Dynamical analysis reveals individuality of locomotion in goldfish

Quantitative comparison of 2D and 3D monitoring dimensions in fish behavior analysis

To improve the accuracy and efficiency of fish behavior assessment, this paper focuses on quantitatively exploring the variations and relationships between different monitoring dimensions. A systematic comparison was conducted between 3D and 2D behavioral factors using an infrared tracing system, during both day and night. Significant differences in swimming distance were observed among the different monitoring methods, as determined by two-way ANOVA and Tukey's test. A correction was applied to account for the disparities observed in 2D swimming distance, ensuring accurate measurements. These findings present a cost-effective and efficient approach for obtaining precise 3D distance data. Additionally, a kinematic factor called the "number of U-turns" was proposed to provide a more intuitive characterization of directional changes in fish swimming. Significant differences were observed between 2D and 3D data, with higher percentages of false U-turn counts and missing U-turn counts compared to correct counts in the 2D view. These findings suggest that reducing the monitoring dimension may impact the accurate estimation of swimming motion, potentially resulting in inaccurate outcomes. Finally, the statistical analyses of the non-linear properties of fractal dimension revealed significant differences among the various monitoring methods. This conclusion has practical implications for biologists and physicists, enabling them to improve the accuracy of behavioral phenotyping for organisms exhibiting 3D motion.

Nonlinear Analysis of the Hand and Foot Force-Time Profiles in the Four Competitive Swimming Strokes

Human locomotion on water depends on the force produced by the swimmer to propel the body forward. Performance of highly complex motor tasks like swimming can yield minor variations that only nonlinear analysis can be sensitive enough to detect. The purpose of the present study was to examine the nonlinear properties of the hand/feet forces and describe their variations across the four competitive swimming strokes performing segmental and full-body swimming. Swimmers performed all-out bouts of 25 m in the four swimming strokes, swimming the full-body stroke, with the arm-pull only and with the leg kicking only. Hand/foot force and swimming velocity were measured. The Higuchi's fractal dimension (HFD) and sample entropy (SampEn) were used for the nonlinear analysis of force and velocity. Both the arm-pull and leg kicking alone were found to produce similar peak and mean hand/foot forces as swimming the full-body stroke. Hand force was more complex in breaststroke and butterfly stroke; conversely, kicking conditions were more complex in front crawl and backstroke. Moreover, the arm-pull and kicking alone tended to be more complex (higher HFD) but more predictable (lower SampEn) than while swimming the full-body stroke. There was no loss of force production from segmental swimming to the full-body counterpart. In conclusion, the number of segments in action influences the nonlinear behavior of the force produced and, when combining the four limbs, the complexity of the hand/foot force tends to decrease.

Entropy and Fractal Techniques for Monitoring Fish Behaviour and Welfare in Aquacultural Precision Fish Farming-A Review

In a non-linear system, such as a biological system, the change of the output (e.g., behaviour) is not proportional to the change of the input (e.g., exposure to stressors). In addition, biological systems also change over time, i.e., they are dynamic. Non-linear dynamical analyses of biological systems have revealed hidden structures and patterns of behaviour that are not discernible by classical methods. Entropy analyses can quantify their degree of predictability and the directionality of individual interactions, while fractal dimension (FD) analyses can expose patterns of behaviour within apparently random ones. The incorporation of these techniques into the architecture of precision fish farming (PFF) and intelligent aquaculture (IA) is becoming increasingly necessary to understand and predict the evolution of the status of farmed fish. This review summarizes recent works on the application of entropy and FD techniques to selected individual and collective fish behaviours influenced by the number of fish, tagging, pain, preying/feed search, fear/anxiety (and its modulation) and positive emotional contagion (the social contagion of positive emotions). Furthermore, it presents an investigation of collective and individual interactions in shoals, an exposure of the dynamics of inter-individual relationships and hierarchies, and the identification of individuals in groups. While most of the works have been carried out using model species, we believe that they have clear applications in PFF. The review ends by describing some of the major challenges in the field, two of which are, unsurprisingly, the acquisition of high-quality, reliable raw data and the construction of large, reliable databases of non-linear behavioural data for different species and farming conditions.

