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Poster C138

Statistical learning of temporal-order regularity is easier in the auditory than visual modality

Poster Session C - Sunday, April 14, 2024, 5:00 – 7:00 pm EDT, Sheraton Hall ABC

Andhika Renaldi1 (, Denise Hsien Wu2; 1Taiwan International Graduate Program in Interdisciplinary Neuroscience, National Central University and Academia Sinica, Taipei, Taiwan, 2Institute of Cognitive Neuroscience, National Central University, Taiwan

It is generally found that temporal and spatial information is relatively salient in the auditory and visual modalities, respectively. In the present study, we investigated such relationship in a novel statistical learning test in which temporal and spatial positional regularities were present in the same stimuli concurrently. In the study phase of the visual concurrent positional statistical learning (cPSL) test, 12 simple geometric shapes were individually specified to appear in either the first or second frame of a trial on the left or right side of the screen. Similarly, in the study phase of the auditory cPSL test, 8 non-verbal sounds were individually specified to appear in the first or second order through the left or right speaker. During the subsequent test phase, participants were required to make yes-no judgments for stimuli positioned correctly in both temporal and spatial positions (T+S+), correct in temporal but incorrect in spatial position (T+S-), correct in spatial but incorrect in temporal position (T-S+), and incorrect in both temporal and spatial positions (T-S-). The results revealed that statistical learning was superior in the auditory than visual modality, mainly because it was more difficult to identify the correct targets (T+S+) and to reject incorrect foils of the T-S+ condition in the visual than auditory modality. The present findings support the saliency of temporal information in the auditory modality and extend the link to the context of statistical learning. Further explorations of the neural correlates of such link would be pursued in future research.

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April 13–16  |  2024