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Tinnitus and cochlear damage have been associated with changes in somatosensory-auditory integration and plasticity in the dorsal cochlear nucleus (DCN). Recently, we demonstrated in vivo that DCN bimodal plasticity is stimulus timing-dependent, with Hebbian and anti-Hebbian timing rules that reflect in vitro spike timing-dependent plasticity. In this in vivo study, we assessed the stimulus timing dependence of bimodal plasticity in a tinnitus model. Guinea pigs were exposed to a narrowband noise that produced a temporary elevation of auditory brainstem response thresholds. A total of 60% of the guinea pigs developed tinnitus as indicated by gap-induced prepulse inhibition of the acoustic startle. After noise exposure and tinnitus induction, stimulus timing-dependent plasticity was mea-sured by comparing responses to sound before and after paired somatosensory and auditory stimulation presented with varying intervals and orders. In comparison with Sham and noise-exposed animals that did not develop tinnitus, timing rules in verified tinnitus animals were more likely to be anti-Hebbian and broader for those bimodal intervals in which the neural activity showed enhancement. Further-more, units from exposed animals with tinnitus were more weakly suppressed than either Sham animals or exposed animals without tinnitus. The broadened timing rules in the enhancement phase in animals with tinnitus, and in the suppressive phase in exposed animals without tinnitus was in contrast to narrow, Hebbian-like timing rules in Sham animals. These findings implicate alterations in DCN bimodal spike timing-dependent plasticity as underlying mechanisms in tinnitus, opening the way for a therapeutic target. [ABSTRACT FROM AUTHOR]

The auditory brainstem response (ABR) is an essential diagnostic indicator of overall cochlear health, used extensively in both basic research and clinical studies. A key quantification of the ABR is threshold, the lowest sound level that elicits a response. Because the morphology of ABR waveforms shift with stimulus level and the overall signal-to-noise ratio is low, threshold estimation is not straightforward. Although several algorithmic approaches have been proposed, the current standard practice remains the visual evaluation of ABR waveforms as a function of stimulus level. We developed an algorithm based on the cross-correlation of two independent averages of responses to the same stimulus. For each stimulus level, the individual responses to each tone-pip are randomly split into two groups. The median waveform for each group is calculated, and then the normalized cross-correlation between these median waveforms is obtained. This process is repeated 500 times to obtain a resampled cross-correlation distribution. For each frequency, the mean values of these distributions are computed for each level and fit with a sigmoid or a power law function to estimate the threshold. Algorithmic thresholds demonstrated robust and accurate performance, achieving 92% accuracy within ±10 dB of human-rated thresholds on a large pool of mouse data. This performance was better than that of several published algorithms on the same dataset. This algorithm has now fully replaced the manual estimation of ABR thresholds for our preclinical studies, thereby saving significant time and enhancing objectivity in the process., Competing Interests: Declaration of interests Luke Shaheen, Seth Koehler, and Yoojin Chung were employees of Decibel Therapeutics or Regeneron Pharmaceuticals at the time of contribution to this publication and may hold company stock and/or stock options. Brad Buran was a paid consultant for Decibel Therapeutics or Regeneron Pharmaceuticals at the time of contribution to this publication.