Introduction Some tinnitus subjects habituate to their tinnitus but some others do not and complain of its annoyance tremendously. Normal sensory memory and change detection processes are needed for detecting the tinnitus signal as a prediction error and habituation to tinnitus. The purpose of this study was to compare auditory mismatch negativity as the index of sensory memory and change detection among the studied groups to search for the factors involving in the perception of tinnitus and preventing habituation in decompensated tinnitus subjects. Methods Electroencephalography was recorded from scalp electrodes in compensated tinnitus, decompensated tinnitus, and no tinnitus control subjects. Mismatch negativity was obtained using the oddball paradigm with frequency, duration, and silent gap deviants. Amplitude, latency, and area under the curve of mismatch negativities were compared among the three studied groups. Results The results showed lower mismatch negativity amplitude and area under the curve for the higher frequency deviant and for the silent gap deviant in decompensated tinnitus group compared to normal control and compensated tinnitus group. Conclusions This study revealed a deficit in sensory memory and change detection processing in decompensated tinnitus subjects. This causes persistent prediction errors; tinnitus signal is consistently detected as a new signal and activates the brain salience network and consequently prevents habituation to tinnitus. Mismatch negativity is proposed as an index for monitoring tinnitus rehabilitation.

About 20 percent of people above 60 years old suffer from tinnitus though no definitive treatment has been found for it. Evaluation of electrical brain activity using Event-Related Potentials (ERPs) is one of the methods to investigate the underlying reasons of tinnitus perception. Previous studies using ERPs suggest that the precognitive memory in tinnitus groups is negatively affected in comparison to the normal hearing groups. In this study, cognitive memory has been assessed using visual and auditory P300 response with oddball paradigm. Fifteen chronic tinnitus subjects and six normal hearing subjects participated in the experiment. T-test with significance level of 0.05 was applied on amplitude and latency of auditory and visual P300 for all electroencephalography (EEG) channels separately to compare tinnitus and normal hearing groups where the tinnitus group showed meaningful lower amplitude of auditory P300 peak in three EEG channels.

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Management and treatment of subjective tinnitus is an ongoing focus of research activities. One of the most viable assessments of such treatment is the evaluation of brain activity in addition to patient response and clinical assessment. This study focuses on sound therapy and evaluation of patients’ electroencephalogram (EEG) in order to verify the potency of this approach. Broadband sound therapy was applied to nineteen participants aging from 25 to 64 and suffering from chronic subjective tinnitus to study the difference of brain activity, a) before fake treatment, b) after fake treatment and c) after the main treatment, using EEG and Visual Analog Scale (VAS) for evaluating Residual Inhibition (RI). Four features were extracted using 4-level wavelet decomposition with Symlet 8 as its mother wavelet. For the “After the main treatment” stage, the mean value of wavelet coefficients for the last wavelet level, which corresponded to delta band of EEG, was lower in the FC3 channel based on Two-Sample T-Test with significance level of 0.01, as compared to the same channel of the “before the treatment” stage, for cases in which decreased tinnitus loudness were reported.

Sequential sampling based mathematical models of decision-making involve evidence accumulation over time during decision formation and have been successful in capturing choice behaviour. A popular model is the drift-diffusion model (DDM). To capture finer aspects of choice behaviour, such as differences in choice reaction times, time-variant gain features that imitate urgency signals have been implemented in standard DDM. In particular, a previous DDM with a time-variant gain can replicate slower error decisions than correct decisions. However, the time-variant gain of the model, and other similar time-variant gain-based models, often implement time-variant gain on both signal and noise features, with the assumption that increasing gain on the drift rate (due to urgency) is similar to DDM with collapsing decision bounds. Hence, it is unclear whether the gain effects on just the signal or noise feature can lead to different choice behaviour. Here, using computational simulations and theoretical approximations, we used a previous time-variant gain DDM and systemically showed that time-variant gain only on the DDM’s noise suffices to produce slower error choices while time-variant gain only on the drift rate speeds up error choices. In addition, the former was associated with more skewness and kurtosis on correct RT distributions while the latter led to more skewness and kurtosis in error RT distributions. Thus, time-variant gain in DDM’s different components can lead to different choice outcomes, which can potentially be used for more systematic data fitting.