Do not go gentle into that good night, old age should burn and rave at close of day; Rage, rage against the dying of the light, though wise men at their end know dark is right, because their words had forked no lightning they, do not go gentle into that good night.
KAIST develops AI that analyzes mouse behavior to detect autism
An image of the BeheVERT model developed by a team led by professor Kim Dae-soo of the Korea Advanced Institute of Science and Technology / Courtesy of Korea Advanced Institute of Science and Technology
By Jhoo Dong-chan
A team at the Korea Advanced Institute of Science and Technology (KAIST) has developed an artificial intelligence model that interprets mouse movement patterns the way language models interpret text, and used it to independently identify behavioral traits linked to autism in mice, the university said Wednesday.
The model, called BehaVERT, was developed by a team led by professor Kim Dae-soo in KAIST's Department of Brain and Cognitive Sciences.
It converts the skeletal movement of the nose, ears, spine, limbs and tail into "tokens," the basic units language models use to process words, then feeds them into a BERT-based transformer, a type of AI architecture originally built for natural language processing.
Without being given any prior biological knowledge, the model successfully identified core social and behavior deficits in mice bred to model autism, the researchers said.
It surpassed existing benchmarks across five international standards covering social interaction, multianimal behavior, 3D motion analysis and autism-related behavior analysis.
In tests distinguishing autism-model mice — bred with a deletion of the Shank3B gene — from typical mice, the AI focused on "oral-oral contact," a finding consistent with prior research showing the mice approach others normally but show deficits in actual social interaction.
"BehaVERT is a new AI model that goes beyond simply classifying behavior to understanding its meaning," Kim said, adding that he expects it to become a key research tool for drug development, psychiatric research and behavioral genetics.
The findings, with Shin Seung-jae as first author, were published March 24 in the International Journal of Computer Vision. The research was funded by Korea's Ministry of Science and ICT and the National Research Foundation of Korea.
This article was published with the assistance of generative AI and edited by The Korea Times.