Category learning is constrained by training context and prior experience

Abstract

Everyday behaviors like interpreting a child’s squeal as thrilled or terrified or understandingdiverse acoustic signals from different talkers to each be the word “thanks” rely oncategorization. Learning to treat perceptually distinct objects as functionally equivalent changeshow we structure our knowledge about the world. Category learning is a major areaof research that spans from cellular neuroscience to human behavioral methods to philosophy.Despite the breadth of research on category learning, much still remains unknown about howhumans create and reorganize mental representations of categories. Even so, the majorityof research on perceptual category learning focuses on visual categories. In this dissertation, Iwill focus on auditory category learning. Sound presents unique learning challenges that areimportant for understanding speech learning, music perception, and everyday listening.This dissertation investigates how humans build on existing knowledge to learn new soundcategories. Chapter 1 presents a theoretical framework on the interaction of sensory experience,perceptual representations, and category learning. Chapters 2 and 3 uncover how factors of thecurrent learning context affect category learning. Chapter 4 examines how existing perceptualrepresentations influence how learners form categories within a perceptual environment.Chapters 5 and 6 investigate how experience with statistically structured sensory informationinfluences similarity-based perceptual representations and the effect of this experience onsubsequent category learning. A neural network model presented in Chapter 7 serves as a startingpoint in understanding the underlying computational mechanisms that allow sensory experienceto shape perceptual representations, which then influence higher-level cognition, such as theprocesses involved in category learning. This research advances understanding of both auditoryand visual categorization by revealing how category learning is both constrained by priorexperience and influenced by regularities and the context of the current learning environment.