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Title: A role for cognitive control in decision making under uncertainty
Author: Bland, Amy Rachel
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2012
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Decision-making relies on one's ability to form a stable representation of the underlying Stimulus-Response-Outcome (S-R-O) rules learned from previous experience of gains and losses (e.g. Seymour et al., 2007; Ridderinkhof et al., 2004; Sutton and Barto, 1998). However, learning these representations is made particularly challenging by frequent changes in S-R-O associations. Therefore a changing and volatile world requires continuous tracking of the S-R-O probabilities in our environment (Behrens, et al., 2007; Krugel et al., 2009; N assar et al., 2010). Computational modelling of behaviour through Reinforcement and Bayesian learning approaches has undoubtedly enhanced our understanding of human decision making in changing environments (Steyvers et al., 2002; Chater et aI., 2006; Yoshida and Ishii, 2006; Nassar et al., 2010). These models describe very specific computational operations implemented in our brains; however, they remain "agnostic" to the nature of the cognitive processes required. Particularly, it is unclear whether decision making during volatility of S-R-O rules requires cognitive control mechanisms. Indeed, the ability to quickly and flexibly adjust behaviour to changing environmental demands is thought to be a defining characteristic of cognitive control (Braver et al., 2003). Although neuroimaging studies have started to elucidate the neural substrates involved in decision making under uncertainty (Huettel et aI., 2005h; Hsu et al., 2005; Tobler et al., 2007; Yoshida and Ishii, 2006; Paulus et al., 2001; Volz et al., 2003) and specifically volatility (Behrens et al., 2007), there remains little electrophysiological evidence.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available