Brain-heart interactions underlying differential recovery after transient systemic anoxia

Abstract

Global cerebral anoxia is a leading cause of death and resuscitated patients often remain persistently affected by neurological deficits. While previous studies suggest that brain-heart electrophysiological interactions may predict severity and prognosis after hypoxic brain injury coma, little is known about the brain-heart dynamics at near-death. Gaining insight into these mechanisms is crucial for developing targeted interventions in critical conditions. Using a rodent model of reversible systemic anoxia (n=29, male and female rats), we investigated whether brain-heart interactions during the asphyxia onset could predict the return of brain electrical activities after resuscitation. Electrophysiological recordings confirmed that cerebral activity declines following asphyxia, coinciding with increased heart rate variability. Notably, the strong coupling between cardiac parasympathetic activity and high-frequency brain activity in the somatosensory cortex and hippocampus serves as a key predictor of a survival. Our study underscores the potential involvement of the brain-heart axis in the physiology of dying and the potential prognostic significance of the underlying mechanisms, paving the way for translational research into critical care, based on new characterizations of cardiac reflexes and brain-heart interactions. Significance StatementUnderstanding the physiological processes that determine survival and recovery following systemic anoxia is critical for improving outcomes in critical care. This study reveals that brain-heart dynamics during the onset of systemic anoxia relate to survival after resuscitation. In particular, the coupling between parasympathetic cardiac activity and high-frequency brain signals. Using a reversible anoxia rodent model, we demonstrate that early brain-heart interactions are not merely consequences of anoxia, but active markers of resilience. These findings offer a novel framework for understanding the physiology of dying and to ultimately developing prognostic tools based on real-time physiological monitoring.