Category learning is constrained by training context and prior experience
thesisposted on 20.08.2019, 18:16 by Casey RoarkCasey Roark
Everyday behaviors like interpreting a child’s squeal as thrilled or terrified or understanding
diverse acoustic signals from different talkers to each be the word “thanks” rely on
categorization. Learning to treat perceptually distinct objects as functionally equivalent changes
how we structure our knowledge about the world. Category learning is a major area
of 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 how
humans create and reorganize mental representations of categories. Even so, the majority
of research on perceptual category learning focuses on visual categories. In this dissertation, I
will focus on auditory category learning. Sound presents unique learning challenges that are
important for understanding speech learning, music perception, and everyday listening.
This dissertation investigates how humans build on existing knowledge to learn new sound
categories. 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 the
current learning context affect category learning. Chapter 4 examines how existing perceptual
representations influence how learners form categories within a perceptual environment.
Chapters 5 and 6 investigate how experience with statistically structured sensory information
influences similarity-based perceptual representations and the effect of this experience on
subsequent category learning. A neural network model presented in Chapter 7 serves as a starting
point in understanding the underlying computational mechanisms that allow sensory experience
to shape perceptual representations, which then influence higher-level cognition, such as the
processes involved in category learning. This research advances understanding of both auditory
and visual categorization by revealing how category learning is both constrained by prior
experience and influenced by regularities and the context of the current learning environment.
- Doctor of Philosophy (PhD)