- Type of research degree
- Application deadline
- Ongoing deadline
- Project start date
- Thursday 1 October 2020
- Country eligibility
- UK and EU
- Competition funded
- Source of funding
- University of Leeds
- Dr Ioannis Delis
Human motor behaviour is the outcome of the combined action of an extensive neural circuit that generates and controls movement and the mechanical properties of the human body. Fundamental to effective motor control are the interactions a) between different levels of the central nervous system (CNS) as well as b) between the neural motor drive and the musculoskeletal system. In this project, we will probe these interactions aiming to a) understand the principles governing motor coordination and b) elucidate the neural mechanisms implementing them. To answer these questions, we will develop a comprehensive analytical framework that quantifies neuronal and muscular interactions in task space. Ultimately, we will obtain insights into the hierarchical organisation of the human motor system and will be able to characterise the neural mechanisms that underlie movement execution. Crucially, the knowledge obtained from this project can have significant implications in a) health research by aiding to identify and rehabilitate alterations in motor patterns in movement disabilities (dyspraxia, spinal cord injury, etc.) and b) biomedical robotics to inform the control of neuroprosthetic limbs.
<p>The main goal of this project is to understand how the central nervous system (CNS) interacts with the musculoskeletal system in order to execute effective movements. These interactions remain poorly understood primarily because of the lack of unifying methodology that allows their characterization at both the behavioural and neural levels. To address this problem, the successful candidate will develop novel algorithms using techniques from machine learning, information theory and/or network theory and couple them with large-scale neurophysiological measurements of neuromuscular activity during static and dynamic motor behaviours. We will first investigate how task variables are actually translated into “muscle synergies”, i.e. how different muscles are functionally coordinated in order to perform the task at hand. Then, we will delve into the mechanisms that implement the encoding and recruitment of muscle synergies in the CNS. Finally, we will infer the neural motor commands that drive muscle activity and assess to what extent they are shared across muscles and how this is modulated by the desired motor task.</p> <p>We will design motor behavioural experiments to assess a) the use of muscle synergies for effective motor coordination and b) the organisation of the neural structures that underpin the implementation and recruitment of muscle synergies.</p> <p>We will first use surface electromyography (sEMG) to record muscle activity from a large number of muscles spanning the human body while participants perform a variety of postural and dynamic motor tasks. Muscle synergies have been proposed as a neural strategy to coordinate the large number of muscles in order to perform the desired motor task. However, there is heated debate over the neural origins of these muscle couplings as they can also be the outcome of anatomical or mechanical, and not neural or task-induced, constraints. Current synergy extraction methodologies cannot dissociate between these possibilities. To address this open problem, we will devise an analytical methodology that will characterise the task-relevance of muscle interactions. This investigation will provide critical insights into the functional organization of muscle activity and its relevance to task performance.</p> <p>We will then aim to identify the neural underpinnings of the identified functional muscle couplings. Synchronous brain rhythms have been suggested as a mechanism for integrating the distributed motor and sensory systems involved in coordinated movement. As such, neuromuscular synchronization may underlie the formation of muscle synergies. Crucially, by assessing the timescales of these synchronisations, we will be able to infer which level of the neural hierarchy (cortical/subcortical/spinal) the common inputs originate from and thus gain insights on the mechanistic interactions of the neural circuitry involved in motor coordination.</p> <p>Then, we will employ high-density EMG (hdEMG) measurements from the forelimb during a wrist force control task. This novel technology will enable me to infer the firing of motor neurons innervating forelimb muscles from the hdEMG recordings. Thus, it will open a unique window into decoding the neural drives to muscles. We will apply the previously developed analyses to the neuronal firing patterns to characterize a) task encoding by the motor neuronal populations and b) information transmission from the motor pool to the muscle. Hence, we will be able to probe the putatively modular structure of the neural motor commands and assess how these neural drives to muscles encode the task at hand.</p> <p>In sum, this project will shed light onto how the CNS coordinates multiple muscles in order to perform a desired motor task with the ultimate objective of revealing for the first time the neural implementation of this functional coordination. Such information will also provide key insights on the neural origins of the impairments following neurological or motor disorders. This understanding will contribute to the diagnosis or even prognosis of neurodevelopmental disorders compromising one’s sensorimotor faculties (developmental coordination disorder - DCD, cerebral palsy, diplegia etc.) and will inform the development of effective interventions to enhance rehabilitation after neural damage (e.g. in stroke or spinal cord injury).</p>
<p>Formal applications for research degree study should be made online through the <a href="http://www.leeds.ac.uk/rsa/prospective_students/apply/I_want_to_apply.html">University's website</a>. Please state clearly in the research information section that the research degree you wish to be considered for is “Neural origins of modularity in human motor control” as well as <a href="https://biologicalsciences.leeds.ac.uk/school-biomedical-sciences/staff/52/dr-ioannis-delis">Dr Ioannis Delis</a> as your proposed supervisor.</p> <p>If English is not your first language, you must provide evidence that you meet the University's minimum English language requirements (below).</p> <p><em>We welcome applications from all suitably-qualified candidates, but UK black and minority ethnic (BME) researchers are currently under-represented in our Postgraduate Research community, and we would therefore particularly encourage applications from UK BME candidates. All scholarships will be awarded on the basis of merit.</em></p>
Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. The criteria for entry for some research degrees may be higher, for example, several faculties, also require a Masters degree. Applicants are advised to check with the relevant School prior to making an application. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Graduate School prior to making an application.
The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.0 overall with at least 5.5 in each component (reading, writing, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.
<p>Candidates are encouraged to apply to the Leeds Doctoral Scholarship and the Emma and Leslie Reid Scholarship for financial support.</p> <p>The award will cover fees at the University of Leeds standard UK/EU rate plus maintenance fees of £12,000 per annum for 3 years.</p>
<p>For further information please contact the Graduate School Office<br /> e: <a href="mailto:firstname.lastname@example.org">email@example.com</a> , t: +44 (0)113 343 8186</p>
<h3 class="heading heading--sm">Linked research areas</h3>