Development of novel tools applied to sound stimulation for the modulation of brain rhythms affected by ageing and disease
The vision of this research is to develop sound stimulation approaches to modulate brain rhythms that are affected by ageing and disease processes.
Start date1 October 2022
Funding sourceEPSRC Doctoral Training Partnership
Enhanced EPSRC stipend (£19,062 per annum for 2022-23, with annual increments based on inflation) and fees covered. Funding also includes a research training and support grant of £3,000 for the duration of the studentship
One of the greatest accomplishments of the 20th century was a remarkable gain in global life expectancy, with an increase of about 30 years in industrialised countries. Whether longevity is a burden or an opportunity to societies will depend on how well individuals age and how societies adapt to provide better health and health care for older adults.
Ageing is associated with alterations in brain dynamics that can be measured and monitored using electroencephalography (EEG). EEG records the electrical activity of neurons in the cortex of the brain and is, therefore, a very useful tool to characterise the changes associated with ageing and neurological disorders. A hallmark of ageing is a general increase in the power of slow oscillations and marked reduction in the amplitude of alpha activity. This is exacerbated in pathological conditions, such as Alzheimer’s disease (AD), and has been shown to be associated with clinical progression of AD. Furthermore, measures of functional connectivity have shown that brain dynamics change with age and can provide an index of brain vulnerability.
Sound stimulation provides a non-invasive, cheap, and tenable strategy to modulate brain rhythms. Recent studies have shown that rhythmic auditory stimulation can impact disease pathology and cognition. In our labs we have established that closed-loop auditory stimulation can be deployed to modulate regional alpha oscillations and modulate long-range brain connectivity. In particular, we were able to modulate the amplitude and frequency of alpha oscillations in young adults at rest.
The successful candidate will work on the development of this technology in older adults, by first tuning the parameters that lead to successful modulation of brain oscillations affected by ageing and developing signal processing algorithms to capture patterns associated with this (Aim 1). This will be followed (Aim 2) by development, testing and deployment of neurotechnologies that can be used at home by older adults and would pave the way to clinical applications.
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Related linksNeMo - NeuroModulation Lab
Applicants should have a minimum of an upper second-class honours degree (BEng/BSc) and/or an MSc/MEng degree (65 per cent or above) in engineering, physical sciences, neuroscience or related discipline.
The ideal candidate will have a strong background in some of the following areas: neuroimaging, signal processing (in particular physiological signals, e.g., EEG), biomedical engineering or machine learning. Experience in programming (e.g., MATLAB, Python and/or R) is highly desirable. Experience in testing human participants is also desirable.
English Language requirements
IELTS Academic: 6.5 or above (or equivalent) with 6 in each individual category.
How to apply
Applications should be submitted via the Psychology PhD programme page on the "Apply" tab (select October 2022 start date). Please clearly state the studentship title and supervisor on your application. Once you have completed and submitted your application, please send an email to the primary supervisors confirming you have applied.
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