Sep 11 – 13, 2025
Campus Luigi Einaudi
Europe/Rome timezone

Spatial associations of losses and gains: Evidence of a SNARC-like effect of valence in a magnitude classification task

Sep 13, 2025, 12:30 PM
2h
Poster Space, time and number Lunch and poster 3

Speaker

Alberto Mariconda (Università degli studi di Trieste)

Description

The SNARC (Spatial-Numerical Association of Response Codes) effect describes the tendency to associate small numbers with the left side and large numbers with the right. Similarly, stimulus valence (positive/negative) is spatially lateralized, with right-handers typically associating negative stimuli with the left and positive with the right. In the present study, we investigated how these dimensions interact when numbers are framed as monetary gains (positive) or losses (negative).
Two experiments were conducted with right-handed participants. In Experiment 1, a valence classification task required participants to classify numbers as gains (green ink) or losses (red ink), pressing a left or right key. Results showed neither a classic SNARC effect nor SNARC-like effects for valence. In Experiment 2, a magnitude classification task required judging whether numbers were smaller or larger than 5, with gains and losses indicated by green or red ink, respectively. Results revealed a classic SNARC effect, with faster responses for small-left and large-right mappings. Moreover, a magnitude × valence compatibility effect was observed: responses were faster when magnitude and valence aligned (small–losses, large–gains) than when they conflicted (large–losses, small–gains). This effect was stronger in the SNARC-compatible block, suggesting "hyper-compatibility" when hand, magnitude, and valence were congruent (e.g., left–small–losses).
Overall, the findings indicate that both number magnitude and valence influence spatial associations in a magnitude classification task, but not in a valence classification task.
This study was funded by the PRIN 2022 program (project Prot. 20227N2Y73).

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Primary authors

Alberto Mariconda (Università degli studi di Trieste) Marta Maisto (Università degli Studi di Trieste) Valter Prpic (eCampus University) Mauro Murgia (University of Trieste)

Presentation materials

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