Spatial source phase: A new feature for identifying spatial differences based on complex‐valued resting‐state fMRI data

Author:

Qiu Yue1,Lin Qiu‐Hua1ORCID,Kuang Li‐Dan2,Gong Xiao‐Feng1,Cong Fengyu34,Wang Yu‐Ping5,Calhoun Vince D.67

Affiliation:

1. School of Information and Communication Engineering, Faculty of Electronic Information and Electrical EngineeringDalian University of Technology Dalian China

2. School of Computer and Communication EngineeringChangsha University of Science and Technology Changsha China

3. School of Biomedical Engineering, Faculty of Electronic Information and Electrical EngineeringDalian University of Technology Dalian China

4. Department of Mathematical Information TechnologyUniversity of Jyvaskyla Jyvaskyla Finland

5. Department of Biomedical EngineeringTulane University New Orleans Louisiana

6. The Mind Research Network Albuquerque New Mexico

7. Department of Electrical and Computer EngineeringUniversity of New Mexico Albuquerque New Mexico

Funder

China Scholarship Council

National Natural Science Foundation of China

National Institutes of Health

Publisher

Wiley

Subject

Clinical Neurology,Neurology,Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology,Anatomy

Reference55 articles.

1. The effect of model order selection in group PICA;Abou E. A.;Human Brain Mapping,2010

2. Complex ICA of Brain Imaging Data [Life Sciences]

3. Complex-valued time series modeling for improved activation detection in fMRI studies

4. Decreased hemispheric connectivity and decreased intra‐ and inter‐ hemisphere asymmetry of resting state functional network connectivity in schizophrenia;Agcaoglu O.;Brain Imaging & Behavior,2017

5. A baseline for the multivariate comparison of resting‐state networks;Allen E. A.;Frontiers in Systems Neuroscience,2011

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