AIMC Topic: Behavior, Animal

Clear Filters Showing 21 to 30 of 281 articles

Balancing ethics and statistics: machine learning facilitates highly accurate classification of mice according to their trait anxiety with reduced sample sizes.

Translational psychiatry
Understanding how individual differences influence vulnerability to disease and responses to pharmacological treatments represents one of the main challenges in behavioral neuroscience. Nevertheless, inter-individual variability and sex-specific patt...

High-throughput behavioral screening in Caenorhabditis elegans using machine learning for drug repurposing.

Scientific reports
Caenorhabditis elegans is a widely used animal model for researching new disease treatments. In recent years, automated methods have been developed to extract mobility phenotypes and analyse, using statistical methods, whether there are differences b...

An integrative assay for measuring social aversion and motivation in freely behaving mice.

Cell reports methods
Social aversion is a key feature of numerous mental health disorders, yet we lack adequate behavioral tools to interrogate social aversion in model systems. Here, we developed a behavioral task-selective access to unrestricted social interaction (SAU...

Machine learning identification of tinnitus-related features in auditory peripheral spontaneous activity in a guinea pig noise-induced tinnitus model.

Hearing research
OBJECTIVES: Tinnitus affects millions globally, yet its clinical assessment relies on subjective reports, limiting diagnostic accuracy and treatment development. This study aimed to identify objective, tinnitus-related features within ensemble sponta...

Association of artificial intelligence-predicted milk yield residuals to behavioral patterns and transition success in multiparous dairy cows.

Journal of dairy science
Data-driven health monitoring based on milk yield has shown potential to identify health-perturbing events during the transition period. As a proof of principle, we explored the association between the cow's residual milk yield, that is, the differen...

Artificial intelligence tools to assess different levels of activity performed by semi-wild horses in grassland ecosystems.

Environmental monitoring and assessment
In order to understand the role of horses in ecosystems and to effectively use their grazing in the protection of grasslands, it is important to assess where they primarily stay, followed by whether these habitats are used for grazing or resting. The...

DeepEthoProfile-Rapid Behavior Recognition in Long-Term Recorded Home-Cage Mice.

eNeuro
Animal behavior is crucial for understanding both normal brain function and dysfunction. To facilitate behavior analysis of mice within their home environments, we developed DeepEthoProfile, an open-source software powered by a deep convolutional neu...

An iterative approach to identify key predictive features of fear reactivity and fearfulness in horses (Equus caballus).

Scientific reports
This study extends previous findings by applying artificial intelligence (AI) methods to a larger dataset to identify key features that predict fear reactivity (i.e., immediate reaction to fear inducing stimuli) and fearfulness (i.e., a stable person...

Gut microbiota composition is related to anxiety and aggression scores in companion dogs.

Scientific reports
There is mounting evidence for a link between behaviour and the gut microbiome in animal and human health. However, the role of the gut microbiome in the development and severity of behavioural issues in companion dogs is not yet fully understood. He...

Enhancing aquatic ecosystem monitoring through fish jumping behavior analysis and YOLOV5: Applications in freshwater fish identification.

Journal of environmental management
Traditional fish monitoring methods suffer from limited continuity and significant uncertainty in tracking population distribution. This study develops recognition rules using the inherent variability in fish jumping behavior, influenced by habitat d...