Development of novel tools applied to sound stimulation for the modulation of brain rhythms affected by ageing and disease

One of the greatest accomplishments of the 20^th 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.

The University of Surrey and our collaborative partners provide a vibrant, interdisciplinary research environment, with access to state-of-the-art facilities.  We see our postgraduate researchers as an integral part of our research community, collaborating and innovating together with academics at all levels. We want the most talented researchers from diverse backgrounds to join us, bringing new ideas and perspectives. We will help you make the most of your potential, removing barriers where we can and supporting you with dedicated career guidance. We offer generous funding packages, sector-leading researcher development training and mentoring, and dedicated employability support.

Whatever your aspirations, Surrey is where research careers are launched and nurtured.

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.