SpringerLink
Log in

Tinnitus: A Dimensionally Segregated, yet Perceptually Integrated Heterogeneous Disorder

  • Database Studies
  • Published:
Journal of the Association for Research in Otolaryngology Aims and scope Submit manuscript

    We’re sorry, something doesn't seem to be working properly.

    Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

Abstract

Objectives

Tinnitus subtypes are proposed to lie on a continuum of different symptom dimensions rather than be categorical. However, there is no comprehensive empirical data showing this complex relationship between different tinnitus symptoms. The objective of this study is to provide empirical evidence for the dimensional nature of tinnitus and how different auditory and non-auditory symptoms interact with each other through complex interactions. We do this using graph theory, a mathematical tool that empirically maps this complex interaction. This way, graph theory can be utilised to highlight a new and possibly important outlook on how we can understand the heterogeneous nature of tinnitus.

Design

In the current study, we use the screening databases of the Treatment Evaluation of Neuromodulation for Tinnitus-Stage A1 (TENT-A1) and A2 (TENT-A2) randomised trials to delineate the dimensional relationship between different clinical measures of tinnitus as a secondary data analysis. We first calculate the empirical relationship by computing the partial correlation. Following this, we use different measures of centrality to describe the contribution of different clinical measures to the overall network. We also calculate the stability of the network and compare the similarity and differences between TENT-A1 and TENT-A2.

Results

Components of the auditory subnetwork (loudness discomfort level, sound sensitivity, average hearing loss and high frequency hearing loss) are highly inter-connected in both networks with sound sensitivity and loudness discomfort level being highly influential with high measures of centrality. Furthermore, the relationship between the densely connected auditory subnetwork with tinnitus-related distress seems to vary at different levels of distress, hearing loss, duration and age of the participants.

Conclusion

Our findings provide first-time evidence for tinnitus varying in a dimensional fashion illustrating the heterogeneity of this phantom percept and its ability to be perceptually integrated, yet behaviourally segregated on different symptomatic dimensions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Germany)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. McCormack A et al (2016) A systematic review of the reporting of tinnitus prevalence and severity. Hear Res 337:70–79

    Article  PubMed  Google Scholar 

  2. Nondahl DM et al (2012) Generational differences in the reporting of tinnitus. Ear Hear 33(5):640

    Article  PubMed  PubMed Central  Google Scholar 

  3. Martinez C et al (2015) Incidence rates of clinically significant tinnitus: 10-year trend from a cohort study in England. Ear Hear 36(3):e69

    Article  PubMed  PubMed Central  Google Scholar 

  4. Zeman F et al (2014) Which tinnitus-related aspects are relevant for quality of life and depression: results from a large international multicentre sample. Health Qual Life Outcomes 12(1):7

    Article  PubMed  PubMed Central  Google Scholar 

  5. Wang TC et al (2020) Noise induced hearing loss and tinnitus-new research developments and remaining gaps in disease assessment, treatment, and prevention. Brain Sci 10(10)

  6. Song Z et al (2021) Tinnitus is associated with extended high-frequency hearing loss and hidden high-frequency damage in young patients. Otol Neurotol 42(3):377–383

    Article  PubMed  Google Scholar 

  7. Ren J et al (2021) Prevalence of hyperacusis in the general and special populations: a sco** review. Front Neurol 12:706555

    Article  PubMed  PubMed Central  Google Scholar 

  8. Andersson G et al (2002) Hypersensitivity to sound (hyperacusis): a prevalence study conducted via the internet and post: Hipersensibilidad al sonido (hiperacusia): un estudio de prevalencia realizado por internet y por correo. Int J Audiol 41(8):545–554

    Article  PubMed  Google Scholar 

  9. Vanneste S, Alsalman O, De Ridder D (2019) Top-down and bottom-up regulated auditory phantom perception. J Neurosci 39(2):364–378

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Vanneste S, De Ridder D (2016) Deafferentation-based pathophysiological differences in phantom sound: tinnitus with and without hearing loss. Neuroimage 129:80–94

    Article  PubMed  Google Scholar 

  11. Vanneste S et al (2010) The neural correlates of tinnitus-related distress. Neuroimage 52(2):470–480

    Article  PubMed  Google Scholar 

  12. Beukes EW et al (2021) Exploring tinnitus heterogeneity. Prog Brain Res 260:79–99

    Article  PubMed  Google Scholar 

  13. Genitsaridi E et al (2020) A review and a framework of variables for defining and characterizing tinnitus subphenotypes. Brain Sci 10(12):938

