Chennu Srivas, Finoia Paola, Kamau Evelyn, Allanson Judith, Williams Guy B, Monti Martin M, Noreika Valdas, Arnatkeviciute Aurina, Canales-Johnson Andrés, Olivares Francisco, Cabezas-Soto Daniela, Menon David K, Pickard John D, Owen Adrian M, Bekinschtein Tristan A
Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom; Medical Research Council, Cognition and Brain Sciences Unit, Cambridge, United Kingdom.
Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom.
PLoS Comput Biol. 2014 Oct 16;10(10):e1003887. doi: 10.1371/journal.pcbi.1003887. eCollection 2014 Oct.
Theoretical advances in the science of consciousness have proposed that it is concomitant with balanced cortical integration and differentiation, enabled by efficient networks of information transfer across multiple scales. Here, we apply graph theory to compare key signatures of such networks in high-density electroencephalographic data from 32 patients with chronic disorders of consciousness, against normative data from healthy controls. Based on connectivity within canonical frequency bands, we found that patient networks had reduced local and global efficiency, and fewer hubs in the alpha band. We devised a novel topographical metric, termed modular span, which showed that the alpha network modules in patients were also spatially circumscribed, lacking the structured long-distance interactions commonly observed in the healthy controls. Importantly however, these differences between graph-theoretic metrics were partially reversed in delta and theta band networks, which were also significantly more similar to each other in patients than controls. Going further, we found that metrics of alpha network efficiency also correlated with the degree of behavioural awareness. Intriguingly, some patients in behaviourally unresponsive vegetative states who demonstrated evidence of covert awareness with functional neuroimaging stood out from this trend: they had alpha networks that were remarkably well preserved and similar to those observed in the controls. Taken together, our findings inform current understanding of disorders of consciousness by highlighting the distinctive brain networks that characterise them. In the significant minority of vegetative patients who follow commands in neuroimaging tests, they point to putative network mechanisms that could support cognitive function and consciousness despite profound behavioural impairment.
意识科学的理论进展提出,意识伴随着平衡的皮层整合与分化,这是由跨多个尺度的高效信息传递网络实现的。在此,我们应用图论来比较32例慢性意识障碍患者的高密度脑电图数据中此类网络的关键特征,并与健康对照的标准数据进行对比。基于标准频段内的连通性,我们发现患者的网络局部和全局效率降低,且α频段的枢纽节点较少。我们设计了一种新的地形学指标——模块化跨度,结果显示患者的α网络模块在空间上也受到限制,缺乏健康对照中常见的结构化长距离相互作用。然而重要的是,图论指标之间的这些差异在δ和θ频段网络中部分得到逆转,而且患者的这些频段网络彼此之间也比对照更为相似。进一步研究发现,α网络效率指标也与行为意识程度相关。有趣的是,一些行为无反应的植物状态患者在功能神经影像学检查中显示出隐性意识的证据,他们并不符合这一趋势:他们的α网络保存得非常好,与对照中观察到的相似。综合来看,我们的研究结果通过突出表征意识障碍的独特脑网络,为当前对意识障碍的理解提供了信息。在神经影像学检查中能遵循指令的少数植物状态患者中,研究结果指出了尽管存在严重行为障碍但仍可能支持认知功能和意识的假定网络机制。