ECSS Paris 2023: OP-BM06
INTRODUCTION: The mechanisms subserving motor learning in the intact human brain are not fully understood. We recently reported that learning a dynamic balancing task (DBT) over a 4-week period in young healthy adults (n = 24) leads to a behaviorally relevant increase in the complexity of cortical neurite orientation in motor brain areas [1], consistent with the idea of synaptic remodeling [2]. However, since a comprehensive understanding of motor learning can only be achieved by studying the interaction of distributed cortical and subcortical areas [2], we will focus here on learning-induced changes of the microstructural composition of the fiber tracts that interconnect hub regions of the motor network. METHODS: We used a powerful within-subjects design with a 4-week life-as-usual control period immediately followed by an equally long period of DBT learning, as described in [1]. A unique set of quantitative MRI (qMRI) contrasts weighted towards diffusion, relaxation times and magnetization transfer were measured at baseline as well as before and after the learning period. Advanced biophysical models of tissue microstructure were fitted to these data, resulting in parameter maps sensitive to features such as tissue density, neurite orientation and density, myelin and iron [3,4]. White matter fiber tracts were virtually dissected using tractography and neural network-based bundle recognition [5], and qMRI parameter maps were projected onto these bundles. Finally, along-tract statistics of latent microstructural changes over time [6] were performed. RESULTS: Non-overlapping 95% bootstrap CIs [6] of factor scores over time suggest significant learning-induced plasticity in major association (anterior thalamic radiation, superior longitudinal fascicle), commissural (corpus callosum) and projection tracts (corticospinal tract, thalamocortical and corticostriatal fibers). Importantly, based on factor loadings on the trajectory of latent change over time, we were able to infer three main drivers of neuroplastic change: process 1 is dominated by myelin-sensitive metrics, process 2 is dominated by neurite density and dispersion-sensitive metrics, process 3 is dominated by iron-sensitive metrics. CONCLUSION: Here we have characterized the multifaceted microstructural changes in white matter in response to motor learning with unprecedented biological specificity. Consistent with theoretical predictions based on animal studies [2], we demonstrate the presence of neuronal, extra-neuronal and myelin-related changes also in the human brain. In perspective, we anticipate our study to be a starting point towards a more comprehensive understanding of the mechanisms subserving motor learning in physiological and pathological aging or in movement disorders. [1] Lehmann et al., J Neurosci, 2023 [2] Zatorre et al., Nat Neurosci, 2012 [3] Zhang et al., Neuroimage, 2012 [4] Weiskopf et al., Front Neurosci, 2013 [5] Wasserthal et al., Med Image Anal, 2019 [6] Madssen et al., PLoS Comput Biol, 2021
Read CV Nico LehmannECSS Paris 2023: OP-BM06
INTRODUCTION: The interconnected nature of human musculature and the neural system suggests that localised activities in the neck and masticatory systems could significantly impact spinal excitability throughout the body. For example, teeth occlusion, occurring voluntarily or non-voluntarily during sports activities, has an immediate facilitatory effect (1). However, the effect of stretching and relaxation of masticatory muscles is not well studied. This study aims to investigate the effects of neck and masticatory musculature mobilisation exercises, as well as specific chewing exercises, on masticatory muscle stiffness and the soleus (SOL) H reflex. METHODS: Ten participants (age 27.2 ± 6.8 years, 4 females) engaged in two interventions: relaxing exercises for the neck and masticatory musculature (EX) and heavy chewing (CW). These interventions were separated by a 30-minute washout period. Masseter muscle tone and stiffness, as well as SOL H-reflex and D1 presynaptic inhibition, were assessed before and after each intervention using a handheld myotonometric device and a 64-channel matrix electrode (GR08MM1305, OT Bioelettronica, Italy). A bipolar version of the signal was computed to extract peak-to-peak amplitudes of electrically elicited responses (Global EMG). Additionally, signals were decomposed to analyse contributions from single motor units (2). A total of 8400 firings from 376 distinct