While sensory stimuli may vary continuously along their physical dimensions, the behaviorally significant events that they represent are often discrete. To represent those discrete events, the sensory system needs to map the continuous stimulus spaces into discrete sensory percepts. Lights of gradually changing wavelength, for instance, are perceived as having discrete hues/colors. This phenomenon is named categorical perception. The neural mechanisms underlying categorical perception are unknown. Categorical perception can be acquired through perceptual training. We proposed to investigate how categorical perceptual learning alters sensory processing in the auditory cortex to elucidate the mechanisms of categorical perceptual learning. Previous studies have shown that sensory experience enlarges cortical representations of the experienced stimuli and shapes categorical perception of the stimuli. Our pilot computational analyses further indicate that stimuli with enlarged cortical representations may be categorically perceived. Based on these results, we propose to test the hypothesis that enlarged cortical representation is a mechanism for categorical sound perception. The long-term goal of the proposed research is to understand the neural mechanisms underlying categorical sound representation and learning. Specifically, we propose to (1) train animals in perceptual discrimination and categorization tasks and determine how the training contribute to categorical sound representations, (2) electrophysiologically examine the auditory cortex of the behaviorally trained animals and quantify learning-induced plasticity effects, and (3) determine using computational methods how the observed cortical plasticity effects would impact perceptual behaviors, which will then be compared with the behavioral learn shown by the animals. The proposed research will provide insights into the complex processes of sensory categorization.
Being able to categorize sensory information is vital for our speech communication, music appreciation and visual recognition. The proposed research aims at understanding how we learn to categorize new sensory information. The results of the proposed research will shed new light on how to improve learning.
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