The auditory brainstem is a barometer of rapid auditory learning

E. Skoe, J. Krizman, E. Spitzer, N. Kraus*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

64 Scopus citations

Abstract

To capture patterns in the environment, neurons in the auditory brainstem rapidly alter their firing based on the statistical properties of the soundscape. How this neural sensitivity relates to behavior is unclear. We tackled this question by combining neural and behavioral measures of statistical learning, a general-purpose learning mechanism governing many complex behaviors including language acquisition. We recorded complex auditory brainstem responses (cABRs) while human adults implicitly learned to segment patterns embedded in an uninterrupted sound sequence based on their statistical characteristics. The brainstem's sensitivity to statistical structure was measured as the change in the cABR between a patterned and a pseudo-randomized sequence composed from the same set of sounds but differing in their sound-to-sound probabilities. Using this methodology, we provide the first demonstration that behavioral-indices of rapid learning relate to individual differences in brainstem physiology. We found that neural sensitivity to statistical structure manifested along a continuum, from adaptation to enhancement, where cABR enhancement (patterned. pseudo-random) tracked with greater rapid statistical learning than adaptation. Short- and long-term auditory experiences (days to years) are known to promote brainstem plasticity and here we provide a conceptual advance by showing that the brainstem is also integral to rapid learning occurring over minutes.

Original languageEnglish (US)
Pages (from-to)104-114
Number of pages11
JournalNeuroscience
Volume243
DOIs
StatePublished - Jul 23 2013

Funding

Supported by NSF-0842376 and the Knowles Hearing Center at Northwestern University. We extend our thanks to Beverly Wright for her discussion of the data and Scott Miller for sharing his stimuli. We also thank Trent Nicol, Travis White-Schwoch, Samira Anderson, and Kali Woodruff for their comments on an earlier draft of the manuscript.

Keywords

  • Auditory
  • Brainstem
  • Statistical learning

ASJC Scopus subject areas

  • General Neuroscience

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