    Article  PubMed  PubMed Central  Google Scholar 

  14. Cederroth CR et al (2019) Editorial: towards an understanding of tinnitus heterogeneity. Front Aging Neurosci 11:53

    Article  PubMed  PubMed Central  Google Scholar 

  15. Mohan A et al (2022) Symptom dimensions to address heterogeneity in tinnitus. Neurosci Biobehav Rev 134:104542

    Article  PubMed  Google Scholar 

  16. Searchfield GD (2023) Specialty grand challenge: smarter solutions for tinnitus. Frontiers in Audiology and Otology 1:1101233

    Article  Google Scholar 

  17. Santacruz JL, De Kleine E, Van Dijk P (2021) Investigating the relation between minimum masking levels and hearing thresholds for tinnitus subty**. Prog Brain Res 263:81–94

    Article  PubMed  Google Scholar 

  18. Rodebaugh TL et al (2023) Investigating individual variation using dynamic structural equation modeling: a tutorial with tinnitus. Clin Psychol Sci 11(3):574–591

    Article  PubMed  Google Scholar 

  19. Riha C et al (2020) Accounting for heterogeneity: mixed-effects models in resting-state EEG data in a sample of tinnitus sufferers. Brain Topogr 33:413–424

    Article  PubMed  PubMed Central  Google Scholar 

  20. Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52(3):1059–1069

    Article  PubMed  Google Scholar 

  21. Jones PJ et al (2018) A network perspective on comorbid depression in adolescents with obsessive-compulsive disorder. J Anxiety Disord 53:1–8

    Article  PubMed  Google Scholar 

  22. Vainik U et al (2019) Obesity has limited behavioural overlap with addiction and psychiatric phenotypes. Nat Hum Behav 4:27–35

  23. Mohan A, De Ridder D, Vanneste S (2017) Robustness and dynamicity of functional networks in phantom sound. Neuroimage 146:171–187

    Article  PubMed  Google Scholar 

  24. Trevis KJ et al (2017) Identification of a neurocognitive mechanism underpinning awareness of chronic tinnitus. Sci Rep 7(1):15220

    Article  PubMed  PubMed Central  Google Scholar 

  25. Tyler R et al (2008) Identifying tinnitus subgroups with cluster analysis. Am J Audiol 17(2):S176–S184

  26. van den Berge MJ et al (2017) Cluster analysis to identify possible subgroups in tinnitus patients. Front Neurol 8:115

    PubMed  PubMed Central  Google Scholar 

  27. D’Arcy S et al (2017) Bi-modal stimulation in the treatment of tinnitus: a study protocol for an exploratory trial to optimise stimulation parameters and patient subty**. BMJ Open 7(10):e018465

    Article  PubMed  PubMed Central  Google Scholar 

  28. Conlon B et al (2020) Bimodal neuromodulation combining sound and tongue stimulation reduces tinnitus symptoms in a large randomized clinical study. Sci Transl Med 12(564):eabb2830

  29. Conlon B et al (2019) Noninvasive bimodal neuromodulation for the treatment of tinnitus: protocol for a second large-scale double-blind randomized clinical trial to optimize stimulation parameters. JMIR Research Protocols 8(9):e13176

    Article  PubMed  PubMed Central  Google Scholar 

  30. Conlon B et al (2022) Different bimodal neuromodulation settings reduce tinnitus symptoms in a large randomized trial. Sci Rep 12(1):10845

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Newman CW, Sandridge SA, Jacobson GP (1998) Psychometric adequacy of the tinnitus handicap inventory (THI) for evaluating treatment outcome. J Am Acad Audiol 9:153–160

    CAS  Google Scholar 

  32. Henry JA et al (2016) Tinnitus functional index: development, validation, outcomes research, and clinical application. Hear Res 334:58–64

    Article  PubMed  Google Scholar 

  33. Vidal JL et al (2022) Measurement of loudness discomfort levels as a test for hyperacusis: test-retest reliability and its clinical value. Clin Exp Otorhinolaryngol 15(1):84–90

    Article  PubMed  PubMed Central  Google Scholar 

  34. Robinaugh DJ, Millner AJ, McNally RJ (2016) Identifying highly influential nodes in the complicated grief network. J Abnorm Psychol 125(6):747

    Article  PubMed  PubMed Central  Google Scholar 

  35. Peng J et al (2009) Partial correlation estimation by joint sparse regression models. J Am Stat Assoc 104(486):735–746

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Shannon P et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13(11):2498–2504

