Discussion
In this report, we have demonstrated that noise-induced tinnitus is associated with an increased ECM density in primary auditory cortex contralateral to the trauma side. This result may point to trauma induced neuroplastic changes in AC, where an ECM density increase may be an indication of tinnitus chronification.
The induction of a mild acoustic noise trauma – here monaurally – is a reliable method of inducing cortical plasticity (e.g., Jeschke et al. , 2021) and tinnitus-related behavioral changes in our rodent animal model (e.g., Grimm et al. , 2022; Kiefer et al. , 2022; Tziridis & Schulze, 2022). To ensure an objective analysis of the data, only automated and parameter-free evaluation methods were used (Schilling et al. , 2019) to rule out human evaluation bias (Zaitoun et al. , 2016). With a mean HL of nearly 10 dB in the exposed ear (12 dB in the most affected frequency of 2 kHz), the effect of the trauma applied here was comparably mild when compared to other studies (e.g., Tziridis & Schulze, 2022). This fact could also explain the relatively low percentage of animals with behavioral signs of tinnitus (4/9, 44%). These behavioral signs of tinnitus were determined with a well-established statistical method (Schilling et al. , 2017) but are no proof that the animals really perceive a human-like tinnitus percept (Eggermont, 2013). On the other hand, the animals with behavioral signs of tinnitus tend to show less hearing loss compared to animals without these behavioral signs. This is in line with reports of differences in human tinnitus patients compared to non-tinnitus patients with hearing loss (e.g., Gollnast et al. , 2017).
Nevertheless, we always combine the behavioral data of possible signs of tinnitus in our animal model with further physiological markers and often find correlations between the tinnitus status of the animals and those markers (e.g., Tziridis et al. , 2021), which indicates a causal connection between behavior and physiological changes. In this report, the further physiological marker is the density of the extracellular matrix of the primary auditory cortices of the animals.
The ECM itself occupies between 10% and 20% of the entire brain volume and plays an important role in genesis, plasticity and regeneration of the central nervous system (Chelyshev et al. , 2022). Furthermore, it is known that it plays a significant part in physiological as well as pathological conditions (Vargova & Sykova, 2014; Krishnaswamy et al. , 2019). The ECM can be divided into different subtypes: perineuronal nets and perisynaptic extracellular matrix (Chelyshevet al. , 2022). Specifically for Mongolian Gerbils it has been shown that the intact ECM in its entirety is important for the correct function of the cortical layer dynamics and cross-columnar frequency integration of the auditory cortex (El-Tabbal et al. , 2021) but its density modulation (i.e., removing it) can also be used for inducing neuronal plasticity and re-learning (Happel et al. , 2014).
With the knowledge of the ECM being that important for neuronal plasticity (or possibly mal-plasticity in the case of tinnitus), we investigated the ECM density of the auditory cortices of Mongolian gerbils 13 d after acoustic noise or sham exposure by using a specific ECM affine marker (WFA-FITC). This marker is a lectin that specifically binds to chondroitin sulfates and thus labels chondroitin sulfate proteoglycans within the ECM (Celio & Blumcke, 1994; Pizzorussoet al. , 2002). The fluorescence luminance of the marker is a direct measurement of the ECM density. To correct for possible differences in marker efficacy on the different histological slices, we corrected the luminance by relating it to a reference region in the brainstem. The 13 days after trauma were selected as a possible ECM rearrangement is finalized after that time (Happel et al. , 2014) and the neurophysiological changes in the auditory cortex – measured by electrophysiological recordings – leading to a chronification of the tinnitus percept are likely to be completed (Ahlf et al. , 2012; Tziridis et al. , 2014). We found the clear evidence that animals with behavioral signs of tinnitus have a much more solidified ECM surrounding of their auditory cortex neurons than animals without these signs or healthy control animals. This effect seems to be stronger in the cortical hemisphere contra-lateral to the trauma ear, which can be explained by the functional crossing of excitatory projections within the auditory pathway to the contra-lateral side.
From the described effect of the ECM being more solidified in tinnitus animals compared to control or non-tinnitus animals, several conclusions can be drawn regarding potential mechanistic tinnitus models, respectively. As it is not possible to provide a complete overview of all existing tinnitus models, we here focus on the most common ones.
