Quantification of the influence of drugs on zebrafish larvae swimming kinematics and energetics

The use of zebrafish larvae has aroused wide interest in the medical field for its potential role in the development of new therapies. The larvae grow extremely quickly and the embryos are nearly transparent which allows easy examination of its internal structures using fluorescent imaging techniques. Medical treatment of zebrafish larvae can directly influence its swimming behaviours. These behaviour changes are related to functional changes of central nervous system and transformations of the zebrafish body such as muscle mechanical power and force variation, which cannot be measured directly by pure experiment observation. To quantify the influence of drugs on zebrafish larvae swimming behaviours and energetics, we have developed a novel methodology to exploit intravital changes based on observed zebrafish locomotion. Specifically, by using an in-house MATLAB code to process the recorded live zebrafish swimming video, the kinematic locomotion equation of a 3D zebrafish larvae was obtained, and a customised Computational Fluid Dynamics tool was used to solve the fluid flow around the fish model which was geometrically the same as experimentally tested zebrafish. The developed methodology was firstly verified against experiment, and further applied to quantify the fish internal body force, torque and power consumption associated with a group of normal zebrafish larvae vs. those immersed in acetic acid and two neuroactive drugs. As indicated by our results, zebrafish larvae immersed in 0.01% acetic acid display approximately 30% higher hydrodynamic power and 10% higher cost of transport than control group. In addition, 500 μM diphenylhydantoin significantly decreases the locomotion activity for approximately 50% lower hydrodynamic power, whereas 100 mg/L yohimbine has not caused any significant influences on 5 dpf zebrafish larvae locomotion. The approach has potential to evaluate the influence of drugs on the aquatic animal’s behaviour changes and thus support the development of new analgesic and neuroactive drugs

Fast simulation of animal locomotion: Lamprey swimming

© 2006 by International Federation for Information Processing. All rights reserved. Biologically realistic computer simulation of vertebrate locomotion is an interesting and challenging problem with applications in computer graphics and robotics. One current approach simulates a relatively simple vertebrate, the lamprey, using recurrent neural networks for the spine and a physical model for the body. The model is realized as a system of differential equations. The drawback with this approach is the slow speed of simulation. This paper describes two approaches to speeding up simulation of lamprey locomotion without sacrificing too much biological realism: (i) use of superior numerical integration algorithms and (ii) simplifications to the neural architecture of the lamprey

Hydrodynamics of Biomimetic Marine Propulsion and Trends in Computational Simulations

[Abstract] The aim of the present paper is to provide the state of the works in the field of hydrodynamics and computational simulations to analyze biomimetic marine propulsors. Over the last years, many researchers postulated that some fish movements are more efficient and maneuverable than traditional rotary propellers, and the most relevant marine propulsors which mimic fishes are shown in the present work. Taking into account the complexity and cost of some experimental setups, numerical models offer an efficient, cheap, and fast alternative tool to analyze biomimetic marine propulsors. Besides, numerical models provide information that cannot be obtained using experimental techniques. Since the literature about trends in computational simulations is still scarce, this paper also recalls the hydrodynamics of the swimming modes occurring in fish and summarizes the more relevant lines of investigation of computational models

A Lagrangian model of copepod dynamics: Clustering by escape jumps in turbulence

Planktonic copepods are small crustaceans that have the ability to swim by quick powerful jumps. Such an aptness is used to escape from high shear regions, which may be caused either by flow per- turbations, produced by a large predator (i.e., fish larvae), or by the inherent highly turbulent dynamics of the ocean. Through a combined experimental and numerical study, we investigate the impact of jumping behaviour on the small-scale patchiness of copepods in a turbulent environment. Recorded velocity tracks of copepods displaying escape response jumps in still water are here used to define and tune a Lagrangian Copepod (LC) model. The model is further employed to simulate the behaviour of thousands of copepods in a fully developed hydrodynamic turbulent flow obtained by direct numerical simulation of the Navier-Stokes equations. First, we show that the LC velocity statistics is in qualitative agreement with available experimental observations of copepods in tur- bulence. Second, we quantify the clustering of LC, via the fractal dimension $D_2$. We show that $D_2$ can be as low as ~ 2.3 and that it critically depends on the shear-rate sensitivity of the proposed LC model, in particular it exhibits a minimum in a narrow range of shear-rate values. We further investigate the effect of jump intensity, jump orientation and geometrical aspect ratio of the copepods on the small-scale spatial distribution. At last, possible ecological implications of the observed clustering on encounter rates and mating success are discussedComment: 13 pages, 9 figure

Robust simulation of lamprey tracking

Biologically realistic computer simulation of vertebrates is a challenging problem with exciting applications in computer graphics and robotics. Once the mechanics of locomotion are available it is interesting to mediate this locomotion with higher level behavior such as target tracking. One recent approach simulates a relatively simple vertebrate, the lamprey, using recurrent neural networks to model the central pattern generator of the spine and a physical model for the body. Target tracking behavior has also been implemented for such a model. However, previous approaches suffer from deficiencies where particular orientations of the body to the target cause the central pattern generator to shutdown. This paper describes an approach to making target tracking more robust. © Springer-Verlag Berlin Heidelberg 2006