respyra: A General-Purpose Respiratory Tracking Toolbox for Interoception Research

Interoception research has focused primarily on perception, with comparatively little attention to the control of bodily state. Respiration offers a tractable entry point to this gap, as breathing is continuously sensed yet voluntarily regulated. We present respyra, an open-source Python toolbox for respiratory tracking experiments that integrates PsychoPy with a low-cost wireless respiration belt to enable closed-loop breathing control with real-time visual feedback. Participants track prescribed breathing waveforms while the system synchronously records respiratory output and target dynamics. Respyra implements visuomotor gain perturbations that distort visual feedback while preserving task goals, allowing dissociation of baseline respiratory control from adaptive responses to altered sensorimotor mappings. In a proof-of-concept study, tracking was stable under veridical feedback, systematically disrupted under perturbation, showed trial-level adaptation, and demonstrated good reliability (Spearman–Brown = 0.86). By extending visuomotor learning paradigms to respiration, respyra provides a practical platform for studying respiratory control, sensorimotor adaptation, and embodied regulation. The toolbox is distributed as an open-source Python package with a fully documented API and reproducible example experiments.