The development of bias in perceptual and financial decision-making




Chen, Mei-Yen, Ph. D.

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Decisions are prone to bias. This can be seen in daily choices. For instance, when the markets are plunging, investors tend to sell stocks instead of purchasing them with lower prices because people in general are more sensitive to the potential losses than the potential gains, or loss averse, in making financial choices. This also can be seen in laboratory tests. When participants receive higher payoffs for successfully discriminating a visual stimulus as one choice against the other, they begin choosing this higher-rewarded option more often even though the objective evidence indicates the alternative. In my dissertation, I used mathematical models and functional magnetic resonance imaging (fMRI) to track the development of bias in perceptual and financial decision-making and presented evidence characterizing the experience-sensitive and domain-general decision-making process in the human brains. The first chapter showed that bias could be developed through associating decision contexts and reward feedback from trial to trial in perceptual decision-making. Although the surface task differed, this learning process involved the same prediction error driven mechanisms implemented in the dopaminergic system as in financial decision-making. Furthermore, the frontal cortex increased its strength of connection between visual and value systems that accounted for the growth of perceptual bias. The second chapter extended this feedback-driven acquisition process to examine the influences of experience on loss aversion in financial decision-making. The results showed that people learned to make riskier or more conservative decisions according to the feedback that they had received in different decision contexts. This alternation in loss aversion was achieved through modulation of the value system’s sensitivity toward the potential gains in evaluation. The frontal cortex mediated this change. The third chapter used a mathematical model to identify the changes in financial decision-making that occurred faster than the temporal resolution of fMRI. The results suggested that people might simplify financial information into some rules of thumb for making a choice. These findings not only integrated the knowledge in different domains of decision neuroscience but also shed lights onto how one may refine the decision-making process against experiences.



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