Watters Harrison, Davis Aleah, Fazili Abia, Daley Lauren, LaGrow T J, Schumacher Eric H, Keilholz Shella
Emory Neuroscience Graduate Program, Emory University, Atlanta, Georgia, USA.
Agnes Scott College, Decatur, Georgia, USA.
Hum Brain Mapp. 2025 Feb 15;46(3):e70049. doi: 10.1002/hbm.70049.
Early efforts to understand the human cerebral cortex focused on localization of function, assigning functional roles to specific brain regions. More recent evidence depicts the cortex as a dynamic system, organized into flexible networks with patterns of spatiotemporal activity corresponding to attentional demands. In functional MRI (fMRI), dynamic analysis of such spatiotemporal patterns is highly promising for providing non-invasive biomarkers of neurodegenerative diseases and neural disorders. However, there is no established neurotypical spectrum to interpret the burgeoning literature of dynamic functional connectivity from fMRI across attentional states. In the present study, we apply dynamic analysis of network-scale spatiotemporal patterns in a range of fMRI datasets across numerous tasks including a left-right moving dot task, visual working memory tasks, congruence tasks, multiple resting state datasets, mindfulness meditators, and subjects watching TV. We find that cortical networks show shifts in dynamic functional connectivity across a spectrum that tracks the level of external to internal attention demanded by these tasks. Dynamics of networks often grouped into a single task positive network show divergent responses along this axis of attention, consistent with evidence that definitions of a single task positive network are misleading. Additionally, somatosensory and visual networks exhibit strong phase shifting along this spectrum of attention. Results were robust on a group and individual level, further establishing network dynamics as a potential individual biomarker. To our knowledge, this represents the first study of its kind to generate a spectrum of dynamic network relationships across such an axis of attention.
早期对人类大脑皮层的研究致力于功能定位，即给特定脑区赋予功能角色。最近的证据表明，皮层是一个动态系统，由灵活的网络组成，其时空活动模式与注意力需求相对应。在功能磁共振成像（fMRI）中，对这种时空模式进行动态分析，极有可能为神经退行性疾病和神经紊乱提供非侵入性生物标志物。然而，目前尚无既定的神经典型频谱来解读来自fMRI的关于跨注意力状态的动态功能连接的大量文献。在本研究中，我们对一系列fMRI数据集进行了网络规模时空模式的动态分析，这些数据集涵盖了众多任务，包括左右移动点任务、视觉工作记忆任务、一致性任务、多个静息态数据集、正念冥想者以及看电视的受试者。我们发现，皮层网络在一个频谱上呈现出动态功能连接的变化，该频谱追踪这些任务所要求的从外部注意力到内部注意力的水平。通常被归为单一任务阳性网络的网络动态在这个注意力轴上表现出不同的反应，这与单一任务阳性网络的定义具有误导性的证据一致。此外，体感和视觉网络在这个注意力频谱上表现出强烈的相位偏移。结果在群体和个体层面都很稳健，进一步确立了网络动态作为一种潜在的个体生物标志物。据我们所知，这是同类研究中首次在这样一个注意力轴上生成动态网络关系频谱的研究。
