720 research outputs found

    Bilateral upper-limb coordination in aging and stroke

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    Bilateral upper-limb coordination is an important ability for our living independency, since most of our daily tasks, such as lifting a box or using knife and fork, require the simultaneous use of both arms (Waller et al., 2006). However, bilateral coordination decline has been observed in both healthy aging and neurological groups (Pollock et al., 2014; Maes et al., 2017) , which often results in decreased quality of life (Broeks et al., 1999; Franceschini et al., 2010). Therefore, this dissertation sought to understand the characteristics and mechanisms of bilateral coordination and its impairments. The two fundamental bilateral movements in human upper limbs, i.e., in-phase (homologous muscles from bilateral arms activate simultaneously) and anti-phase (different muscle groups from bilateral arms activate simultaneously) movements, have been found to show different characteristics in behavioral and neural measurements (Swinnen and Wenderoth, 2004). Behaviorally, anti-phase movements are found to be performed with lower movement accuracy and higher phase variability between hands compared to in-phase movements (Wuyts et al., 1996; Byblow et al., 2000; Pollok et al., 2007). On the neural level, fMRI studies demonstrated that the left hemisphere shows larger task-related BOLD signal changes compared to the right hemisphere during in-phase movements (Aramaki et al., 2006), while the BOLD signal changes between the two hemispheres are similar during anti-phase movements (Walsh et al., 2008). These results suggest a left-dominated control of in-phase movements. However, a critical limitation in the literature is the lack of causal evidence supporting hemispherical specialization in bilateral coordination. Therefore, it is unclear whether the observed behavioral differences between anti-phase and in-phase movements were truly due to distinct hemispheric control. Another limitation of the literature is the design of existing paradigms. While most of our daily activities involve movements engaging multiple joints at the same time (Keenan et al., 2006; Murphy et al., 2006), previous studies mostly investigated single joint movements (e.g. index finger tapping, forearm pronation-supination). Contrary to single joint movements, bilateral movements engaging multiple joints require not only inter-limb coordination, but also additional intra-limb coordination. Therefore, it is unclear whether the previous findings from single joint movements could be directly applied to multiple joint movements. In this dissertation, we used a bilateral coordination paradigm involving both shoulder and elbow joints to investigate the neural mechanisms behind bilateral coordination and its decline. We designed three studies focusing on 1) the differences between bilateral in-phase and anti-phase movements from a human motion perspective, 2) how aging affects different bilateral coordination patterns and its neural correlates, as well as 3) how lesioned hemisphere affects bilateral coordination impairments and whether distinct rehabilitation treatments are needed after a left or right hemispheric stroke. In Study 1, we examined the two basic bilateral coordination modes, in-phase and anti-phase movements, in healthy young right-handed participants. We used a bilateral circle drawing task involving both shoulder and elbow joints. During the movements, we measured participants’ hand positions with high temporal and spatial precision, and developed intra-limb and inter-limb measures to differentiate movement characteristics during the two basic movement modes. For intra-limb coordination, we quantified trajectory variability of each hand during the movements. For inter-limb coordination, we computed the phase synchronization between hands. We found that intra-limb coordination was worse in the non-dominant hand during anti-phase compared to in-phase movements. In contrast, intra-limb coordination in the dominant hand did not differ between anti-phase and in-phase movements. Second, participants showed worse inter-limb synchronization during anti-phase compared to in-phase movements. Moreover, we examined the hand acceleration profile of both hands, and found that participants’ bilateral hands accelerated and decelerated in an in-phase manner during in-phase movements. In contrast, the acceleration and deceleration of the two hands were unrelated during anti-phase movements. These inter-limb acceleration profiles support the idea of differential neural mechanisms behind bilateral anti-phase and in-phase movements: during in-phase movements, the hands are governed by a common neural generator, while during anti-phase movements, the two hands are controlled by both hemispheres more independently. Taken together, Study 1 showed that the current experimental setup is able to differentiate the performance between bilateral in-phase and anti-phase movements engaging multiple joints. Therefore, we used the same paradigm combined with electroencephalography (EEG) to examine the presumed decline of bilateral coordination in aging. In Study 2, we