Modeling the spectral transition selectivity in the primary auditory cortex

From an information processing point of view, a common computational principle in neural systems is to analyze and map the features of the input signal into multidimensional, spatially organized areas. A mathematical model based on biological data mimicking the functions of the primary auditory cortex is presented. The model embraces a three dimensional representation which corresponds respectively to the following acoustic features: frequency components, local spectral shape and local spectral bandwidth. The model representation of nonstationary acoustic features is examined, specifically, the direction and the rate of spectral transitions, which are crucial in speech and sound perception.<
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