Institute of Neuroscience and Medicine, Brain and Behavior (INM-7), Research Centre Jülich, Jülich, Germany.
Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
Nat Rev Neurosci. 2018 Nov;19(11):672-686. doi: 10.1038/s41583-018-0071-7.
A defining aspect of brain organization is its spatial heterogeneity, which gives rise to multiple topographies at different scales. Brain parcellation - defining distinct partitions in the brain, be they areas or networks that comprise multiple discontinuous but closely interacting regions - is thus fundamental for understanding brain organization and function. The past decade has seen an explosion of in vivo MRI-based approaches to identify and parcellate the brain on the basis of a wealth of different features, ranging from local properties of brain tissue to long-range connectivity patterns, in addition to structural and functional markers. Given the high diversity of these various approaches, assessing the convergence and divergence among these ensuing maps is a challenge. Inter-individual variability adds to this challenge but also provides new opportunities when coupled with cross-species and developmental parcellation studies.
大脑组织的一个显著特点是其空间异质性,这种异质性在不同尺度上产生了多种拓扑结构。因此,脑分割——定义大脑中的不同分区,无论是由多个不连续但密切相互作用的区域组成的区域还是网络——对于理解大脑的组织和功能至关重要。在过去的十年中,基于磁共振成像的方法在识别和分割大脑方面取得了爆炸式的发展,这些方法基于大量不同的特征,从脑组织的局部性质到远程连接模式,以及结构和功能标记物。鉴于这些不同方法的高度多样性,评估这些后续图谱之间的收敛和发散是一项挑战。个体间的变异性增加了这一挑战,但在与跨物种和发育分割研究相结合时也提供了新的机会。