Noise Invariance in Inferior Colliculus Neurons is Dependant on the Input Noisy Conditions

The auditory system is extremely efficient to extract audio information in the presence of background noise. However, the neural mechanisms related to this efficiency is still greatly misunderstood, especially in the inferior colliculus (IC). In fact, while noise processing under different conditions has been investigated at the auditory cortex level, studies in the IC have been much limited. One interesting observation has been that there seems to be some degree of noise invariance in the IC in the presence of white noise. We wish to broaden this knowledge by investigating if there is a difference in the activity of neurons in the IC, when presenting noisy vocalisations with different types of noises, input signal-to-noise ratios (SNR) and signal levels. We do so using a generalized linear model (GLM), which gives us the ability to study the neural activity under these different conditions at a per neuron level. We found that non-stationary noise is the only noise type that clearly contributes to the neural activity in the IC, regardless of the SNR, input level or vocalisation type. However, when presenting white or natural stationary noises, a great diversity of responses was observed for the different conditions, where the activity of some neurons was affected by the presence of noise and the activity of others was not. Therefore, there seems to be some level of background noise invariance as early as the IC level, as reported before, however, this invariance seems to be highly dependent on the noisy conditions.