In advancing our understanding of tinnitus, some of the more impactful contributions in the past two decades have come from human brain imaging studies, specifically the idea of both auditory and extra-auditory neural networks that mediate tinnitus. These networks subserve both the perception of tinnitus and the psychological reaction to chronic, continuous tinnitus. In this article, we review particular studies that report on the nodes and links of such neural networks and their inter-network connections. Innovative neuroimaging tools have contributed significantly to the increased understanding of anatomical and functional connections of attention, emotion-processing, and default mode networks in adults with tinnitus. We differentiate between the neural correlates of tinnitus and those of comorbid hearing loss; surprisingly, tinnitus and hearing loss when they co-occur are not necessarily additive in their impact and, in rare cases, additional tinnitus may act to mitigate the consequences of hearing loss alone on the brain. The scale of tinnitus severity also appears to have an impact on brain networks, with some of the alterations typically attributed to tinnitus reaching significance only in the case of bothersome tinnitus. As we learn more about comorbid conditions of tinnitus, such as depression, anxiety, hyperacusis, or even aging, their contributions to the network-level changes observed in tinnitus will need to be parsed out in a manner similar to what is currently being done for hearing loss or severity. Together, such studies advance our understanding of the heterogeneity of tinnitus and will lead to individualized treatment plans.
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http://dx.doi.org/10.1007/s10162-023-00914-1 | DOI Listing |
Acta Bioeng Biomech
September 2024
Faculty of Computer Science, Kazimierz Wielki University, Bydgoszcz, Poland.
Monitoring and assessing the level of lower limb motor skills using the Biodex System plays an important role in the training of football players and in post-traumatic rehabilitation. The aim of this study was to build and test an artificial intelligence-based model to assess the peak torque of the lower limb extensors and flexors. The model was based on real-world results in three groups: hearing ( = 19) and deaf football players ( = 28) and non-training deaf pupils ( = 46).
View Article and Find Full Text PDFJ Acoust Soc Am
January 2025
Department of Biology, University of Aarhus, Aarhus, 8000, Denmark.
Gransier and Kastelein [J. Acoust. Soc.
View Article and Find Full Text PDFCNS Neurosci Ther
January 2025
Department of Otolaryngology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
Background: Sudden sensorineural hearing loss (SSNHL) is associated with abnormal changes in the brain's central nervous system. Previous studies on the brain networks of SSNHL have primarily focused on functional connectivity within the brain. However, in addition to functional connectivity, structural connectivity also plays a crucial role in brain networks.
View Article and Find Full Text PDFEar Hear
January 2025
McMaster Institute for Music and the Mind, McMaster University, Hamilton, Ontario, Canada.
Objectives: Live music creates a sense of connectedness in older adults, which can help alleviate the social isolation frequently associated with hearing loss and aging. However, most hearing-aid (HA) users are dissatisfied with the sound quality of live music and rate sound quality as important to them. Assistive listening systems are frequently independent of a user's HAs and fall short in tailoring to each individual's hearing loss.
View Article and Find Full Text PDFLaryngoscope
January 2025
Department of Otolaryngology-Head and Neck Surgery, NewYork-Presbyterian/Columbia University Irving Medical Center, Columbia University Vagelos College of Physicians and Surgeons, 180 Fort Washington Avenue, HP8, New York, New York, 10032, U.S.A.
Objectives: Hearing loss (HL) has significant implications on social functioning. Here, we study the relationship between HL, race, and these combined categories as risk factors for discrimination in the large national All of Us cohort.
Methods: The National Institutes of Health All of Us dataset was analyzed after including individuals who completed the Everyday Discrimination Survey between November 2021 and January 2022.
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