My name is Rebeca, and I have completed my MPhil between the Department of Psychiatry and the MRC Cognition and Brain Sciences Unit.
I am a biologist by background who has always had a fascination for behavioural sciences, particularly those related to cognition and mental health. Hence, I am continuing my postgraduate education at the MRC Cognition and Brain Sciences Unit.
My PhD will involve bridging genetics and network neuroscience to better understand the impact of rare genetic variants on brain network development at both structural and functional levels, using computational methods.
The Details
Name: Rebeca Ana Ianov Vitanov
Research group: Brain Mapping Unit
Supervisor: Dr Sarah Morgan
Advisor: Dr Danyal Akarca
Title of your PhD/MPhil: Characterising links between hierarchically-organised mental health dimensions and functional brain connectivity in youth at neurodevelopmental risk.
Can you give us a short background into what your PhD/MPhil was about?
Mental health and cognition are critically shaped during childhood and adolescence. These two brain functions are closely related to school performance, educational attainment and general wellbeing, and they disruptively co-exist in neurodevelopmental conditions.
Thus, children on the neurodevelopmental spectrum are particularly prone to mental health difficulties which might be triggered by internalising symptoms related to their cognitive difficulties but also by external factors, such as stigma and discrimination.
During my MPhil, I investigated associations between patterns of functional brain connectivity and mental health in a youth sample with learning difficulties. Thus, I first replicated a hierarchical model of mental health comprising six mental health dimensions: a general p-factor of mental health at the apex, a broad internalising and an externalising dimension below and three more specific dimensions at the lowest level of the hierarchy (specific internalising, neurodevelopmental, social maladjustment).
The second aim of the current study was to relate the derived mental health dimensions to resting-state functional connectivity at three different scales of resolution: connectivity within and between large-scale functional networks and regional and edge levels. Lastly, I investigated whether the latent dimensions of connectivity related to mental health also associate with learning outcomes in various academic tests: reading, spelling, maths, and general learning outcomes.
How would you sum up your main findings?
All six mental health dimensions were significantly associated with patterns of connectivity within and between large-scale functional networks, but also with regional connectivity patterns. This showed the relevance of these mental health dimensions at a neurobiological level, as opposed to traditional diagnostic categories, which don’t usually map well onto neural biomarkers.
More specifically, the six derived mental health dimensions, which were positively correlated with symptom severity, were associated with increased functional connectivity within the default-mode network and between the default-mode network and the executive, subcortical and limbic networks. The neurodevelopmental factor displayed the strongest links with these connectivity patterns, which reflects reduced segregation between the task-negative default mode network and the task-positive networks, a trend often seen in neurodevelopmental conditions.
At the regional level, opposite patterns of connectivity between internalising and externalising mental health symptoms were identified, with positive associations between the externalising dimensions and connectivity in the parietal, occipital and cingulate cortices.
I also identified associations between functional connectivity patterns related to mental health and learning outcomes, which might suggest an interaction between poor mental health and school performance in youth at neurodevelopmental risk. More precisely, I identified that the regional connectivity patterns related to the internalising dimension were significantly associated with maths ability, general learning problems and spelling ability, whereas the regional patterns linked to externalising symptoms were significantly related to poor spelling outcomes.
What made you want to do an MPhil?
I wanted to do an MPhil because I wanted to gain research experience and theoretical knowledge in network neuroscience and get adequate preparation for a PhD in the field. I have always enjoyed reading about various neuroscience-related topics in my free time, but it wasn’t until the end of my Bachelor’s that I decided that I would like to pursue future postgraduate-level studies working on models of the brain related to cognitive development.
What was your best day during your MPhil?
The best day during my MPhil was my viva, when I had a fruitful discussion with two researchers in the field about my motivations behind the project, the results of my work and the future directions in which I could potentially take the project next. I also obtained invaluable advice on how to polish my MPhil work for a potential publication.
What was your worst day during your MPhil?
Probably the day when my connection to the computer cluster was not working at all, and I couldn’t do what I planned for that day, as I spent most of the time on the call with the IT person. Otherwise, I haven’t really had bad days during my MPhil!
Do you have any words of advice for future PhD/MPhil students in Psychiatry?
Try to read papers and attend talks as diverse as possible – this is how novel ideas for your project, but also new interests might emerge! Reach out to people, collaborate and be resilient!
What do you hope to do next?
I will pursue a PhD at the MRC Cognition and Brain Sciences Unit on developmental computational neuroscience.
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