We have used Bayesian probability theory and stochastic control theory to understand how the brain negotiates the tension between exploration and exploitation such as in multi-armed bandit tasks (Zhang & Yu, 2013; Guo & Yu, 2018; Ryali, Reddy, Yu, 2018; Cogliati Dezza et al, 2017; Guo & Yu, 2018; Cogliati Dezza et al, 2020), and between speed and accuracy in optimal stopping problems (Yu, 2007; NIPS, 2008), as well as the dynamic allocation of covert attention (Yu, Dayan, Cohen, 2009) and overt attention (active sensing) (Yu & Huang, 2014; Ahmad, Huang, Yu, 2014), according to environmental statistics and behavioral goals.
This body of work contributes to a formal framework for investigating active cognition, an important area that has been relatively neglected in cognitive neuroscience due to its computational complexity.
Collaboration with psychiatrists
Collaborating with psychiatrists, we have also investigated how the underlying neural processes go awry in depression, anxiety (Harlé et al, 2017), drug abuse (Harlé et al, 2015a), and gambling addiction (Cogliati Dezza et al, 2020).
Related Papers
- Frazier, P & Yu, A J (2008). Sequential hypothesis testing under stochastic deadlines. Advances in Neural Information Processing Systems. MIT Press, Cambridge, MA.
- Yu, A J, Dayan, P, & Cohen J D (2009). Dynamics of attentional selection under conflict: Toward a rational Bayesian account. Journal of Experimental Psychology: Human Perception and Performance, 35: 700-717.
- Zhang, S & Yu, A J (2013). Forgetful Bayes and myopic planning: Human learning and decision-making in a bandit setting. Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press.
- Yu, A J & Huang, H (2014). Maximizing masquerading as matching: Statistical learning and decision-making in choice behavior. Decision, 1 (4): 275-287.
- Ahmad, S, Huang, H, & Yu, A J (2014). Cost-sensitive Bayesian control policy in human active sensing. Frontiers in Human Neuroscience, doi: 19.3389/fnhum.2014.00955.
- Harlé, K M, Zhang, S, Schiff, M, Mackey, S, Paulus*, M P, & Yu*, A J. *co-senior authors. Altered statistical learning and decision-making in methamphetamine dependence: Evidence from a two-armed bandit task Frontiers in Psychology, 6:1910.
- Harlé, K M, Guo, D, Zhang, S, Paulus, M, Yu, A J (2017). Anhedonia and anxiety underlying depressive symptomatology have distinct effects on reward-based decision-making. PLoS ONE, 12(10):e0186473.
- Cogliati Dezza, I, Yu, A J, Cleeremans, A, Alexander, W (2017). Learning the value of information and reward over time when solving exploration-exploitation problems. Nature Scientific Reports, 7:16919.
- Ryali, C, Reddy, G, Yu, A J (2018). Demystifying excessively volatile human learning: A Bayesian persistent prior and a neural approximation. Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press.
- Guo, D, Yu, A J (2018). Why so gloomy? A Bayesian explanation of human pessimism bias in the multi-armed bandit task. Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press.
- Zhou, C, Guo, D, Yu, A J (2020). Devaluation of unchosen options: A Bayesian account of the provenance and maintenance of overly optimistic expectations Proceedings of the Cognitive Science Society Conference.
- Cogliati Dezza, I, Noel, X, Cleeremans, A, Yu, A J (2020). What drive information-seeking in healthy and addicted behaviors. BioRxiv.
