Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires 1428, Argentina.
Department of Neurology, Christian Albrechts University, Kiel 24118, Germany.
Chaos. 2021 Sep;31(9):093117. doi: 10.1063/5.0046047.
The dynamic core hypothesis posits that consciousness is correlated with simultaneously integrated and differentiated assemblies of transiently synchronized brain regions. We represented time-dependent functional interactions using dynamic brain networks and assessed the integrity of the dynamic core by means of the size and flexibility of the largest multilayer module. As a first step, we constrained parameter selection using a newly developed benchmark for module detection in heterogeneous temporal networks. Next, we applied a multilayer modularity maximization algorithm to dynamic brain networks computed from functional magnetic resonance imaging (fMRI) data acquired during deep sleep and under propofol anesthesia. We found that unconsciousness reconfigured network flexibility and reduced the size of the largest spatiotemporal module, which we identified with the dynamic core. Our results represent a first characterization of modular brain network dynamics during states of unconsciousness measured with fMRI, adding support to the dynamic core hypothesis of human consciousness.
动态核心假说假设意识与大脑区域的瞬态同步、同时整合和分化的集合相关。我们使用动态脑网络来表示随时间变化的功能交互作用,并通过最大多层模块的大小和灵活性来评估动态核心的完整性。作为第一步,我们使用新开发的用于异构时变网络中模块检测的基准来约束参数选择。接下来,我们应用了一种多层模块化最大化算法,对从深度睡眠和异丙酚麻醉期间获得的功能磁共振成像 (fMRI) 数据计算的动态脑网络进行了分析。我们发现,无意识状态重新配置了网络的灵活性并减少了最大时空模块的大小,我们将该模块识别为动态核心。我们的研究结果代表了用 fMRI 测量的无意识状态下脑网络动力学的首次特征化,为人类意识的动态核心假说提供了支持。