Recovering Hidden Responder Groups in Individuals Receiving Neurofeedback for Tinnitus
The widespread understanding that chronic tinnitus is a heterogeneous phenomenon with various neural oscillatory profiles has spurred investigations into individualized approaches in its treatment. Neurofeedback, as a non-invasive tool for altering neural activity, has become increasingly popular in...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-06-01
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| Series: | Frontiers in Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2022.867704/full |
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| author | Constanze Riha Constanze Riha Dominik Güntensperger Tobias Kleinjung Tobias Kleinjung Martin Meyer Martin Meyer Martin Meyer |
| author_facet | Constanze Riha Constanze Riha Dominik Güntensperger Tobias Kleinjung Tobias Kleinjung Martin Meyer Martin Meyer Martin Meyer |
| author_sort | Constanze Riha |
| collection | DOAJ |
| description | The widespread understanding that chronic tinnitus is a heterogeneous phenomenon with various neural oscillatory profiles has spurred investigations into individualized approaches in its treatment. Neurofeedback, as a non-invasive tool for altering neural activity, has become increasingly popular in the personalized treatment of a wide range of neuropsychological disorders. Despite the success of neurofeedback on the group level, the variability in the treatment efficacy on the individual level is high, and evidence from recent studies shows that only a small number of people can effectively modulate the desired aspects of neural activity. To reveal who may be more suitable, and hence benefit most from neurofeedback treatment, we classified individuals into unobserved subgroups with similar oscillatory trajectories during the treatment and investigated how subgroup membership was predicted by a series of characteristics. Growth mixture modeling was used to identify distinct latent subgroups with similar oscillatory trajectories among 50 individuals suffering from chronic subjective tinnitus (38 male, 12 female, mean age = 47.1 ± 12.84) across 15 neurofeedback training sessions. Further, the impact of characteristics and how they predicted the affiliation in the identified subgroups was evaluated by including measures of demographics, tinnitus-specific (Tinnitus Handicap Inventory) and depression variables, as well as subjective quality of life subscales (World Health Organization—Quality of Life Questionnaire), and health-related quality of life subscales (Short Form-36) in a logistic regression analysis. A latent class model could be fitted to the longitudinal data with a high probability of correctly classifying distinct oscillatory patterns into 3 different groups: non-responder (80%), responder (16%), and decliner (4%). Further, our results show that the health-related wellbeing subscale of the Short Form-36 questionnaire was differentially associated with the groups. However, due to the small sample size in the Responder group, we are not able to provide sufficient evidence for a distinct responder profile. Nevertheless, the identification of oscillatory change-rate differences across distinct groups of individuals provides the groundwork from which to tease apart the complex and heterogeneous oscillatory processes underlying tinnitus and the attempts to modify these through neurofeedback. While more research is needed, our results and the analytical approach presented may bring clarity to contradictory past findings in the field of tinnitus research, and eventually influence clinical practice. |
| first_indexed | 2024-04-13T16:55:23Z |
| format | Article |
| id | doaj.art-cf9c7ea3d23243c0b32757886a24a7ea |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-04-13T16:55:23Z |
| publishDate | 2022-06-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Neuroscience |