investigated the effect of aging on the two basic bilateral movement modes. We used intra- and inter-limb measures as the behavioral measures, and EEG as a neural measure. Behaviorally, we found that older adults only showed significant impairments in anti-phase movements, but not in-phase movements, compared to young adults. On the neural level, we found that older adults showed different neural responses during anti-phase and in-phase movements compared to young adults. Specifically, during in-phase movements, young adults showed a more pronounced decrease of alpha power (8-12 Hz) over the left compared to the right hemisphere, while older adults showed similar levels of alpha power decrease over both hemispheres. Furthermore, in the older adults, we found a marginal correlation between the change in alpha power over the right hemisphere and the behavioral performance, which indicated a compensatory brain response. As for the anti-phase movements, we found that participants with stronger directional inter-hemispheric connectivity in the beta band (15-25 Hz) showed worse behavioral performance, and this effect was more pronounced in the older adults. This result implies that a balanced inter-hemispheric contribution is essential for executing a successful anti-phase movement. Our findings therefore show that the two hemispheres are differentially involved in the two basic bilateral coordination modes. These different neural characteristics may explain the distinct decline patterns of in-phase and anti-phase movements in older adults. However, causal evidence to support hemispherical specialization is needed to confirm our findings. Therefore, we conducted Study 3, where we used stroke as a lesion model to examine the influence of the lesioned hemisphere on bilateral coordination. In Study 3, we examined the bilateral coordination ability in patients with left (LHS) and right hemispheric stroke (RHS), as well as healthy controls. Given that healthy young participants show a left-dominant control in in-phase movements in Study 2 and in the previous literature (Aramaki et al., 2006; Maki et al., 2008), we expected that LHS patients would display a more pronounced impairment of in-phase movements compared to RHS patients. In contrast, since anti-phase movements require a more balanced inter-hemispheric contribution as shown in Study 2, and RHS patients show larger inter-hemispheric inhibition compared to healthy participants and LHS patients (Lewis and Perreault, 2007b), we expected that RHS patients would show more impairment in anti-phase movements compared to LHS patients. As predicted, we found that patients with RHS patients exhibited greater impairment during anti-phase movements (both intra- and inter-limb parameters) and LHS patients showed greater impairment during in-phase movements (intra-limb parameters only). Though LHS patients did not show greater impairment in inter-limb coordination during in-phase movements compared to RHS patients, our regression analysis revealed that only LHS patients swapped hand dominance during the task. We interpreted this result as a compensatory mechanism whereby bilateral in-phase movements in the LHS group switched from a left-dominated cortical control to a right-dominated cortical control. Our findings not only provide causal evidence for hemispheric specialization in bilateral movement coordination, but also characterize the differential impairments in bilateral coordination after a left or right hemispheric stroke. Taken together, this dissertation highlighted differential neural control processes involved in bilateral in-phase and anti-phase movements, and demonstrated how these distinct mechanisms lead to impaired bilateral coordination in aging and stroke. The present results could therefore advance the development of therapeutic strategies that seek to counteract bilateral coordination decline, such as differential treatment for patients with left and right hemispheric lesions, or the use of noninvasive brain stimulation at a target hemisphere.:List of abbreviations List of figures List of tables Chapter 1. General introduction 1.1. Introduction 1.2. Bilateral coordination in human upper extremities 1.3. Age-related motor decline 1.4. Stroke-induced motor impairments Chapter 2. Rationale of the Dissertation Chapter 3. Study I: Human motion characteristics during bilateral in-phase and anti-phase movements 3.1. Introduction 3.2. Materials and methods 3.3. Results 3.4. Discussion 3.5. Conclusion Chapter 4. Study II: The effect of aging on bilateral coordination 49 4.1. Introduction 4.2. Materials and methods 4.3. Results 4.4. Discussion 4.5. Conclusion Chapter 5. Study III: Effects of lesioned side on bilateral coordination after strokes 5.1. Introduction 5.2. Materials and methods 5.3. Results 5.4. Discussion 5.5. Conclusion Chapter 6. General discussion 6.1. Summary of research 6.2. Contributions and clinical implications 6.3. Outlook for future research Chapter 7. Summary of the dissertation References Appendix Appendix 1. Supplementary information for study 1 Appendix 2. Supplementary information for study 2 Appendix 3. Supplementary information for study 3 Appendix 4. Declaration of authenticit

