Cortico-incertal connectivity analysis workflow.

(a) The zona incerta (ZI) seed region used for connectivity analyses. Diffusion MRI data were processed to reconstruct (b) streamlines via diffusion tractography and (c) connectivity matrices quantifying the number of streamlines between each ZI voxel and cortical region as defined by the HCP-MMP1.0 atlas. (d-f) ZI gradients and clusters were computed to illustrate the principal organizations of connectivity variability among ZI voxels. (d) Significant patterns were highlighted based on inter-voxel similarity using the normalized cosine angle. (e) Diffusion map embedding and spectral clustering were used to construct the gradients and clusters, respectively. (f) Gradient-weighted cortical maps were created by multiplying each row of the initial connectivity matrices with the corresponding principal gradient value, then averaging these rows to produce a single cortical representation of each gradient. A winner-takes-all approach was used to create a cortical map with areas color-coded according to their connectivity with the ZI clusters.

Cortico-incertal structural connectivity patterns.

(a) The first two gradients of the zona incerta (ZI) based on structural connectivity shown using axial and 3D radiological views both revealed a rostral-caudal axis. (b) Similarly, spectral clustering shows a topographic organization of discrete clusters along a rostral-caudal axis, with cluster 1 positioned most rostrally. (c) Gradient-weighted cortical maps corresponding to gradients 1 and 2 and the spectral clustering results (left to right).

Cluster-wise tractography.

(a) Example cluster-wise tractograms for the left hemisphere of a single subject. (b) Group-level cluster-wise cortical connectomes, where parcels are color-coded and have varying opacity levels (linearly scaled), reflecting the number of streamlines connecting each parcel with the clusters (row-wise). (c) Boxplot shows the total number of streamlines connecting the cortex with each cluster.

Replicability and reliability of zona incerta (ZI) connectivity patterns.

(a) Axial cross-sections of gradient 1 and 2 per MRI dataset. (b) Similar to a but with ZI voxels displayed in the respective 2D gradient coordinates space. (c) Procrustes disparity scores for each comparison of 2D gradient coordinates among datasets.

Replicability and reliability of the spectral clustering results.

(a) Axial cross-sections of spectral clustering results (k=6) for each MRI dataset (left to right). (b) Comparison of cluster centroids between datasets, with results matched column-wise. Bright labels correspond to the 3T and 3T retest datasets. (c) Dice overlap scores and centroid distances for each comparison of spectral clustering results among datasets for the left and right hemispheres.

Individual subject replicability.

(a) Spatial correlation between individual and group-level structural connectivity for each of the two retained gradients. (c) Centroid distances and (d) Dice scores for the alignment between individual and group-level clusters. Results are shown for both left and right hemispheres.

Correlation analysis between cortico-incertal structural connectivity patterns and cortical properties.

The gradient-weighted cortical maps (Figure 2c) and cluster-wise connectomes (Supplementary Figure 11) exhibit significant correlations with various (a) cognitive terms (e.g., movement) and (b) cortical hierarchies (e.g., sensorimotor-association axis) based on Spearman’s correlation coefficient (colored markers). Marker colors represent P-values, corrected for spatial autocorrelation using N=10k spin tests. Semi-transparent black bars show permuted values. The source file containing all Spearman’s correlation coefficients is available in the code repository referenced in the manuscript.

Mapping a deep brain stimulation (DBS) case electrode stimulation volume to ZI tractography-based gradients and clusters.

(a) DBS electrode reconstruction was performed using the Lead-DBS (v3.0.0) software and visualized in a common space overlayed with the ZI clusters derived in this work. (b) Propagated coordinates of the left and right stimulation volumes (black markers) into gradient space. Stimulation volume centroids are shown with red outlines. (c) Distribution of gradient scores within stimulation volumes and percent (%) of the DBS stimulation volume overlapping with ZI clusters.