| spelling | doaj.art-cf9c7ea3d23243c0b32757886a24a7ea2022-12-22T02:38:50ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2022-06-011610.3389/fnins.2022.867704867704Recovering Hidden Responder Groups in Individuals Receiving Neurofeedback for TinnitusConstanze Riha0Constanze Riha1Dominik Güntensperger2Tobias Kleinjung3Tobias Kleinjung4Martin Meyer5Martin Meyer6Martin Meyer7Department of Psychology, University of Zurich, Zurich, SwitzerlandResearch Priority Program “ESIT—European School of Interdisciplinary Tinnitus Research,” Zurich, SwitzerlandDepartment of Psychology, University of Zurich, Zurich, SwitzerlandDepartment of Otorhinolaryngology, University Hospital Zurich, Zurich, SwitzerlandNeuroscience Center Zurich (ZNZ), ETH Zürich, Zurich, SwitzerlandDepartment of Psychology, University of Zurich, Zurich, SwitzerlandNeuroscience Center Zurich (ZNZ), ETH Zürich, Zurich, SwitzerlandUniversity Research Priority Program “Dynamics of Healthy Aging,” University of Zurich, Zurich, SwitzerlandThe widespread understanding that chronic tinnitus is a heterogeneous phenomenon with various neural oscillatory profiles has spurred investigations into individualized approaches in its treatment. Neurofeedback, as a non-invasive tool for altering neural activity, has become increasingly popular in the personalized treatment of a wide range of neuropsychological disorders. Despite the success of neurofeedback on the group level, the variability in the treatment efficacy on the individual level is high, and evidence from recent studies shows that only a small number of people can effectively modulate the desired aspects of neural activity. To reveal who may be more suitable, and hence benefit most from neurofeedback treatment, we classified individuals into unobserved subgroups with similar oscillatory trajectories during the treatment and investigated how subgroup membership was predicted by a series of characteristics. Growth mixture modeling was used to identify distinct latent subgroups with similar oscillatory trajectories among 50 individuals suffering from chronic subjective tinnitus (38 male, 12 female, mean age = 47.1 ± 12.84) across 15 neurofeedback training sessions. Further, the impact of characteristics and how they predicted the affiliation in the identified subgroups was evaluated by including measures of demographics, tinnitus-specific (Tinnitus Handicap Inventory) and depression variables, as well as subjective quality of life subscales (World Health Organization—Quality of Life Questionnaire), and health-related quality of life subscales (Short Form-36) in a logistic regression analysis. A latent class model could be fitted to the longitudinal data with a high probability of correctly classifying distinct oscillatory patterns into 3 different groups: non-responder (80%), responder (16%), and decliner (4%). Further, our results show that the health-related wellbeing subscale of the Short Form-36 questionnaire was differentially associated with the groups. However, due to the small sample size in the Responder group, we are not able to provide sufficient evidence for a distinct responder profile. Nevertheless, the identification of oscillatory change-rate differences across distinct groups of individuals provides the groundwork from which to tease apart the complex and heterogeneous oscillatory processes underlying tinnitus and the attempts to modify these through neurofeedback. While more research is needed, our results and the analytical approach presented may bring clarity to contradictory past findings in the field of tinnitus research, and eventually influence clinical practice.https://www.frontiersin.org/articles/10.3389/fnins.2022.867704/fulltinnitusneurofeedback (NFB)inefficacy problemEEGbrain computer interfacegrowth mixture model |
| spellingShingle | Constanze Riha Constanze Riha Dominik Güntensperger Tobias Kleinjung Tobias Kleinjung Martin Meyer Martin Meyer Martin Meyer Recovering Hidden Responder Groups in Individuals Receiving Neurofeedback for Tinnitus Frontiers in Neuroscience tinnitus neurofeedback (NFB) inefficacy problem EEG brain computer interface growth mixture model |
| title | Recovering Hidden Responder Groups in Individuals Receiving Neurofeedback for Tinnitus |
| title_full | Recovering Hidden Responder Groups in Individuals Receiving Neurofeedback for Tinnitus |
| title_fullStr | Recovering Hidden Responder Groups in Individuals Receiving Neurofeedback for Tinnitus |
| title_full_unstemmed | Recovering Hidden Responder Groups in Individuals Receiving Neurofeedback for Tinnitus |
| title_short | Recovering Hidden Responder Groups in Individuals Receiving Neurofeedback for Tinnitus |
| title_sort | recovering hidden responder groups in individuals receiving neurofeedback for tinnitus |
| topic | tinnitus neurofeedback (NFB) inefficacy problem EEG brain computer interface growth mixture model |
| url | https://www.frontiersin.org/articles/10.3389/fnins.2022.867704/full |
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