    Multiscale Topological Properties Of Functional Brain Networks During Motor Imagery After Stroke

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    In recent years, network analyses have been used to evaluate brain reorganization following stroke. However, many studies have often focused on single topological scales, leading to an incomplete model of how focal brain lesions affect multiple network properties simultaneously and how changes on smaller scales influence those on larger scales. In an EEG-based experiment on the performance of hand motor imagery (MI) in 20 patients with unilateral stroke, we observed that the anatomic lesion affects the functional brain network on multiple levels. In the beta (13-30 Hz) frequency band, the MI of the affected hand (Ahand) elicited a significantly lower smallworldness and local efficiency (Eloc) versus the unaffected hand (Uhand). Notably, the abnormal reduction in Eloc significantly depended on the increase in interhemispheric connectivity, which was in turn determined primarily by the rise in regional connectivity in the parieto-occipital sites of the affected hemisphere. Further, in contrast to the Uhand MI, in which significantly high connectivity was observed for the contralateral sensorimotor regions of the unaffected hemisphere, the regions that increased in connection during the Ahand MI lay in the frontal and parietal regions of the contralaterally affected hemisphere. Finally, the overall sensorimotor function of our patients, as measured by Fugl-Meyer Assessment (FMA) index, was significantly predicted by the connectivity of their affected hemisphere. These results increase our understanding of stroke-induced alterations in functional brain networks.Comment: Neuroimage, accepted manuscript (unedited version) available online 19-June-201

    Ageing and the Ipsilateral M1 BOLD Response: A Connectivity Study.

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    Young people exhibit a negative BOLD response in ipsilateral primary motor cortex (M1) when making unilateral movements, such as button presses. This negative BOLD response becomes more positive as people age. In this study, we investigated why this occurs, in terms of the underlying effective connectivity and haemodynamics. We applied dynamic causal modeling (DCM) to task fMRI data from 635 participants aged 18-88 from the Cam-CAN dataset, who performed a cued button pressing task with their right hand. We found that connectivity from contralateral supplementary motor area (SMA) and dorsal premotor cortex (PMd) to ipsilateral M1 became more positive with age, explaining 44% of the variability across people in ipsilateral M1 responses. In contrast, connectivity from contralateral M1 to ipsilateral M1 was weaker and did not correlate with individual differences in rM1 BOLD. Neurovascular and haemodynamic parameters in the model were not able to explain the age-related shift to positive BOLD. Our results add to a body of evidence implicating neural, rather than vascular factors as the predominant cause of negative BOLD-while emphasising the importance of inter-hemispheric connectivity. This study provides a foundation for investigating the clinical and lifestyle factors that determine the sign and amplitude of the M1 BOLD response in ageing, which could serve as a proxy for neural and vascular health, via the underlying neurovascular mechanisms

    A computational model based on corticospinal functional MRI revealed asymmetrically organized motor corticospinal networks in humans

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    新規MRI技術で利き手の神経制御メカニズムを解明 --手指運動中の脳・脊髄機能結合パターンの左右差を世界で初めて計測--. 京都大学プレスリリース. 2022-08-08.Evolution of the direct, monosynaptic connection from the primary motor cortex to the spinal cord parallels acquisition of hand dexterity and lateralization of hand preference. In non-human mammals, the indirect, multi-synaptic connections between the bilateral primary motor cortices and the spinal cord also participates in controlling dexterous hand movement. However, it remains unknown how the direct and indirect corticospinal pathways work in concert to control unilateral hand movement with lateralized preference in humans. Here we demonstrated the asymmetric functional organization of the two corticospinal networks, by combining network modelling and simultaneous functional magnetic resonance imaging techniques of the brain and the spinal cord. Moreover, we also found that the degree of the involvement of the two corticospinal networks paralleled lateralization of hand preference. The present results pointed to the functionally lateralized motor nervous system that underlies the behavioral asymmetry of handedness in humans

