Title: A Computational Approach to Understanding Maladaptive Cognition in Depression
Funder: Economic and Social Research Council

Abstract: 1. Understand the cognitive mechanisms underlying the attribution of events to oneself vs. external causes. I will develop a task (Task 1) that allows a precise assessment of how accurately people can track the causes of specific events, by measuring the consequences of biases in the attribution of contingent (self-caused) vs. non-contingent (externally-triggered) events to value-based decision-making and learning processes. 2. Understand the cognitive mechanisms underlying metacognitive evaluation (e.g. decision confidence), and how metacognitive signals are attributed to cognitive processes. I will develop a task (Task 2) that allows a precise assessment of the accuracy of metacognitive signals and of their attribution to on-going cognitive processes, by measuring biases in the metacognitive evaluation of decision confidence, and the consequences of the misattribution of decision confidence to action-outcome learning. 3. Identify behavioural markers of maladaptive (meta)cognition, operationalized through maladaptive attribution (in Tasks 1 & 2), that are related to depressive symptoms. I will conduct large-scale online studies in non-clinical samples, with behavioural tasks and a selection of mental health questionnaires. Behavioural markers of attribution will be identified, leveraging computational models, and their relationship to depressive symptoms will be assessed. Employing a transdiagnostic approach, by measuring several symptoms, will enable testing the specificity of markers of maladaptive attribution to depressive symptoms, relative to other common mental health problems. 4. Assess the clinical relevance of identified behavioural markers of maladaptive cognition. I will conduct a study with the aforementioned behavioural tasks in major depressive disorder patients with (i) a current depressive episode or (ii) remitted from a depressive episode, together with (iii) matched healthy volunteers. This will serve to test the translational value of identified behavioural markers, and clarify which are specifically related to clinically depressed mood (in currently depressed patients) and depressive relapse vulnerability (in remitted patients). 5. Elucidate the neural basis of adaptive attribution processes. An fMRI study in healthy participants with both behavioural tasks will reveal the neural mechanisms associated with adaptive cognition in these tasks. Additionally, we will assess how individual differences in sub-clinical depressive symptoms relate to variability in neural activation during these tasks. 6. Assess the relationship between the cognitive and neural mechanisms of different attributional processes, from tracking the causes of external events (Task 1), to tracking the sources of metacognitive signals (Task 2). Testing both tasks in the same individuals, in the fMRI and clinical studies, will serve to clarify whether maladaptive patterns of attribution tend to be generalised or specific (i.e. across both Tasks 1 & 2, or only at one level).

Lay abstract: CONTEXT Depression is the single leading cause of disability worldwide and a major public health problem. Even with the best treatments, around 30% of patients remain unwell, demonstrating the importance of improving our understanding of depression. Decades of research in clinical psychology suggests that vulnerability to depression is associated with negative cognitive styles, such as attributing negative events to stable and global causes, often blaming oneself, and maladaptive metacognitive beliefs (about one's own cognitive processes), such as low self-confidence. These biases are a focus of psychological therapies such as cognitive behavioural therapy (CBT), but the assessment of maladaptive depressive cognition is limited by imprecise measurement, relying on introspection and self-report. AIMS AND OBJECTIVES This project aims to improve our understanding of the maladaptive cognitions driving depressive symptoms. To gain a more mechanistic understanding of the neurocognitive bases of (mal)adaptive cognition, we will leverage computational models of behaviour. This overarching goal will be achieved by conceptualising maladaptive depressive cognition as maladaptive attributions. To test this we will measure: (a) biases in the attribution of positive and negative events to the self vs. external causes; (b) biases in the metacognitive evaluations of decision confidence and their potential misattribution to action-outcome learning. Using cutting-edge analysis methods, across online, clinical, and neuroimaging studies, this project will achieve the following objectives: 1. Clarify the neurocognitive mechanisms underlying adaptive attribution (of external events and of metacognitive signals), in healthy participants. 2. Identify behavioural markers of maladaptive attribution related to depressive symptoms in a non-clinical sample. 3. Test the specificity of markers of maladaptive attribution to depressive symptoms, relative to other common mental health problems. 4. Test the clinical relevance of markers of maladaptive attribution. POTENTIAL APPLICATIONS AND BENEFITS Improving our understanding of the mechanisms that drive maladaptive cognition in depression, and underpin attributional processes in healthy participants, will constitute an important scientific contribution to the fields of clinical psychology and cognitive and computational neuroscience. Given the high societal cost of depression, this research is of high societal and clinical relevance. Disseminating our findings to the wider society will demonstrate how a better understanding of basic cognitive processes may translate to understanding everyday behaviour. Presenting our project and findings to people with mental health problems, including service users, will allow receiving their feedback on our experimental designs and findings, and help broaden the perspective for future research. The work will also be regularly disseminated to academic audiences, through publications and conferences, across the fields of psychology, neuroscience, and mental health. Engaging with clinical experts, by organising an interdisciplinary workshop, will help increase our clinical impact, establish novel collaborations, and receive expert feedback. Identifying behavioural and neural markers related to maladaptive cognition in depression 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.

Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS
Health categories: MENTAL HEALTH