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Abstract #2588

Il Gatto Sta Ingrassando: Novel Connectivity Tools and Additions in AFNI-FATCAT

Paul A Taylor 1,2 and Ziad S Saad 3

1 Faculty of Health Sciences, University of Cape Town, Cape Town, Western Cape, South Africa, 2 African Institute for Mathematical Sciences, South Africa, 3 NIMH, National Institutes of Health, Bethesda, MD, United States

We present developments in the AFNI-FATCAT suit of tools for analyzing MRI functional and structural connectivity. Improvements include: enhanced deterministic tracking to utilize voxelwise uncertainty; increased options for combatting false positives and negatives with including multi-directional tracking and anti-masking ROIs; combined visualization with SUMA and AFNI, allowing interactive manipulation of tracking and regions. These additions to AFNI-FATCAT increase researchers' capabilities for integrating functional and diffusion-based tractographic connectivity.

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