Fig. 1.

Workflow for quantifying the extent of each cortical area’s thalamic anatomical connectivity pattern using Euclidean distance (ED). (A) Schematic overview of the thresholding and ED calculation framework applied to group-level and individual-level human probabilistic tractography data ($\mathrm{n}=828$). ED was used to measure the extent of each cortical parcel’s anatomical connectivity pattern within ipsilateral thalamus (see Fig. S8 for bilateral calculation). (B) Thalamic connectivity patterns for right motor area 1 (M1) and dorsolateral prefrontal cortex (DLPFC). M1 and DLPFC illustrate focal and diffuse thalamic connectivity patterns, respectively. (C) ED matrix depicting pairwise distances calculated between surviving thalamic voxels for 100 thresholds. Cortical parcels with more diffuse thalamic connectivity patterns exhibited higher ED values across thresholds (e.g., DLPFC). (D) Cortical $E{D}_{pc1}$ loading map obtained through principal component analysis (PCA) of the ED matrix. The first PC accounted for 92% of the variance. (E) Cortical $E{D}_{\sigma }$ map representing the standard deviation of ED across 100 thresholds for each cortical parcel. $E{D}_{\sigma }$ values were highly correlated with $E{D}_{pc1}$ loadings $\left(r_s=0.99;p_{sa}<0.001\right)$, with p-values estimated using spatial-autocorrelation (sa) preserving surrogate brain maps (44). $r_s$: Spearman rho. (F) Correlations between $E{D}_{pc1}$ and $E{D}_{\sigma }$ were highly consistent across subjects. (G) $E{D}_{pc1}$ loadings and ED values negatively correlated at more conservative thresholds, indicating that higher $E{D}_{pc1}$ loadings correspond to more focal thalamic connectivity patterns.