 months) mice underwent training on the accelerating rotarod to evoke motor learning-induced structural plasticity. Our analysis reveals that, in comparison with axons from young mice, those from aged mice have fewer EPBs at baseline that also tend to be larger in size. Aged axons also express learning-related structural plasticity-like new bouton stabilization and bouton enlargement-that is less persistent than that of young axons. This study reveals striking baseline differences in young and aged axon morphology as well as differences in the deployment of learning-related structural plasticity across axons.

Differences in motor imagery abilities in active and sedentary individuals: new insights from backward-walking imagination

Evidence has shown that imagining a complex action, like backward-walking, helps improve the execution of the gesture. Despite this, studies in sport psychology have provided heterogeneous results on the use of motor imagery (MI) to improve performance. We aimed to fill this gap by analyzing how sport experience influences backward-walking MI processes in a sample of young women (n = 41, mean age = 21 ± 2.2) divided into Active and Sedentary. All participants were allocated to two randomized mental chronometric tasks, in which they had first to imagine and then execute forward-walking (FW) and backward-walking (BW). The Isochrony Efficiency measured the difference between imagination and execution times in both conditions (FW and BW). Moreover, we analyzed the ability to vividly imagine FW and BW within various perspectives in both groups through the Vividness of Movement Imagery Questionnaire (VMIQ-2). Findings showed that active individuals performed better in the BW imagery task when compared to sedentary ones (F1,39 = 4.98; p = 0.03*), while there were no differences between groups in the FW imagery task (F1,39 = .10; p = 0.75). Further, VMIQ-2 had evidenced that the ability to imagine backward is influenced by perspective used. Specifically, the use of internal visual imagery (IVI) led to worse Isochrony Efficiency (t32,25 = 2.16; p = 0.04*), while the use of kinesthetic imagery (KIN) led to better Isochrony Efficiency (t32,25 =  - 2.34; p = 0.03*). These results suggest a close relation between motor experience and complex motor imagery processes and open new insights for studying these mental processes.

Classification of EEG Signals Based on Sparrow Search Algorithm-Deep Belief Network for Brain-Computer Interface

In brain-computer interface (BCI) systems, challenges are presented by the recognition of motor imagery (MI) brain signals. Established recognition approaches have achieved favorable performance from patterns like SSVEP, AEP, and P300, whereas the classification methods for MI need to be improved. Hence, seeking a classification method that exhibits high accuracy and robustness for application in MI-BCI systems is essential. In this study, the Sparrow search algorithm (SSA)-optimized Deep Belief Network (DBN), called SSA-DBN, is designed to recognize the EEG features extracted by the Empirical Mode Decomposition (EMD). The performance of the DBN is enhanced by the optimized hyper-parameters obtained through the SSA. Our method's efficacy was tested on three datasets: two public and one private. Results indicate a relatively high accuracy rate, outperforming three baseline methods. Specifically, on the private dataset, our approach achieved an accuracy of 87.83%, marking a significant 10.38% improvement over the standard DBN algorithm. For the BCI IV 2a dataset, we recorded an accuracy of 86.14%, surpassing the DBN algorithm by 9.33%. In the SMR-BCI dataset, our method attained a classification accuracy of 87.21%, which is 5.57% higher than that of the conventional DBN algorithm. This study demonstrates enhanced classification capabilities in MI-BCI, potentially contributing to advancements in the field of BCI.

Leveraging Motor Imagery Rehabilitation for Individuals with Disabilities: A Review

Motor imagery, an intricate cognitive procedure encompassing the mental simulation of motor actions, has surfaced as a potent strategy within the neuro-rehabilitation domain. It presents a non-invasive, economically viable method for facilitating individuals with disabilities in enhancing their motor functionality and regaining self-sufficiency. This manuscript delivers an exhaustive analysis of the significance of motor imagery in augmenting functional rehabilitation for individuals afflicted with physical impairments. It investigates the fundamental mechanisms governing motor imagery, its applications across diverse disability conditions, and the prospective advantages it renders. Moreover, this document addresses the prevailing obstacles and prospective trajectories in this sector, accentuating the necessity for continued investigation and the invention of cutting-edge technologies that optimize the potentiality of motor imagery in aiding disabled persons.

