Hoffmann Lukas A, Kelly Conor W, Nicholson David A, Sober Samuel J
Department of Biology, Emory University, GA, USA.
J Vis Exp. 2012 Nov 26(69):e50027. doi: 10.3791/50027.
Experimental manipulations of sensory feedback during complex behavior have provided valuable insights into the computations underlying motor control and sensorimotor plasticity(1). Consistent sensory perturbations result in compensatory changes in motor output, reflecting changes in feedforward motor control that reduce the experienced feedback error. By quantifying how different sensory feedback errors affect human behavior, prior studies have explored how visual signals are used to recalibrate arm movements(2,3) and auditory feedback is used to modify speech production(4-7). The strength of this approach rests on the ability to mimic naturalistic errors in behavior, allowing the experimenter to observe how experienced errors in production are used to recalibrate motor output. Songbirds provide an excellent animal model for investigating the neural basis of sensorimotor control and plasticity(8,9). The songbird brain provides a well-defined circuit in which the areas necessary for song learning are spatially separated from those required for song production, and neural recording and lesion studies have made significant advances in understanding how different brain areas contribute to vocal behavior(9-12). However, the lack of a naturalistic error-correction paradigm - in which a known acoustic parameter is perturbed by the experimenter and then corrected by the songbird - has made it difficult to understand the computations underlying vocal learning or how different elements of the neural circuit contribute to the correction of vocal errors(13). The technique described here gives the experimenter precise control over auditory feedback errors in singing birds, allowing the introduction of arbitrary sensory errors that can be used to drive vocal learning. Online sound-processing equipment is used to introduce a known perturbation to the acoustics of song, and a miniaturized headphones apparatus is used to replace a songbird's natural auditory feedback with the perturbed signal in real time. We have used this paradigm to perturb the fundamental frequency (pitch) of auditory feedback in adult songbirds, providing the first demonstration that adult birds maintain vocal performance using error correction(14). The present protocol can be used to implement a wide range of sensory feedback perturbations (including but not limited to pitch shifts) to investigate the computational and neurophysiological basis of vocal learning.
在复杂行为过程中对感觉反馈进行实验性操作，为深入了解运动控制和感觉运动可塑性背后的计算机制提供了有价值的见解(1)。持续的感觉扰动会导致运动输出的补偿性变化，这反映了前馈运动控制的变化，从而减少了所经历的反馈误差。通过量化不同的感觉反馈误差如何影响人类行为，先前的研究探索了视觉信号如何用于重新校准手臂运动(2,3)，以及听觉反馈如何用于改变语音产生(4 - 7)。这种方法的优势在于能够模拟行为中的自然误差，使实验者能够观察所经历的产生误差是如何用于重新校准运动输出的。鸣禽为研究感觉运动控制和可塑性的神经基础提供了一个优秀的动物模型(8,9)。鸣禽的大脑提供了一个定义明确的神经回路，其中歌曲学习所需的区域在空间上与歌曲产生所需的区域分开，并且神经记录和损伤研究在理解不同脑区如何对发声行为做出贡献方面取得了重大进展(9 - 12)。然而，缺乏一种自然的纠错范式——即实验者对一个已知的声学参数进行扰动，然后由鸣禽进行校正——使得难以理解发声学习背后的计算机制，或者神经回路的不同元件如何对发声误差的校正做出贡献(13)。这里描述的技术使实验者能够精确控制鸣禽歌唱时的听觉反馈误差，允许引入任意的感觉误差，这些误差可用于驱动发声学习。在线声音处理设备用于对歌声的声学特性引入已知的扰动，并且一个小型头戴式耳机装置用于实时用扰动信号替代鸣禽的自然听觉反馈。我们已经使用这种范式对成年鸣禽听觉反馈的基频（音高）进行扰动，首次证明成年鸟类使用误差校正来维持发声表现(14)。本方案可用于实施广泛的感觉反馈扰动（包括但不限于音高变化），以研究发声学习的计算和神经生理学基础。
