Unpicking influences on goal-directed behaviour across the lifespan: a computational modelling approach

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Goal-directed behaviour [GDB] involves focusing on relevant information and ignoringdistractors based on specific goals. Nonetheless, goal-directed actions do not always lead tothe desired outcome. Two personality traits thought to influence GDB are impulsivity andcompulsivity, with the former initiating actions and the latter terminating them. Importantly,impulsivity and compulsivity vary over short periods of time [1] and across the lifespan [2],though the two are predominantly studied at trait level [3]. The link between real-life statemeasures and physiological and neural markers remains unclear, and their effects on GDB isunknown. Using an accelerated longitudinal design, the aim of this computationaldevelopmental neuroscience project is to investigate the relationship between impulsivity,compulsivity, and GDB across the lifespan [4].This project will use a smartphone app to collect real-world, ecologically valid measures ofimpulsivity, compulsivity and GDB during three developmental periods: late adolescence[18-24yrs], middle adulthood [35-45yrs], and older adulthood [55-65yrs]. Longitudinalmeasurements from a large sample will capture inter- and intra-individual differences anddata will be analysed using network analysis. Laboratory measures of impulsivity,compulsivity and GDB will be collected in a subset of the sample. For example, we haveestablished a Pavlovian conditioning task with eye-tracking to measure goal-trackingbehaviour. Resting state fMRI data will be employed to assess how differences across thelifespan in state and trait impulsivity and compulsivity relate to within- and between-restingstatenetwork architecture. Data will be analysed using computational modelling approaches.The primary supervisor will lead on behavioural neuroscience, including laboratory measuresof impulsivity, compulsivity and GDB using eye-tracking. The secondary supervisor will leadon computational modelling, longitudinal experience sampling and rs-fMRI. The twosupervisors provide distinct theoretical knowledge for this interdisciplinary project, with theprimary supervisor providing input relating behavioural neuroscience and the secondarysupervisor concerning computational neuroscience.