Connectivity matrices

Instead of offering a bewildering number of options for constructing connectivity matrices, qsirecon will construct as many connectivity matrices as it can given the reconstruction methods. It is highly recommended that you pick a weighting scheme before you run these pipelines and only look at those numbers. If you look at more than one weighting method be sure to adjust your statistics for the additional comparisons.

Atlases

The following atlases are included in qsirecon and are used by default in the preconfigured_workflows. If you use one of them please be sure to cite the relevant publication.

• schaefer100, schaefer200, schaefer400: Schaefer et al.[1], Yeo et al.[2]

• brainnetome246: Fan et al.[3]

• aicha384: Joliot et al.[4]

• gordon333: Gordon et al.[5]

• aal116: Tzourio-Mazoyer et al.[6]

Using custom atlases

It’s possible to use your own atlases provided you can match the format qsirecon uses to read atlases. The qsirecon atlas set can be downloaded directly from box.

In this directory there must exist a JSON file called atlas_config.json containing an entry for each atlas you would like included. The format is:

{
  "my_custom_atlas": {
    "file": "file_in_this_directory.nii.gz",
    "node_names": ["Region1_L", "Region1_R" ... "RegionN_R"],
    "node_ids": [1, 2, ..., N]
  }
  ...
}

Where "node_names" are the text names of the regions in "my_custom_atlas" and "node_ids" are the numbers in the nifti file that correspond to each region. When custom_reconstruction you can then inclued "my_custom_atlas" in the "atlases":[] section.

The directory containing atlas_config.json and the atlas nifti files should be mounted in the container at /atlas/qsirecon_atlases. If using qsirecon-docker or qsirecon-singularity this can be done with --custom-atlases /path/to/my/atlases or if you’re running on your own system (not recommended) you can set the environment variable QSIRECON_ATLAS=/path/to/my/atlases.

The nifti images should be registered to the MNI152NLin2009cAsym included in qsirecon. It is essential that your images are in the LPS+ orientation and have the sform zeroed-out in the header. Be sure to check for alignment and orientation in your outputs.

References

[1]

Alexander Schaefer, Ru Kong, Evan M Gordon, Timothy O Laumann, Xi-Nian Zuo, Avram J Holmes, Simon B Eickhoff, and BT Thomas Yeo. Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity mri. Cerebral cortex, 28(9):3095–3114, 2018. URL: https://doi.org/10.1093/cercor/bhx179, doi:10.1093/cercor/bhx179.

[2]

BT Thomas Yeo, Fenna M Krienen, Jorge Sepulcre, Mert R Sabuncu, Danial Lashkari, Marisa Hollinshead, Joshua L Roffman, Jordan W Smoller, Lilla Zöllei, Jonathan R Polimeni, and others. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of neurophysiology, 2011. URL: https://doi.org/10.1152/jn.00338.2011, doi:10.1152/jn.00338.2011.

[3]

Lingzhong Fan, Hai Li, Junjie Zhuo, Yu Zhang, Jiaojian Wang, Liangfu Chen, Zhengyi Yang, Congying Chu, Sangma Xie, Angela R Laird, and others. The human brainnetome atlas: a new brain atlas based on connectional architecture. Cerebral cortex, 26(8):3508–3526, 2016. URL: https://doi.org/10.1093/cercor/bhw157, doi:10.1093/cercor/bhw157.

[4]

Marc Joliot, Gaël Jobard, Mikaël Naveau, Nicolas Delcroix, Laurent Petit, Laure Zago, Fabrice Crivello, Emmanuel Mellet, Bernard Mazoyer, and Nathalie Tzourio-Mazoyer. Aicha: an atlas of intrinsic connectivity of homotopic areas. Journal of neuroscience methods, 254:46–59, 2015. URL: https://doi.org/10.1016/j.jneumeth.2015.07.013, doi:10.1016/j.jneumeth.2015.07.013.

[5]

Evan M Gordon, Timothy O Laumann, Babatunde Adeyemo, Jeremy F Huckins, William M Kelley, and Steven E Petersen. Generation and evaluation of a cortical area parcellation from resting-state correlations. Cerebral cortex, 26(1):288–303, 2016. URL: https://doi.org/10.1093/cercor/bhu239, doi:10.1093/cercor/bhu239.

[6]

Nathalie Tzourio-Mazoyer, Brigitte Landeau, Dimitri Papathanassiou, Fabrice Crivello, Octave Etard, Nicolas Delcroix, Bernard Mazoyer, and Marc Joliot. Automated anatomical labeling of activations in spm using a macroscopic anatomical parcellation of the mni mri single-subject brain. Neuroimage, 15(1):273–289, 2002. URL: https://doi.org/10.1006/nimg.2001.0978, doi:10.1006/nimg.2001.0978.