@inproceedings{d44ae86707cf4f548719790e780ccad5,
title = "Blockmodels for connectome analysis",
abstract = "In the present work we study a family of generative network model and its applications for modeling the human connectome. We introduce a minor but novel variant of the Mixed Membership Stochastic Blockmodel and apply it and two other related model to two human connectome datasets (ADNI and a Bipolar Disorder dataset) with both control and diseased subjects. We further provide a simple generative classifier that, alongside more discriminating methods, provides evidence that blockmodels accurately summarize tractography count networks with respect to a disease classification task.",
keywords = "Connectomics, Diffusion Weighted Imaging, Random Network Models",
author = "Daniel Moyer and Boris Gutman and Gautam Prasad and Joshua Faskowitz and {Ver Steeg}, Greg and Paul Thompson",
note = "Publisher Copyright: {\textcopyright} 2015 SPIE.; 11th International Symposium on Medical Information Processing and Analysis, SIPAIM 2015 ; Conference date: 17-11-2015 Through 19-11-2015",
year = "2015",
doi = "10.1117/12.2211519",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Garcia-Arteaga, {Juan D.} and Jorge Brieva and Natasha Lepore and Eduardo Romero",
booktitle = "11th International Symposium on Medical Information Processing and Analysis",
address = "United States",
}