Probabilistic Selection Task
Learn to select rewarding stimuli under probabilistic feedback; Go/NoGo learning indices.
Frequently Asked Questions
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What is measured?
Learning from positive vs negative feedback (Go vs NoGo).
What is the structure of the PST?
You first learn which symbol in each of three pairs usually pays off (80/20, 70/30, 60/40), and transfer is then tested with novel recombinations of the symbols — Frank and colleagues' design.
What do transfer choices reveal?
Choosing the positive symbol in a new pairing (positive transfer) and avoiding the negative one (negative transfer) index how much you learned from reward versus punishment respectively.
Why is this task influential?
It maps onto dopaminergic learning signals in computational models and has been widely used in psychiatric and pharmacological research.
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About the Probabilistic Selection Task
Background
The Probabilistic Selection Task (PST), developed by Frank and colleagues at the University of Arizona, investigates how humans learn from probabilistic feedback. Participants must learn which of two stimuli is more likely to be rewarded through trial and error.
Computational Psychiatry
The task separates learning from positive feedback (Go learning: stimulus A+) from learning through negative feedback (NoGo learning: stimulus B-). Computational models suggest these rely on different neurotransmitter systems — dopamine for positive prediction errors and serotonin for negative ones.
Research Applications
The PST has been used to investigate psychiatric conditions including OCD, depression, and Parkinson's disease. Different patient populations show distinct patterns of Go vs NoGo bias, suggesting the task can index specific cognitive mechanisms.
References
- Frank, M. J., Seeberger, L. C., & O'Reilly, R. C. (2004). By carrot or by stick: Cognitive reinforcement learning in parkinsonism. Science, 306(5703), 1940-1943. 10.1126/science.1102941
- Frank, M. J., Moustafa, A. A., Haughey, H. M., Curran, T., & Hutchison, K. E. (2007). Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning. Proceedings of the National Academy of Sciences, 104(41), 16311-16316.
- Collins, A. G. E., & Frank, M. J. (2012). How much of reinforcement learning is working memory, not reinforcement learning? A behavioral, computational, and neurogenetic analysis. European Journal of Neuroscience, 35(7), 1024-1035. 10.1111/j.1460-9568.2011.07980.x
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About This Experiment
This experiment is an educational adaptation for demonstration purposes. It is not a clinical diagnostic tool. Results reflect your performance in this specific session and should not be interpreted as an assessment of your cognitive abilities.
Data Privacy
Your experiment data is processed and stored locally in your browser. No data is uploaded to any server unless you explicitly export it.
