Representation of auditory space in the avian midbrain: integration without a map?

虽然鸟类的空间视觉很好理解，但大多数鸟类的空间听觉处理仍然令人困惑。尽管大多数鸟类在高度结构化的世界中在所有三个维度上移动，但大多数鸟类的听觉定位被认为仅限于方位角，即只沿水平维度移动。确定声源高度的高度线索通常由大多数鸟类不具备的外耳结构引入；只有像仓鸮这样的专家才有解剖学上的特征（比如不对称的耳孔），可以在海拔高度进行定位。然而，最近的数据表明，鸟类的球形头部引起了声学非线性，这可能允许通过头部运动在海拔高度定位声音。我们将在一个受控的范例中研究鸡的这种行为，以确定非专业物种是否确实能够在所有维度上定位声音。此外，我们将研究听觉信息如何整合到中脑视觉顶盖的视觉空间图中。如果听觉系统确实无法在海拔高度定位声音，那么听觉信息如何被整合到顶盖中视觉空间的精确地图中呢？我们将记录中脑神经元在听觉、视觉和视听刺激下的反应，以确定每种模式下的接受野并描绘整合规则。初步数据表明，仓鸮的视听整合与之前发展的模型有很大不同。我们期望找到一种计算机制，即使没有以前认为必不可少的外围结构，也能实现足够的行为精度。

While spatial vision in birds is well understood, spatial auditory processing remains puzzling for most avian species. Even though most bird species move in all three dimensions in a highly structured world, auditory localization is believed to be restricted to the azimuth in most birds, that is, only along the horizontal dimension. Elevational cues to determine the height of a sound source are usually introduced by outer ear structures that most bird species do not possess; only specialists such as the barn owl have anatomical features (such as asymmetric ear openings) that allow localization in elevation. However, recent data have shown that the spherical avian head induces acoustic nonlinearities that might allow sound localization in elevation by head movements. We will study this behavior in chicken in a controlled paradigm to determine whether non-specialists species are indeed able to locate sound in all dimensions. In addition, we will investigate how the auditory information is integrated into the map of visual space in the midbrain optic tectum. If the auditory system is indeed incapable of locating sounds in elevation, how can auditory information be integrated into the precise map of visual space in the tectum? We will record the responses of midbrain neurons under auditory, visual, and audio-visual stimulation to determine the receptive fields in each modality and delineate the integration rules. Preliminary data indicate that audio-visual integration is very different from the previous models developed in barn owls. We expect to find computational mechanisms that allow sufficient behavioral precision even without the peripheral structures that were previously thought to be indispensable.