Three‐way parallel group independent component analysis: Fusion of spatial and spatiotemporal magnetic resonance imaging data-Reference-Cited by-同舟云学术

Three‐way parallel group independent component analysis: Fusion of spatial and spatiotemporal magnetic resonance imaging data

Published:2021-11-22 Issue: Volume: Page:
ISSN:1065-9471
Container-title:Human Brain Mapping
language:en
Short-container-title:Hum Brain Mapp

Author:

Qi Shile¹^ORCID,Silva Rogers F.²,Zhang Daoqiang¹,Plis Sergey M.²,Miller Robyn²,Vergara Victor M.²^ORCID,Jiang Rongtao³,Zhi Dongmei⁴^ORCID,Sui Jing⁴,Calhoun Vince D.²

Affiliation:

1. College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China

2. Tri‐institutional Center for Translational Research in Neuroimaging and Data Sciences (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University] Atlanta Georgia USA

3. Department of Radiology and Biomedical Imaging Yale University New Haven Connecticut USA

4. State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University Beijing China

Funder

National Natural Science Foundation of China

Beijing Municipal Science and Technology Commission

National Science Foundation of Sri Lanka

Publisher

Wiley

Subject

Neurology (clinical),Neurology,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology,Anatomy

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/hbm.25720

Reference59 articles.

1. Multimodal Neuroimaging in Schizophrenia: Description and Dissemination

2. Natural Gradient Works Efficiently in Learning

3. Multimodal Machine Learning: A Survey and Taxonomy

4. Variability in the analysis of a single neuroimaging dataset by many teams

5. Subcortical visual dysfunction in schizophrenia drives secondary cortical impairments

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