Neuromechanics of learned sensorimotor vocal integration

描述（由申请人提供）：连续的、快速的声音产生是如何在皮层中表征的，以及表征是如何在皮层区域中变化的，目前尚不清楚。这一知识上的差距使言语和语言产生的适当皮层模型的发展复杂化，该模型可以帮助解释言语和语言病理。本文从生物力学的角度建立了斑胸草雀鸣管和上声道的数学动力系统模型。该模型成功地简化了对复杂鸣叫行为的描述，确定了组成鸣叫的一系列基本“手势”。手势是微小的声音动作，压力的协调变化（通过鸣管的空气量的变化）和张力的变化（鸣管膜的变化）是鸟唱歌时时间的函数。通过研究皮层歌声系统区域HVC中压力和张力的时变特征的神经相关性，我们发现HVC神经元的活动编码了运动过程中的重要时刻（手势轨迹中的极值点或最大值点）。这表明HVC有一个声音行为的内部模型，由手势序列表示。神经元活动的时间精确地与鸟类唱歌的时间几乎为零的滞后相关联，这是由神经元编码的手势。由于在神经元活动和歌唱之间应该存在实质性的传导延迟，这激发了HVC活动预测运动输出的假设。这提示了一种声音运动控制组织的新模型：HVC投射神经元群体的输出代表了用于处理反馈的手势动态的预测（“前向”模型），并且转换为运动前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。第一个目标是使用睡眠鸟和歌唱鸟的单个HVC神经元的录音进行测试

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.