意识
听力学
心理学
沟通
语音识别
计算机科学
神经科学
医学
作者
Andria Pelentritou,Christian Pfeiffer,Manuela Iten,Matthias Hænggi,Frédéric Zubler,Sophie Schwartz,Marzia De Lucia
标识
DOI:10.1073/pnas.2505454122
摘要
In healthy awake individuals, the neural processing of bodily signals is not only essential for survival but can also influence perception and compete with external stimulus processing. Yet, the mechanism underlying this bidirectional processing of bodily and external stimuli, as well as its persistence or modulation in unconscious states, remains largely unknown. Here, we investigated the role of cardiac activity on auditory regularity processing in coma. We recorded continuous electroencephalography and electrocardiography in 48 comatose patients on the first day after cardiac arrest during a closed-loop auditory paradigm. We tested whether sounds presented in synchrony with the ongoing heartbeat and sounds presented with fixed, isochronous intervals, would facilitate auditory processing, compared to an asynchronous sequence with variable heartbeat-to-sound and sound-to-sound intervals and a baseline without auditory stimulation. To assess sound prediction based on sequence regularity, we introduced sound omissions within the sequences, violating expected auditory patterns. In coma survivors only, the neural omission response differed in the synchronous against both control conditions. These results were corroborated by a multivariate decoding analysis of the single-trial neural responses to the synchronous omissions and baseline wherein survivors exhibited a higher degree of cardio-audio regularity encoding compared to nonsurvivors. Furthermore, omissions within the synchronous sequence elicited a heart rate deceleration exclusively in coma survivors, which was predictive of patient outcome. We show that the unconscious human brain infers on the temporal relationship across cardiac and auditory inputs and that the neural and cardiac correlates of cardio-audio regularity encoding are predictive of patient outcome.
科研通智能强力驱动
Strongly Powered by AbleSci AI