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DECODING THE OXYTOCINERGIC AND BEHAVIORAL SIGNATURE OF MILK EJECTION
Zhihua Gaoand 1 co-author
Zhejiang University
FENS Forum 2026 (2026)
Barcelona, Spain
Board PS02-07PM-030
Presentation
Date TBA
Board: PS02-07PM-030
Event Information
Poster Board
PS02-07PM-030
Poster
View posterAbstract
Oxytocin-mediated milk ejection (ME) is pivotal to effective breastfeeding and productive health, yet behaviorally decoding and revealing neural mechanisms of ME remains challenging. Here, we combined in vivo calcium imaging and intramammary pressure recording to uncover the temporal connections between episodic activity of oxytocin neurons and ME in conscious lactating rats. Leveraging the association and behavioral responses in dam and pup, we developed a supervised machine learning framework (ME Decoder) to enable automated analyses of ME. Inspired by its interpretable features, we defined the activity-coupled dam-pup interactions (ADPI), manifested by high kyphosis of the dam followed by pup treading and stretch, as the behavioral signatures of ME. By ME Decoder and ADPI analyses, we detected reduced ME and verified the validity these approaches. Our study uncovers the oxytocinergic and behavioral signatures of ME and provides a scalable approach for further investigation.
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