The effects of lateralized set presentation on numerical and feature-based judgments: An investigation across ANS, OTS, and VWM performance

Numerical and spatial processing are closely intertwined, yet whether spatial–numerical associations generalize across distinct quantitative systems remains an open question. We investigated how stimulus position (central, left, and right visual fields) modulates performance across three systems: the Approximate Number System (ANS), the Object Tracking System (OTS), and Visual Working Memory (VWM). Using a go/no-go paradigm that avoided explicit lateralized responses, adult participants performed numerosity discrimination or change-detection tasks while stimuli were presented at varying spatial locations. Performance across all tasks was primarily shaped by core computational demands—numerical ratio in the ANS and set size in OTS and VWM. Critically, only the ANS showed a spatial–numerical congruency effect (i.e., Spatial-Numerical Association of Response Codes (SNARC) effect), with faster responses when smaller numerosities appeared on the left and larger ones on the right. OTS instead exhibited a strong central advantage, with higher accuracy and faster responses for centrally presented stimuli, but no magnitude-dependent spatial organization. VWM showed minimal spatial modulation, with performance driven almost entirely by memory load. We examined whether individual differences in OTS and VWM performance were correlated: spatial-bias indices based on accuracy were not correlated across tasks, but Reaction Time–based and efficiency-based measures, as well as center-position performance, showed reliable positive associations, in line with previous literature. These findings indicate that spatial–numerical congruency is specific to approximate magnitude processing and does not generalize to systems relying on discrete, item-based representations. This pattern suggests that the continuous and compressed representational format of the ANS may be a key condition for the emergence of spatial–numerical associations.