List of available PhD projects

Group research interests - The NeuroInformatics group is a computational group with a strong interest in studying lifespan brain health. A multitude of factors can affect our brain health from as early as pre-conception. These factors can pose great threats to the brain, leading to immense missed developmental potential, global disease burden and disability. We aim to tackle the diversity of challenges to studying brain health across the lifespan my using big data (both in terms of number of individuals, as well as in terms of numbers of features) and by developing novel approaches to integrating data across modalities and scales. In line with this goal our research program has three broad pillars: 1. Normative models of lifespan brain health: in this pillar we generate normative references for different brain features that can be measured with non-invasive brain imaging techniques such as MRI or CT. We also use these normative reference models to study deviations in clinical cohorts ranging from developmental and rare genetics disorders to conditions of accelerated ageing such as Alzheimer's and related dementias. See for an example: Bethlehem, Seidlitz, White et al. 2022, Nature. 2. Multi-scale integration: in this pillar we aim to integrate other data modalities with neuroimaging to gain a more complete understand of what it is that we are actually measuring with in-vivo neuroimaging techniques. This often included integration with genomics and transcriptomics. See for examples of this: Warrier et al. 2023, Nat. Gen. & Romero-Garcia, Warrier et al. 2019, Mol. Psychiatry. 3. Predictive applications: in this pillar we aim to develop novel machine learning approaches for risk prediction of ill brain health. See for an example: Azevedo et al. 2022 Medical Image Analysis

In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s): 

1. Imaging-genetics - integrating different data types at different scales is vital for a comprehensive understanding of brain health. We currently collaborate closely with Prof. Varun Warrier to integrate our large-scale imaging with genetics databases to both create a resource for the wider community but also to better understand the integrated relationships across brain phenotype and the biology underlying potential deviations in brain related phenotypes.

2. Normative models for atypical development (i.e., autism and adhd) - as we continue to improve our normative reference models there is an increasing need and interest to test the clinical or translational potential of these. While the group mainly focuses on testing the efficacy of these models in neurodevelopmental conditions such as autism and adhd, we also closely collaborate with a much wider network of researchers and clinicians to understand the translational potential in other clinical conditions.

3. Developing open tools for brain network analyses - with a strong interest in standardising approaches to quantify biological data we are building open workflow and tools for studying biological networks with a specific emphasis on network data derived from human in-vivo brain imaging.

4. Image segmentation and analysis - as we are dealing with more and bigger data we have several project underway to try and optimise processing pipelines for human in-vivo imaging. In addition, we are increasingly interested in integrating clinically acquired (as opposed to research grade) data and this requires processing adaptation and optimisation.

In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):

1. Neuro-cognitive foundations of combinatorial language function. Studying how the brain encodes this defining feature of human language; how this capacity might have emerged, and to what extent these processes differ across languages

2. The encoding of semantic and syntactic information in bilingualism. The demands of learning and using multiple languages modulate the way our neural system encodes perceptual signal. Does this extend to the processing of higher-level linguistic information?

3. Determinants of second language learning. How different variables and their interactions affect L2 learning and ‘mould’ an individual learner? Can this be used to personalise L2 teaching?

In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):

Corvid cognition. This is my top priority given that my corvid palace was saved from closure https://www.theguardian.com/environment/2022/jun/19/queen-of-corvids-the-scientist-fighting-to-save-the-worlds-brainiest-birds https://www.newscientist.com/article/2329991-cambridge-lab-for-clever-birds-saved-from-closure-by-public-donations/

I’m particularly interested in exploring aspects of mental time travel, self control and social cognition, and the use of magic effects to investigate constraints on cognition, i.e. blind spots in seeing and roadblocks in thinking. This work is conducted at the Sub-department of Animal Behaviour at Madingley, but there is also the opportunity to incorporate field work both in Madingley woods and further afield. Cephalopod cognition. I’m fascinated by cephalopods in general. Topics include idynamic camouflage and its relationship to both cognition and magic, as well as other aspects of cognition such as curiosity. This work is generally conducted at the MBL in Plymouth as we do not (yet) have a cephalopod facility in Cambridge. Comparative cognition. Questions about what are the critical comparisons in comparative cognition, from studies investigating similarities and differences in performance on tasks that tap into cognition in children and crows, to questions about convergent evolution in corvids, apes and cephalopods. The lab is genuinely interdisciplinary with additional studies on adult humans, as well as monkeys, elephants, parrots, dogs and dolphins, and transdisciplinary approaches and applications to cognition from philosophy to modelling and AI. Cultural cognition in humans. A relatively recent focus has been to compare the development in young children, and existence in adults, of cultural differences in cognition, from self control and future planning to Theory of Mind especially Level 2 perspective taking. So far these comparisons have focused on Individualistic and collectivist cultures, focusing on differences between UK and Chinese populations.

In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s): 

Visual Attention and Awareness. A primary focus of the lab is to develop new behavioural measures to profile visual awareness during complex tasks. Findings from this work have motivated novel security screening strategies in our applied work. In collaboration, we are currently expanding this work to include M/EEG correlates.  Social Cognition, with special emphasis on Gaze Perception  A second focus concerns rapid appraisal of social information by human observers, especially in relation to eye gaze. At one level, another person’s eyes are just like other visual stimuli, at another, they indicate the presence of another mind and are seeing as well as being seen. Our previous and current work investigates how high level knowledge that a person can see influences our perception of eyes and responses to them.               

In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):

Cognitive computational neuroimaging studies of learning and brain plasticity: Our studies combine ultra-high field brain imaging (7T fMRI, MR Spectroscopy), electrophysiology (EEG), interventional (TMS, tDCS) and neurocomputational (machine learning, reinforcement learning) approaches to understand the network dynamics that support learning and brain plasticity. AI and Neuroinformatics: We develop and translate AI-guided tools for a) understanding brain processes underlying cognition (e.g. learning and brain plasticity), b) early detection of brain and mental health disorders to inform clinical practice (healthcare, clinical trials). Our research involves working on research cohort and clinical data, developing machine learning models to synthesise biological (brain imaging, genetic) cognitive and epidemiological data, validating AI-guided tools in clinical data, translating these tools for adoption in healthcare and industry settings.

In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):

Our research explores geographical variation in personality. The basis of this work heavily relies on large-scale survey studies. Recent advancements in natural language processing have showcased the potential to accurately predict personality traits by analyzing individuals' language choices. In line with this progress, the current project endeavors to construct computational models capable of personality prediction based on textual content from online social media platforms. Subsequently, these models will be applied to geo-tagged social media posts, enabling us to further explore the geographical distributions of personality traits.