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

Neurodevelopmental disorders can stem from pharmacological, genetic, or environmental causes and early diagnosis is often a key to successful treatment. To improve early detection of neurological motor impairments, we developed a deep neural network for data-driven analyses. The network was applied to study the effect of maternal nicotine exposure prior to conception on 10-day-old rat pup motor behavior in an open field task. Female Long-Evans rats were administered nicotine (15 mg/L) in sweetened drinking water (1% sucralose) for seven consecutive weeks immediately prior to mating. The neural network outperformed human expert designed animal locomotion measures in distinguishing rat pups born to nicotine exposed dams vs. control dams (87 vs. 64% classification accuracy). Notably, the network discovered novel movement alterations in posture, movement initiation and a stereotypy in “warm-up” behavior (repeated movements along specific body dimensions) that were predictive of nicotine exposure. The results suggest novel findings that maternal preconception nicotine exposure delays and alters offspring motor development. Similar behavioral symptoms are associated with drug-related causes of disorders such as autism spectrum disorder and attention-deficit/hyperactivity disorder in human children. Thus, the identification of motor impairments in at-risk offspring here shows how neuronal networks can guide the development of more accurate behavioral tests to earlier diagnose symptoms of neurodevelopmental disorders in infants and children.

Prenatal stress (PS) can impact fetal brain structure and function and lead to higher vulnerability to neurodevelopmental and neuropsychiatric disorders. To understand how PS alters evoked and spontaneous cortical activity and intrinsic brain functional connectivity, mesoscale voltage imaging was performed in adult C57BL/6NJ mice who were exposed to an auditory stress paradigm on gestational days 12-16. PS mice demonstrated a four-fold higher basal corticosterone level, reduced amplitude of all cortical sensory-evoked responses (visual, auditory, whisker, forelimb, and hindlimb), decreased overall resting-state functional connectivity, declined network efficiency, reduced inter-module connectivity, enhanced intra-module connectivity, and altered frequency of auditory and forelimb spontaneous sensory motifs relative to control animals. In fact, for PS, the resting-state functional connectivity changes drastically towards an overall less connected structure that consists of largely disjoint but tight modules, leading to a declined network efficiency. The changes in structure also indicate that the posterior secondary motor, primary barrel, and secondary hindlimb cortices are cortical areas with higher susceptibility to dysfunction. Our findings highlight the PS modulation of brain functional connectivity that can pose offspring at risk for stress-related neuropsychiatric disorders.

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