Cross-species behavior analysis with attention-based domain-adversarial deep neural networks.

ABSTRACT: Since the variables inherent to various diseases cannot be controlled directly in humans, behavioral dysfunctions have been examined in model organisms, leading to better understanding their underlying mechanisms. However, because the spatial and temporal scales of animal locomotion vary widely among species, conventional statistical analyses cannot be used to discover knowledge from the locomotion data. We propose a procedure to automatically discover locomotion features shared among animal species by means of domain-adversarial deep neural networks. Our neural network is equipped with a function which explains the meaning of segments of locomotion where the cross-species features are hidden by incorporating an attention mechanism into the neural network, regarded as a black box. It enabl

SUBMITTER: Maekawa T 

PROVIDER: S-EPMC8448872 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature