Implicit sequence learning using auditory cues leads to modality-specific representations

doi:10.3758/s13423-021-02001-z

2021-10-20

Y. Catherine Han

Paul J. Reber *

DOI：10.3758/s13423-021-02001-z

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摘要

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The implicit acquisition of statistical information from the environment is considered a fundamental type of human learning. Paradigms using visually cued sequences have been frequently used to study implicit learning. However, learning sequences of auditory cues is likely to be important in domains such as language or music. In three experiments, we established a novel auditorily cued implicit perceptual-motor sequence learning paradigm to compare to traditional visually cued sequence learning and identify whether this type of learning generalizes across cue modality. Participants exhibited reliable sequence-specific learning to auditory cues in all three experiments (Experiments 1-3), which was generally not influenced by explicit knowledge (Experiment 2). In Experiment 3, a large drop in knowledge expression in the novel cue modality was observed, suggesting that the acquired implicit sequence knowledge depended largely on sensory-specific representations. Overall, auditorily cued learning was similar to, though proceeded faster than, learning in comparable visually cued sequence learning paradigms. Similarity between learning from cues in different sensory modalities suggests that there may be a common process for the automatic extraction of sequential statistical structure. However, the lack of robust transfer sequence knowledge across modalities argues against a purely domain-general learning mechanism for all kinds of sequences. By expanding quantitative methodologies to characterize sequence learning in the auditory domain, these findings illustrate the possibility of bridging research in sequence and statistical learning domains to identify common mechanisms of complex cognitive skill and language learning.

Keyword:

Implicit learning and memory

Modality effects

Sequence learning

Statistical learning