Assessing movement changes in degenerative ataxias: from the pre-ataxic disease stage to the effects of a bio-feedback intervention

Degenerative ataxias are a heterogenous group of movement disorders defined by progressive ataxia due to a degeneration of the cerebellum and its associated tracts, often of genetic origin. Disease-modifying drugs are still lacking for degenerative ataxias, thus highlighting the need for paving the way for both interventional drug trials and for innovative neurorehabilitation approaches. Detailed quantitative movement analysis might hereby help to detect and grade cerebellar dysfunction, possibly even at the preataxic stages of the disease, thus helping to chart a promising window for early treatment interventions before clinical disease onset. Moreover, it might help to gain new insights into the functional role of the cerebellum in motor control and related sensory integration mechanisms, which might be used to inform future neurorehabilitation strategies. Correspondingly, we here hypothesized (1) that quantitative movement analysis allows to reveal early movement changes when clinical signs are still absent and to capture motor progression in subjects at the preataxic stage of spinocerebellar ataxia (SCA) (study #1). Moreover, we hypothesized (2) that quantitative movement analysis allows to identify the effects of a biofeedback intervention in patients with degenerative ataxia, where they might be able to exploit real-time acoustic bio-feedback signals (ABF) of trunk acceleration to compensate for impaired postural control (study #2). Study 1: 46 participants (14 preataxic SCA mutation carriers [SCAs 1,2,3,6], 9 SCA patients at an early symptomatic stage; and 23 healthy controls) were analysed by quantitative movement analysis during stance and walking tasks of increasing complexity. We identified motor features that (i) differentiated between preataxic mutation carriers and healthy controls, even in absence of clinical signs and (ii) correlated with repeat expansion-based estimated time to disease onset. These results demonstrate that quantitative movement analysis in combination with tasks of rising difficulty levels allows to detect subclinical motor changes in spinocerebellar ataxia before clinical manifestation, which may enable the quantification of disease progression in the preclinical phase. Study 2: Quantitative movement analysis was used to investigate the effects on postural sway during stance in a short-term ABF intervention group versus a no-ABF disease control group (23 and 17 cerebellar patients, respectively). Postural sway under the conditions ‘eyes open’ and ‘eyes closed’ was measured prior to ABF, under ABF, and post ABF. Our analysis revealed a significant reduction of body sway under ABF in the ‘eyes closed’ condition. Patients who had the largest extent of postural sway at baseline even improved their stability in the ‘eyes open’ condition under ABF. Correlations were found between the degree of postural sway at baseline and the benefits of both ABF and vision, and moreover, between the benefits of both sensory modalities (i.e. ABF and vision). The no-ABF control group did not exhibit any changes in sway across stance trials. These results provide proof-of-principle evidence that despite cerebellar degeneration, patients are still able to improve dysfunctional postural control by integrating augmented sensory cues: In absence of vision, the reliance on added auditory cues can be exploited to a similar extent as vision. In case of strong postural sway, augmented auditory information can be exploited also in combination with vision. These findings indicate promising compensatory strategies of cerebellar patients to maintain balance and might inform future assistive approaches

