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A nested cortex parcellation combining analysis of MEG forward problem and diffusion MRI tractography

机译:巢状皮层剥离术结合MEG正向问题分析与弥散MRI术式成像

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Understanding the relationship between structure and function is a major challenge in neuroscience. Diffusion MRI (dMRI) in the only non-invasive modality allowing to have access to the neural structure. Magnetoencephalography (MEG) is another non-invasive modality that allows a direct access to the temporal succession of cognitive processes. Functional cortex parcellation being one of the most important ways to understand structure-function relationship, we propose an innovative method merging MEG and dMRI to parcellate the cortex. The combination of MEG forward problem and connectivity information reveals cortical areas generating a similar magnetic field at sensors while having a similar connectivity. Results show suitable clusters that forecast interesting studies for inter- and intra-subjects comparisons of the cortex parcellations. The automatic nested cortex parcellation we propose could be a first step to analyse sources that are seeds of long or short range connectivity and to differentiate these connectivities in the white matter.
机译:理解结构与功能之间的关系是神经科学的主要挑战。扩散MRI(dMRI)是唯一一种允许进入神经结构的非侵入性方式。磁脑电图(MEG)是另一种非侵入性方式,可以直接访问认知过程的时间序列。功能性皮层剥离是理解结构与功能关系的最重要方法之一,我们提出了一种融合MEG和dMRI的创新方法来皮层剥离。 MEG正向问题和连通性信息的结合显示出皮质区域在传感器处产生相似的磁场,同时具有相似的连通性。结果显示了合适的类群,这些类群预测了有趣的研究,以进行皮层间的个体间和个体间比较。我们提出的自动嵌套皮层分割可能是第一步,是分析作为长距离或短距离连接的种子的源,并区分白质中的这些连接。

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