Major Depressive Disorder (MDD)- a computational neuroscience approach
Research type
Research Study
Full title
Probing Social Exchanges and Emotions– A Computational Neuroscience Approach to the Understanding of Major Depressive Disorder
IRAS ID
161423
Contact name
Peter Fonagy
Contact email
Sponsor organisation
University College London
Clinicaltrials.gov Identifier
under review, Data Protection ref number
Duration of Study in the UK
3 years, 0 months, 31 days
Research summary
With the proposed project we plan to investigate the brain activation patterns of people suffering from Major Depressive Disorder (MDD) and to compare them with healthy control participants as well as to track their treatment response and outcome via neuroscientific paradigms. Only little is known about the neurobiology of MDD. Our study design will address some of these gaps in the literature, mainly by focusing on brain scan paradigms during which social interactions which are assumed to be at the core of patients' difficulties will be investigated. We will link the data from our neuroimaging assessments with patients’ symptomatology, their attachment and developmental history, their mentalisation capacities and clinical outcome. This will allow us to gain a better understanding of the disorder and to develop more informed and effective treatments from which clients will benefit.
More specifially, we plan to investigate the neural correlates and computational mechanisms of social processes that are fundamental both for understanding how the healthy brain computes interactions, and for characterizing disease-related dysfunction in MDD. Using the framework of computational psychiatry we aim to identify biomarkers or endophenotypes specific to MDD as well as those that may represent shared neurobehavioural characteristics between the it and other psychopathologies, particularly personality disorders which present a substantial co-occurring diagnosis.
By drawing on socio-interactive paradigms and hyperscanning technique (the simultaneous brain scanning of two participants engaged in task in which they mutually influence one another) we will investigate the mechanisms underlying second order belief reasoning, recursive modelling of relationships, trust, and impulsivity. We will also account for individual differences such as attachment representations and reflective functioning in order to assess the variance these can explain in our computational models of both behavioural performance and brain activity in economic exchange probes.REC name
London - Queen Square Research Ethics Committee
REC reference
16/LO/0077
Date of REC Opinion
15 Apr 2016
REC opinion
Further Information Favourable Opinion