Neuronal Plasticity and Age-Related Functional Decline in the Motor Cortex

Physiological aging causes a decline of motor function due to impairment of motor cortex function, losses of motor neurons and neuromuscular junctions, sarcopenia, and frailty. There is increasing evidence suggesting that the changes in motor function start earlier in the middle-aged stage. The mechanism underlining the middle-aged decline in motor function seems to relate to the central nervous system rather than the peripheral neuromuscular system. The motor cortex is one of the responsible central nervous systems for coordinating and learning motor functions. The neuronal circuits in the motor cortex show plasticity in response to motor learning, including LTP. This motor cortex plasticity seems important for the intervention method mechanisms that revert the age-related decline of motor function. This review will focus on recent findings on the role of plasticity in the motor cortex for motor function and age-related changes. The review will also introduce our recent identification of an age-related decline of neuronal activity in the primary motor cortex of middle-aged mice using electrophysiological recordings of brain slices.

Motor Imagery as a Key Factor for Healthy Ageing: A Review of New Insights and Techniques

Motor imagery (MI) describes a dynamic cognitive process where a movement is mentally simulated without taking place and holds potential as a means of stimulating motor learning and regaining motor skills. There is growing evidence that imagined and executed actions have common neural circuitry. Since MI counteracts cognitive and motor decline, a growing interest in MI-based mental exercise for older individuals has emerged. Here we review the last decade's scientific literature on age-related changes in MI skills. Heterogeneity in the experimental protocols, as well as the use of populations with unrepresentative age, is making it challenging to draw unambiguous conclusions about MI skills preservation. Self-report and behavioural tasks have shown that some MI components are preserved, while others are impaired. Evidence from neuroimaging studies revealed that, during MI tasks, older individuals hyperactivate their sensorimotor and attentional networks. Some studies have argued that this represents a compensatory mechanism, others claim that this is a sign of cognitive decline. However, further studies are needed to establish whether MI could be used as a promotion factor to improve cognitive functioning and well-being in older people.

Neural Bases of Age-Related Sensorimotor Slowing in the Upper and Lower Limbs

With advanced age, there is a loss of reaction speed that may contribute to an increased risk of tripping and falling. Avoiding falls and injuries requires awareness of the threat, followed by selection and execution of the appropriate motor response. Using event-related potentials (ERPs) and a simple visual reaction task (RT), the goal of our study was to distinguish sensory and motor processing in the upper- and lower-limbs while attempting to uncover the main cause of age-related behavioral slowing. Strength (amplitudes) as well as timing and speed (latencies) of various stages of stimulus- and motor-related processing were analyzed in 48 healthy individuals (young adults, n = 24, mean age = 34 years; older adults, n = 24, mean age = 67 years). The behavioral results showed a significant age-related slowing, where the younger compared to older adults exhibited shorter RTs for the upper- (222 vs. 255 ms; p = 0.006, respectively) and the lower limb (257 vs. 274 ms; p = 0.048, respectively) as well as lower variability in both modalities (p = 0.001). Using ERP indices, age-related slowing of visual stimulus processing was characterized by overall larger amplitudes with delayed latencies of endogenous potentials in older compared with younger adults. While no differences were found in the P1 component, the later components of recorded potentials for visual stimuli processing were most affected by age. This was characterized by increased N1 and P2 amplitudes and delayed P2 latencies in both upper and lower extremities. The analysis of motor-related cortical potentials (MRCPs) revealed stronger MRCP amplitude for upper- and a non-significant trend for lower limbs in older adults. The MRCP amplitude was smaller and peaked closer to the actual motor response for the upper- than for the lower limb in both age groups. There were longer MRCP onset latencies for lower- compared to upper-limb in younger adults, and a non-significant trend was seen in older adults. Multiple regression analyses showed that the onset of the MRCP peak consistently predicted reaction time across both age groups and limbs tested. However, MRCP rise time and P2 latency were also significant predictors of simple reaction time, but only in older adults and only for the upper limbs. Our study suggests that motor cortical processes contribute most strongly to the slowing of simple reaction time in advanced age. However, late-stage cortical processing related to sensory stimuli also appears to play a role in upper limb responses in the elderly. This process most likely reflects less efficient recruitment of neuronal resources required for the upper and lower extremity response task in older adults.

