INTRODUCTION: Aging negatively influences the structure of the human brain including the white matter. The objective of our study was to identify, using fixel-based morphometry, the age induced changes in the pathways connecting several regions of the central auditory system (inferior colliculus, Heschl's gyrus, planum temporale) and the pathways connecting these structures with parts of the limbic system (anterior insula, hippocampus and amygdala). In addition, we were interested in the extent to which the integrity of these pathways is influenced by hearing loss and tinnitus. METHODS: Tractographic data were acquired using a 3 T MRI in 79 volunteers. The participants were categorized into multiple groups in accordance with their age, auditory thresholds and tinnitus status. Fixel-based analysis was utilized to identify alterations in the subsequent three parameters: logarithm of fiber cross-section, fiber density, fiber density and cross-section. Two modes of analysis were used: whole brain analysis and targeted analysis using fixel mask, corresponding to the pathways connecting the aforementioned structures. RESULTS: A significantly negative effect of aging was present for all fixel-based metrics, namely the logarithm of the fiber cross-section, (7 % fixels in whole-brain, 14% fixels in fixel mask), fiber density (5 % fixels in whole-brain, 15% fixels in fixel mask), fiber density and cross section (7 % fixels in whole-brain, 19% fixels in fixel mask). Expressed age-related losses, exceeding 30% fixels, were particularly present in pathways connecting the auditory structures with limbic structures. The effect of hearing loss and/or tinnitus did not reach significance. CONCLUSIONS: Our results show that although an age-related reduction of fibers is present in pathways connecting several auditory regions, the connections of these structures with limbic structures are even more reduced. To what extent this fact influences the symptoms of presbycusis, such as decreased speech comprehension, especially in noise conditions, remains to be elucidated.

Department of Auditory Neuroscience Institute of Experimental Medicine of the Czech Academy of Sciences Prague Czechia

Department of Otorhinolaryngology 3rd Faculty of Medicine Charles University Prague University Hospital Královské Vinohrady Prague Czechia

Department of Otorhinolaryngology and Head and Neck Surgery 1st Faculty of Medicine Charles University Prague University Hospital Motol Prague Czechia

Department of Radiodiagnostic and Interventional Radiology Institute of Clinical and Experimental Medicine Prague Czechia

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Aldhafeeri F. M., Mackenzie I., Kay T., Alghamdi J., Sluming V. (2012). Neuroanatomical correlates of tinnitus revealed by cortical thickness analysis and diffusion tensor imaging. Neuroradiology 54, 883–892. 10.1007/s00234-012-1044-6 PubMed DOI

Andersson J. L. R., Graham M. S., Drobnjak I., Zhang H., Filippini N., Bastiani M. (2017). Towards a comprehensive framework for movement and distortion correction of diffusion MR images: within volume movement. Neuroimage 152, 450–466. 10.1016/j.neuroimage.2017.02.085 PubMed DOI PMC

Andersson J. L. R., Graham M. S., Zsoldos E., Sotiropoulos S. N. (2016). Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images. Neuroimage 141, 556–572. 10.1016/j.neuroimage.2016.06.058 PubMed DOI

Andersson J. L. R., Skare S., Ashburner J. (2003). How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging. Neuroimage 20, 870–888. 10.1016/S1053-8119(03)00336-7 PubMed DOI

Andersson J. L. R., Sotiropoulos S. N. (2016). An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage 125, 1063–1078. 10.1016/j.neuroimage.2015.10.019 PubMed DOI PMC

Belkhiria C., Vergara R. C., San Martin S., Leiva A., Martinez M., Marcenaro B., et al. . (2020). Insula and amygdala atrophy are associated with functional impairment in subjects with presbycusis. Front. Aging Neurosci. 12, 102. 10.3389/fnagi.2020.00102 PubMed DOI PMC

