Human Tractography Atlas


  • Averaged from ~800 subjects' data from the Human Connectome Project 
  • Generated from a fiber tracking method with the highest valid connection
  • Tracks clustered into 550 bundles for examination and labeling by a neuroanatomy team
  • Provides entire fiber pathways in addition to end-to-end connectivity
  • Provides connectogram and connectivity matrix for each pathway system


White matter localization

The HCP842 tractography atlas can be matched with the TBSS or VMB mask to explore which pathways are involved in the finding. The following steps describe how to do this.

1. Download DSI Studio at
2. Download HCP842 template file:
3. Download HCP842 tractography TRK files:   
    I recommend download only the projection, association, and commissural pathway. The following steps can be repeated for each pathway system, respectively.
4. Run DSI Studio (unzip to a folder and click dsi_studio.exe)
5. Click [STEP3 Fiber Tracking] and open HCP842_1mm.fib.gz (the HCP842 template file)
6. Load the TBSS or VBM mask file as a region by [Regions][Open Region]. 
    You may check the ROI window at the left bottom window to make sure that the mask appears correctly
7. Load the tractography TRK files by [Tracts][Open Tracts] and select the TRK files of a pathway system (e.g. TRK files in the projection folder)
8. [Tracts][Filter Tracts by ROI/ROA/END] to remove tracks that are not passing through the mask
9. [Tracts][Statistics] and save the results as a text file. 
10. Open the text file in Excel. Check out "number of tracks" row to see the streamline count in the remaining tractography. If the number of tracks is 0, then it means the pathway does not go through the mask. A higher streamline count indicates possible higher chance the pathway is related to the mask region.


[1]Yeh, F. C., S. Panesar, D. Fernandes, A. Meola, M. Yoshino, J. C. Fernandez-Miranda, J. M. Vettel, and T. Verstynen. "Population-averaged atlas of the macroscale human structural connectome and its network topology." NeuroImage (2018).