Neural Coding of Natural Sounds

描述（由申请人提供）：复杂声音的听觉处理对包括人类在内的许多物种的感知和交流至关重要，但令人惊讶的是，人们对大脑高级区域如何完成这项任务知之甚少。我们建议在鸣禽的听觉前脑中解决这个问题，使用复杂的自然声音，包括鸟鸣。我们假设，系统地使用这类丰富的听觉刺激，与动物行为学相关，将使我们能够揭示高层次听觉处理的复杂和非线性方面，并将证明听觉前脑神经元被优化以有效地代表这些刺激。因此，在我们的第一个目标中，我们将描述鸟鸣合奏的自然统计特征，并开发新的基于协方差的方法来量化对这些声音的神经反应，包括反应的非线性方面。在我们的第二个和第三个目标中，我们将使用目标1中开发的方法来描述位于听觉丘脑和歌曲系统之间的听觉前脑区域的感受野。对不同区域的神经反应进行比较，可以揭示每个区域内复杂声音的编码，以及不同区域之间处理的功能阶段。此外，使用四极体和多个电极，结合对结果的信息理论分析，应该揭示局部电路在这些神经反应中的作用，并进一步验证一些声音是由神经元群体而不是单个高度选择性细胞编码的假设。本研究揭示的神经编码原理可能与理解听觉感知及其障碍具有普遍的相关性。

DESCRIPTION (provided by applicant): Auditory processing of complex sounds is critical for perception and communication in many species, including humans, but surprisingly little is known about how high level brain areas accomplish this task. We propose to tackle this question in the auditory forebrain of songbirds, using complex natural sounds, including bird songs. We hypothesize that the systematic use of this rich class of auditory stimuli, of ethological relevance to the animal, will enable us to reveal complex and nonlinear aspects of high level auditory processing, and will demonstrate that auditory forebrain neurons are optimized to efficiently represent these stimuli. In our first aim, we will therefore characterize the natural statistics of ensembles of bird song, and develop new covariance-based methods for quantifying neural responses to these sounds, including nonlinear aspects of the responses. In our second and third aims, we will use the methods developed in Aim 1 to describe receptive fields of the auditory forebrain areas that lie between the auditory thalamus and the song system. Comparison of neural responses in different areas should shed light on encoding of complex sounds within each area and on the functional stages of processing between areas. In addition, the use of tetrodes and multiple electrodes, combined with information theoretic analyses of results, should reveal the role of local circuitry in these neural responses, and test the further hypothesis that some sounds are encoded by populations of neurons rather than by single, highly selective cells. The neural coding principles revealed by this study are likely to be of general relevance to an understanding of auditory perception and its disorders.