Benson R. R., Gattu R., Cacace A. T. (2014). Left hemisphere fractional anisotropy increase in noise-induced tinnitus: a diffusion tensor imaging (DTI) study of white matter tracts in the brain. Hear Res. 309, 8–16. 10.1016/j.heares.2013.10.005 PubMed DOI

Chang Y., Lee S. H., Lee Y. J., Hwang M. J., Bae S. J., Kim M. N., et al. . (2004). Auditory neural pathway evaluation on sensorineural hearing loss using diffusion tensor imaging. Neuroreport 15, 1699–1703. 10.1097/01.wnr.0000134584.10207.1a PubMed DOI

Chen Q., Wang Z., Lv H., Zhao P., Yang Z., Gong S., et al. . (2020). Reorganization of brain white matter in persistent idiopathic tinnitus patients without hearing loss: evidence from baseline data. Front. Neurosci. 14:591. 10.3389/fnins.2020.00591 PubMed DOI PMC

Choy S. W., Bagarinao E., Watanabe H., Ho E. T. W., Maesawa S., Mori D., et al. . (2020). Changes in white matter fiber density and morphology across the adult lifespan: a cross-sectional fixel-based analysis. Hum. Brain Mapp. 41, 3198–3211. 10.1002/hbm.25008 PubMed DOI PMC

Cordero-Grande L., Christiaens D., Hutter J., Price A. N., Hajnal J. V. (2019). Complex diffusion-weighted image estimation via matrix recovery under general noise models. Neuroimage 200, 391–404. 10.1016/j.neuroimage.2019.06.039 PubMed DOI PMC

Crippa A., Lanting C. P., van Dijk P., Roerdink J. B. T. M. (2010). A diffusion tensor imaging study on the auditory system and tinnitus. Open Neuroimag. J. 4, 16–25. 10.2174/1874440001004010016 PubMed DOI PMC

De Ridder D., Vanneste S., Congedo M. (2011). The distressed brain: a group blind source separation analysis on tinnitus. PLoS ONE 6, e24273. 10.1371/journal.pone.0024273 PubMed DOI PMC

Dhollander T., Clemente A., Singh M., Boonstra F., Civier O., Duque J. D., et al. . (2021). Fixel-based analysis of diffusion MRI: methods, applications, challenges and opportunities. Neuroimage 241, 118417. 10.1016/j.neuroimage.2021.118417 PubMed DOI

Dhollander T., Raffelt D., Connelly A. (2016). Unsupervised 3-tissue response function estimation from single-shell or multi-shell diffusion MR data without a co-registered T1 image, in ISMRM Workshop on Breaking the Barriers of Diffusion MRI (Lisbon: ), p. 5.

Fischl B. (2012). FreeSurfer. Neuroimage 62, 774–781. 10.1016/j.neuroimage.2012.01.021 PubMed DOI PMC

Fischl B., van der Kouwe A., Destrieux C., Halgren E., Ségonne F., Salat D. H., et al. . (2004). Automatically parcellating the human cerebral cortex. Cereb. Cortex 14, 11–22. 10.1093/cercor/bhg087 PubMed DOI

Fuksa J., Profant O., Tintěra J., Svobodová V., Tóthová D., Škoch A., et al. . (2022). Functional changes in the auditory cortex and associated regions caused by different acoustic stimuli in patients with presbycusis and tinnitus. Front. Neurosci. 16:921873. 10.3389/fnins.2022.921873 PubMed DOI PMC

Holmes C. J., Hoge R., Collins L., Woods R., Toga A. W., Evans A. C. (1998). Enhancement of MR images using registration for signal averaging. J. Comput. Assist. Tomogr. 22, 324–333. 10.1097/00004728-199803000-00032 PubMed DOI

Husain F. T., Medina R. E., Davis C. W., Szymko-Bennett Y., Simonyan K., Pajor N. M., et al. . (2011). Neuroanatomical changes due to hearing loss and chronic tinnitus: a combined VBM and DTI study. Brain Res. 1369, 74–88. 10.1016/j.brainres.2010.10.095 PubMed DOI PMC

