Troyer T W, Doupe A J
Department of Psychiatry, University of California, San Francisco, California 94143-0444, USA.
J Neurophysiol. 2000 Sep;84(3):1204-23. doi: 10.1152/jn.2000.84.3.1204.
Birdsong learning provides an ideal model system for studying temporally complex motor behavior. Guided by the well-characterized functional anatomy of the song system, we have constructed a computational model of the sensorimotor phase of song learning. Our model uses simple Hebbian and reinforcement learning rules and demonstrates the plausibility of a detailed set of hypotheses concerning sensory-motor interactions during song learning. The model focuses on the motor nuclei HVc and robust nucleus of the archistriatum (RA) of zebra finches and incorporates the long-standing hypothesis that a series of song nuclei, the Anterior Forebrain Pathway (AFP), plays an important role in comparing the bird's own vocalizations with a previously memorized song, or "template." This "AFP comparison hypothesis" is challenged by the significant delay that would be experienced by presumptive auditory feedback signals processed in the AFP. We propose that the AFP does not directly evaluate auditory feedback, but instead, receives an internally generated prediction of the feedback signal corresponding to each vocal gesture, or song "syllable." This prediction, or "efference copy," is learned in HVc by associating premotor activity in RA-projecting HVc neurons with the resulting auditory feedback registered within AFP-projecting HVc neurons. We also demonstrate how negative feedback "adaptation" can be used to separate sensory and motor signals within HVc. The model predicts that motor signals recorded in the AFP during singing carry sensory information and that the primary role for auditory feedback during song learning is to maintain an accurate efference copy. The simplicity of the model suggests that associational efference copy learning may be a common strategy for overcoming feedback delay during sensorimotor learning.
鸟鸣学习为研究时间上复杂的运动行为提供了一个理想的模型系统。在已充分了解的鸣唱系统功能解剖学的指导下，我们构建了一个鸣唱学习感觉运动阶段的计算模型。我们的模型使用简单的赫布学习规则和强化学习规则，并证明了一组关于鸣唱学习过程中感觉运动相互作用的详细假设的合理性。该模型聚焦于斑胸草雀的运动核团HVC和古纹状体粗核（RA），并纳入了一个长期存在的假设，即一系列鸣唱核团，即前脑通路（AFP），在将鸟类自身的发声与先前记忆的歌曲或“模板”进行比较时发挥重要作用。“AFP比较假设”受到了AFP中处理的假定听觉反馈信号会经历显著延迟的挑战。我们提出，AFP并不直接评估听觉反馈，而是接收与每个发声姿态或歌曲“音节”相对应的反馈信号的内部生成预测。这种预测，即“传出副本”，是通过将投射到RA的HVC神经元中的运动前活动与投射到AFP的HVC神经元中记录的由此产生的听觉反馈相关联，在HVC中学习得到的。我们还展示了负反馈“适应”如何用于在HVC内分离感觉和运动信号。该模型预测，歌唱过程中在AFP中记录的运动信号携带感觉信息，并且鸣唱学习过程中听觉反馈的主要作用是维持准确的传出副本。该模型的简单性表明，联想传出副本学习可能是感觉运动学习过程中克服反馈延迟的一种常见策略。
