Oxytocin receptor blockade reduces milk ejection but not oxytocinergic neuron activity in lactating rats

Effective breastfeeding and reproductive health critically depend on oxytocin-mediated milk ejection (ME). However, the precise behavioral decoding and neural mechanisms underlying ME have remained challenging to unravel. Current research faces difficulties in establishing clear temporal links between episodic activity of oxytocin neurons and the complex dam-pup interactions that signify ME. This knowledge gap hinders our understanding of issues like insufficient milk supply, which often stems from impaired ME, and limits the development of targeted interventions.

Researchers combined in vivo calcium imaging and intramammary pressure recording in conscious lactating rats to simultaneously monitor oxytocin neuron activity and ME. They developed a supervised machine learning framework called ME Decoder, leveraging coordinated dam-pup behavioral responses. This framework enabled automated analysis of ME. The study then defined "activity-coupled dam-pup interactions (ADPI)" as specific behavioral signatures. A control arm involved systemic blockade of oxytocin receptors to assess its impact on ME and neuronal activity.

The study successfully uncovered the temporal connections between episodic activity of oxytocin neurons and milk ejection (ME) in conscious lactating rats. The ME Decoder and ADPI analyses accurately identified specific behavioral signatures of ME, characterized by pronounced kyphosis in dams, followed by pup treading and stretching. These behavioral cues, previously challenging to quantify, now provide a reliable, observable marker for ME events. The machine learning framework proved effective in automating the analysis of these complex dam-pup interactions.

Systemic blockade of oxytocin receptors led to significantly reduced ME, yet remarkably, the activity of oxytocinergic neurons remained unaffected.