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Updated: Jul 9, 2026

A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning
Published on: January 19, 2022
Stimulus coding in human associative learning: flexible representations of parts and wholes
Klaus G Melchers1, David R Shanks, Harald Lachnit
1Universität Zürich, Switzerland.
Abstract:
An enduring theme for theories of associative learning is the problem of explaining how configural discriminations--ones in which the significance of combinations of cues is inconsistent with the significance of the individual cues themselves-are learned. One approach has been to assume that configurations are the basic representational form on which associative processes operate, another has tried in contrast to retain elementalism. We review evidence that human learning is representationally flexible in a way that challenges both configural and elemental theories. We describe research showing that task demands, prior experience, instructions, and stimulus properties all influence whether a particular problem is solved configurally or elementally. Lines of possible future theory development are discussed.
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