AIMC Topic: Behavior, Animal

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Nature's All-in-One: Multitasking Robots Inspired by Dung Beetles.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Dung beetles impressively coordinate their 6 legs to effectively roll large dung balls. They can also roll dung balls varying in the weight on different terrains. The mechanisms underlying how their motor commands are adapted to walk and simultaneous...

Deep learning-assisted detection of psychoactive water pollutants using behavioral profiling of zebrafish embryos.

Journal of hazardous materials
Water pollution poses a significant risk to the environment and human health, necessitating the development of innovative detection methods. In this study, a series of representative psychoactive compounds were selected as model pollutants, and a new...

Machine learning reveals prominent spontaneous behavioral changes and treatment efficacy in humanized and transgenic Alzheimer's disease models.

Cell reports
Computer-vision and machine-learning (ML) approaches are being developed to provide scalable, unbiased, and sensitive methods to assess mouse behavior. Here, we used the ML-based variational animal motion embedding (VAME) segmentation platform to ass...

Development and validation of machine-learning models for monitoring individual behaviors in group-housed broiler chickens.

Poultry science
Animals' individual behavior is commonly monitored by live or video observation by a person. This can be labor intensive and inconsistent. An alternative is the use of machine learning-based computer vision systems. The objectives of this study were ...

Automated analysis of a novel object recognition test in mice using image processing and machine learning.

Behavioural brain research
The novel object recognition test (NORT) is one of the most commonly employed behavioral tests in experimental animals designed to evaluate an animal's interest in and recognition of novelty. However, manual procedures, which rely on researchers' obs...

Artificial intelligence-based analysis of behavior and brain images in cocaine-self-administered marmosets.

Journal of neuroscience methods
BACKGROUND: The sophisticated behavioral and cognitive repertoires of non-human primates (NHPs) make them suitable subjects for studies involving cocaine self-administration (SA) schedules. However, ethical considerations, adherence to the 3Rs princi...

Deep learning dives: Predicting anxiety in zebrafish through novel tank assay analysis.

Physiology & behavior
Behavior is fundamental to neuroscience research, providing insights into the mechanisms underlying thoughts, actions and responses. Various model organisms, including mice, flies, and fish, are employed to understand these mechanisms. Zebrafish, in ...

The Use of Triaxial Accelerometers and Machine Learning Algorithms for Behavioural Identification in Domestic Dogs (): A Validation Study.

Sensors (Basel, Switzerland)
Assessing the behaviour and physical attributes of domesticated dogs is critical for predicting the suitability of animals for companionship or specific roles such as hunting, military or service. Common methods of behavioural assessment can be time ...

Tracking perching behavior of cage-free laying hens with deep learning technologies.

Poultry science
Providing perches in cage-free (CF) housing offers significant benefits for laying hens, such as improved leg muscle development, bone health, reduced abdominal fat, and decreased fear and aggression. A precise detection method is essential to ensure...

KineWheel-DeepLabCut Automated Paw Annotation Using Alternating Stroboscopic UV and White Light Illumination.

eNeuro
Uncovering the relationships between neural circuits, behavior, and neural dysfunction may require rodent pose tracking. While open-source toolkits such as DeepLabCut have revolutionized markerless pose estimation using deep neural networks, the trai...