The Salk Institute for Biological Studies, La Jolla CA 92037, United States.
Curr Opin Neurobiol. 2011 Oct;21(5):761-7. doi: 10.1016/j.conb.2011.05.027. Epub 2011 Jun 23.
Understanding the neural mechanisms of invariant object recognition remains one of the major unsolved problems in neuroscience. A common solution that is thought to be employed by diverse sensory systems is to create hierarchical representations of increasing complexity and tolerance. However, in the mammalian auditory system many aspects of this hierarchical organization remain undiscovered, including the prominent classes of high-level representations (that would be analogous to face selectivity in the visual system or selectivity to bird's own song in the bird) and the dominant types of invariant transformations. Here we review the recent progress that begins to probe the hierarchy of auditory representations, and the computational approaches that can be helpful in achieving this feat.
理解不变物体识别的神经机制仍然是神经科学中尚未解决的主要问题之一。人们认为，不同的感觉系统采用的一种常见解决方案是创建越来越复杂和宽容的分层表示。然而，在哺乳动物的听觉系统中，这种分层组织的许多方面仍然没有被发现，包括高级代表性的突出类别（类似于视觉系统中的面部选择性或鸟类自身歌曲的选择性）和主导不变转换类型。在这里，我们回顾了最近的进展，这些进展开始探索听觉表示的层次结构，以及有助于实现这一壮举的计算方法。
