Dynamical properties of a plastic neural network model for tinnitus therapy and inhibition of oscillation using noise stimulus

Tinnitus is the perception of phantom sounds in the ears or in the head. Sound therapy techniques for tinnitus have been proposed. To account for mechanisms of tinnitus generation and the clinical effects of sound therapies from the viewpoint of neural engineering, we have proposed a plastic neural network model for the human auditory system. We found that this model has a bistable state, i.e., a stable oscillatory state and a stable equilibrium (non-oscillatory) state coexist at a certain parameter region. We also found that the oscillation can be inhibited by supplying sinusoidal stimulus, which is hypothesized as sound for treatment of tinnitus, to the model. By hypothesizing that the oscillation and the equilibrium correspond to generation and inhibition of tinnitus, respectively, we reported that these phenomena could explain the fact that the habituated human auditory system temporarily halts perception of tinnitus following sound therapy. This paper describes dynamical properties of the model and inhibition of the oscillation for two kinds of noise stimuli which correspond to sound for treatment of tinnitus in clinical. Through numerical simulations we found that adequate noise stimulus can inhibits the oscillation.