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Poster presented at the 36th Annual Meeting of the Society for Neuroscience (SfN), Atlanta GA, USA.

机译:在美国佐治亚州亚特兰大举行的神经科学学会(SfN)第36届年会上发表了海报。

摘要

A comparison of activation maps obtained with fMRI reveals substantial inter-individual variability in the anatomical location of activated areas. In group studies functional data are smoothed with a Gaussian kernel to increase the functional overlap between activated areas from different subjects.We present an alternative approach to increase this overlap, based on non-linear deformations of individual contrast maps to a sample-specific minimal deformation target. Functional images were obtained from six adult subjects passively viewing a short stimulus sequence. The stimuli were organized in a blocked design with three conditions: static objects, faces and moving natural scenes. All functional images were spatially normalized to the standard MNI template. Individual statistical maps were calculated, contrasting each of the three conditions with a fixation condition.Deformation fields resulting from viscous fluid registrations between these individual contrast maps were obtained to create sample-specific minimal deformation targets for the three contrasts. For each subject we then calculated the average deformation needed to register each contrast map with its associated target. This subject-specific deformation field was subsequently applied to all functional images for that specific subject.This procedure does increase the inter-subject overlap in activated areas, as evidenced by a comparison between the results of fixed-effects group analyses on the deformed and on the undeformed functional images. The analysis on the functionally deformed images yields about one third more activated clusters than the analysis on the functionally undeformed images (33 versus 24). With functionally deformed images the contrast between moving scenes and fixation reveals a number of areas that are not significantly activated with functionally undeformed images: hMT/V5, the frontal eye fields (FEF) and both the anterior and lateral dorsal intraparietal sulcus regions (DIPSA and DIPSL).We believe the enhanced functional overlap generated by this functional atlas fitting paradigm improves the analysis of functional group data. Moreover, this paradigm provides a means for a direct mapping of a functional brain atlas to individual contrast maps. As such, it may enable automated labeling of functional areas and as such provide a valuable diagnostic tool for functional patient studies.
机译:通过功能磁共振成像获得的激活图的比较显示,激活区域的解剖位置存在很大的个体差异。在小组研究中,使用高斯核对功能数据进行平滑处理以增加不同对象的激活区域之间的功能重叠。基于个体对比图的非线性变形到特定于样本的最小变形,我们提出了另一种方法来增加这种重叠目标。从六个成年受试者被动观看短刺激序列获得功能图像。刺激以封闭的设计进行组织,并具有三个条件:静态物体,面部和移动的自然场景。将所有功能图像在空间上标准化为标准MNI模板。计算单独的统计图,将三个条件中的每一个与一个固定条件进行对比,获得由这些单个对比图之间的粘性流体配准导致的形变场,以创建三个对比的特定于样品的最小变形目标。然后,对于每个对象,我们计算出将每个对比度图与其关联目标对齐所需的平均变形。该对象特定的变形场随后应用于该特定对象的所有功能图像。此过程确实增加了激活区域中的对象间重叠,这通过对变形和变形的固定效果组分析结果进行比较来证明。未变形的功能图像。对功能变形图像的分析比对功能未变形图像的分析产生的活化簇大约多三分之一(33对24)。对于功能变形的图像,运动场景和注视之间的对比揭示了许多功能未变形的图像无法显着激活的区域:hMT / V5,额叶视野(FEF)以及前,后背顶壁沟内沟区域(DIPSA和DIPSL)。我们认为,此功能图集拟合范例所产生的增强的功能重叠可改善对功能组数据的分析。而且,该范例为将功能性大脑图谱直接映射到单个对比图提供了一种方法。这样,它可以实现功能区域的自动标记,从而为功能患者研究提供有价值的诊断工具。

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