Abnormalities in central auditory maturation in children with language-based learning problems

Phillip M. Gilley, Anu Sharma, Michael Dorman, Kathryn Martin

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

Objective: To examine maturation of the central auditory pathways in children with language-based learning problems (LP). Methods: Cortical auditory evoked potentials (CAEPs) recorded from 26 children with LP were compared to CAEPs recorded from 38 typical children. CAEP responses were recorded in response to a speech sound, /uh/, which was presented in a stimulus train with decreasing inter-stimulus intervals (ISIs) of 2000, 1000, 560, and 360 ms. Results: We identified three atypical morphological categories of CAEP responses in the LP group. Category 1 responses revealed delayed P1 latencies and absent N1/P2 components. Category 2 responses revealed typical P1 responses, but delayed N1 and P2 responses. Category 3 responses revealed generally low-amplitude CAEP responses. A fourth sub-group of LP children had normal CAEP responses. Conclusions: Overall, the majority of children with LP had abnormal CAEP responses. These children fell into distinct categories based on the abnormalities in maturational patterns of their CAEP responses. Significance: We describe a rate sensitive stimulation paradigm which may be used to identify and categorize LP children who exhibit abnormal patterns of central auditory maturation.

Original languageEnglish (US)
Pages (from-to)1949-1956
Number of pages8
JournalClinical Neurophysiology
Volume117
Issue number9
DOIs
StatePublished - Sep 2006

Keywords

  • Auditory processing deficits
  • Cortical auditory evoked potential (CAEP)
  • Language impaired
  • Learning impaired
  • N1
  • P1
  • P2
  • Stimulation rate

ASJC Scopus subject areas

  • Sensory Systems
  • Neurology
  • Clinical Neurology
  • Physiology (medical)

Fingerprint

Dive into the research topics of 'Abnormalities in central auditory maturation in children with language-based learning problems'. Together they form a unique fingerprint.

Cite this