Imaging Motor Unit Recruitment Patterns

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Within skeletal muscles the fibres are grouped into distinct functional units, motor units (MUs), with groups of fibres innervated by a single motoneuron located in the spinal chord. The size of MUs (number of innervated fibres) and their physiological properties varies within and between muscles. To complete any movement the nervous system must activate the appropriate number and combination of MUs to produce the varying levels of force required throughout the task.Quantifying patterns of MU activation provides a means of i) studying how MUs are controlled by the nervous system to produce force; ii) measuring dysfunction caused by diseases such as cerebral palsy or Parkinson's disease; iii) diagnosing neurodegenerative diseases e.g. motor neurone disease; iv) estimating changes in MU number which occur due to disease, injury or ageing. Currently such studies are completed using electromyography (EMG), a method of recording electrochemical changes in the muscle fibre which occur when it is activated. However, the techniques available to analyse EMG signals and provide information on MU recruitment patterns limit the range of movement tasks that can be studied. So it is not currently possible to study patterns of MU recruitment during the majority of movements completed during acts of daily living (e.g. reaching, grasping) or more demanding tasks (e.g. running, negotiating different terrains or inclines).Activation of MUs causes muscle tissue to move. The number and distribution of the fibres of a MU in a muscle will influence: i) the area of the muscle over which tissue movement spreads and ii) the timing of the spread of the movement which occurs when the MU is activated. Activation of MUs with different properties should therefore cause different 'signature' muscle tissue movement patterns to occur. The relationship between MU activation and tissue movement patterns has not yet been fully explored, but could be revealed using ultrasound imaging. These types of images have already been shown to reveal surprisingly small contractions (e.g. activation of single muscle fibres) and can be easily collected during different movements e.g. locomotion, reaching and grasping. We therefore propose developing novel ultrasound image analysis techniques, to provide a new way of studying MU recruitment patterns and extending the conditions under which MU properties can be studied.We will develop algorithms to provide: i) high frame rate (>1000 frames per second) ultrasound imaging of skeletal muscle in 3D; ii) a means of defining muscle movement templates, identifying the 'signature' muscle tissue movement patterns associated with activation of different MUs; iii) a means of using the signature movement patterns to analyse image sequences and identify activation patterns of different MUs.This work will therefore provide a new method of studying MU recruitment during a wide range of different movement tasks. In addition, our work will provide a means of: i) collecting experimental evidence to underpin the development of more accurate and valid mathematical models of muscle; ii) evaluating and monitoring changes in MU properties which occur as a result of ageing, injury, rehabilitation, disease and different forms of treatment aimed at improving physical health and well-being; iii) non-invasive investigation of MU properties which could be applied in humans and animals and provide novel data from the same or smaller numbers of animals.