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. Author manuscript; available in PMC: 2019 Apr 1.
Published in final edited form as: Neuroimage. 2017 Dec 5;169:106–116. doi: 10.1016/j.neuroimage.2017.12.004

Figure 4. Construction of the connectivity-based atlas.

Figure 4

(A) Pipeline of the connectivity-based parcellation. Whole-brain tractography was performed for each seed voxel. The connectivity probability between each seed voxel and each target voxel was calculated to construct a seed-target connectivity matrix, which was then used to parcellate each seed region using a spectral clustering algorithm. (B) To avoid the influence of different cortical layers on the parcellation, only voxels residing in the GM-WM boundary were parcellated and then fused to the whole cortex according to our “columnar-anisotropy” method. (C) The number of clusters (K) was determined by computing multiple statistical indices followed by manual inspection. For example, although the indices suggested K=8 as the best solution to parcellate the insular cortex, manual inspection showed it resulted in many small and jagged clusters; on the other hand, the second optimal K=4 generated a better result and was selected for the final parcellation.