@inproceedings{aa42239729c947e8802b85f403cc27e3,
title = "A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes",
abstract = "We propose a novel matrix autoencoder to map functional connectomes from resting state fMRI (rs-fMRI) to structural connectomes from Diffusion Tensor Imaging (DTI), as guided by subject-level phenotypic measures. Our specialized autoencoder infers a low dimensional manifold embedding for the rs-fMRI correlation matrices that mimics a canonical outer-product decomposition. The embedding is simultaneously used to reconstruct DTI tractography matrices via a second manifold alignment decoder and to predict inter-subject phenotypic variability via an artificial neural network. We validate our framework on a dataset of 275 healthy individuals from the Human Connectome Project database and on a second clinical dataset consisting of 57 subjects with Autism Spectrum Disorder. We demonstrate that the model reliably recovers structural connectivity patterns across individuals, while robustly extracting predictive and interpretable brain biomarkers in a cross-validated setting. Finally, our framework outperforms several baselines at predicting behavioral phenotypes in both real-world datasets.",
keywords = "Functional connectivity, Manifold alignment, Matrix autoencoder, Phenotypic prediction, Structural connectivity",
author = "D{\textquoteright}Souza, {Niharika Shimona} and Nebel, {Mary Beth} and Deana Crocetti and Joshua Robinson and Stewart Mostofsky and Archana Venkataraman",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021 ; Conference date: 27-09-2021 Through 01-10-2021",
year = "2021",
doi = "10.1007/978-3-030-87234-2_59",
language = "English (US)",
isbn = "9783030872335",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "625--636",
editor = "{de Bruijne}, Marleen and Cattin, {Philippe C.} and St{\'e}phane Cotin and Nicolas Padoy and Stefanie Speidel and Yefeng Zheng and Caroline Essert",
booktitle = "Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 - 24th International Conference, Proceedings",
address = "Germany",
}