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Updated: Aug 11, 2026

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
Published on: July 17, 2021
An investigation of learning strategy supporting transitive inference performance in humans compared to other species
Sandra N Moses1, Christina Villate, Jennifer D Ryan
1Rotman Research Institute, Baycrest Centre for Geriatric Care, Toronto, Canada. smoses@rotman-baycrest.on.ca
Abstract:
Generalizations about neural function are often drawn from non-human animal models to human cognition, however, the assumption of cross-species conservation may sometimes be invalid. Humans may use different strategies mediated by alternative structures, or similar structures may operate differently within the context of the human brain. The transitive inference problem, considered a hallmark of logical reasoning, can be solved by non-human species via associative learning rather than logic. We tested whether humans use similar strategies to other species for transitive inference. Results are crucial for evaluating the validity of widely accepted assumptions of similar neural substrates underlying performance in humans and other animals. Here we show that successful transitive inference in humans is unrelated to use of associative learning strategies and is associated with ability to report the hierarchical relationship among stimuli. Our work stipulates that cross-species generalizations must be interpreted cautiously, since performance on the same task may be mediated by different strategies and/or neural systems.
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