November 27, 2020

Data-driven analysis of rat pup behavior reveals novel effects of maternal pre-conception exposure to nicotine

We present a deep neural network for data-driven analyses of infant rat behavior in an open field task. The network was applied to study the effect of maternal nicotine exposure prior to conception on offspring motor development. The neural network outperformed human expert designed animal locomotion measures in distinguishing rat pups born of preconception nicotine dams versus control dams. Notably, the network discovered novel movement alterations in posture, movement initiation and a stereotypy in warm-up behavior (repetition of movement along specific dimensions) that were the most predictive of nicotine exposure. This suggests that maternal preconception nicotine exposure delays and alters offspring motor development. In summary, we demonstrated that a deep neural network can automatically assess animal behavior with high accuracy, and that it offers a novel, data-driven approach to investigating brain alterations in development

 bioRxiv Subject Collection: Neuroscience

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