Neuromechanics of learned sensorimotor vocal integration

描述（由申请人提供）：如何顺序，快速发声在皮层中表示，以及如何在皮层区域之间表示变化仍然知之甚少。这种知识上的差距使开发一个适当的言语和语言产生的皮质模型变得复杂，这可能有助于解释言语和语言病理。在这里，生物力学的角度来开发一个数学动力系统模型的斑胸草雀鸣管和上声道。该模型成功地引入了简化描述复杂的歌唱行为，识别一系列的元素“手势”，包括鸟的歌曲。手势是微小的声音运动，协调的压力变化（改变通过空洞的空气量）和张力变化（软骨膜）作为时间的函数，就像鸟唱歌一样。检查神经相关的时变特征的压力和紧张的皮质歌曲系统区域HVC已经确定，HVC神经元的活动编码运动过程中的重要时刻（极端或最大点的手势轨迹）。这表明HVC具有由手势序列表示的发声行为的内部模型。神经元活动的时间精确地与鸟类发出由神经元编码的手势的时间几乎为零的时间滞后相关联。由于神经元活动和歌唱之间应该存在很大的传导延迟，这激发了HVC活动是运动输出预测的假设。这表明一种新的模型组织的声乐运动控制：输出的人口的HVC投射神经元表示预测（“向前”模型）的动态的手势，用于处理反馈，并转换为前运动活动发生在初级运动皮层RA。两个具体目标将检验这些假设。第一个目标将使用睡眠鸟类和唱歌鸟类中单个识别的HVC神经元的记录来测试 手势假说的预言反馈将被扰动，以评估它是否会影响假设为预测的机械基础的非线性时间总和。数据将被评估的姿态轨迹的参数敏感的统计模型。第二个目标将测试的假设，即从HVC到RA的信息的变化涉及从手势极值的表示到通过歌曲的连续路径的变换。RA的地形组织将通过RA的系统记录进行评估。在一个相关的目标，该模型将通过引入双边相互作用和时间依赖的上声道过滤，并创建自动化程序，以促进歌曲的快速分析， 其他目的的刺激。这些研究可以对发声运动编码产生新的见解，并为人类语音产生的研究提供信息。

DESCRIPTION (provided by applicant): How sequential, rapid vocal production is represented in the cortex, and how representations change across cortical regions remains poorly understood. This gap in knowledge complicates development of an adequate cortical model for speech and language production which could help to explain speech and language pathologies. Here, a biomechanical perspective is taken to develop a mathematical dynamical systems model of the zebra finch syrinx and upper vocal tract. The model successfully introduces simplifications in describing the complex singing behavior, identifying a sequence of elemental "gestures" that comprise the bird's song. Gestures are small vocal movements, coordinated changes in pressure (varying the amount of air going through the syrinx) and changes in tension (of the syringeal membrane) as a function of time as a bird sings. Examining neural correlates of the time-varying features of pressure and tension in a cortical song system area HVC has identified that the activity of HVC neurons encode significant moments during movements (extreme or maximal points in the gesture trajectories). This indicates that HVC has an internal model of vocal behavior, represented by sequences of gestures. The timing of neuronal activity is precisely associated with near zero time lag to the time a bird is singing the gesture encoded by the neurons. Since there should be a substantial conduction delay between neuronal activity and singing, this motivates the hypothesis that the activity in HVC is a prediction of motor output. This suggests a new model of organization of vocal motor control: the output of the population of HVC projection neurons represents a predication ("forward" model) of the dynamics of gestures, used to process feedback, and the conversion to pre-motor activity occurs in primary motor cortex RA. Two specific aims will test these hypotheses. The first aim will use recordings of single identified HVC neurons in sleeping birds and in singing birds to test predictions of the gesture hypothesis. Feedback will be perturbed to assess if it affects non-linear temporal summation hypothesized to be the mechanistic basis for the prediction. The data will be assessed in terms of a statistical model sensitive to parameters of gesture trajectories. The second aim will test the hypothesis that the change of information from HVC to RA involves transformations from representations of gesture extrema to continuous paths through song. The topographic organization of RA will be assessed by systematic recordings in RA. In a related aim, the model will be improved through introducing bilateral interactions and time-depending upper vocal tract filtering, and creating automated procedures to facilitate rapid analysis of song stimuli for the other aims. These studies can generate new insight into vocal motor coding, and inform studies of human speech production.