Detection of EEG dynamic complex patterns in disorders of consciousness

作者：Gabriel Della Bella, Di Zang, Peng Gui, Diego M. Mateos, Jacobo Sitt, Tristán Bekinschtein, Dragana Manasova, Benjamine Sarton, Fabrice Ferré, Stein Silva, Pedro W. Lamberti, Xuehai Wu, Ying Mao, Liping Wang, Pablo Barttfeld · 发表于：Communications Biology · 年份：2025 · DOI：10.1038/s42003-025-08666-9 · 被引用次数：6 · 研究领域：Traumatic Brain Injury Research、Functional Brain Connectivity Studies、EEG and Brain-Computer Interfaces

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. EEG-based brain state modeling reveals connectivity patterns linked to consciousness levels and recovery, enabling real-time bedside assessment in patients with disorders of consciousness.