Learning Temporally Stable Representations from Natural Sounds: Temporal Stability as a General Objective Underlying Sensory Processing

Abstract. In order to understand the general principles along which sensory processing is organized, several recent studies optimized partic-ular coding objectives on natural inputs for different modalities. The homogeneity of neocortex indicates that a sensitive objective should be able to explain response properties of different sensory modalities. The temporal stability objective was successfully applied to somatosensory and visual processing. We investigate if this objective can also be ap-plied to auditory processing and serves as a general optimization objec-tive for sensory processing. In case of audition, this translates to a set of non-linear complex filters optimized for temporal stability on natural sounds. We show that following this approach we can develop filters that are localized in frequency and time and extract the frequency content of the sound wave. A subset of these filters respond invariant to the phase of the sound. A comparison of the tuning of these filters to the tuning of cat auditory nerves shows a close match. This suggests that temporal stability can be seen as a general objective describing somatosensory, visual and auditory processing.