May Christina E, Cellini Benjamin, van Breugel Floris, Nagel Katherine I
Department of Neuroscience, NYU Grossman School of Medicine, New York, NY 10016, USA.
Department of Mechanical Engineering, University of Nevada Reno, Reno, NV 89512, USA.
bioRxiv. 2025 May 9:2025.05.09.653128. doi: 10.1101/2025.05.09.653128.
External forces shape navigation, but cannot be directly measured by an animal in motion. How the brain integrates multi-modal cues to estimate external forces remains unclear. Here we investigated the representation of multi-modal self-motion cues across columnar inputs to the fly navigation center, known as PFNs. We find that one type integrates optic flow and airflow direction signals with distinct dynamics. We reveal airspeed encoding by a different type. Based on these data, we construct and validate models of how multi-sensory dynamics are encoded across PFNs, allowing us to simulate neural responses during rapid flight maneuvers. Applying a nonlinear observability analysis to these responses, we show that PFN representations during active maneuvers are sufficient to decode the direction of an external force (wind) during free flight. Our work provides evidence that active sensation, combined with multisensory encoding, can allow a compact nervous system to infer a property of the external world that cannot be directly measured by a single sensory system.
外力塑造导航，但运动中的动物无法直接测量这些外力。大脑如何整合多模态线索来估计外力仍不清楚。在这里，我们研究了跨柱状输入到果蝇导航中心（称为PFNs）的多模态自我运动线索的表征。我们发现一种类型以不同的动态方式整合视觉流和气流方向信号。我们揭示了另一种类型对空速的编码。基于这些数据，我们构建并验证了跨PFNs对多感官动态进行编码的模型，使我们能够模拟快速飞行机动过程中的神经反应。对这些反应进行非线性可观测性分析，我们表明主动机动过程中的PFN表征足以解码自由飞行过程中外力（风）的方向。我们的工作提供了证据，即主动感知与多感官编码相结合，可以使紧凑的神经系统推断出单个感官系统无法直接测量的外部世界属性。
