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Updated: Mar 7, 2026

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
Published on: October 27, 2016
Multiple processes in two-dimensional visual statistical learning
Eiichi Hoshino1,2, Ken Mogi2
1Department of Computational Intelligence and System Science, Tokyo Institute of Technology, Nagatsuta-cho, Midori-ku, Yokohama, Japan.
Abstract:
Knowledge about the arrangement of visual elements is an important aspect of perception. This study investigates whether humans learn rules of two-dimensional abstract patterns (exemplars) generated from Reber's artificial grammar. The key question is whether the subjects can implicitly learn them without explicit instructions, and, if so, how they use the acquired knowledge to judge new patterns (probes) in relation to their finite experience of the exemplars. The analysis was conducted using dissimilarities among patterns, which are defined with n-gram probabilities and the Levenshtein distance. The results show that subjects are able to learn rules of two-dimensional visual patterns (exemplars) and make categorical judgment of probes based on knowledge of exemplar-based representation. Our analysis revealed that subjects' judgments of probes were related to the degree of dissimilarities between the probes and exemplars. The result suggests the coexistence of configural and element-based processing in exemplar-based representations. Exemplar-based representation was preferred to prototypical representation through tasks requiring discrimination, recognition and working memory. Relations of the studied judgment processes to the neural basis are discussed. We conclude that knowledge of a finite experience of two-dimensional visual patterns would be crystalized in different levels of relations among visual elements.
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