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Zamana dayalı kararların olasılıksal ilişkiler tarafından adaptif modülasyonu

2016
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Advisor: Doç. Dr. Fuat Balcı

Abstract (EN)

Abstract This thesis investigated the effect of experienced probabilistic contingencies on the temporal decisions of humans and mice and evaluated the observed alterations in decision outputs within the framework of optimality. The first study aimed to evaluate the optimality of two-alternative forced (retrospective temporal) choice behavior of human participants under different stimulus probabilities and payoff matrices (with or without penalty for erroneous decisions). The results of this study showed that human participants adapted their two-alternative time-based decisions in response to the manipulations of stimulus probabilities and nearly maximized their gain irrespective of the payoff matrix. The second study aimed to investigate the generalizability of optimal temporal decision-making performance of humans and mice to conditions with more than two temporal options. In this experiment, the probabilities of different options were manipulated between experimental conditions and subjects were required to make two sequential temporal decisions within a trial (as opposed to a single decision in the first study). The results of this study revealed that the number of temporal options constituted a limiting factor for the optimality of human time-based decision making. Although, humans could adapt their initial decisions in response to probabilistic information, their subsequent decisions were not sensitive to probabilistic relations. On the other hand, mice could adapt both their initial and subsequent decisions in response to probabilistic contingencies. These experiments extended the scope of temporal risk-assessment studies to include retrospective decision-making and defined a limiting factor for human optimal time-based decisions. Keywords: Time discrimination, Optimality, Reward maximization

Author

Dr. Filiz Çoşkun

How to Cite

Filiz Çoşkun (Master Thesis). Zamana dayalı kararların olasılıksal ilişkiler tarafından adaptif modülasyonu, 2016, Koç University.

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