Loligo泳槽：超越推進：肌肉本體感覺使魚類身體具備流體動力感知能力
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：
在水生環境中，自由游泳魚類的肌肉活動不僅推動身體波動以產生推力，還充當檢測周圍流體動力學的本體感覺傳感器。由于肌肉與游泳活動的深度融合，測試肌肉的本體感覺功能具有挑戰性。為了解決這個問題，我們介紹了一個實驗平臺，該平臺可以記錄多達12個通道的肌電圖（EMG）信號，這些信號與錦鯉和鯉魚的詳細運動學同步。我們首先應用各種神經網絡將密集收集的EMG信號映射到基于同步視頻的身體運動學，從而驗證我們的EMG收集系統。然后，我們比較了在各種層流和卡門渦流中游泳的魚類的肌電圖數據。我們的結果表明，在各種層流中，肌肉活動的階段始終先于身體運動學。在卡門渦旋中，我們觀察到一種混合相位關系，其中肌肉活動有時領先，有時落后于身體運動學。這表明，魚類在與復雜的水流（如附近的漩渦）相互作用時可能會使用肌肉本體感覺。我們的研究不僅為生物肌電研究引入了新方法，還提供了可能影響仿生水下傳感系統設計的見解。
關鍵詞：本體感覺、魚類游泳中的流體力學、肌電圖到運動學的映射，Loligo泳槽，Swimming tunnel，生物學、生態學、系統生物學
