Research Imaging Institute and Department of Radiology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, USA.
Neuroimage. 2012 Jun;61(2):407-26. doi: 10.1016/j.neuroimage.2011.12.051. Epub 2012 Jan 5.
After more than twenty years busily mapping the human brain, what have we learned from neuroimaging? This review (coda) considers this question from the point of view of structure-function relationships and the two cornerstones of functional neuroimaging; functional segregation and integration. Despite remarkable advances and insights into the brain's functional architecture, the earliest and simplest challenge in human brain mapping remains unresolved: We do not have a principled way to map brain function onto its structure in a way that speaks directly to cognitive neuroscience. Having said this, there are distinct clues about how this might be done: First, there is a growing appreciation of the role of functional integration in the distributed nature of neuronal processing. Second, there is an emerging interest in data-driven cognitive ontologies, i.e., that are internally consistent with functional anatomy. We will focus this review on the growing momentum in the fields of functional connectivity and distributed brain responses and consider this in the light of meta-analyses that use very large data sets to disclose large-scale structure-function mappings in the human brain.
经过二十多年来对人类大脑的忙碌绘制,我们从神经影像学中了解到了什么?从结构-功能关系以及功能神经影像学的两个基石(即功能分离和整合)的角度来看,这篇综述(结语)考虑了这个问题。尽管在大脑的功能结构方面取得了显著的进展和深入的了解,但人类大脑映射最早和最简单的挑战仍然没有得到解决:我们没有一种原则性的方法可以将大脑功能映射到其结构上,而这种方法可以直接与认知神经科学对话。话虽如此,但关于如何做到这一点,有明显的线索:首先,人们越来越认识到功能整合在神经元处理的分布式性质中的作用。其次,人们对数据驱动的认知本体论(即与功能解剖学内部一致的本体论)产生了兴趣。我们将把这篇综述的重点放在功能连接和分布式大脑反应领域的不断增长的动力上,并根据使用非常大数据集来揭示人类大脑的大规模结构-功能映射的元分析来考虑这一点。