The Applied Computational Psychiatry lab focuses on developing computational tools with real potential for clinical applications.
Computational Psychiatry is a multidisciplinary field of research at the intersection of psychiatry, neuroscience, machine learning and statistics. The aim of the field is to harness advances in these fields to advance treatments for mental illnesses.
We are part of the Divison of Psychiatry and the Max Planck UCL Centre for Computational Psychiatry and Ageing Research in the Institute of Neurology at University College London.
For overviews over computational psychiatry, see Huys et al., 2016 Nature Neuroscience and Huys et al. 2020 Neuropsychopharmacology
When an organ is unable to meet the demands placed on it, illness can arise. As the main functions of the brain are to compute and learn, an understanding of mental illnesses will benefit from an understanding of the computational and learning functions the brain performs, and how these are affected in states of ill-health.
Latest Peer-Reviewed Original Publications
Susceptibility to interference between Pavlovian and instrumental control predisposes risky alcohol use developmental trajectory from ages 18 to 24
We examined if susceptibility to interference between Pavlovian and instrumental control assessed via a PIT task predicts drinking trajectories until age 24. Overall, it might be viewed as a predisposing mechanism towards hazardous alcohol use during young adulthood, and the identified high-risk group may profit from targeted interventions.
Elevated amygdala responses during de-novo Pavlovian conditioning in alcohol-use disorder are associated with Pavlovian-to-Instrumental transfer and relapse latency
Cue-reactivity research has demonstrated the power of alcohol-associated cues to activate the brain’s reward system, which has been linked to craving and subsequent relapse. However, whether de-novo Pavlovian conditioning is altered in alcohol use disorder (AUD) has been rarely investigated. We provide evidence of altered neural correlates of de-novo Pavlovian conditioning in patients with AUD, especially for appetitive stimuli. Thus, heightened processing of Pavlovian cues might constitute a behaviorally relevant mechanism in alcohol addiction.
Latest Preprints
On the misery of cognitive effort
The effect of cognitive effort on mood is unclear. Expending cognitive effort is generally avoided but expenditure of cognitive effort is the primary feature of some popular recreational activities, such as sudoku or video games. It is unknown what immediate impact cognitive effort has on momentary mood. With a letter sorting task, we found that increased difficulty, and consequently cognitive effort, leads to more errors and lower mood ratings. In a follow up study, we validated our results in a different sample and showed that, even with removal of reward feedback, cognitive effort remain impactful on mood.
Chen, Huys, Stringaris and Nielson (2023): On the Misery of Cognitive Effort psyArXiv
Do discontinuation symptoms predict depression relapse after antidepressant cessation?
Discontinuing antidepressants after recovering from a depressive episode is associated with a risk for two events: discontinuation symptoms and relapse. Little is known about who can discontinue safely and whether discontinuation symptoms constitute a risk factor for relapse. This study investigated risk factors for experiencing discontinuation symptoms and whether discontinuation symptoms are associated with depression relapse. Antidepressant discontinuation symptoms were relatively common and experienced mainly by women. Experiencing discontinuation symptoms may adversely impact relapse risk.