Speaker
Description
The nature of numerical representations, whether abstract and notation-independent, still sparks a fervent debate in the numerical cognition field. Recent behavioral evidence using distributional semantics have challenged the abstract coding view, showing that linguistic experience accounts for notation-dependent distance effects. This study examines whether linguistic priors also account for neurophysiological responses, using EEG in healthy adults.
EEG data from 64 channels were recorded while participants completed three tasks: (1) passive viewing of single digits, (2) sequential number comparison, and (3) simultaneous number comparison. Representational Similarity Analysis (RSA) was used to determine whether neural patterns align with predictions from distributional semantic models. Preliminary analyses replicate the behavioral pattern observed in previous studies, with linguistic priors predicting performance better than real numerical distance. Importantly, EEG patterns also align better with the linguistic distribution of numbers. Behavioral results confirm that. These findings challenge the amodal representation of numbers, calling in turn for more comprehensive accounts integrating the role of experiential priors.
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