Della Bella Gabriel A, Zang Di, Gui Peng, Mateos Diego M, Sitt Jacobo D, Bekinschtein Tristan A, Manasova Dragana, Sarton Benjamine, Ferre Fabrice, Silva Stein, Lamberti Pedro W, Wu Xuehai, Mao Ying, Wang Liping, Barttfeld Pablo
Cognitive Science Group. Instituto de Investigaciones Psicológicas (IIPsi,CONICET-UNC), Facultad de Psicología, Universidad Nacional de Córdoba, Córdoba, Argentina.
Facultad de Matemática, Astronomía, Física y Computación (FaMAF), Universidad Nacional de Córdoba, Córdoba, Argentina.
Commun Biol. 2025 Aug 12;8(1):1204. doi: 10.1038/s42003-025-08666-9.
Diagnosing Disorders of Consciousness (DoC) remains a critical challenge in cognitive neuroscience. In this study we introduce Electroencephalography (EEG)-based brain states as a real-time, bedside tool for assessing dynamic brain connectivity in DoC patients. We analyze EEG data from 237 acute and chronic DoC patients across three centers, identifying five recurrent functional connectivity patterns. The probability of these patterns correlated strongly with consciousness levels, with high-entropy patterns exclusive to healthy controls and low-entropy patterns prevalent in severe DoC, predicting individual recovery outcomes. Real-time testing validated reliable bedside detection of these patterns. Our findings demonstrate EEG's potential for monitoring dynamic brain connectivity, offering insights into the neural basis of consciousness and advancing diagnostic strategies for DoC.
诊断意识障碍（DoC）仍然是认知神经科学中的一项关键挑战。在本研究中，我们引入基于脑电图（EEG）的脑状态作为一种实时床边工具，用于评估DoC患者的动态脑连接性。我们分析了来自三个中心的237例急性和慢性DoC患者的EEG数据，识别出五种反复出现的功能连接模式。这些模式的概率与意识水平密切相关，高熵模式仅见于健康对照，而低熵模式在严重DoC中普遍存在，可预测个体恢复结果。实时测试验证了这些模式在床边的可靠检测。我们的研究结果证明了EEG在监测动态脑连接性方面的潜力，为意识的神经基础提供了见解，并推进了DoC的诊断策略。
