Hypergraph Laplacian Diffusion Model for Predicting Resting Brain Functional Connectivity from Structural Connectivity-Reference-Cited by-同舟云学术

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Hypergraph Laplacian Diffusion Model for Predicting Resting Brain Functional Connectivity from Structural Connectivity

Published:2022-10-21 Issue: Volume: Page:
ISSN:
Container-title:2022 16th IEEE International Conference on Signal Processing (ICSP)
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Author:

Ma Jichao¹,Yuan Yue²,Wang Yanjiang¹

Affiliation:

1. China University of Petroleum (East China),College of Control Science and Engineering,Qingdao,China,266580

2. Hisense Group Holdings Co., Ltd.,,BPIT & DT Department,Qingdao,China,266071

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9964480/9964481/09965288.pdf?arnumber=9965288

Reference35 articles.

1. A connectivity-based test-retest dataset of multi-modal magnetic resonance imaging in young healthy adults

2. Learning with hypergraphs: clustering, classification, and embedding;zhou;in Advances in Neural Information Processing Systems 19Proceedings of the Twentieth Annual Conference on Neural Information Processing Systems,2006

3. Functional brain connectivity is predictable from anatomic network's Laplacian eigen-structure

4. Network diffusion accurately models the relationship between structural and functional brain connectivity networks

5. BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics

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