CEU eTD Collection (2019); Arató, József: Active learning as a link between environmental statistics and the development of internal representations

CEU Electronic Theses and Dissertations, 2019
Author Arató, József
Title Active learning as a link between environmental statistics and the development of internal representations
Summary Although it is known that facing a dynamically changing sensory stream, people’s perceptual decisions could be influenced not only by individual past stimuli, but also by extracted summary statistics of the stimuli, the effects of these long-term influences are underexplored. In the present thesis, I explored the impact of past stimulus statistics on two distinct types of visual decisions. In the first line of research, in Chapters 2-3, I focused on visual explorative decisions via eye-movements and investigated whether hidden statistical structures of complex scenes could influence visual exploration. I found that spatial regularities of visual stimuli influenced explorative eye-movement patterns, that this effect emerged over time, and it could predict the success in learning the underlying structure of the input. These findings suggest a strong relationship between visual exploration and learning, during which the two processes continuously influence each other. I also showed how this relationship depended on the explicit vs. implicit nature of the task. In the second line of research, in Chapters 4-5, I explored long-term statistical influences in perceptual decision making. To this end, I tested the influence of past probabilities of appearance on discrimination judgments about ambiguous stimuli. I found that statistics of past stimulus strongly influenced perceptual decisions independently of the well-documented short-term sequential effects. This past influence depended on the change-dynamics between long-term and recent stimulus probabilities, sometimes resulting in locally irrational biases. Taken together, the results in these two research domains are consistent with a framework, in which past stimulus statistics are perpetually and automatically built into complex internal representations, which in turn, depending on the task and type of regularity, can dramatically influence visual decisions.
Supervisor József Fiser
Department Cognitive Science PhD
Full texthttps://www.etd.ceu.edu/2019/arato_jozsef.pdf

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