a corticothalamic circuit model for sound identification in complex scenes声音识别corticothalamic电路模型在复杂的场景.pdfVIP

A Corticothalamic Circuit Model for Sound Identification in Complex Scenes Gonzalo H. Otazu1,2*, Christian Leibold1,2 ¨ 1 Division of Neurobiology, Department Biology II, Ludwig-Maximilians-Universitat, Munich, Germany, 2 Bernstein Center for Computational Neuroscience, Munich, Germany Abstract The identification of the sound sources present in the environment is essential for the survival of many animals. However, these sounds are not presented in isolation, as natural scenes consist of a superposition of sounds originating from multiple sources. The identification of a source under these circumstances is a complex computational problem that is readily solved by most animals. We present a model of the thalamocortical circuit that performs level-invariant recognition of auditory objects in complex auditory scenes. The circuit identifies the objects present from a large dictionary of possible elements and operates reliably for real sound signals with multiple concurrently active sources. The key model assumption is that the activities of some cortical neurons encode the difference between the observed signal and an internal estimate. Reanalysis of awake auditory cortex recordings revealed neurons with patterns of activity corresponding to such an error signal. Citation: Otazu GH, Leibold C (2011) A Corticothalamic Circuit Model for Sound Identification in Complex Scenes. PLoS ONE 6(9): e24270. doi:10.1371/ journal.pone.0024270 Editor: Olaf Sporns, Indiana University, United States of America Received March 29, 2011; Accepted August 7, 2011; Published September 13, 2011 Copyright: 2011 Otazu, Leibold. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution,