Loligo泳槽：超越推进：肌肉本体感觉使鱼类身体具备流体动力感知能力
Abstract
In aquatic environments, muscle activity in free-swimming fishes not only propels body undulations to generate thrust but also serves as proprioceptive sensors for detecting surrounding fluid dynamics. Testing the proprioceptive function of the muscle is challenging owing to its deep integration with swimming activity. To address this, we introduce an experimental platform that records up to 12-channel electromyography (EMG) signals synchronized with detailed kinematics in koi and carp. We first apply various neural networks to map densely collected EMG signals to synchronized video-based body kinematics, thereby validating our EMG collection system. We then compare EMG data from fishes swimming in various laminar flows and within Kármán vortices. Our results show that the phase of muscle activity consistently precedes body kinematics in various laminar flows. While within Kármán vortices, we observe a mixed phase relationship, where muscle activity sometimes leads and at other times lags behind body kinematics. This suggests that fishes may use muscle proprioceptive sensing when interacting with complex flows, such as nearby vortices. Our research not only introduces novel methods for biological EMG studies but also offers insights that could influence the design of bio-inspired underwater sensory systems.
摘要：
在水生环境中，自由游泳鱼类的肌肉活动不仅推动身体波动以产生推力，还充当检测周围流体动力学的本体感觉传感器。由于肌肉与游泳活动的深度融合，测试肌肉的本体感觉功能具有挑战性。为了解决这个问题，我们介绍了一个实验平台，该平台可以记录多达12个通道的肌电图（EMG）信号，这些信号与锦鲤和鲤鱼的详细运动学同步。我们首先应用各种神经网络将密集收集的EMG信号映射到基于同步视频的身体运动学，从而验证我们的EMG收集系统。然后，我们比较了在各种层流和卡门涡流中游泳的鱼类的肌电图数据。我们的结果表明，在各种层流中，肌肉活动的阶段始终先于身体运动学。在卡门涡旋中，我们观察到一种混合相位关系，其中肌肉活动有时领先，有时落后于身体运动学。这表明，鱼类在与复杂的水流（如附近的漩涡）相互作用时可能会使用肌肉本体感觉。我们的研究不仅为生物肌电研究引入了新方法，还提供了可能影响仿生水下传感系统设计的见解。
关键词：本体感觉、鱼类游泳中的流体力学、肌电图到运动学的映射，Loligo泳槽，Swimming tunnel，生物学、生态学、系统生物学
