This dissertation comprises three essays that study dynamic decisions under uncertainty--in particular, ambiguity. The first two chapters develop new decision models that emphasize the role of making statistical inferences in decisions. The third chapter highlights, in the context of persuasion, how different decision models can lead to distinct conclusions in...
Although there has been profound evidence showing the positive correlation between spatial abilities and math performances, we still know very little about how and why spatial thinking facilitates the learning of mathematics. This dissertation unpacks several aspects of mathematics that are embedded in learning and playing an ancient and rich...
Classical conditioning is a form of associative learning and can be used as a behavioral paradigm to model and investigate the neural mechanisms underlying associative learning. In this work, classical conditioning paradigms are used to test the effectiveness of a disease model on the impact of learning and emotional regulation...
Dynamic decision-making is a complex process that relies on our ability to generate, evaluate and implement a variety of strategies. Understanding how people navigate this process is a difficult problem that requires a wide range of methodologies. This study details a combination of behavioral experiments, computational modeling, and neuroimaging that...
To survive, animals, including human beings, have developed an amazing ability to learn the constantly changing environment. Specifically, detecting specific odorants in a noisy, variable background is crucial for finding food and water, mating, and avoiding potential dangers. For this purpose, rodents have developed an olfactory system that is powerful...