Non-contact behavioral study through intelligent image analysis is becoming increasingly vital in animal neuroscience and ethology. The shift from traditional "black box" methods to more open and intelligent approaches is driven by advances in deep l...
ETHNOPHARMACOLOGICAL RELEVANCE: Niuhuang Jiedu (NHJD) is a Chinese medicine prescription containing realgar (AsS), which is neurotoxic, and seven other traditional Chinese medicines (TCMs). However, whether the multiple TCMs contained in NHJD can mit...
The Morris Water Maze (MWM) is a widely used behavioral test to assess the spatial learning and memory of animals, particularly valuable in studying neurodegenerative disorders such as Alzheimer's disease. Traditional methods for analyzing MWM experi...
There is great interest in using genetically tractable organisms such as to gain insights into the regulation and function of sleep. However, sleep phenotyping in has largely relied on simple measures of locomotor inactivity. Here, we present FlyVI...
Revealing the evolved mechanisms that give rise to collective behavior is a central objective in the study of cellular and organismal systems. In addition, understanding the algorithmic basis of social interactions in a causal and quantitative way of...
In this study, we explore machine learning models for predicting emotional states in ridden horses. We manually label the images to train the models in a supervised manner. We perform data exploration and use different cropping methods, mainly based ...
Proceedings of the National Academy of Sciences of the United States of America
40198707
Engineering small autonomous agents capable of operating in the microscale environment remains a key challenge, with current systems still evolving. Our study explores the fruit fly, , a classic model system in biology and a species adept at microsca...
Despite advancements in video-based behaviour analysis and detection models for various species, existing methods are suboptimal to detect macaques in complex laboratory environments. To address this gap, we present MacqD, a modified Mask R-CNN model...
Deep learning-based methods have advanced animal pose estimation, enhancing accuracy, and efficiency in quantifying animal behavior. However, these methods frequently experience tracking drift, where noise-induced jumps in body point estimates compro...