A Perceptually Grounded Neural Dynamic Architecture Establishes Analogy Between Visual Object Pairs

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Matthis Hesse, Daniel Sabinasz, Gregor Schöner

Published: 2022, Last Modified: 15 May 2025CogSci 2022EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Author(s): Hesse, Matthis E; Sabinasz, Daniel; Schöner, Gregor | Abstract: Detecting analogy is an important high-level cognitive skill that is involved in many aspects of human reasoning. While Structure Mapping Theory (Gentner, 1983) is a well-recognized high-level theory of analogy, it lacks a neural process implementation that links to perception and attention. Avoiding algorithmic computation on ungrounded symbols, we present a dynamic neural architecture built from interacting neural populations that establishes analogy between objects in two visually presented scenes. Consistent with SMT, it accounts for how humans find such analogies.