Motion adaptation facilitates optic flow-based spatial vision

Neuronal representation and extraction of spatial information are essential for behavioral control. For flying insects, a plausible way to gain spatial information is to exploit distance-dependent optic flow that is generated during translational self-motion. Optic flow is computed by arrays of local motion detectors retinotopically arranged in the second neuropile layer of the insect visual system. These motion detectors have adaptive response characteristics, i.e. their responses to motion with a constant or only slowly changing velocity decrease, while their sensitivity to rapid velocity changes is maintained or even increases. We analyzed by a modeling approach how motion adaptation affects signal representation at the output of arrays of motion detectors during simulated flight in artificial and natural 3D environments. We focused on translational flight, because spatial information is only contained in the optic flow induced by translational locomotion. Indeed, flies, bees and other insects segregate their flight into relatively long intersaccadic translational flight sections interspersed with brief and rapid saccadic turns, presumably to maximize periods of translation (80% of the flight). With a novel adaptive model of the insect visual motion pathway, we could show that the motion detector responses to background structures of cluttered environments are largely attenuated as a consequence of motion adaptation, while responses to foreground objects stay constant or even increase. This conclusion even holds under the dynamic flight conditions of insects.神经元对空间信息的表征与提取，对于行为调控至关重要。对于飞行昆虫而言，获取空间信息的一种可行途径，是利用平移自运动过程中产生的距离依赖性光流（optic flow）。光流由局部运动检测器阵列计算得到，这类检测器在昆虫视觉系统的第二神经髓层中呈视网膜拓扑式（retinotopically）排布。此类运动检测器具备自适应响应特性：当运动速度恒定或仅缓慢变化时，其响应会减弱；而对速度快速变化的敏感度则得以维持，甚至有所提升。本研究通过建模方法，分析了在人工与自然三维环境中模拟飞行时，运动适应如何影响运动检测器阵列输出端的信号表征。我们将研究重点聚焦于平移飞行，因为空间信息仅存在于平移运动所诱导的光流之中。事实上，果蝇、蜜蜂及其他昆虫的飞行模式可划分为两个部分：相对较长的扫视间期平移飞行阶段，以及穿插其中的短暂快速扫视转向阶段，该模式推测是为了最大化平移飞行的时长（占整个飞行过程的80%）。借助我们构建的昆虫视觉运动通路新型自适应模型，研究表明：受运动适应作用影响，杂乱环境中背景结构对应的运动检测器响应会大幅衰减，而对前景物体的响应则保持不变，甚至有所提升。这一结论在昆虫的动态飞行条件下依然成立。