    Manual dexterity: functional lateralisation patterns and motor efficiency

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    Manual tasks are an important goal-directed ability. In this EEG work, we studied how handedness affects the hemispheric lateralisation patterns during performance of visually-driven movements with either hand. The neural correlates were assessed by means of EEG coherence whereas behavioural output was measured by motor error. The EEG data indicated that left- and right-handers showed distinct recruitment patterns. These involved local interactions between brain regions as well as more widespread associations between brain systems. Despite these differences, brain-behaviour correlations highlighted that motor efficiency depended on left-sided brain regions across groups. These results suggest that skilled hand motor control relies on different neural patterns as a function of handedness whereas behavioural efficiency is linked with the left hemisphere. In conclusion, the present findings add to our understanding about principles of lateralised organisation as a function of handedness

    Whole-brain estimates of directed connectivity for human connectomics

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    Connectomics is essential for understanding large-scale brain networks but requires that individual connection estimates are neurobiologically interpretable. In particular, a principle of brain organization is that reciprocal connections between cortical areas are functionally asymmetric. This is a challenge for fMRI-based connectomics in humans where only undirected functional connectivity estimates are routinely available. By contrast, whole-brain estimates of effective (directed) connectivity are computationally challenging, and emerging methods require empirical validation. Here, using a motor task at 7T, we demonstrate that a novel generative model can infer known connectivity features in a whole-brain network (>200 regions, >40,000 connections) highly efficiently. Furthermore, graph-theoretical analyses of directed connectivity estimates identify functional roles of motor areas more accurately than undirected functional connectivity estimates. These results, which can be achieved in an entirely unsupervised manner, demonstrate the feasibility of inferring directed connections in whole-brain networks and open new avenues for human connectomics

    Effects of Parkinson’s disease on motor asymmetry

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    Introduction: Persons with Parkinson’s disease (PD) experience changes cortically, subcortically and behaviorally. This dissertation examines the asymmetry of motor behavior to explore the role of asymmetry in persons with PD and its connection to clinical symptoms. Purpose: Project 1: To assess the hand asymmetry difference in young adults versus older adults. Project 2: To investigate the difference in hand asymmetry in older adults and persons with PD. Project 3: To explore the correlation between function and clinical symptoms of persons with PD. Methods: 55 right-handed participants [Young Adults (YA) = 20, Female = 10; Older Adults (OA) = 20, Female = 10; Persons with PD = 15, Female = 5] were recruited and performed motor tasks: Purdue Pegboard test, grip strength test, response task, thumb opposition task, tapping task, three variations of timed-up-and-go test (TUG), single leg stance task (SLS), Weight Distribution test and Limits of Stability test. The two-way ANOVA was conducted to examine a variance between YA and OA. A separate two-way ANOVA was conducted comparing variance between OA and persons with PD. The purpose was to explore asymmetries, characterized by a significant difference between groups’ left and right sides. Pearson’s correlation was implemented to examine connection of clinical symptoms and motor behavior. Statistics: IBM SPSS 24 software was used. Two 2-way ANOVAs with the between group factor of group (Young vs. Older in Project 1; Older vs. PD in project 2), and within group factor of hand (Right vs. Left in Study 1 & Study 2) were used to examine if age (or PD) changes hand asymmetry. Pearson’s correlation coefficient was used to determine correlations between Unified Parkinson’s Disease Rating Scale (UPDRS) and motor tasks in PD patients (Study 3). Results: Project 1: Results indicate asymmetry reduces with age in fine motor tasks containing speed, dexterity and strength components. Project 2: The basal ganglia dysfunction does not overall further exacerbate the reduced asymmetry with age. Project 3: Clinical symptoms of PD measured by the UPDRS are generally not associated with fine motor tasks of this study

