Statistical Learning of Unfamiliar Sounds as Trajectories Through a Perceptual Similarity Space.

We present experiments in which this hypothesis makes sharply different predictions from hypotheses based on the assumption that sequences are learned over discrete, labeled stimuli. We also present a series of simulation models that encode stimuli as positions in a continuous two-dimensional space, and predict the next location from the current location. Although no model captures all of the data presented here, the results of three critical experiments are more consistent with the view that participants represent trajectories through similarity space rather than sequences of discrete labels under particular conditions.
PMID: 31446661 [PubMed - in process]

Source: Cognitive Science - July 31, 2019 Category: Neuroscience Authors: Wang FH, Hutton EA, Zevin JD Tags: Cogn Sci Source Type: research