Iglesias J. E., Augustinack J. C., Nguyen K., Player C. M., Player A., Wright M., et al. . (2015). A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: application to adaptive segmentation of in vivo MRI. Neuroimage 115, 117–137. 10.1016/j.neuroimage.2015.04.042 PubMed DOI PMC

Jenkinson M., Beckmann C. F., Behrens T. E. J., Woolrich M. W., Smith S. M. (2012). FSL. Neuroimage 62, 782–790. 10.1016/j.neuroimage.2011.09.015 PubMed DOI

Jeurissen B., Tournier J. D., Dhollander T., Connelly A., Sijbers J. (2014). Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data. Neuroimage 103, 411–426. 10.1016/j.neuroimage.2014.07.061 PubMed DOI

Jilek M., Šuta D., Syka J. (2014). Reference hearing thresholds in an extended frequency range as a function of age. J. Acoust. Soc. Am. 136, 1821–1830. 10.1121/1.4894719 PubMed DOI

Kelley S., Plass J., Bender A. R., Polk T. A. (2021). Age-related differences in white matter: understanding tensor-based results using fixel-based analysis. Cereb. Cortex 31, 3881–3898. 10.1093/cercor/bhab056 PubMed DOI PMC

Kellner E., Dhital B., Kiselev V. G., Reisert M. (2016). Gibbs-ringing artifact removal based on local subvoxel-shifts. Magn. Reson. Med. 76, 1574–1581. 10.1002/mrm.26054 PubMed DOI

Koops E. A., Haykal S., van Dijk P. (2021). Macrostructural changes of the acoustic radiation in humans with hearing loss and tinnitus revealed with fixel-based analysis. J. Neurosci. 41, 3958–3965. 10.1523/JNEUROSCI.2996-20.2021 PubMed DOI PMC

Lin F. R., Ferrucci L., An Y., Goh J. O., Doshi J., Metter E. J., et al. . (2014). Association of hearing impairment with brain volume changes in older adults. Neuroimage 90, 84–92. 10.1016/j.neuroimage.2013.12.059 PubMed DOI PMC

Lin Y., Wang J., Wu C., Wai Y., Yu J., Ng S. (2008). Diffusion tensor imaging of the auditory pathway in sensorineural hearing loss: changes in radial diffusivity and diffusion anisotropy. J. Magnet. Reson. Imag. 28, 598–603. 10.1002/jmri.21464 PubMed DOI

Maudoux A., Lefebvre P., Cabay J. E., Demertzi A., Vanhaudenhuyse A., Laureys S., et al. . (2012). Connectivity graph analysis of the auditory resting state network in tinnitus. Brain Res. 1485, 10–21. 10.1016/j.brainres.2012.05.006 PubMed DOI

Newman C. W., Jacobson G. P., Spitzer J. B. (1996). Development of the tinnitus handicap inventory. Arch. Otolaryngol. Head Neck Surg. 122, 143–148. 10.1001/archotol.1996.01890140029007 PubMed DOI

Profant O., Škoch A., Balogová Z., Tintěra J., Hlinka J., Syka J. (2014). Diffusion tensor imaging and MR morphometry of the central auditory pathway and auditory cortex in aging. Neuroscience 260, 87–97. 10.1016/j.neuroscience.2013.12.010 PubMed DOI

Profant O., Škoch A., Tintěra J., Svobodová V., Kuchárová D., Svobodová Burianová J., et al. . (2020). The influence of aging, hearing, and tinnitus on the morphology of cortical gray matter, amygdala, and hippocampus. Front. Aging Neurosci. 12:553461. 10.3389/fnagi.2020.553461 PubMed DOI PMC

Puonti O., Iglesias J. E., Van Leemput K. (2016). Fast and sequence-adaptive whole-brain segmentation using parametric Bayesian modeling. Neuroimage 143, 235–249. 10.1016/j.neuroimage.2016.09.011 PubMed DOI PMC

