Weisman Ronald G, Hoeschele Marisa, Bloomfield Laurie L, Mewhort Douglas, Sturdy Christopher B
Queen's University, Canada.
Behav Processes. 2010 May;84(1):421-7. doi: 10.1016/j.beproc.2010.01.010. Epub 2010 Jan 25.
The spectral frequency ranges of song notes are important for recognition in avian species tested in the field. Frequency-range discriminations in both the field and laboratory require absolute pitch (AP). AP is the ability to perceive pitches without an external referent. The authors provided a network model designed to account for differences in AP among avian species and evaluated it against discriminative performance in eight-frequency-range laboratory tests of AP for five species of songbirds and two species of nonsongbirds. The model's sensory component describes the neural substrate of avian auditory perception, and its associative component handles learning of the discrimination. Using only two free parameters to describe the selectivity and the sensitivity of each species' auditory sensory filters, the model provided highly accurate predictions of frequency-range discrimination in songbirds and in a parrot species, but performance and its prediction were less accurate in pigeons: the only species tested that does not learn its vocalizations. Here for the first time, the authors present a model that predicted individual species' performance in frequency-range discriminations and predicted differences in discrimination among avian species with high accuracy.
在野外测试的鸟类物种中，鸣叫音符的频谱频率范围对于识别很重要。在野外和实验室中进行频率范围辨别都需要绝对音高（AP）。绝对音高是指在没有外部参照的情况下感知音高的能力。作者提供了一个网络模型，旨在解释鸟类物种之间绝对音高的差异，并在针对五种鸣禽和两种非鸣禽的绝对音高的八频率范围实验室测试中，根据辨别性能对其进行评估。该模型的感觉成分描述了鸟类听觉感知的神经基础，其联想成分处理辨别学习。该模型仅使用两个自由参数来描述每个物种听觉感觉滤波器的选择性和敏感性，就对鸣禽和一种鹦鹉物种的频率范围辨别提供了高度准确的预测，但在鸽子中的表现及其预测准确性较低：鸽子是测试的唯一不会学习其发声的物种。作者首次在此展示了一个模型，该模型能够高精度地预测个体物种在频率范围辨别中的表现，并预测鸟类物种之间辨别能力的差异。
