PRIMITIVE AUDITORY SEGREGATION BASED ON OSCILLATORY CORRELATION

Auditory scene analysis is critical for complex auditory processing. W e study auditory segregation from the neural network perspective, and develop ct framework for primitive auditory scene analysis, The archit ecture is a laterally coupled two-dimensional network of relaxation os cillators with a global inhibitor. One dimension represents time and a nother one represents frequency. We show that this architecture, plus systematic delay lines, con in real time group auditory features into a stream by phase synchrony and segregate different streams by desynch ronization. The network demonstrates a set of psychological phenomena regarding primitive auditory scene analysis, including dependency on f requency proximity and the rare of presentation, sequential capturing, and competition among different perceptual organizations. We offer a neurocomputational theory-shifting synchronization theory-for explaini ng how auditory segregation might be achieved in the brain, and the ps ychological phenomenon of stream segregation. Possible extensions of t he model are discussed.