Predictive coding in the auditory brainstem

Abstract

Predictive coding is an influential concept in sensory and cognitive neuroscience. It is often understood as involving top-down prediction of bottom-up sensory patterns, but the term also applies to feed-forward predictive mechanisms, for example in the retina. Here, I discuss a recent model of low-level predictive processing in the auditory brainstem that is of the feed-forward flavor. Past sensory input from the cochlea is delayed and compared with the current input, via a predictive model that is tuned with the objective of minimizing prediction error. This operation is performed independently within each peripheral channel, with parameters determined from information within that channel. The result is a sensory representation that is invariant to a certain class of interfering sounds (harmonic, quasi-harmonic, or spectrally sparse), thus contributing to Auditory Scene Analysis. The purpose of this paper is to discuss that model in the light of predictive coding, and examine how it might fit within a wider hierarchical model that supports the perceptual representation of objects and events in the world.