Characterizaton of Non-linear Auditory Receptive Fields

描述（由申请人提供）：听觉神经元的特征是它们的感受野属性，它描述了神经元对刺激的频率和振幅等参数的组织。相对而言，听觉系统较低层次的神经元的感受野得到了更好的描述，但高阶神经元表现出复杂的非线性，无法进行系统的量化。然而，表征高阶感受野是理解正常和异常听觉感知过程的基础，也可能有助于优化假肢装置的性能。欧椋鸟的高阶听觉神经元对嵌入在自然信号（歌曲）中的声学对象（“主题”）具有高度选择性，已经描述了一个有吸引力的模型系统。最近的研究结果表明，欧椋鸟具有非凡的序列解析能力，对原型语法结构表现出敏感性。在本研究中，新的统计技术将与椋鸟的“cmHV”神经元的生理记录相结合，椋鸟的鸣叫识别行为受操作控制。在第一个实验中，将开发统计方法，用于学习母基结构的有效基集，并使用贝叶斯推理模型的马尔可夫随机场并结合非线性时间动力学，使用分层非线性回归估计基于特征的接受场。在第二个实验中，我们将使用操作程序来识别椋鸟在歌曲识别行为中使用的基序的自然特征和基序序列参数。在第三个实验中，将对cmHV反应进行表征，重点分析通过行为测试识别的特征，并使用统计方法表征非线性特性。这种方法的成功发展将为复杂的声学对象和序列识别行为提供定量的神经生理学见解，同时为皮层感觉生理学开发一种通用的方法。

DESCRIPTION (provided by applicant): Auditory neurons are characterized by their receptive field properties, which describe the organization of parameters such as frequency and amplitude of stimuli that the neurons respond to. Receptive fields are relatively better described for neurons at lower levels of the auditory system, but higher-order neurons exhibit complex non-linearities that have resisted systematic quantification. Characterization of higher-order receptive fields, however, is fundamental to understanding normal and abnormal auditory perceptual processes, and also may help optimize performance of prosthetic devices. An attractive model system has been described whereby high-order auditory neurons in starlings become highly selective for acoustic objects ("motifs") embedded in natural signals (songs). Recent results implicate remarkable sequence parsing abilities of starlings that exhibit sensitivity to prototypic grammar-like structures. In the proposed research, novel statistical techniques will be combined with physiological recordings of "cmHV" neurons of starlings whose song recognition behavior is under operant control. In the first experiment, the statistical methodologies will be developed for learning efficient basis sets for motif structure and for estimating feature-based receptive fields with hierarchical non-linear regression, using Markov random fields of Bayesian inference models and incorporating non-linear temporal dynamics. In the second experiment, operant procedures will be used to identify natural features of motifs and parameters of motif sequences that starlings utilize in song recognition behavior. In the third experiment, cmHV responses will be characterized, with emphasis on analysis of the features identified by behavioral testing, and using the statistical methods for characterization of non-linear properties. Successful development of this approach would give quantitative neurophysiological insight into complex acoustic object and sequence recognition behavior while developing an approach of general utility to cortical sensory physiology.