Wei Xiao1,2,3 · Qian Zheng2,4 · Yang Wang2,4 · Ying Yuan1,2,3 · Yuge Chen1,2,3 · Tianxing Zheng5  · Yuzhu Chen1  · Yijia Gao6  · Bingrui Song1  · Bin Zhang1,2,3  · Liyao Qiu1,2,3  · Linghui Zeng7  · Huan Ma1,2,3,8 · Colin H. Brown9  · Shumin Duan1,2,3 · Gang Pan2,4 · Zhihua Gao1,2,3

1 Department of Neurology of Second Affiliated Hospital and Liangzhu Laboratory, School of Brain Science and Brain Medicine, Zhejiang University School of Medicine, Hangzhou 310058, China 

2 State Key Laboratory of Brain‑machine Intelligence, MOE Frontier Science Center for Brain Science and Brain‑machine Integration, Zhejiang University, Hangzhou 311121, China 

3 NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China 

4 College of Computer Science and Technology, Zhejiang University, Hangzhou 310058, China 

5 Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China 

6 College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China 

7 Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou 310015, China 

8 Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310013, China 

9 Faculty of Biomedical Sciences, Centre for Neuroendocrinology and Department of Physiology, University of Otago, Dunedin 9054, New Zealand

Abstract

Oxytocin-mediated milk ejection (ME) is pivotal to effective breastfeeding and reproductive 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 coordinated behavioral responses of dams and pups, 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 pronounced kyphosis in dams, followed by pup treading and stretching, as the behavioral signatures of ME. By ME Decoder and ADPI analyses, we detected reduced ME but unaffected activity of oxytocinergic neurons after systemic blockade of oxytocin receptors. Our study uncovers the oxytocinergic and behavioral signatures of ME and provides a generalizable approach for further investigation.

Keywords

Oxytocin; Lactation; Neuronal activity; Milk ejection; Deep learning framework; Neural pathways

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