GABAergic Modulation in Movement Related Oscillatory Activity: A Review of the Effect Pharmacologically and with Aging

Gamma-aminobutyric acid (GABA) is a ubiquitous inhibitory neurotransmitter critical to the control of movement both cortically and subcortically. Modulation of GABA can alter the characteristic rest as well as movement-related oscillatory activity in the alpha (8-12 Hz), beta (13-30 Hz, and gamma (60-90 Hz) frequencies, but the specific mechanisms by which GABAergic modulation can modify these well-described changes remains unclear. Through pharmacologic GABAergic modulation and evaluation across the age spectrum, the contributions of GABA to these characteristic oscillatory activities are beginning to be understood. Here, we review how baseline GABA signaling plays a key role in motor networks and in cortical oscillations detected by scalp electroencephalography and magnetoencephalography. We also discuss the data showing specific alterations to baseline movement related oscillatory changes from pharmacologic intervention on GABAergic tone as well as with healthy aging. These data provide greater insight into the physiology of movement and may help improve future development of novel therapeutics for patients who suffer from movement disorders.

Does Hemispheric Asymmetry Reduction in Older Adults in Motor Cortex Reflect Compensation?

Older adults tend to display greater brain activation in the nondominant hemisphere during even basic sensorimotor responses. It is debated whether this hemispheric asymmetry reduction in older adults (HAROLD) reflects a compensatory mechanism. Across two independent fMRI experiments involving adult life span human samples (N = 586 and N = 81, approximately half female) who performed right-hand finger responses, we distinguished between these hypotheses using behavioral and multivariate Bayes (MVB) decoding approaches. Standard univariate analyses replicated a HAROLD pattern in motor cortex, but in and out of scanner behavioral results both demonstrated evidence against a compensatory relationship in that reaction time measures of task performance in older adults did not relate to ipsilateral motor activity. Likewise, MVB showed that this increased ipsilateral activity in older adults did not carry additional information, and if anything, combining ipsilateral with contralateral activity patterns reduced action decoding in older adults (at least in experiment 1). These results contradict the hypothesis that HAROLD is compensatory and instead suggest that the age-related ipsilateral hyperactivation is nonspecific, consistent with alternative hypotheses about age-related reductions in neural efficiency/differentiation or interhemispheric inhibition.

SIGNIFICANCE STATEMENT A key goal in the cognitive neuroscience of aging is to provide a mechanistic explanation of how brain–behavior relationships change with age. One interpretation of the common finding that task-based hemispheric activity becomes more symmetrical in older adults is that this shift reflects a compensatory mechanism, with the nondominant hemisphere needing to help out with computations normally performed by the dominant hemisphere. Contrary to this view, our behavioral and brain data indicate that the additional activity in ipsilateral motor cortex in older adults is not reflective of better task performance nor better neural representations of finger actions.

Physical activity, motor performance and skill learning: a focus on primary motor cortex in healthy aging

Participation in physical activity benefits brain health and function. Cognitive function generally demonstrates a noticeable effect of physical activity, but much less is known about areas responsible for controlling movement, such as primary motor cortex (M1). While more physical activity may support M1 plasticity in older adults, the neural mechanisms underlying this beneficial effect remain poorly understood. Aging is inevitably accompanied by diminished motor performance, and the extent of plasticity may also be less in older adults compared with young. Motor complications with aging may, perhaps unsurprisingly, contribute to reduced physical activity in older adults. While the development of non-invasive brain stimulation techniques have identified that human M1 is a crucial site for learning motor skills and recovery of motor function after injury, a considerable lack of knowledge remains about how physical activity impacts M1 with healthy aging. Reducing impaired neural activity in older adults may have important implications after neurological insult, such as stroke, which is more common with advancing age. Therefore, a better understanding about the effects of physical activity on M1 processes and motor learning in older adults may promote healthy aging, but also allow us to facilitate recovery of motor function after neurological injury. This article will initially provide a brief overview of the neurophysiology of M1 in the context of learning motor skills, with a focus on healthy aging in humans. This information will then be proceeded by a more detailed assessment that focuses on whether physical activity benefits motor function and human M1 processes.