Comparison of Classical Kinematics, Entropy, and Fractal Properties As Measures of Complexity of the Motor System in Swimming

The aim of this study was to compare the non-linear properties of the four competitive swim strokes. Sixty-eight swimmers performed a set of maximal 4 × 25 m using the four competitive swim strokes. The hip's speed-data as a function of time was collected with a speedo-meter. The speed fluctuation (dv), approximate entropy (ApEn) and the fractal dimension by Higuchi's method (D) were computed. Swimming data exhibited non-linear properties that were different among the four strokes (14.048 ≤ dv ≤ 39.722; 0.682 ≤ ApEn ≤ 1.025; 1.823 ≤ D ≤ 1.919). The ApEn showed the lowest value for front-crawl, followed by breaststroke, butterfly, and backstroke (P < 0.001). Fractal dimension and dv had the lowest values for front-crawl and backstroke, followed by butterfly and breaststroke (P < 0.001). It can be concluded that swimming data exhibits non-linear properties, which are different among the four competitive swimming strokes.

Casting a wider fish net on animal models in neuropsychiatric research

Neuropsychiatric disorders, such as schizophrenia, are associated with abnormal brain development. In this review, we discuss how studying dimensional components of these disorders, or endophenotypes, in a wider range of animal models will deepen our understanding of how interactions between biological and environmental factors alter the trajectory of neurodevelopment leading to aberrant behavior. In particular, we discuss some of the advantages of incorporating studies of brain and behavior using a range of teleost fish species into current neuropsychiatric research. From the perspective of comparative neurobiology, teleosts share a fundamental pattern of neurodevelopment and functional brain organization with other vertebrates, including humans. These shared features provide a basis for experimentally probing the mechanisms of disease-associated brain abnormalities. Moreover, incorporating information about how behaviors have been shaped by evolution will allow us to better understand the relevance of behavioral variation to determine their physiological underpinnings. We believe that exploiting the conservation in brain development across vertebrate species, and the rich diversity of fish behavior in lab and natural populations will lead to significant new insights and a holistic understanding of the neurobiological systems implicated in neuropsychiatric disorders.

Effect of sodium hypochlorite on zebrafish swimming behavior estimated by fractal dimension analysis

The behavioral responses of zebrafish (Danio rerio) to sublethal concentrations of sodium hypochlorite (NaClO)-based household bleach were quantified in order to index toxicity of the solution. The swimming behavior of zebrafish was captured using nonplanar 3D stereocameras in combination with 3D coordinate computation with perspective correction (3DCCPC) to compute for actual 3D coordinates. Swimming trajectory and velocity were quantified by fractal dimension analysis. The results showed that, under incremental concentrations of NaClO-based aqueous solutions with the maximum of 0.005% v/v, the fractal dimension of swimming velocity trended to increase with the concentration. The fractal dimension of swimming trajectories trended to increase with pH. Hence, the results have proven that the system is a useful tool to indicate behavioral changes, which may be implemented in biomonitoring systems for acute toxicity bioassay.

Quantitative characterization of animal behavior following blast exposure

The simplest approach to quantifying animal behavior begins by identifying a list of discrete behaviors and observing the animal's behavior at regular intervals for a specified period of time. The behavioral distribution (the fraction of observations corresponding to each behavior) is then determined. This is an incomplete characterization of behavior, and in some instances, mild injury is not reflected by statistically significant changes in the distribution even though a human observer can confidently and correctly assert that the animal is not behaving normally. In these circumstances, an examination of the sequential structure of the animal's behavior may, however, show significant alteration. This contribution describes procedures derived from symbolic dynamics for quantifying the sequential structure of animal behavior. Normalization procedures for complexity estimates are presented, and the limitations of complexity measures are discussed.