Application of fMRI for action representation: decoding, aligning and modulating

Functional magnetic resonance imaging (fMRI) is an important tool for understanding neural mechanisms underlying human brain function. Understanding how the human brain responds to stimuli and how different cortical regions represent the information, and if these representational spaces are shared across brains and critical for our understanding of how the brain works. Recently, multivariate pattern analysis (MVPA) has a growing importance to predict mental states from fMRI data and to detect the coarse and fine scale neural responses. However, a major limitation of MVPA is the difficulty of aligning features across brains due to high variability in subjects’ responses and hence MVPA has been generally used as a subject specific analysis. Hyperalignment, solved this problem of feature alignment across brains by mapping neural responses into a common model to facilitate between subject classifications. Another technique of growing importance in understanding brain function is real-time fMRI Neurofeedback, which can be used to enable individuals to alter their brain activity. It facilitates people’s ability to learn control of their cognitive processes like motor control and pain by learning to modulate their brain activation in targeted regions. The aim of this PhD research is to decode and to align the motor representations of multi-joint arm actions based on different modalities of motor simulation, for instance Motor Imagery (MI) and Action Observation (AO) using functional Magnetic Resonance Imaging (fMRI) and to explore the feasibility of using a real-time fMRI neurofeedback to alter these action representations. The first experimental study of this thesis was performed on able-bodied participants to align the neural representation of multi-joint arm actions (lift, knock and throw) during MI tasks in the motor cortex using hyperalignment. Results showed that hyperalignment affords a statistically higher between-subject classification (BSC) performance compared to anatomical alignment. Also, hyperalignment is sensitive to the order in which subjects entered the hyperalignment algorithm to create the common model space. These results demonstrate the effectiveness of hyperalignment to align neural responses in motor cortex across subjects to enable BSC of motor imagery. The second study extended the use of hyperalignment to align fronto-parietal motor regions by addressing the problems of localization and cortical parcellation using cortex based alignment. Also, representational similarity analysis (RSA) was applied to investigate the shared neural code between AO+MI and MI of different actions. Results of MVPA revealed that these actions as well as their modalities can be decoded using the subject’s native or the hyperaligned neural responses. Furthermore, the RSA showed that AO+MI and MI representations formed separate clusters but that the representational organization of action types within these clusters was identical. These findings suggest that the neural representations of AO+MI and MI are neither the same nor totally distinct but exhibit a similar structural geometry with respect to different types of action. Results also showed that MI dominates in the AO+MI condition. The third study was performed on phantom limb pain (PLP) patients to explore the feasibility of using real-time fMRI neurofeedback to down-regulate the activity of premotor (PM) and anterior cingulate (ACC) cortices and whether the successful modulation will reduce the pain intensity. Results demonstrated that PLP patients were able to gain control and decrease the ACC and PM activation. Those patients reported decrease in the ongoing level of pain after training, but it was not statistically significant. The fourth study was conducted on healthy participants to study the effectiveness of fMRI neurofeedback on improving motor function by targeting Supplementary Motor Cortex (SMA). Results showed that participants learnt to up-regulate their SMA activation using MI of complex body actions as a mental strategy. In addition, behavioural changes, i.e. shortening of motor reaction time was found in those participants. These results suggest that fMRI neurofeedback can assist participants to develop greater control over motor regions involved in motor-skill learning and it can be translated into an improvement in motor function. In summary, this PhD thesis extends and validates the usefulness of hyperalignment to align the fronto-parietal motor regions and explores its ability to generalise across different levels of motor representation. Furthermore, it sheds light on the dominant role of MI in the AO+MI condition by examining the neural representational similarity of AO+MI and MI tasks. In addition, the fMRI neurofeedback studies in this thesis provide proof-of-principle of using this technology to reduce pain in clinical applications and to enhance motor functions in a healthy population, with the potential for translation into the clinical environment

Real-time fMRI connectivity neurofeedback for modulation of the motor system

Advances in functional magnetic resonance imaging (fMRI) have enabled an understanding of the neural mechanisms underlying human brain functions such as motor functions. In recent decades fMRI, which is a non-invasive and highresolution technique, has been used to investigate the functions of the human brain using the blood oxygen level dependent (BOLD) response as an indirect measurement of brain neural activities. Real-time fMRI (rt-fMRI) has been used as neurofeedback to enable individuals to regulate their neural activity to achieve improvements in their health and performance, such as their motor performance. Neurofeedback can be defined as the measurement of the neural activity of a participant that is presented to them as visual or auditory signals that enable self-regulation of neural activity. Rt-fMRI has also been used to provide feedback about the connectivity between brain regions. Such connectivity neurofeedback can be a more effective feedback strategy than providing feedback from a single region. Recently, connectivity neurofeedback has been explored to examine how functional connectivity of cortical areas and subcortical areas of the brain can be modulated. Enhancing connectivity between cortical and subcortical regions holds promise for the improvement of performance, particularly motor function performance. The aim of this PhD research was to modulate connectivity neurofeedback by using real-time fMRI neurofeedback (rt-fMRI-NF) between brain regions and to investigate whether any possible enhancement in the activation due to a successful fMRI-NF will translate into changes in behavioural measures. The thesis research began with experimental work to establish the experimental paradigm. This included work, using fMRI, to develop and test localisers for different motor areas such as primary motor cortex (M1), supplementary motor cortex (SMA), the motor cerebellum and the motor thalamus. The results showed that the execution of actions, such as hand clenching, can be used to functionally activate many motor areas including M1, SMA and the cerebellum. The motor thalamus was localised using a motor thalamus mask that was created offline using the Talairach atlas. All localisers tested in this research were feasible and able to be used for applications such as rt-fMRI-NF research to define the regions of interest. The first rt-fMRI connectivity neurofeedback experimental study of this thesis was conducted to determine whether healthy participants can use neurofeedback to enhance the connectivity between M1 and the thalamus using rt-fMRI. It also aimed to investigate whether successful rt-fMRI-NF of M1- thalamus connectivity could translate into changes in behavioural measures. For this purpose, the behavioural tasks were conducted before and after each MRI session. Two behavioural tasks were used in this experiment: Go/No Go and switching tasks. The results of this experiment showed a significant increase in connectivity neurofeedback in the experimental group (M1-thalamus), hence, rt-fMRI-NF is a useful tool to modulate functional connectivity between M1 and the thalamus using motor imagery and it facilitates the learning by participants of new mental strategies to upregulate M1-thalamus connectivity. The behavioural tasks showed a significant reduction in the switching time in the experimental group while Go/No Go task did not show a significant reduction in the reaction time in the experimental group. The second rt-fMRI connectivity neurofeedback experimental study of this thesis was conducted to investigate the ability of neurofeedback to modulate M1-cerebellum connectivity using motor imagery based rt-fMRI-NF. The results of this research showed enhanced connectivity between M1 and the cerebellum in each participant. However, this enhancement was not statistically significant. In summary, this PhD thesis extends and validates the usefulness of connectivity neurofeedback using motor imagery based rt-fMRI to modulate the correlation between cortical and subcortical brain regions. Successful modulation using this technique has the potential to lead to an enhancement in motor functions. Thereby, the results of this PhD research may help to advance connectivity neurofeedback for use as a supplementary treatment for many brain disorders such as stroke recovery and Parkinson’s disease