Raffelt D. A., Smith R. E., Ridgway G. R., Tournier J. D., Vaughan D. N., Rose S., et al. . (2015). Connectivity-based fixel enhancement: whole-brain statistical analysis of diffusion MRI measures in the presence of crossing fibres. Neuroimage 117, 40–55. 10.1016/j.neuroimage.2015.05.039 PubMed DOI PMC

Raffelt D. A., Tournier J. D., Smith R. E., Vaughan D. N., Jackson G., Ridgway G. R., et al. . (2017). Investigating white matter fibre density and morphology using fixel-based analysis. Neuroimage 144, 58–73. 10.1016/j.neuroimage.2016.09.029 PubMed DOI PMC

Ren F., Ma W., Li M., Sun H., Xin Q., Zong W., et al. . (2018). Gray matter atrophy is associated with cognitive impairment in patients with presbycusis: a comprehensive morphometric study. Front. Neurosci. 12:744. 10.3389/fnins.2018.00744 PubMed DOI PMC

Saygin Z. M., Kliemann D., Iglesias J. E., van der Kouwe A. J. W., Boyd E., Reuter M., et al. . (2017). High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas. Neuroimage 155, 370–382. 10.1016/j.neuroimage.2017.04.046 PubMed DOI PMC

Smith R. E., Tournier J. D., Calamante F., Connelly A. (2012). Anatomically-constrained tractography: improved diffusion MRI streamlines tractography through effective use of anatomical information. Neuroimage 62, 1924–1938. 10.1016/j.neuroimage.2012.06.005 PubMed DOI

Smith S. M., Nichols T. E. (2009). Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage 44, 83–98. 10.1016/j.neuroimage.2008.03.061 PubMed DOI

Tournier J. D., Calamante F., Connelly A. (2007). Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution. Neuroimage 35, 1459–1472. 10.1016/j.neuroimage.2007.02.016 PubMed DOI

Tournier J. D., Smith R., Raffelt D., Tabbara R., Dhollander T., Pietsch M., et al. . (2019). MRtrix3: a fast, flexible and open software framework for medical image processing and visualisation. Neuroimage 202, 116137. 10.1016/j.neuroimage.2019.116137 PubMed DOI

Utianski R. L., Duffy J. R., Clark H. M., Machulda M. M., Dickson D. W., Whitwell J. L., et al. . (2019). Prominent auditory deficits in primary progressive aphasia: A case study. Cortex 117, 396–406. 10.1016/j.cortex.2019.01.021 PubMed DOI PMC

Veraart J., Novikov D. S., Christiaens D., Ades-Aron B., Sijbers J., Fieremans E. (2016). Denoising of diffusion MRI using random matrix theory. Neuroimage 142, 394–406. 10.1016/j.neuroimage.2016.08.016 PubMed DOI PMC

Winkler A. M., Ridgway G. R., Webster M. A., Smith S. M., Nichols T. E. (2014). Permutation inference for the general linear model. Neuroimage 92, 381–397. 10.1016/j.neuroimage.2014.01.060 PubMed DOI PMC

Yeend I., Beach E. F., Sharma M. (2019). Working memory and extended high-frequency hearing in adults: diagnostic predictors of speech-in-noise perception. Ear Hear 40, 458–467. 10.1097/AUD.0000000000000640 PubMed DOI

Yoo H. B., De Ridder D., Vanneste S. (2016). The importance of aging in gray matter changes within tinnitus patients shown in cortical thickness, surface area and volume. Brain Topogr. 29, 885–896. 10.1007/s10548-016-0511-5 PubMed DOI

Zivari Adab H., Chalavi S., Monteiro T. S., Gooijers J., Dhollander T., Mantini D., et al. . (2020). Fiber-specific variations in anterior transcallosal white matter structure contribute to age-related differences in motor performance. Neuroimage 209, 116530. 10.1016/j.neuroimage.2020.116530 PubMed DOI