Abstract
Tinnitus is the phantom perception of sound, experienced by 10%-15% of the global population. Computational models have been used to investigate the mechanisms underlying the generation of tinnitus-related activity. However, existing computational models have rarely benchmarked the modeled perception of a phantom sound against recorded data relating to a person's perception of tinnitus characteristics, such as pitch or loudness. This article details the development of two perceptual models of tinnitus. The models are validated using empirical data from people with tinnitus and the models' performance is compared with the existing perceptual models of tinnitus pitch. The first model extends existing perceptual models of tinnitus, while the second model utilizes an entirely novel approach to modeling tinnitus perception using a linear mixed effects (LMEs) model. The LME model is also used to model the perceived loudness of the phantom sound which has not been considered in previous models. The LME model creates an accurate model of tinnitus pitch and loudness and shows that both tinnitus-related activity and individual perception of sound are factors in the perception of the phantom sound that characterizes tinnitus.
Original language | English |
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Article number | 8952682 |
Pages (from-to) | 332-343 |
Number of pages | 12 |
Journal | IEEE Transactions on Cognitive and Developmental Systems |
Volume | 12 |
Issue number | 2 |
Early online date | 8 Jan 2020 |
DOIs | |
Publication status | Published (in print/issue) - 10 Jun 2020 |
Keywords
- Linear mixed effects (lmes) model
- Perceptual model
- Tinnitus
- Tinnitus loudness
- Tinnitus pitch
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Martin Mc Ginnity
- School of Computing, Eng & Intel. Sys - Professor of Intelligent Systems
- Faculty Of Computing, Eng. & Built Env. - Full Professor
Person: Academic