Roca Pauline, Tucholka Alan, Rivière Denis, Guevara Pamela, Poupon Cyril, Mangin Jean-François
CEA Saclay, Neurospin/LNAO, Bât 145, 91191 Gif-sur-Yvette cedex, France.
Med Image Comput Comput Assist Interv. 2010;13(Pt 2):347-54. doi: 10.1007/978-3-642-15745-5_43.
This paper presents a connectivity-based parcellation of the human post-central gyrus, at the level of the group of subjects. The dimension of the clustering problem is reduced using a set of cortical regions of interest determined at the inter-subject level using a surface-based coordinate system, and representing the regions with a strong connection to the post-central gyrus. This process allows a clustering based on criteria which are more reproducible across subjects than in an intra-subject approach. We obtained parcels relatively stable in localisation across subjects as well as homogenous and well-separated to each other in terms of connectivity profiles. To address the parcellation at the inter-subject level provides a direct matching between parcels across subjects. In addition, this method allows the identification of subject-specific parcels. This property could be useful for the study of pathologies.
本文展示了基于连通性的人类中央后回分区，该分区是在受试者群体层面进行的。使用一组基于表面坐标系在个体间水平确定的感兴趣皮质区域来降低聚类问题的维度，这些区域代表与中央后回有强连接的区域。此过程允许基于比个体内方法在受试者间更具可重复性的标准进行聚类。我们获得了在受试者间定位相对稳定且在连通性概况方面彼此同质且分离良好的脑区。在个体间水平进行分区可实现受试者间脑区的直接匹配。此外，该方法还能识别个体特异性脑区。这一特性可能对病理学研究有用。
