A deep neural network for automatic prediction of mouse behavior from ultrasonic vocalizations emitted during social interaction test

The study of ultrasonic vocalizations (USVs) is fundamental as they represent a primary form of communication in mice, offering valuable insights into their social behaviors and underlying neural processes. This study introduces the first deep learning system designed to predict mouse behavior using only USVs as input. Applied to both wild-type (WT) and p50 knockout (KO) transgenic mice that present behavioral deficits, our results reveal a clear correlation between mouse communication and behavior. We also observed asymmetric cross-genotype generalization: models trained on WT USVs generalize to KO mice, whereas models trained on KO data fail to generalize to WT, suggesting differences in the distribution of spectrotemporal patterns between genotypes.