MECHANISMS OF MOTOR AND PERCEPTUAL LEARNING IN LOCOMOTOR ADAPTATION

Moving in the real world requires continually learning and updating movement to account for systematic changes in the environment (e.g. walking in snow versus grass). One form of motor learning is ‘motor adaptation’, defined as the trial-by-trial automatic process that reduces movement errors caused by environment perturbations. This process can also recalibrate perception of the adapted movement. Adaptation is traditionally thought to operate by implicitly recalibrating an internal model that predicts the sensory consequences of a motor command in response to errors in that prediction. Work suggests that there may be additional mechanisms at play in adaptation, but these mechanisms are not fully understood. In this dissertation, we aim to better dissect the learning mechanisms that contribute to walking adaptation. We first provide evidence to suggest that the sensorimotor recalibration mechanism may modify both movement and perception of walking, such that perceptual recalibration may be used as a marker of implicit recalibration. We also find that perceptual recalibration transfers from treadmill to overground walking, suggesting that implicit recalibration may contribute to transfer of adaptation to untrained environments. We then investigate what additional learning mechanisms may play a role in locomotor adaptation. We demonstrate a novel mechanism of adaptation during walking that does not conform with sensorimotor recalibration: the mechanism does not change perception, yet can flexibly correct movement for a range of different perturbations that need not have been experienced. Results from a dual-tasking paradigm further suggest that cognitive processes such as working memory may also play a role in locomotor adaptation. Finally, we provide insight into how the different learning mechanism of adaptation change throughout the life span. We show that perceptual recalibration only develops between 6-8 years of age in childhood. We also show that capacity to perform a cognitive task simultaneously to locomotor adaptation worsens between young to middle-age, suggesting that cognitive mechanisms of adaptation may decline with age. Taken together, our results suggest that, despite occurring largely automatically, locomotor adaptation engages different learning mechanisms that have variable levels of flexibility and are likely to have distinct neural underpinnings

The effect of manipulating action observation variables on corticospinal excitability using transcranial magnetic stimulation

Action observation interventions have been shown to contribute to improvements in motor performance and (re)learning. This thesis examined the effect of manipulating action observation variables on corticospinal excitability (CSE) using transcranial magnetic stimulation (TMS), with the aim of informing interventions for motor (re)learning. Eye-tracking and interview techniques were employed in combination with TMS to provide novel explorations for how screen position, visual context, and emotional valence influence CSE, visual attention, and individual experience during action observation. The Pilot Experiment (Chapter 5) tested the appropriateness of both single- and paired-pulse TMS techniques during action observation. Results determined that single-pulse TMS was appropriate for the subsequent experiments included in this thesis. Experiment 1 (Chapter 6) investigated the effect of screen position during action observation on CSE. The results demonstrated greater CSE during action observation on a horizontal, compared to a vertical, screen position, but only once each individual’s viewing preference had been taken into account. Experiment 2 (Chapter 7) investigated the effect of congruent and incongruent contexts on CSE. The results indicated that congruent context during action observation facilitates CSE more than control conditions in contrast to an incongruent visual context. Experiment 3 (Chapter 8) explored the effect of each participant’s most preferred, least preferred, and neutral preference food items involved in an observed reach and grasp action on CSE. The results showed no significant differences between the control condition and observing a reach and grasp of each participant’s personalised least preferred and neutral preference food items. Significant inhibition of CSE was shown during observation of a reach and grasp of each participant’s most preferred food item. The three main experiments in this thesis provide novel contributions to action observation literature by incorporating eye-tracking and interview techniques in combination with TMS to better determine the nature of CSE modulation. Taken together, these findings directly inform both future research and practice in motor (re)learning by highlighting the importance of meaning and context during action observation