Complete cross-frequency transfer of tone frequency learning after double training

Ying Zi Xiong, Ding Lan Tang, Yu Xuan Zhang, Cong Yu

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

A person's ability to discriminate fine differences in tone frequency is vital for everyday hearing such as listening to speech and music. This ability can be improved through training (i.e., tone frequency learning). Depending on stimulus configurations and training procedures, tone frequency learning can either transfer to new frequencies, which would suggest learning of a general task structure, or show significant frequency specificity, which would suggest either changes in neural representations of trained frequencies, or reweighting of frequency-specific neural responses. Here we tested the hypothesis that frequency specificity in tone frequency learning can be abolished with a double-training procedure. Specifically, participants practiced tone frequency discrimination at 1 or 6 kHz, presumably encoded by different temporal or place coding mechanisms, respectively. The stimuli were brief tone pips known to produce significant specificity. Tone frequency learning was indeed initially highly frequency specific (Experiment 1). However, with additional exposure to the other untrained frequency via an irrelevant temporal interval discrimination task, or even background play during a visual task, learning transferred completely (1-to-6 kHz or 6-to-1 kHz; Experiments 2-4). These results support general task structure learning, or concept learning in our term, in tone frequency learning despite initial frequency specificity. They also suggest strategies to design efficient auditory training in practical settings.

Original languageEnglish (US)
Pages (from-to)94-103
Number of pages10
JournalJournal of Experimental Psychology: General
Volume149
Issue number1
DOIs
StatePublished - Jan 2020

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Keywords

  • Double training
  • Perceptual learning
  • Specificity
  • Tone frequency discrimination
  • Transfer

PubMed: MeSH publication types

  • Journal Article

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