Neuroscience Program, Oberlin College, Oberlin, OH, 44074, USA.
Cognitive Science Program, Indiana University, Bloomington, IN, 47401, USA.
Commun Biol. 2024 Jan 24;7(1):126. doi: 10.1038/s42003-024-05766-w.
Previous studies have adopted an edge-centric framework to study fine-scale network dynamics in human fMRI. To date, however, no studies have applied this framework to data collected from model organisms. Here, we analyze structural and functional imaging data from lightly anesthetized mice through an edge-centric lens. We find evidence of "bursty" dynamics and events - brief periods of high-amplitude network connectivity. Further, we show that on a per-frame basis events best explain static FC and can be divided into a series of hierarchically-related clusters. The co-fluctuation patterns associated with each cluster centroid link distinct anatomical areas and largely adhere to the boundaries of algorithmically detected functional brain systems. We then investigate the anatomical connectivity undergirding high-amplitude co-fluctuation patterns. We find that events induce modular bipartitions of the anatomical network of inter-areal axonal projections. Finally, we replicate these same findings in a human imaging dataset. In summary, this report recapitulates in a model organism many of the same phenomena observed in previously edge-centric analyses of human imaging data. However, unlike human subjects, the murine nervous system is amenable to invasive experimental perturbations. Thus, this study sets the stage for future investigation into the causal origins of fine-scale brain dynamics and high-amplitude co-fluctuations. Moreover, the cross-species consistency of the reported findings enhances the likelihood of future translation.
先前的研究采用了以边缘为中心的框架来研究人类 fMRI 中的细粒度网络动态。然而,迄今为止,还没有研究将该框架应用于从模式生物中收集的数据。在这里,我们通过边缘为中心的视角分析轻度麻醉小鼠的结构和功能成像数据。我们发现了“突发”动态和事件的证据——短暂的高振幅网络连接时期。此外,我们表明,在每一帧的基础上,事件可以最好地解释静态 FC,并且可以分为一系列具有层次关系的集群。与每个集群中心相关的共波动模式将不同的解剖区域联系起来,并在很大程度上遵守算法检测到的功能大脑系统的边界。然后,我们研究了支持高振幅共波动模式的解剖连接。我们发现,事件诱导了区域间轴突投射的解剖网络的模块化二分。最后,我们在人类成像数据集上复制了相同的发现。总之,本报告在模型生物中再现了以前以边缘为中心的人类成像数据分析中观察到的许多相同现象。然而,与人类受试者不同,鼠类神经系统易于进行侵入性实验干扰。因此,这项研究为未来研究细粒度大脑动态和高振幅共波动的因果起源奠定了基础。此外,所报告发现的跨物种一致性增加了未来转化的可能性。