First, the effect points to the assumption that in contrast to former models, chronic tinnitus is not a result of a re-organization of the tonotopic map after a cochlear damage as claimed by Mühlnickel et al. (Mühlnickel et al. , 1998), but is instead characterized by a fixation of the wiring scheme after transient re-wiring in the cortex (Ahlf et al. , 2012). Indeed, the hypothesis raised by Mühlnickel et al. has been falsified by several other groups in various recent studies, where huge tinnitus cohorts were investigated with fMRI (Koopset al. , 2020; Koops & van Dijk, 2021).
Second, our findings suggest that during tinnitus chronification the responses of the neural system enter a neural attractor, which is further reinforced by stiffening of the ECM in the auditory cortex. In this context, the combined stochastic-resonance-predictive-coding model introduced by Schilling and co-workers might provide an explanation (Schilling et al. , 2023b). In a nutshell, the model describes tinnitus as a result of intrinsically generated neural noise coming from outside the auditory system (see also Zeng, 2013; Koops & Eggermont, 2021) used to compensate for reduced hearing thresholds resulting from decreased cochlear output due to noise-induced cochlear damage (Krausset al. , 2016; Gollnast et al. , 2017; Krauss et al. , 2017; Krauss et al. , 2018; Krauss et al. , 2019; Tziridiset al. , 2021; Schilling & Krauss, 2022; Schulze et al. , 2023). Thus, a feedback loop implemented in the brainstem tunes for the optimal noise level to maximize information transmission along the auditory pathway by means of adaptive stochastic resonance (for details see Krauss et al. , 2016; Schilling et al. , 2021). This part of the model has already led to several testable hypotheses and was tested in computer simulations (Schilling et al. , 2022). It delivered a mechanistic explanation for the little brother of tinnitus, the Zwicker tone (Zwicker, 1964; Schilling et al. , 2023a; Schilling et al. , 2023c) and explains increased auditory sensitivity after simulated hearing loss in an animal model (Krauss & Tziridis, 2021), and provided individualized treatment approaches for human patients (Schilling et al. , 2020; Tziridis et al. , 2022). Nevertheless, this part of the model is a pure brainstem model and does not account for the expected and described cortical effects. To that means, it was assumed that the intrinsically generated neural noise is amplified along the auditory pathway via central gain effects and is then transmitted to higher brain structures such as the thalamus and the auditory cortex.
Complementary to this bottom-up information flow, top-down mechanisms seem to play a crucial role in tinnitus development and especially tinnitus manifestation (Sedley et al. , 2016; Hullfish et al. , 2019). Thus, the brain and especially the cortex is assumed to operate as prediction machines trying to predict the cause of certain signals transmitted via the auditory pathway. Thus, the brain makes a default prediction (predictor for the Bayesian brain formalism), which is silence under normal conditions. The product of predictor (silence) and the top-down neuronal signal (likelihood) are the actual percept.
According to the combined stochastic-resonance-predictive-coding model which unifies the bottom-up and top-down mechanisms (Schilling et al. , 2023b), the increased bottom-up neural activity (neural noise) caused by the stochastic resonance effect is mis-interpreted as neuronal signal evoked by a real auditory stimulus. The noise thus leads to increased activity and might also cause a decreased sensory precision – i.e., higher mean and lower variance of the likelihood – as brain states with low activity become very unlikely due to the continuous neural noise. In other words, the neural noise leads to continuous mis-predictions of the cortex with regards to incoming auditory signal. Thus, the brain updates the predictions in a pathological manner and starts to manifest a continuous auditory input as default prediction (updated predictor), or attractor.
On the other hand, it is assumed that certain plastic changes in the cortex could decrease the precision again or even prevent it from happening at all and therefore reset / keep the default prediction to silence (Sedley et al. , 2016; Hullfish et al. , 2019). The here described results support this idea as in animals without tinnitus the ECM density is not increased, neuronal plasticity is therefore still possible. In tinnitus animals however, the new synaptic weights and the mis-predictions (falsely updated predictor) are consolidated by the solidified ECM.
In conclusion, we assume the tinnitus percept to be caused by increased neural noise, mis-interpreted as auditory input and manifested via an updated predictor (attractor) of higher brain areas. If this mis-prediction is manifested via an increased ECM density there is no possibility for the system anymore to change this wrong predictor, and consequently tinnitus is perceived chronically.