World-Leading Doctoral Scholarship in Psychology and Neuroscience

Project

Frontotemporal dementia (FTD) is an incurable progressive disease characterised by the degeneration of neurons in the frontal and temporal lobes of the brain. FTD is the second most common cause of young onset dementia, and it overlaps with Amyotrophic Lateral Sclerosis (ALS) at clinical, genetic, and pathological levels. Among FTD symptoms are changes in behaviour and personality, executive deficits, and language dysfunctions. Subjects affected by FTD present impaired ability to process and display emotions, since apathy is among the earliest symptoms. Neuropsychological tests assessing recognition of emotions can discriminate with high diagnostic accuracy between patients with mild FTD and healthy subjects, even when other tests for frontal lobe functions are within normal range. 

Transgenic mice carrying human FTD mutations are available and known to show FTD-like phenotype (social withdrawal, stereotypic behaviour). Neural circuits affected in disease remain unknown and, due to the complexity of studying emotions and mild changes in social interactions in mice, investigations on pathophysiology have proven difficult. A recent study showed that mice exhibit stereotyped facial expressions in response to emotionally relevant events, and upon manipulation of neuronal circuits controlling those emotional responses. These stereotyped facial expressions can be classified by Machine Learning (ML)-based analysis and can be used as readouts of emotional states. In our previous work, ML and artificial intelligence (AI)-based analysis of ALS mice were extremely beneficial in highlighting differences in phenotype which would not be quantifiable otherwise. This approach allowed us to identify a subpopulation of neurons degenerating early in disease, at a timepoint that was previously considered pre-symptomatic. 

We now aim to develop an AI-driven approach to study FTD mice and investigate changes in neural circuits underling behavioural alterations. Here, we will use an inducible mouse model of FTD, where the same mouse can be analysed before and after induction of disease. First, mice will be recorded in a head fixed-set up with virtual reality and reward system, designed for pose estimation and facial analysis. Positive and adverse stimuli will be presented to trigger a range of responses before and after FTD induction to detect changes in response. Recorded videos will be analysed using deep learning methods which can be used to extract features from video frames. These features can be further analysed by embedding them into a semantic space of emotions to enable possible phenotype prediction. Similar approaches have been used to classify human facial emotions using large public datasets. Our final aim is to use a multi-mouse set-up with a combination of fixed- and moving- cameras to study behavioural changes during social interaction. Here, moving cameras will be controlled by Arduino-like microcontrollers and videos will be analysed using specialised deep learning models. Neurons of the prefrontal cortex have been implicated in processing affective states, and previous studies indicate that balance between neuronal excitation and inhibition plays a critical role in controlling these cognitive functions. Dysfunctions of inhibitory neurons found in the prefrontal cortex were previously linked to FTD-like disorders. Thus, the behavioural analysis will be correlated with neural activity in vivo. In vivo Ca2+ imaging of inhibitory/excitatory neurons will be investigated during behaviour, to identify changes in neural activity before and after FTD onset. Mice will be assessed in both set-ups (head-fixed and social interaction) and Ca2+ quantifications will be correlated to ML-based data. By achievement of this set of experiments, we will identify the earliest FTD symptoms and unravel the prefrontal neural circuits affected in disease. 

Informal enquiries regarding this scholarship may be addressed to Dr. Ilary Allodi and Dr. Raghavendra Selvan via email to ia51@st-andrews.ac.uk and raghav@di.ku.dk.

Value of award (per year)

Full tuition fees (Home or International rate)

Annual maintenance paid monthly at UKRI rates (£17,668 2022/23) 

Duration of award

Up to 3.5 years. The successful candidate will be expected to have completed the doctorate degree by the end of the award term. The award term excludes the continuation period and any extension periods.

At what stage of my course application can I apply for this scholarship?

Please apply for the scholarship after you have submitted your application for a place at St Andrews.  You do not need to wait until you have received an offer of a place before applying for the scholarship.

Additional criteria

You must have applied for a PhD programme at St Andrews.

You must not already (i) hold a doctoral degree; or (ii) be matriculated for a doctoral degree at the University of St Andrews or another institution.

As part of the scholarship application you will be required to upload a personal statement. This should serve as a cover letter for the research project application as a whole, and should include:

• An outline of your suitability for the project (project criteria can be found in the "Eligibility" and "Project Description" sections above).
• Why the project interests you.
• What you would bring to the project in terms of previous skills and expertise.
• Any ideas that you may have for the realisation of the project.

How to apply

1. Apply for admission as a doctoral student beginning in the academic year 2023-24. Please see the advice on applying for research programmes. After submitting your PhD application, you must allow at least two working days for processing and issue of your log-in details before you can apply for the scholarship. Once you have received an email confirming your access to the My application portal: 
2. Apply for the scholarship, which is available through the World-Leading Scholarship 7: Facing Dementia: Investigating disease onset in a mouse model of Frontotemporal Dementia application form. You can access this application through the Scholarships and funding catalogue in the Scholarships and Funding section of My application. 
• Enter the catalogue by following the instructions in the email, then choosing Scholarships and funding (under 'Useful links') and then clicking View the scholarships and funding catalogue.
• Select 2023/4 as the Academic Year and click ‘Refresh list’.
• Find the World-Leading St Andrews Doctoral Scholarship that you wish to apply for in the list of scholarships (using the filter box if necessary), click Apply and complete the application form.
• You can also use the catalogue to search and apply for other scholarships for which you are eligible. 

Scholarship application form guidance

If you are a current student at St Andrews, you can access Scholarships and Funding through MySaint. However, you should wait until after you have applied for your intended postgraduate programme before doing so, to ensure that the scholarship application is linked to that course.

Terms and conditions

Please read the University of St Andrews scholarships terms and conditions (opens in new tab) 

If you apply to this scholarship, details from your course application may be passed to the selection panel solely for the purpose of merit-based assessment. 

When will I know the outcome?

The outcome of your scholarship application will be available on View or continue my funding applications in the Scholarships and Funding section of My Application within two months of the application deadline.