Computational modelling of reinforcement learning and functional neuroimaging of probabilistic reversal for dissociating compulsive behaviours in gambling and cocaine use disorders
Department of Psychology, University of Cambridge, UK; Behavioural and Clinical Neuroscience Institute, University of Cambridge, UK; and the Alan Turing Institute, London, UK
Juan Verdejo-Román
Department of Personality, Assessment and Psychological Treatment, Universidad de Granada, Spain; and Mind, Brain and Behavior Research Center, Universidad de Granada, Spain
Luke Clark
Department of Psychology and Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Canada
Natalia Albein-Urios
Cognitive Neuroscience Unit, School of Psychology, Deakin University, Australia
Carles Soriano-Mas
Department of Psychiatry, Bellvitge Biomedical Research Institute-IDIBELL, Spain; Department of Social Psychology and Quantitative Psychology, University of Barcelona, Spain; and CIBERSAM, Carlos III Health Institute, Madrid, Spain
Rudolf N. Cardinal
Behavioural and Clinical Neuroscience Institute, University of Cambridge, UK; Department of Psychiatry, University of Cambridge, UK; and Liaison Psychology, Cambridgeshire and Peterborough NHS Foundation Trust, UK
Trevor W. Robbins
Department of Psychology, University of Cambridge, UK; and Behavioural and Clinical Neuroscience Institute, University of Cambridge, UK
Jeffrey W. Dalley
Department of Psychology, University of Cambridge, UK; Behavioural and Clinical Neuroscience Institute, University of Cambridge, UK; and Department of Psychiatry, University of Cambridge, UK
Antonio Verdejo-García
School of Psychological Sciences, Monash University, Australia; and Turner Institute for Brain and Mental Health, Monash University, Australia
Jonathan W. Kanen
Department of Psychology, University of Cambridge, UK; and Behavioural and Clinical Neuroscience Institute, University of Cambridge, UK
Background Individuals with cocaine use disorder or gambling disorder demonstrate impairments in cognitive flexibility: the ability to adapt to changes in the environment. Flexibility is commonly assessed in a laboratory setting using probabilistic reversal learning, which involves reinforcement learning, the process by which feedback from the environment is used to adjust behavior. Aims It is poorly understood whether impairments in flexibility differ between individuals with cocaine use and gambling disorders, and how this is instantiated by the brain. We applied computational modelling methods to gain a deeper mechanistic explanation of the latent processes underlying cognitive flexibility across two disorders of compulsivity. Method We present a re-analysis of probabilistic reversal data from individuals with either gambling disorder (n = 18) or cocaine use disorder (n = 20) and control participants (n = 18), using a hierarchical Bayesian approach. Furthermore, we relate behavioural findings to their underlying neural substrates through an analysis of task-based functional magnetic resonanceimaging (fMRI) data. Results We observed lower ‘stimulus stickiness’ in gambling disorder, and report differences in tracking expected values in individuals with gambling disorder compared to controls, with greater activity during reward expected value tracking in the cingulate gyrus and amygdala. In cocaine use disorder, we observed lower responses to positive punishment prediction errors and greater activity following negative punishment prediction errors in the superior frontal gyrus compared to controls. Conclusions Using a computational approach, we show that individuals with gambling disorder and cocaine use disorder differed in their perseverative tendencies and in how they tracked value neurally, which has implications for psychiatric classification.
