Abstract: Oxytocin plays a critical role in social behavior and maternal physiology, yet the intracellular dynamics of oxytocin-containing vesicles in neurons remain poorly characterized. Here, we combine experimental data from live cell imaging of oxytocin-containing compartments with computational analysis to investigate their mobility within hypothalamic neurons. Using machine learning-based trajectory classification, we reveal that the majority of oxytocin compartments exhibit subdiffusive motion, suggesting constraints imposed by the complex intracellular environment. This behavior likely reflects interactions with cytoskeletal structures, vesicle maturation states, or localized functional demands. Our findings provide new insights into the intracellular trafficking of neuropeptides and highlight the utility of data-driven approaches for uncovering mechanisms of neurophysiological relevance.

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