    Systems Biology Determinants of Motor Behavior in Humans

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    Motor skills are mediated by a dynamic and finely regulated interplay of the primary motor cortex (M1) with various cortical and subcortical regions engaged in movement preparation and execution. Several neuroimaging studies already demonstrated that increasing motor performance in simple motor tasks is associated with higher activation levels in the motor system. Additional to the extrinsic modulation of motor performance, neural activity is also influenced by intrinsic factors such as handedness. Handedness – defined as the preference to use one hand over the other – is associated with differences in activation levels in various motor tasks performed with the dominant or non-dominant hand. However, motor actions are implemented in a distributed network of motor regions rather than a single cortical area. For that reason, it is important to consider the neural processes underlying motor behavior from a network perspective that is offered by connectivity analyses. Models of effective connectivity allow the estimation of the influence that areas exert over each other while functional connectivity is defined as temporal coherence between remote, segregated neurophysiological events. The present thesis aimed to investigate how the dynamic modulation of motor performance and connectivity is mediated by extrinsic and intrinsic factors in the human motor system. In the first study, we used functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to investigate effective connectivity of key motor areas at different movement frequencies performed by right-handed subjects (n=36) with the left or right hand. The network of interest consisted of motor regions in both hemispheres including M1, supplementary motor area (SMA), ventral premotor cortex (PMv), motor putamen, and motor cerebellum. The connectivity analysis showed that performing hand movements at higher frequencies was associated with a linear increase in neural coupling strength from premotor areas (SMA, PMv) contralateral to the moving hand and ipsilateral cerebellum towards contralateral, active M1. In addition, we found hemispheric differences in the amount by which the coupling of premotor areas and M1 was modulated, depending on which hand was moved. Other connections were not modulated by changes in motor performance. The results suggest that a stronger coupling, especially between contralateral premotor areas and M1, enables increased motor performance of simple unilateral hand movements. In the second study, we used fMRI and DCM to investigate effective connectivity between key motor areas during fist closures of the dominant or non-dominant hand performed by 18 right- and 18 left-handers. Handedness was assessed employing the Edinburgh-Handedness-Inventory (EHI). The network of interest consisted of key motor regions in both hemispheres including M1, SMA, PMv, motor putamen and motor cerebellum. The connectivity analysis revealed that in right-handed subjects movements of the dominant hand were associated with significantly stronger coupling of contralateral (left, i.e., dominant) SMA with ipsilateral SMA, ipsilateral PMv, contralateral motor putamen and contralateral M1 compared to equivalent connections in left-handers. The degree of handedness as indexed by the individual EHI scores also correlated with coupling parameters of these connections. In contrast, we found no differences between right- and left-handers when testing for the effect of movement speed on effective connectivity. In conclusion, the data show that handedness is associated with differences in effective connectivity within the human motor network with a prominent role of SMA in right-handers. Left-handers featured less asymmetry in effective connectivity implying different hemispheric mechanisms underlying hand motor control compared to right-handers. However, differences in task performance are inherent putative confounds for all task based fMRI studies. For example, performing a standard motor task might be less demanding when using the dominant hand compared to the non-dominant hand, which may also affect neural activation levels, e.g., in frontoparietal areas. Thus, resting-state fMRI seems an attractive approach to overcome these putative confounds as it allows investigating networks independent from performance. In the third study, we, therefore, scanned 18 right- and 18 left-handers with resting-state fMRI. Handedness was assessed by the EHI. We computed whole-brain functional connectivity maps of the left and right M1. To test for the effect of handedness, we computed differential contrasts and regression analyses including EHI as a covariate. We further used a multivariate linear support vector machine (SVM) classifier algorithm to reveal the individual specificity of brain regions showing differences between the resting-state maps of right- and left-handers. Using left M1 as a seed region revealed stronger interhemispheric functional connectivity between M1 and dorsolateral premotor cortex (PMd) in right-handers as compared to left-handers. Furthermore, this individual cluster in right PMd classified right- and left-handers with 86.2% accuracy. Control analyses using non-motor resting-state networks, including the (Broca) speech and the visual network, revealed no significant differences in functional connectivity related to handedness. Higher connectivity in right-handers might, therefore, reflect a systematic impact of handedness on an intrinsic functional level and might explain the observation that right-handedness is usually more lateralised than left-handedness. Furthermore, enhanced connectivity between M1 and PMd serves as an individual marker / endophenotype of handedness. In summary, the present thesis demonstrates that the dynamic modulation of the motor system during motor performance is mediated by a specific set of brain regions in both rightand left-handers. Furthermore, the results indicate that differences in coupling strength between right- and left-handers reflect the impact of handedness on both functional and effective connectivity
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