CHARACTERIZATION OF SPATIAL DYNAMICS OF FMRI DATA IN WHITE MATTER USING DIFFUSION-INFORMED WHITE MATTER HARMONICS.

Hamid Behjat, Iman Aganj, David Abramian, Anders Eklund, Carl-Fredrik Westin
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引用次数: 4

Abstract

In this work, we leverage the Laplacian eigenbasis of voxel-wise white matter (WM) graphs derived from diffusion-weighted MRI data, dubbed WM harmonics, to characterize the spatial structure of WM fMRI data. Our motivation for such a characterization is based on studies that show WM fMRI data exhibit a spatial correlational anisotropy that coincides with underlying fiber patterns. By quantifying the energy content of WM fMRI data associated with subsets of WM harmonics across multiple spectral bands, we show that the data exhibits notable subtle spatial modulations under functional load that are not manifested during rest. WM harmonics provide a novel means to study the spatial dynamics of WM fMRI data, in such way that the analysis is informed by the underlying anatomical structure.

利用扩散信息白质谐波表征白质fmri数据的空间动力学。
在这项工作中,我们利用来自扩散加权MRI数据(称为WM谐波)的体素白质(WM)图的拉普拉斯特征基来表征WM fMRI数据的空间结构。我们进行这种表征的动机是基于研究表明,WM功能磁共振成像数据显示出与潜在纤维模式相一致的空间相关各向异性。通过量化与多个谱带WM谐波子集相关的WM fMRI数据的能量含量,我们发现,在功能负载下,数据表现出明显的微妙空间调制,而在休息时则没有表现出来。WM谐波提供了一种新的方法来研究WM fMRI数据的空间动力学,以这种方式,分析是由潜在的解剖结构通知。
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