MUs were categorised based on low, medium, and high firing thresholds. Data were analysed using repeated measures nested linear mixed-effect models. RESULTS: The H-reflex amplitude decreased post-EX intervention, in contrast to the CW intervention, where it remained unchanged, resulting in a significant interaction effect (p < 0.001). No statistically significant changes were observed in D1 presynaptic inhibition (p = 0.2). Analysis at the single MU level reflected results consistent with the global EMG, but interventions did not selectively affect MUs of different threshold categories. Masseter muscle stiffness and tone increased post-EX and decreased post-CW, showing a significant interaction effect (p < 0.001). CONCLUSION: Neck and masticatory muscle stretching and mobility exercises significantly reduced SOL H-reflex amplitude, indicating a potential global reduction in spinal excitability and enhanced relaxation. This effect does not appear to be mediated by D1 presynaptic inhibition mechanisms and could involve other spinal ionotropic and neuromodulatory mechanisms (3). In contrast, an increase in muscle tone and stiffness was observed during EX, possibly due to increased blood flow in the active muscles, while the decrease post-CW might be attributed to fatigue-induced mechanisms. REFERENCES: 1. Yamada et al., Health Science Reports, 2023 2. Kalc et al., IEEE TNSRE, 2023 3. Mesquita et al., J Physiol, 2022
Read CV Miloš KalcECSS Paris 2023: OP-BM06
INTRODUCTION: Positive effects of exercise on cognition are thought to be especially strong at either ends of the life span spectrum [1]. Particularly in case of older adults approaching physical and cognitive decline, optimisation of exercise induced benefits is necessary [2]. One proposed approach is to match the difficulty level of the task being trained to the individual’s abilities and applying this optimised ratio during training [3]. Therefore, we hypothesized that optimal training conditions would induce higher learning gains and enhance transfer effects onto untrained motor and cognitive tasks. METHODS: We conducted a randomized, single-blinded, 6-week dynamic balance training (DBT) intervention [4] optimised to the participants individual balance ability [3] (n=30, age range 60-80 yrs). Balance ability was assessed using 6-different levels of task difficulties ranging from level 0 (highest) to level 5 (lowest). Training was formulated to emulate either overload, underload or optimal load conditions. Cognitive (memory and executive) and near-far motor transfer (untrained variations of DBT and Wii) were investigated half-way through training duration (mid) and post training (post). Statistical analyses were conducted using repeated measures ANOVA with simultaneous component analysis (RM-ASCA+), a method combining linear mixed models with PCA [5]. Using the optimal group as the reference condition, group differences were inferred from non-overlapping 95% bootstrap intervals of the factor scores [5]. RESULTS: RM-ASCA+ revealed higher learning gains after the first training session in the optimal training group (95% CI [0.17, 1.44]) compared to both overload (95%CI [-2.46, -0.07]) and underload conditions (95%CI [-2.08, 0.03]). Similarly, higher learning gains after second (optimal vs underload: 95%CI [-1.76, 0.089]) and fifth training sessions (optimal vs overload: 95%CI [-1.83, 0.22]) were detected. This advantage of optimal training load was more pronounced at higher task difficulty levels as group differences were driven by higher factor loadings at level 1, 2 and 5. Furthermore, optimal load (95%CI [0.34, 1.01]) induced higher transfer effects mid- (underload: 95%CI [-1.29, 0.47], overload: 95%CI [-1.64, -0.3]) and post-intervention (underload: 95%CI [-1.46, -0.04], overload: 95%CI [-2.01, -0.34]). These differences were driven by higher factor loadings for motor transfer and executive tasks. CONCLUSION: Our results show that benefits of optimising practice conditions in old age are not just limited to greater learning gains on the trained task, but are also reflected as performance improvements in transfer tasks. These findings further highlight the underlying neural mechanisms involved that enable transfer across domains. [1] Tomporowski & Pesce, Psychol Bull., 2019 [2] Ludyga et al., Nat Hum Behav., 2020 [3] Guadagnoli & Lee, J Mot Behav., 2004 [4] Taubert et al., J Neurosci., 2010 [5] Jarmund et al., Front Mol Biosci., 2022
Read CV Nisha Maria PrabhuECSS Paris 2023: OP-BM06