Affinity matrices from fMRI data

This is a set of 27x27 matrices constructed from the fMRI data for 2 participants from the ABIDE data set [Craddock et al., 2013] and 10 from the HCP Young Adult data set [Van Essen et al., 2013, Glasser et al., 2013]. A subset of 118 matrices (saved in a folder titled 'Random') was produced by sampling uniformly from the interval [0,1]. Each matrix represents the affinity in the immediate neighbourhood of a randomly-selected vertex on the midthickness surface of the brain, and was generated with the VB toolbox as outlined in [Bajada et al., 2020]. Note, however, that the referenced work takes a surface-based approach, but we used a version of the toolbox that is newer and employs a hybrid method whereby the randomly-chosen vertex is first mapped to the corresponding voxel, a 27-voxel neighbourhood (which includes the original voxel) is identified, and the affinity in said neighbourhood calculated. The element aij of the matrix constructed for the neighbourhood indicates the degree of correlation between voxels i and j on the basis of their fMRI data. The particular version of the VB toolbox utilised for this work is available at https://github.com/VBIndex/py_vb_toolbox/tree/Local-gradients-paper (but please note that it would have to be modified to print out the affinity matrices for a set of randomly-selected vertices). The matrices are made available as numpy array files and are separated into folders according to the origin of the fMRI data used to construct them (the prefix ABIDE_ added to folder names indicates that the matrices contained inside were generated with the fMRI data of subjects from the ABIDE data set, while HCP is the Human Connectome Project counterpart. Each folder pertains to a different data subject, but note that the numbering scheme employed (DS1, DS2, etc.) has no correspondence to the original ABIDE or HCP participant numbers.本数据集由27×27矩阵构成，其数据来源于ABIDE数据集[Craddock等人，2013]中的2名受试者与HCP青年成人数据集[Van Essen等人，2013、Glasser等人，2013]中的10名受试者的功能磁共振成像（fMRI，functional Magnetic Resonance Imaging）数据。其中118个矩阵存储于名为“Random”的文件夹中，是从区间[0,1]内均匀采样生成的。 每个矩阵代表大脑中厚度皮层表面上随机选取的顶点的局部邻域亲和性，其生成过程遵循[Bajada等人，2020]中所述的VB工具箱（VB toolbox）流程。需注意的是，原参考文献采用基于皮层表面的处理方法，而本研究使用了该工具箱的更新版本，该版本采用混合处理流程：先将随机选取的顶点映射至对应的体素，随后识别包含该原始体素在内的27个体素邻域，并计算该邻域内的亲和性。矩阵元素a_ij代表基于fMRI数据计算得到的体素i与体素j之间的相关程度。本研究使用的VB工具箱特定版本可从https://github.com/VBIndex/py_vb_toolbox/tree/Local-gradients-paper获取（请注意：需对该版本进行修改，才能输出随机选取顶点集合的亲和性矩阵）。 本数据集以NumPy数组文件形式提供，根据构建矩阵所用fMRI数据的来源划分为不同文件夹：文件夹名称前缀为“ABIDE_”时，表示其内部矩阵由ABIDE数据集中受试者的fMRI数据生成；以“HCP”为前缀的文件夹则对应人类连接组计划（Human Connectome Project, HCP）的受试者数据。每个文件夹对应一名不同的受试者，但需注意：所采用的编号方案（如DS1、DS2等）与ABIDE或HCP原始受试者编号无对应关系。