Richards, Thomas Christopher ORCID: https://orcid.org/0000-0002-4447-4334 (2018) Identifying Shared Pathways Across Multiple Muscle Groups of the Human Upper Limb. PhD thesis, University of Leeds.
Abstract
Experimental limitations in humans mean that neurophysiological recordings must usually be limited to non-invasive, indirect measures. Consequently, we often overlook pathways in areas such as the spinal cord and brainstem in favour of pathways which are more accessible for stimulation and recording, such as cortical areas and the corticospinal tract. However, we currently lack the tools to effectively examine these systems. This may explain the large variability between the predicted and observed recovery which is common in clinical populations such as those affected by stroke. Whilst this significantly hampers clinical assessment, it has also led to large gaps in our understanding of shared pathways between shoulder and upper limb muscles, which is important information since the shoulder supports the weight of the arm. Applying algorithms for muscle synergy analysis to muscle activation patterns gives us interesting mechanistic insight. In clinical scenarios, it has also been used to show aberrant muscle activation patterns which are thought to relate to dysfunction in specific pathways. However muscle synergy studies do not reveal the neural drive to the muscles. This thesis addresses these problems by applying novel analytical approaches to non-invasive electromyographic (EMG) recordings of behavioural tasks and by using stimulation techniques to activate specific pathways. To accomplish this, it was necessary to generate new analytical systems which would enable us to be able to extract the relevant information.
Synaptic input to motoneurones can be identified non-invasively by performing frequency coherence analysis on EMG signals. Coherent frequencies between 6-60 Hz are often assumed to reflect efferent activity of direct projections from the motor cortex to the spinal motoneurones. By applying a high resolution time-frequency analysis of evoked responses, we were able to show for the first time that EMG activity in the 15-60 Hz range is present at latencies which match those expected for the corticospinal pathway. We were also able to show the contribution of subcortical pathways, likely reticular, in the 35-100 Hz range, and spinal pathways in the 60-100 Hz range. This could be applied as a useful clinical metric for assessing remaining functional pathways following injury. We then assessed intermuscular coherence within these frequency bands across muscles of the upper limb to classify muscles into modules based on specific pathways. Using this technique, we provide a catalogue of muscle pairs sharing common drive across joints of the upper limb, and show how muscle interactions shift depending on task and limb position. We also propose a novel behavioural task for use in the clinic which we can use to identify key muscle interactions which are indicative of a functional descending drive. Finally, we demonstrate the involvement of high and low threshold peripheral pathways in a dynamic and static task of the upper limb.
Metadata
Supervisors: | Chakrabarty, Samit and Astill, Sarah L and O'Connor, Rory |
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Related URLs: | |
Publicly visible additional information: | Thomas Richards – ORCID 0000-0002-4447-4334, Samit Chakrabarty – ORCID 0000-0002-4389-8290 |
Keywords: | Muscle synergies, muscle synergy analysis, intermuscular coherence, spinal reflex pathways, corticospinal pathway, common drive, electromyography, EMG, transcranial magnetic stimulation, TMS, peripheral nerve stimulation, PNS, corticospinal pathway, non-invasive, reticulospinal pathway, spinal pathways, frequency analysis, wavelet transform, wavelet synchro-squeezed transform, dynamic, isometric, non-negative matrix factorisation |
Awarding institution: | University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) |
Identification Number/EthosID: | uk.bl.ethos.778634 |
Depositing User: | Dr Thomas Richards |
Date Deposited: | 24 Jun 2019 12:58 |
Last Modified: | 11 Aug 2022 09:53 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:24138 |
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