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Simple Signed-Distance Function Depth Calculation Applied to Measurement of the fMRI BOLD Hemodynamic Response Function in Human Visual Cortex

机译:简单的符号距离功能深度计算应用于测量人类视觉皮层中FMRI大胆血液动力响应函数的测量

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Functional magnetic resonance imaging (fMRI) often relies on a hemodynamic response function (HRF) elicited by a brief stimulus. At conventional spatial resolutions (> 3 mm), signals in a voxel include contributions from various tissue types and pia vasculature. To better understand these contributions, full characterization of the depth dependence of the HRF is required in gray matter as well as and its apposed white-matter and pial vasculature. We introduce new methods to calculate 3D depth that combines a signed-distance function with an algebraic morphing definition of distance. The new scheme is much simpler than methods that rely upon deformable surface propagation. The method is demonstrated by combining the distance map with high-resolution fMRI (0.9-mm voxels) measurements of the depth-dependent HRF. The depth dependence of the HRF is reliable throughout a broad depth range in gray matter as well as in white-matter and extra-pial compartments apposed to active gray matter. The proposed scheme with high-resolution fMRI can be useful to separate HRFs in the gray matter from undesirable and confounding signals.
机译:功能磁共振成像(FMRI)通常依赖于短暂刺激引发的血流动力学响应函数(HRF)。在常规空间分辨率(> 3mm),体素中的信号包括来自各种组织类型和PIA脉管系统的贡献。为了更好地理解这些贡献,在灰质和物质以及其所吸引的白品和小族脉管系统中需要完全表征HRF的深度依赖性。我们介绍了计算3D深度的新方法,这些方法将符号距离功能与距离的代数变形定义相结合。新方案比依赖可变形的表面传播的方法更简单。通过将距离图与深度依赖性HRF的高分辨率FMRI(0.9-mm Voxels)测量组合来说明该方法。 HRF的深度依赖性在灰质的宽度范围内是可靠的,并且在呈现为活跃的灰质的白色物质和外部小型隔室中。具有高分辨率FMRI的所提出的方案可用于从不期望和混杂信号中分离灰质中的HRF。

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