Howard Hughes Medical Institute, Cambridge, Massachusetts, United States of America.
PLoS Comput Biol. 2010 Jun 10;6(6):e1000808. doi: 10.1371/journal.pcbi.1000808.
Information processing in the human brain arises from both interactions between adjacent areas and from distant projections that form distributed brain systems. Here we map interactions across different spatial scales by estimating the degree of intrinsic functional connectivity for the local (<or=14 mm) neighborhood directly surrounding brain regions as contrasted with distant (>14 mm) interactions. The balance between local and distant functional interactions measured at rest forms a map that separates sensorimotor cortices from heteromodal association areas and further identifies regions that possess both high local and distant cortical-cortical interactions. Map estimates of network measures demonstrate that high local connectivity is most often associated with a high clustering coefficient, long path length, and low physical cost. Task performance changed the balance between local and distant functional coupling in a subset of regions, particularly, increasing local functional coupling in regions engaged by the task. The observed properties suggest that the brain has evolved a balance that optimizes information-processing efficiency across different classes of specialized areas as well as mechanisms to modulate coupling in support of dynamically changing processing demands. We discuss the implications of these observations and applications of the present method for exploring normal and atypical brain function.
人类大脑中的信息处理既来自相邻区域之间的相互作用，也来自形成分布式大脑系统的远距离投射。在这里，我们通过估计直接围绕脑区的局部（≤14mm）邻域的内在功能连接程度，来绘制不同空间尺度上的相互作用图谱，从而与远距离（＞14mm）相互作用进行对比。在静息状态下测量的局部和远距离功能相互作用之间的平衡形成了一张图谱，将感觉运动皮层与异模态联合区域区分开来，并进一步确定了那些同时具有高局部和远距离皮质-皮质相互作用的区域。网络度量的图谱估计表明，高局部连接性通常与高聚类系数、长路径长度和低物理代价相关。任务表现改变了局部和远距离功能耦合在一部分区域中的平衡，特别是在与任务相关的区域中增加了局部功能耦合。观察到的性质表明，大脑已经进化出一种平衡，在不同类别的专门区域之间优化信息处理效率，以及调节耦合的机制，以支持动态变化的处理需求。我们讨论了这些观察结果的意义以及本方法在探索正常和异常大脑功能方面的应用。
