Neural network models of tinnitus

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this chapter we review the relatively recent effort on the part of neuroscientists to use computational neural network modeling to investigate the neural basis of subjective tinnitus. There are advantages and challenges in using a modeling framework to understand this complex auditory disorder. The foremost challenge to modeling a subjective condition such as tinnitus is the evaluation of the occurrence of tinnitus in the model. We propose comparing measures of the model's activities (simulated neuronal activity, behavioral activity, or neuroimaging activity) with experimental data obtained from studies of tinnitus in humans and animals; strong agreement with experimental data will provide support for the validity of the simulation of tinnitus in a particular model. A major advantage of neural network modeling is that it allows experimentation not possible in animals. Models make it possible to evaluate the contribution of different neural mechanisms affecting tinnitus in a principled manner. A model makes predictions that can be tested by experiments thus leading to the designing of focused experiments. We review several neural models of tinnitus and discuss published findings from simulations using these models. We conclude with a proposed scheme for investigating tinnitus that combines neural network modeling with brain imaging experiments.

Original languageEnglish (US)
Title of host publicationTinnitus
Subtitle of host publicationPathophysiology and Treatment
EditorsB. Langguth, G. Hajak, T. Kleinjung, A. Cacace, A.R. Moller
Pages125-140
Number of pages16
DOIs
StatePublished - Oct 24 2007
Externally publishedYes

Publication series

NameProgress in Brain Research
Volume166
ISSN (Print)0079-6123

Keywords

  • auditory
  • cerebral cortex
  • electrophysiological
  • fMRI
  • neuroimaging
  • thalamus

ASJC Scopus subject areas

  • Neuroscience(all)

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