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Abstract : |
It is known that humans can make finer discriminations between familiar sounds (e.g. syllables) than between unfamiliar ones (e.g. different noise segments). Here we show that a corresponding enhancement is present in early auditory processing stages. Based on previous work which demonstrated that natural sounds had robust statistical properties that could be quantified, we hypothesize that the auditory system exploits those properties to construct efficient neural codes. To test this hypothesis, we measure the information rate carried by auditory spike trains on narrow-band stimuli whose amplitude modulation has naturalistic characteristics, and compare it to the information rate on stimuli with non-naturalistic modulation. We find that naturalistic inputs significantly enhance the rate of transmitted information, indicating that auditiory neural responses are matched to characteristics of natural auditory scenes. 1 Natural Scene Statistics and the Neural Code A primary goal of hearing research is to understand how complex sounds that occur in natural scenes are processed by the auditory system. However, natural sounds are difficult to describe quantitatively and the complexity of auditory responses they evoke makes it hard to gain insight into their processing. Hence, most studies of auditory physiology are restricted to pure tones and noise stimuli, resulting in a limited understanding of auditory encoding. In this paper we pursue a novel approach to the study of natural sound encoding in auditory spike trains. Our method consists of measuring statistical characteristics of natural auditory scenes,, |
