When launching the UK Loneliness Strategy in late 2018, Theresa May called loneliness one of the greatest public health challenges, on par with smoking and obesity. Loneliness affects people across the spectrum of age, race, and socioeconomic status and has grave consequences for mental and physical health. Most of the research has focused on loneliness in older people. However, young people may be even more affected. For instance, epidemiological research indicates an increase of over 60% in adolescent loneliness between 1991 and 2014. This trend is likely to be accelerated by the impact of the COVID-19 pandemic. While we increasingly understand the negative impact of loneliness, we know a lot less about the mechanisms that explain why some people struggle to overcome loneliness. We are open to any project ideas that aim to explain persistent loneliness in childhood or adolescence. Potential questions include: Is persistent loneliness associated with lower Theory of Mind or a bias to detect social threats? Do the mechanisms differ between children and adolescents? Does early experience predict persistent loneliness? The project will be based on cognitive tasks, questionnaires, and semi-structured interviews. Depending on the applicant's interests, this can be complemented by neuroimaging investigations (EEG, fMRI, structural MRI).

Dr Bathelt is also happy to discuss ideas for student-led projects, particularly in the area of developmental cognitive neuroscience, atypical development, and transdiagnostic developmental research. Potential projects can include MRI and/or EEG. Please see the following pages for more information: PURE page, website.

As understanding of causality and explanation develops, profound limits on what is ascertainable using predominantly data driven approaches are becoming apparent that cannot be surmounted merely by making that data “bigger.” A reckoning along these lines will be welcomed most at the “small data” end of the spectrum, in contexts such as healthcare provision where care delivery is necessarily an individual endeavour. Research in psychology that purports to further treatment solutions needs to provide specific answers for how it promotes the bridging of the nomothetic-idiographic divide. In the anticipated project, we would implement an approach to clinical measurement that focuses on psychological constructs rather than symptoms and is anchored in a development cycle that continually feeds information reciprocally from the bottom-up and top-down, drawing on methodological advances in such areas as network psychometrics, natural language processing, small N experimentation and data aggregation, and theoretical understandings about the propositional nature of learning and cognitive processes underlying self-report. This would be firmly anchored in clinical practice through a standardised approach to clinical formulation viewed from the standpoint of abductive reasoning that systematically implements functional analysis through a diagrammatic representation framework that links conceptually to formal therapy models.

Dr Brown is also happy to discuss ideas for student-led projects, particularly in the areas of psychotherapy mechanism research, risk for emotional problems, and clinical psychology measurement. Please see Pure for more information.

Conversations through video call software (such as Zoom or Teams) are increasingly used in medical, educational, and legal settings. This technology changes how our faces, bodies, and voices appear, and often disrupts the normal timing cues in social interaction—all of which may adversely affect how participants perceive each other and develop a rapport. Groups who are digitally challenged or having communication deficits arising from mental health may be particularly disadvantaged.  This project investigates how video calls shape social interactions in 'official' contexts (e.g. legal or medical), by testing pairs of participants while they speak to one another in-person or online, and then measuring how well they coordinate their behaviour and establish rapport, and self and other perception. (For example, do people view each other as trustworthy and honest in online interactions? Do individuals establish rapport by aligning and mimicking each others’ behaviour to the same degree in online as offline interactions?) There is much room for flexibility in how the successful applicant shapes the project to fit their interests. Dr Jasmin’s expertise is in speech, language and social interaction. Prof Memon directs the Centre for the Study of Emotion & Law, and is an expert in the social and cognitive psychology of police investigation and witness testimony.

Dr Jasmin is also happy to discuss student-led projects on the topics of speech, language, social interaction, music, and autism. Please details see the Sound Mind Lab website.

The cost of road traffic collision injuries and fatalities has a profound impact on society. A wide variety of factors contribute to RTCs, their nature and interaction are currently poorly understood but both speed and attentional factors have proven to be instrumental in determining the likelihood and severity of accidents. The purpose of this project is to identify key factors that modulate driver behaviour and road traffic collision (RTC) likelihood by assessing both real-world accident data and driver behaviour in a simulator. The manipulation of scenes in the simulator environment will be informed by an Artificial Intelligence (AI) machine learning algorithm that will be trained on real-world data to predict accident likelihood and identify key factors that conspire to increase the probability of RTCs. In order to develop a more comprehensive understanding of RTCs and driver behaviour, the machine learning algorithm will also be trained on the subsequently acquired real-time data from the simulator studies.

Making good choices requires learning how our actions relate to specific events in the external world. Yet, this learning process can be biased by how we make, and evaluate, our decisions. While such biases can be generally adaptive, understanding them could help improve decision making. Moreover, such interactions can give rise to, and maintain, maladaptive patterns of (meta)cognition linked to psychiatric symptoms, e.g. depression or compulsions. Given the high economic and societal costs of mental illness, the leading cause of disability in the UK, better treatment and prevention strategies are needed. Combining behavioural, computational and neuroimaging methods will improve our understanding of how learning and decision making interact with self-monitoring and attribution, in mental health and illness. Focusing on symptoms, over diagnostic categories, will serve to identify specific patterns of maladaptive cognition. This offers a unique opportunity to develop novel tools that may subsequently help to refine differential diagnosis and improve treatment selection, as well as provide a foundation for the development of novel psychological interventions.

Dr Sidarus is happy to discuss ideas for student-led projects, in the areas of computational psychiatry and cognitive neuroscience. Please see the following pages for more information: lab website, and personal website.

Imagine living on the surface of a perfect sphere which is so large that you don’t notice its ever-so-slight curvature in all directions, wherever you are. Walking on such a sphere is like moving on an infinite surface where you can explore without changing location. Whilst it would be challenging to explore such a space in the real world, it can be constructed in virtual reality (VR). We will populate this virtual space with isolated or assembled objects – such as basic geometric bodies, architectural creations, or trees, for example - which are dotted around on this surface. Different locations containing such visual markers can be demarcated and connected to three other locations to form a network of navigation decision points. We can connect each location to three others, meaning each is reached from a preceding location and leads to two possible destinations, thus forming a decision point: this generates a network of two-alternative choices for anyone moving in this ‘infinite decision space’. Because naturalistic movement in VR is limited to a small play area, we will assemble a VR bicycle (similar to a static exercise bike) that uses sensors on the wheels and handlebar to detect the movement intended by the participant and use it to control the rotation of the environment in the VR headset – which the participant experiences as cycling through the virtual ‘infinite decision space’. This combination of constructed VR environment and a VR bike will allow us to investigate preferences in a continuous journey, with highly specific stimuli (3D virtual objects) that can be designed in multiple possible ways.  A PhD project can use this space to explore a great variety of preference questions, including favourable geometric objects, complex tiling patterns, architectural compositions, trees, animals, cars, furniture, social cues, and so on – this can be used to develop quantitative measures in context as diverse as aesthetics, industrial design, wellbeing, and mental health, or even indicators of trust.

Johannes is also happy to discuss ideas for student-led projects in the area of visual perception and empirical aesthetics, in particular related to geometric aspects and mathematics of perceived ‘beauty’, and the experience of arts in 2 and 3 dimensions.