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Scholz M (2010) Node similarity as a basic principle behind connectivity in complex networks. ar**v preprint https://arxiv.org/abs/1010.0803

  38. Epskamp S, Borsboom D, Fried EI (2018) Estimating psychological networks and their accuracy: a tutorial paper. Behav Res Methods 50(1):195–212

    Article  PubMed  Google Scholar 

  39. Epskamp S, Fried EI (2018) A tutorial on regularized partial correlation networks. Psychol Methods 23(4):617–634

    Article  PubMed  Google Scholar 

  40. McNally RJ (2021) Network analysis of psychopathology: controversies and challenges. Annu Rev Clin Psychol 17:31–53

    Article  PubMed  Google Scholar 

  41. van Borkulo CD et al (2022) Comparing network structures on three aspects: a permutation test. Psychol Methods 26(6):1273–1285

  42. Gay NG et al (2020) Posttraumatic stress disorder symptom network structures: a comparison between men and women. J Trauma Stress 33(1):96–105

    Article  PubMed  Google Scholar 

  43. Hevey D (2018) Network analysis: a brief overview and tutorial. Health Psychol Behav Med 6(1):301–328

    Article  PubMed  PubMed Central  Google Scholar 

  44. Borsboom D et al (2021) Network analysis of multivariate data in psychological science. Nat Rev Methods Primers 1(1)

  45. Herráiz C et al (2003) Study of hyperacusis at a tinnitus unit. Acta Otorrinolaringologica Espanola 54(9):617–622

    Article  PubMed  Google Scholar 

  46. Cederroth CR et al (2020) Association between hyperacusis and tinnitus. J Clin Med 9(8)

  47. Baguley DM et al (2013) Troublesome tinnitus in childhood and adolescence: data from expert centres. Int J Pediatr Otorhinolaryngol 77(2):248–251

    Article  PubMed  Google Scholar 

  48. Sedley W et al (2016) An integrative tinnitus model based on sensory precision. Trends Neurosci 39(12):799–812

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Mohan A et al (2017) Evidence for behaviorally segregated, spatiotemporally overlap** subnetworks in phantom sound perception. Brain Connectivity 7(3):197–210

    Article  PubMed  Google Scholar 

  50. Vanneste S, Congedo M, De Ridder D (2014) Pinpointing a highly specific pathological functional connection that turns phantom sound into distress. Cereb Cortex 24(9):2268–2282

    Article  PubMed  Google Scholar 

  51. Schaette R, McAlpine D (2011) Tinnitus with a normal audiogram: physiological evidence for hidden hearing loss and computational model. J Neurosci 31(38):13452–13457

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. **ong B et al (2019) Missed hearing loss in tinnitus patients with normal audiograms. Hear Res 384:107826

    Article  PubMed  Google Scholar 

  53. González-Rodríguez G, Colubi A, Gil MÁ (2006) A fuzzy representation of random variables: an operational tool in exploratory analysis and hypothesis testing. Comput Stat Data Anal 51(1):163–176

    Article  Google Scholar 

Download references

Funding

This work was sponsored by Neuromod Devices (Dublin, Ireland). The data was collected in two previous randomised clinical trials which investigated efficacy of a bimodal-stimulation device, Lenire® for the treatment of tinnitus.

Author information

Author notes

  1. Anusha Mohan and Katherine Adcock have shared first authorship of this article.

Authors and Affiliations

  1. Trinity Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland

    Anusha Yasoda-Mohan, Katherine Adcock & Sven Vanneste

  2. Neuromod Devices Limited, Dublin, D08 R2YP, Ireland

    Sook Ling Leong, Emma Meade & Hubert Lim

  3. Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, 93053, Germany

    Berthold Langguth

  4. Interdisciplinary Tinnitus Center of University of Regensburg, Regensburg, 93053, Germany

    Berthold Langguth & Martin Schecklmann

  5. Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, 55455, USA

    Hubert Lim

Authors
  1. Anusha Yasoda-Mohan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Katherine Adcock
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sook Ling Leong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Emma Meade
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Berthold Langguth
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Martin Schecklmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hubert Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Sven Vanneste
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sven Vanneste.

Ethics declarations

Competing Interests

SLL, EM and HL are employees of Neuromod Devices.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yasoda-Mohan, A., Adcock, K., Leong, S.L. et al. Tinnitus: A Dimensionally Segregated, yet Perceptually Integrated Heterogeneous Disorder. JARO 25, 215–227 (2024). https://doi.org/10.1007/s10162-023-00923-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10162-023-00923-0

Keywords

Search

Navigation