NeuroData's MRI to Graphs
m2g provides robust and reliable estimates of MRI connectivity across a wide range of datasets at 1mm resolution, across 25 parcellations, ranging in size from 48 to 72,000 nodes, all in MNI152 standard space.
m2g is a turn-key pipeline that provides session and group-level analysis, performing connectome estimation and summary statistic computation.
m2g runs reliably and robustly datasets spanning multiple scanners, acquisition parameters, and population demographics.
Publications
- A. Nikolaidis, A. S. Heinsfeld, T. Xu, P. Bellec, J. T. Vogelstein, and M. Milham. Bagging Improves Reproducibility of Functional Parcellation of the Human Brain. NeuroImage, 2020.
- G. Kiar, E. Bridgeford, W. G. Roncal, (CoRR), V. Chandrashekhar, D. Mhembere, S. Ryman, X. Zuo, D. S. Marguiles, R. C. Craddock, C. E. Priebe, R. Jung, V. Calhoun, B. Caffo, R. Burns, M. P. Milham, and J. Vogelstein. A High-Throughput Pipeline Identifies Robust Connectomes But Troublesome Variability. bioRxiv, 2018.
- G. Kiar, E. Bridgeford, V. Chandrashekhar, D. Mhembere, R. Burns, W. R. G. Roncal, and J. T. Vogelstein. A comprehensive cloud framework for accurate and reliable human connectome estimation and meganalysis. bioRxiv, 2017.
- G. Kiar, K. J. Gorgolewski, D. Kleissas, W. G. Roncal, B. Litt, B. Wandell, R. A. Poldrack, M. Wiener, R. J. Vogelstein, R. Burns, and J. T. Vogelstein. Science in the cloud (SIC): A use case in MRI connectomics. GigaScience, (5)6:1–10, 2017.