Identifying novel neuro-computational treatment targets for mood instability

Bipolar disorder is one of the most debilitating conditions worldwide. People with bipolar disorder experience extreme highs and lows in their mood. These extreme moods may make them more likely to take risks that they may not otherwise take. Carried out jointly at University College London and King's College London, this research aims to better understand how cycles of unstable mood occur, and which brain networks are responsible.

Participants will track their mood and decision-making using a bespoke smartphone app. This will log how their mood changes in response to positive and negative life events and how this affects their subsequent behaviour. The research will test whether positive and negative moods have a stronger effect on how bipolar disorder patients perceive good and bad outcomes, compared to healthy participants, and ask whether perceiving events as better than they actually are can explain why they take bigger risks. Brain imaging will be used to how emotion- and motivation-related areas of the brain might link extreme moods to the perception of events and risks.

The research will also test whether psychological therapies have the potential to reduce how much moods colour the perception of risks and to similarly reduce fluctuations in activity in the underlying brain networks. The goal is that this research will lead to improved mood regulation treatments.

Our mood could be the single most important determinant of life satisfaction, affecting all areas of our functioning and the actions we take in daily life. Clinically, mood instability is a highly debilitating feature of many psychiatric disorders, especially bipolar disorder, and is linked to risky and often harmful behaviours. This year, a commission for improving psychological treatments urged a return to basic mechanistic processes, which historically yielded many significant advances in evidence-based treatment but have unfortunately been largely ignored in recent research and treatment.

The computational psychiatry approach is a promising and rigorous means of recapitulating symptoms into cognitive, behavioural and neurobiological processes. I will use this interdisciplinary approach to characterise the two-way relationship between mood instability and decision-making in bipolar disorder. Specifically, I will test a recent neuro-computational model in which elevated mood leads potential rewards to be perceived as bigger than they are, potentially leading to risk-taking behavior and further escalation in mood.

I will use experimental tasks that manipulate mood states and model the resulting impact of mood on behaviour. By remotely deploying these tasks through a smartphone app, I will test whether model parameters from these tasks can track the trajectory of patients' mood instability in daily life.
I will combine lab- and smartphone-based measures of mood instability with functional MRI to characterise the neural circuits that mediate the mood bias on reward perception.
Finally, testing the translational potential of this approach, I will evaluate whether this mood-on-reward-perception bias and fluctuations in the underlying neural signals can be reduced by mood regulation strategies.

Taken together, this work will deliver a refined mechanistic understanding of mood instability that will provide a direct pathway for novel psychological intervention

Scientific impact: This highly interdisciplinary approach will deliver a novel model of mood instability in bipolar disorder, as well as new ways to potentially assess, intervene, and evaluate outcomes. My findings will benefit psychiatric researchers interested in mood and psychotic disorders, cognitive neuroscientists researching emotion and decision-making, and academic clinical psychologists researching psychological therapies for mood disorders.

Healthcare impact: The translational component of my work will impact on clinicians, especially psychiatrists, clinical psychologists and psychological therapists. This work will deliver a new model that provides a pathway to novel psychological and pharmacological interventions that improve on existing treatments. More effective treatments would lead to economic gains by recovering costs in the management of bipolar disorder as well as working days lost from disability and unemployment.

Societal impact: My work will increase awareness of the role of mood in the decisions we make. By describing the bias that mood exerts on our perception of the world and how we behave, this work could challenge stigma towards people with bipolar disorder by providing a better understanding of the unusual behaviours characteristic of mood episodes. By engaging with people with bipolar disorder, I also see potential in reducing self-stigma associated with the devastating effects that behaviour during major mood episodes can have.