Neural adaptation in the auditory system: competing demands for object recognition and localization

Abstract:

Because the coding range of sensory systems is restricted, they have to adapt to changes of the statistics of the relevant stimulus space. Sensory adaptation can ensure precise encoding of the environment over several orders of magnitude of mean intensity. By removing the mean intensity level, adaptation enables object recognition invariant of the local context. Thus, adaptation removes information from the sensory representation, for example the mean intensity. However, sensory systems have to represent different features of a stimulus in parallel, and the information that is important for detection of these may differ. Consequently, adaptation should act differently in different parts of the pathway.

In the auditory pathway of both invertebrates and vertebrates, the time course of amplitude modulations is used for object recognition, while the absolute amplitude difference between both ears plays an important role in sound localisation. I will present results from both analytical calculations and numeric simulations, which show that these two task pose different demands on adaptation in the sensory periphery. However, modeling also suggested a possible solution to this conflict. Experimental results from the grasshoppers auditory system revealed the neural substrate for the solution and behavioral experiments confirmed model predictions. The mammalian auditory pathway exhibits similar neural mechanisms, suggesting a convergent solution to a common problem.