TY  - EJOUR
AU  - Kong, Ru Q
AU  - Spreng, R. Nathan
AU  - XUE, AIHUIPING
AU  - Betzel, Richard
AU  - Cohen, Jessica R
AU  - Damoiseaux, Jessica
AU  - De Brigard, Felipe
AU  - Eickhoff, Simon B
AU  - Fornito, Alex
AU  - Gratton, Caterina
AU  - Gordon, Evan M
AU  - Holmes, Avram J
AU  - Laird, Angela R
AU  - Larson-Prior, Linda
AU  - Nickerson, Lisa D
AU  - Pinho, Ana Luisa
AU  - Razi, Adeel
AU  - Sadaghiani, Sepideh
AU  - Shine, James
AU  - Yendiki, Anastasia
AU  - Yeo, B. T. Thomas
AU  - Uddin, Lucina Q
TI  - A network correspondence toolbox for quantitative evaluation of novel neuroimaging results
JO  - bioRxiv beta
CY  - Cold Spring Harbor
PB  - Cold Spring Harbor Laboratory, NY
M1  - FZJ-2024-04986
PY  - 2024
AB  - Decades of neuroscience research has shown that macroscale brain dynamics can be reliably decomposed into a subset of large-scale functional networks, but the specific spatial topographies of these networks and the names used to describe them can vary across studies. Such discordance has hampered interpretation and convergence of research findings across the field. To address this problem, we have developed the Network Correspondence Toolbox (NCT) to permit researchers to examine and report spatial correspondence between their novel neuroimaging results and sixteen widely used functional brain atlases, consistent with recommended reporting standards developed by the Organization for Human Brain Mapping. The atlases included in the toolbox show some topographical convergence for specific networks, such as those labeled as default or visual. Network naming varies across atlases, particularly for networks spanning frontoparietal association cortices. For this reason, quantitative comparison with multiple atlases is recommended to benchmark novel neuroimaging findings. We provide several exemplar demonstrations using the Human Connectome Project task fMRI results and UK Biobank independent component analysis maps to illustrate how researchers can use the NCT to report their own findings through quantitative evaluation against multiple published atlases. The NCT provides a convenient means for computing Dice coefficients with spin test permutations to determine the magnitude and statistical significance of correspondence among user-defined maps and existing atlas labels. The NCT also includes functionality to incorporate additional atlases in the future. The adoption of the NCT will make it easier for network neuroscience researchers to report their findings in a standardized manner, thus aiding reproducibility and facilitating comparisons between studies to produce interdisciplinary insights.
LB  - PUB:(DE-HGF)25
DO  - DOI:10.1101/2024.06.17.599426
UR  - https://juser.fz-juelich.de/record/1029130
ER  -