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Dimension-Based Statistical Learning in Older Adults

  • Alana J. Hodson
  • , Mishaela DiNino
  • , Barbara G. Shinn-Cunningham
  • , Lori L. Holt
  • Carnegie Mellon University

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations

Abstract

The ability to perceptually “reweight” acoustic dimensions in response to changes in distributional statistics is known as dimension-based statistical learning (DBSL). However, it is currently unknown whether DBSL imposes a cognitive load. Older adults, who typically have age-related declines in cognitive ability, may be sensitive to this load. We examined young and older adults' categorization of beer and pier sounds when the statistical relationship between VOT and F0 was consistent with that of American English, followed by a condition in which those statistics were reversed. Listeners made categorization decisions on each stimulus (Experiment 1), or after passive exposure to a string of stimuli (Experiment 2). In both experiments, younger and older participants demonstrated DBSL following exposure to the reversed statistics. Older adults tracked distributional statistics even when learning required accumulation of statistics over 8 sec, suggesting that rapid adaptation to regularities in speech input is robust across differing perceptual loads.

Original languageEnglish
Pages2394-2400
Number of pages7
StatePublished - 2022
Event44th Annual Meeting of the Cognitive Science Society: Cognitive Diversity, CogSci 2022 - Hybrid, Toronto, Canada
Duration: Jul 27 2022Jul 30 2022

Conference

Conference44th Annual Meeting of the Cognitive Science Society: Cognitive Diversity, CogSci 2022
Country/TerritoryCanada
CityHybrid, Toronto
Period07/27/2207/30/22

Keywords

  • aging
  • cognition
  • perceptual learning
  • speech perception
  • statistical learning
  • working memory

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