Identification of the neurophysiological basis of central tinnitus
Final Report Abstract
In this project, we analyzed spatio-temporal activity patterns in auditory cortex (AC) during the development of central tinnitus in our animal model. We could confirm our hypothesis that neuronal activity reflecting tinnitus is characterized by attractor-like spatiotemporal activity patterns within AC. To do so, we advanced our new statistical approach for the analysis and visualization of high-dimensional data from multichannel cortical recordings of local field potentials (LFPs), which allowed for a statistical quantification of dissimilarity between different activity patterns in AC. Using these statistics we were able to demonstrate that neuronal attractors are specific for the perceptual quality of the percept. Therefore, during the development of subjective tinnitus, the neuronal attractor that can be measured in the absence of sound stimulation becomes similar to that of the corresponding stimulus driven activity that leads to a similar perceptual quality as the tinnitus. In another part of the project we successfully cross-validated the behavioral paradigm for the assessment of tinnitus in our animal model, the gap-prepulse inhibition of the acoustic startle reflex (GPIAS), by introducing a new, conditioning-based shuttle-box paradigm that uses a comparable gap-detection configuration. In addition to our original work plan, we advanced the GPIAS paradigm in order to standardize the statistical analysis across laboratories. Furthermore, in order to achieve a deeper understanding of the neuronal dynamics underlying the cortical attractor dynamics we have started to simulate artificial neuronal networks that finally shall model the processing in AC. A first step towards this goal was the analysis of the dynamics of very small neuronal ensembles, so-called three-neuron motifs. The results of this analysis will serve as a toolbox and starting point for future, more complex computational modelling of neuronal processing. We also further developed our computational model of tinnitus development, and implemented a simulation of the auditory pathway based on deep neural networks trained on speech recognition. Here we could show that intrinsic noise after simulated hearing loss improves the accuracy for speech recognition by means of stochastic resonance as proposed by our previously existing model. Finally, we could demonstrate that the explanatory power of our model even extends to another auditory phantom percept, the Zwicker tone illusion, and resdial inhibition phenomena.
Publications
- (2017). A new statistical approach for the evaluation of gap-prepulse inhibition of the acoustic startle reflex (GPIAS) for tinnitus assessment. Frontiers in Behavioral Neuroscience
Schilling, A., Krauss, P., Gerum, R., Metzner, C., Tziridis, K., & Schulze, H.
(See online at https://doi.org/10.3389/fnbeh.2017.00198) - (2018). A statistical method for analyzing and comparing spatiotemporal cortical activation patterns. Scientific Reports
Krauss, P., Metzner, C., Schilling, A., Tziridis, K., Traxdorf M., Wollbrink, A., Rampp, S., Pantev, C., & Schulze, H.
(See online at https://doi.org/10.1038/s41598-018-23765-w) - (2018). Cross-modal stochastic resonance as a universal principle to enhance sensory processing. Frontiers in Neuroscience, 12:578, 2018
Krauss, P., Tziridis, K., Schilling, A., & Schulze, H.
(See online at https://doi.org/10.3389/fnins.2018.00578) - (2018). How deep is deep enough? Quantifying class separability in the hidden layers of deep neural networks
Schilling, A., Metzner, C., Rietsch, J., Gerum, R., Schulze, H., & Krauss, P.
(See online at https://doi.org/10.48550/arXiv.1811.01753) - (2019) Analysis of structure and dynamics in three-neuron motifs. Frontiers in Computational Neuroscience
Krauss, P., Zankl, A., Schilling, A., Schulze, H. & Metzner, C.
(See online at https://doi.org/10.3389/fncom.2019.00005) - (2019) Das Fiepen im Rauschen. Gehirn & Geist, 8:66-71
Krauss, P., Schulze, H.
- (2019) Objective estimation of sensory thresholds based on neurophysiological parameters. Front. Neurosci. 13:481
Schilling, A.; Gerum, R.C.; Krauss, P.; Metzner, C.; Tziridis, K.; Schulze, H.
(See online at https://doi.org/10.3389/fnins.2019.00481) - (2019) Open(G)PIAS: An open-source solution for the construction of a high-precision Acoustic-Startle-Response setup for tinnitus screening and threshold estimation in rodents. Front. Behav. Neurosci. 13:140
Gerum, R.; Rahlfs, H.; Streb, M.; Krauss, P.; Grimm, J.; Metzner, C.; Tziridis, K.; Günther, M.; Schulze, H.; Kellermann, W.; Schilling, A.
(See online at https://doi.org/10.3389/fnbeh.2019.00140) - (2019) Weight statistics controls dynamics in recurrent neural networks. PLoS ONE, 14(4): e0214541
Krauss, P.; Schuster, M.; Dietrich, V.; Schilling, A.; Schulze, H.; Metzner, C.
(See online at https://doi.org/10.1371/journal.pone.0214541) - (2021) Acute and long-term circuit-level effects in the auditory cortex after sound trauma. Front. Neurosci. 14:598406
Jeschke, M.; Happel, M.F.K., Tziridis, K., Krauss, P., Schilling, A., Schulze, H., Ohl, F.W.
(See online at https://doi.org/10.3389/fnins.2020.598406) - The stochastic resonance model of auditory perception: A unified explanation of tinnitus development, Zwicker tone illusion, and residual inhibition. Progress in Brain Research. 2021. ISSN 0079-6123
Achim Schilling, Konstantin Tziridis, Holger Schulze, Patrick Krauss
(See online at https://doi.org/10.1016/bs.pbr.2021.01.025)
