Proceedings of the Annual Meeting of the Cognitive Science Society

Number comparison is a task that has been widely used to investigate the mental representation of number magnitudes. It is frequently assumed that the mapping from numerals to a "mental number line" is compressive (i.e., logarithmic) or that magnitude representations have the property of scalar variability. In this study, w e simulate the process of selecting the larger of two numbers in a neural network model. We show that it is possible to account for the main experimental effects (e.g., the distance effect and the number size effect) with a simple architecture using a linear representation of numerical magnitudes. The compressive effects that are found in the reaction times emerge from the non-linear interactions that are intrinsic to the decision process.