Differences in speech processing among elderly hearing-impaired listeners with or without hearing aid experience: Eye-tracking and fMRI measurements

Authors

  • Julia Habicht Medizinische Physik and Cluster of Excellence “Hearing4all”, Oldenburg University, Oldenburg, Germany
  • Oliver Behler Medizinische Physik and Cluster of Excellence “Hearing4all”, Oldenburg University, Oldenburg, Germany
  • Birger Kollmeier Medizinische Physik and Cluster of Excellence “Hearing4all”, Oldenburg University, Oldenburg, Germany
  • Tobias Neher Medizinische Physik and Cluster of Excellence “Hearing4all”, Oldenburg University, Oldenburg, Germany; Institute of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark

Keywords:

Hearing loss, hearing aids, plasticity, speech comprehension, eye-tracking, fMRI

Abstract

In contrast to the effects of hearing loss, the effects of hearing aid (HA) experience on speech-in-noise (SIN) processing are underexplored. Using an eye-tracking paradigm that allows determining how fast a participant can grasp the meaning of a sentence presented in noise together with two pictures that correctly or incorrectly depict the sentence meaning (the ‘processing time’), Habicht et al. (2016, 2017) found that inexperienced HA (iHA) users were slower than experienced HA (eHA) users, despite no differences in speech recognition. To examine the influence of HA use on SIN processing further, the eye-tracking paradigm was adapted for functional magnetic resonance imaging (fMRI) measurements. Groups of eHA (N = 13) and iHA (N = 14) users matched in terms of age, hearing loss and working memory capacity participated. As before, despite no difference in speech recognition, the iHA group had longer processing times than the eHA group. Furthermore, the iHA group showed more brain activation for SIN relative to noise-only stimuli in left precentral gyrus, cerebellum anterior lobe, superior temporal gyrus and right medial frontal gyrus compared to the eHA group. Together, these results support the idea that HA experience positively influences the ability to process SIN quickly and that it reduces the recruitment of brain regions outside the core speech-comprehension network.

References

Adank, P. (2012). “Design choices in imaging speech comprehension: an activation likelihood estimation (ALE) meta-analysis,” Neuroimage, 63, 1601-1613.

Byrne, D., Dillon, H., Ching, T., Katsch, R., and Keidser, G. (2001). “NAL-NL1 procedure for fitting nonlinear hearing aids: characteristics and comparisons with other procedures,” J. Am. Acad. Audiol., 12, 37-51.

Carroll, R., Meis, M., Schulte, M., Vormann, M., Kießling, J., and Meister, H. (2015). “Development of a German reading span test with dual task design for application in cognitive hearing research,” Int. J. Audiol., 54,136-141.

Friederici, A.D., Fiebach, C.J., Schlesewsky, M., Bornkessel, I.D., and Von Cramon, D.Y. (2006). “Processing linguistic complexity and grammaticality in the left frontal cortex,” Cerebral Cortex, 16, 1709-1717.

Grimm, G., Herzke, T., Berg, D., and Hohmann, V. (2006). “The master hearing aid: a PC-based platform for algorithm development and evaluation,” Acta Acust. United Ac., 92, 618-628.

Habicht, J., Kollmeier, B., and Neher, T. (2016). “Are experienced hearing aid users faster at grasping the meaning of a sentence than inexperienced users? An eye-tracking study,” Trends Hear., 20. doi: 10.1177/2331216516660966

Habicht, J., Finke, M., and Neher, T. (2017). “Auditory acclimatization to bilateral hearing aids: Effects on sentence-in-noise processing times and speech-evoked potentials,” Ear Hearing. doi: 10.1097/AUD.0000000000000476

Lee, Y.-S., Min, N.E., Wingfield, A., Grossman, M., and Peelle, J.E. (2016). “Acoustic richness modulates the neural networks supporting intelligible speech processing,” Hear. Res., 333, 108-117.

Peelle, J.E., Troiani, V., Wingfield, A., and Grossman, M. (2009). “Neural processing during older adults’ comprehension of spoken sentences: age differences in resource allocation and connectivity,” Cereb. Cortex, 20, 773-782.

Peelle, J.E., and Wingfield, A. (2016). “The neural consequences of age-related hearing loss,” Trends Neurosci., 39, 486-497.

Rodd, J.M., Davis, M.H., and Johnsrude, I.S. (2005). “The neural mechanisms of speech comprehension: fMRI studies of semantic ambiguity,” Cereb. Cortex, 15, 1261-1269.

Sandmann, P., Plotz, K., Hauthal, N., de Vos, M., Schönfeld, R., and Debener, S. (2015). “Rapid bilateral improvement in auditory cortex activity in postlingually deafened adults following cochlear implantation,” Clin. Neurophysiol., 126, 594-607.

Uslar, V.N., Carroll, R., Hanke, M., Hamann, C., Ruigendijk, E., Brand, T., and Kollmeier, B. (2013). “Development and evaluation of a linguistically and audiologically controlled sentence intelligibility test,” J. Acoust. Soc. Am., 134, 3039-3056.

Wendt, D., Brand, T., and Kollmeier, B. (2014). “An eye-tracking paradigm for analyzing the processing time of sentences with different linguistic complexities,” PLoS ONE, 9, e100186.

Additional Files

Published

2017-12-11

How to Cite

Habicht, J., Behler, O., Kollmeier, B., & Neher, T. (2017). Differences in speech processing among elderly hearing-impaired listeners with or without hearing aid experience: Eye-tracking and fMRI measurements. Proceedings of the International Symposium on Auditory and Audiological Research, 6, 287–294. Retrieved from https://proceedings.isaar.eu/index.php/isaarproc/article/view/2017-35

Issue

Section

2017/5. Speech perception: Behavioral measures and modelling