Clustering in artificial categories: an equivalence analysis
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Updated: Oct 3, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
M Galizio1, K L Stewart, C Pilgrim
1Department of Psychology, University of North Carolina, Wilmington 28403, USA. galizio@uncwil.edu
Abstract:
Category clustering is a robust finding in the free recall of familiar category members, but has rarely been studied with artificial categories. In the present study, college students learned artificial categories via stimulus-equivalence methodology. Arbitrary match-to-sample training with nonsense syllables established three interrelated conditional discriminations, and, for most subjects, unreinforced test trials revealed the emergent stimulus-control relations considered to be evidence of equivalence classes. Free-recall tests revealed evidence of significant within-class clustering both before and after equivalence testing, but was more pronounced after the equivalence tests. These findings confirm that classic phenomena like clustering in free recall can be studied with stimulus-equivalence methodology, thus allowing for experimental control over relevant variables.
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