Bartels Andreas, Zeki Semir
Wellcome Department of Imaging Neuroscience, University College London, Gower Street, London WC1E 6BT, UK.
Philos Trans R Soc Lond B Biol Sci. 2005 Apr 29;360(1456):733-50. doi: 10.1098/rstb.2005.1627.
We review here a new approach to mapping the human cerebral cortex into distinct subdivisions. Unlike cytoarchitecture or traditional functional imaging, it does not rely on specific anatomical markers or functional hypotheses. Instead, we propose that the unique activity time course (ATC) of each cortical subdivision, elicited during natural conditions, acts as a temporal fingerprint that can be used to segregate cortical subdivisions, map their spatial extent, and reveal their functional and potentially anatomical connectivity. We argue that since the modular organisation of the brain and its connectivity evolved and developed in natural conditions, these are optimal for revealing its organisation. We review the concepts, methodology and first results of this approach, relying on data obtained with functional magnetic resonance imaging (fMRI) when volunteers viewed traditional stimuli or a James Bond movie. Independent component analysis (ICA) was used to identify voxels belonging to distinct functional subdivisions, based on their differential spatio-temporal fingerprints. Many more regions could be segregated during natural viewing, demonstrating that the complexity of natural stimuli leads to more differential responses in more functional modules. We demonstrate that, in a single experiment, a multitude of distinct regions can be identified across the whole brain, even within the visual cortex, including areas V1, V4 and V5. This differentiation is based entirely on the differential ATCs of different areas during natural viewing. Distinct areas can therefore be identified without any a priori hypothesis about their function or spatial location. The areas we identified corresponded anatomically across subjects, and their ATCs showed highly area-specific inter-subject correlations. Furthermore, natural conditions led to a significant de-correlation of interregional ATCs compared to rest, indicating an increase in regional specificity during natural conditions. In contrast, the correlation between ATCs of distant regions of known substantial anatomical connections increased and reflected their known anatomical connectivity pattern. We demonstrate this using the example of the language network involving Broca's and Wernicke's area and homologous areas in the two hemispheres. In conclusion, this new approach to brain mapping may not only serve to identify novel functional subdivisions, but to reveal their connectivity as well.
我们在此回顾一种将人类大脑皮层划分为不同亚区的新方法。与细胞构筑学或传统功能成像不同，它不依赖于特定的解剖标记或功能假设。相反，我们提出，在自然条件下诱发的每个皮层亚区独特的活动时间进程（ATC），可作为一种时间指纹，用于区分皮层亚区、描绘其空间范围，并揭示其功能及潜在的解剖连接。我们认为，由于大脑的模块化组织及其连接性是在自然条件下进化和发展的，因此这些条件最适合揭示其组织情况。我们回顾了这种方法的概念、方法和初步结果，这些结果依赖于志愿者观看传统刺激物或一部詹姆斯·邦德电影时通过功能磁共振成像（fMRI）获得的数据。独立成分分析（ICA）用于根据不同的时空指纹识别属于不同功能亚区的体素。在自然观看过程中可以区分出更多区域，这表明自然刺激的复杂性会在更多功能模块中引发更多不同的反应。我们证明，在一个单一实验中，甚至在视觉皮层内，包括V1、V4和V5区，整个大脑中都能识别出众多不同的区域。这种区分完全基于自然观看期间不同区域的差异ATC。因此，无需对其功能或空间位置有任何先验假设就能识别出不同区域。我们识别出的区域在不同受试者之间在解剖学上是对应的，并且它们的ATC显示出高度区域特异性的受试者间相关性。此外，与静息状态相比，自然条件导致区域间ATC的显著去相关，这表明在自然条件下区域特异性增加。相反，已知有大量解剖连接的远距离区域的ATC之间的相关性增加，并反映了它们已知的解剖连接模式。我们以涉及布洛卡区和韦尼克区以及两个半球同源区域的语言网络为例进行了说明。总之，这种新的脑图谱绘制方法不仅可能有助于识别新的功能亚区，还能揭示它们的连接性。
