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Review article: Structural brain alterations in prelingually deaf.

Manja Hribar1, Dušan Šuput2, Saba Battelino3

  • 1Center for Clinical Physiology, Faculty of Medicine, University of Ljubljana, Slovenia; Clinic for Otorhinolaryngology and Cervicofacial Surgery, University Medical Centre Ljubljana, Slovenia; Department of Otorhinolaryngology, Faculty of Medicine, University of Ljubljana, Slovenia.

Neuroimage
|June 14, 2020
PubMed
Summary

Congenital deafness leads to significant brain structural changes, particularly in auditory white matter. These alterations are primarily driven by cross-modal plasticity and the use of sign language.

Keywords:
BrainHearing lossPlasticityPrelingually deafStructure

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Area of Science:

  • Neuroscience
  • Neuroimaging
  • Auditory Neuroscience

Background:

  • The brain exhibits remarkable neuroplasticity, reorganizing in response to sensory deprivation.
  • Congenital deafness presents a unique model for studying brain adaptation without auditory input.

Purpose of the Study:

  • To review and synthesize findings on structural brain alterations in individuals with congenital deafness.
  • To identify common patterns and regions affected by the absence of hearing.

Main Methods:

  • Systematic review of studies investigating structural changes in the brains of congenitally deaf subjects.
  • Analysis of findings from whole-brain and region-of-interest investigations.

Main Results:

  • Predominant structural alterations observed in auditory white matter, especially in the right hemisphere.
  • Common findings include reduced white matter volume and fractional anisotropy in auditory areas.
  • Limited alterations noted in auditory grey matter, possibly due to cross-modal plasticity or methodological sensitivity.

Conclusions:

  • Structural brain alterations in congenital deafness are significant and widespread, extending beyond auditory regions.
  • Cross-modal plasticity, driven by the absence of sound and use of sign language, is the likely primary cause.
  • Preservation of grey matter may indicate compensatory mechanisms or limitations in current neuroimaging techniques.