Sparse ensemble neural code for a complete vocal repertoire

完整声音曲目的稀疏集合神经代码

阅读:4
作者:H Robotka, L Thomas, K Yu, W Wood, J E Elie, M Gahr, F E Theunissen

Abstract

The categorization of animal vocalizations into distinct behaviorally relevant groups for communication is an essential operation that must be performed by the auditory system. This auditory object recognition is a difficult task that requires selectivity to the group identifying acoustic features and invariance to renditions within each group. We find that small ensembles of auditory neurons in the forebrain of a social songbird can code the bird's entire vocal repertoire (∼10 call types). Ensemble neural discrimination is not, however, correlated with single unit selectivity, but instead with how well the joint single unit tunings to characteristic spectro-temporal modulations span the acoustic subspace optimized for the discrimination of call types. Thus, akin to face recognition in the visual system, call type recognition in the auditory system is based on a sparse code representing a small number of high-level features and not on highly selective grandmother neurons.

特别声明

1、本文转载旨在传播信息,不代表本网站观点,亦不对其内容的真实性承担责任。

2、其他媒体、网站或个人若从本网站转载使用,必须保留本网站注明的“来源”,并自行承担包括版权在内的相关法律责任。

3、如作者不希望本文被转载,或需洽谈转载稿费等事宜,请及时与本网站联系。

4、此外,如需投稿,也可通过邮箱info@biocloudy.com与我们取得联系。