Activities per year
Abstract
Tinnitus is the phantom perception of sound, experiencedby 10-15% of the global population. Computationalmodels have been used to investigate the mechanisms underlyingthe generation of tinnitus-related activity. However, existingcomputational models have rarely benchmarked the modelledperception of a phantom sound against recorded data relating toa person’s perception of tinnitus characteristics; such as pitch orloudness. This paper details the development of two perceptualmodels of tinnitus. The models are validated using empiricaldata from people with tinnitus and the models’ performance is compared with existing perceptual models of tinnitus pitch. The first model extends existing perceptual models of tinnitus, while the second model utilises an entirely novel approach to modelling tinnitus perception using a Linear Mixed Effects (LME) 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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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 | 08 Jan 2020 |
DOIs | |
Publication status | Published - Jun 2020 |
Keywords
- tinnitus
- perceptual model
- linear mixed effects model
- tinnitus pitch
- tinnitus loudness
Fingerprint
Dive into the research topics of 'Perceptual Modeling of Tinnitus Pitch and Loudness'. Together they form a unique fingerprint.-
American Tinnitus Association (External organisation)
Gault, R. (Member)
17 Apr 2024 → …Activity: Membership types › Membership of peer review panel or committee
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How can computational models explore the underlying mechanisms behind the experimental data?
Gault, R. (Invited speaker)
07 Jun 2023Activity: Talk or presentation types › Invited talk
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The role of Computational modelling in a multidisciplinary area: Lessons from modelling Tinnitus
Gault, R. (Invited speaker)
21 Mar 2023Activity: Talk or presentation types › Invited talk
Research output
- 4 Citations
- 2 Article
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Feasibility of deep learning to predict tinnitus patient outcomes
Adcock, K. S., Byczynski, G., Meade, E., Ling Leong, S., Gault, R., Lim, H. & Vanneste, S., 25 May 2024, In: Intelligence-Based Medicine. 9, 8 p., 100141.Research output: Contribution to journal › Article › peer-review
Open AccessFile39 Downloads (Pure) -
A Computational Model of Thalamocortical Dysrhythmia in People With Tinnitus
Gault, R., McGinnity, T. M. & Coleman, S., Sept 2018, In: IEEE Transactions on Neural Systems and Rehabilitation Engineering. 26, 9, p. 1845-1857 13 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile9 Citations (Scopus)666 Downloads (Pure)