Work

State-space model with deep learning for functional dynamics estimation in resting-state fMRI

Year: 2016

Type: article

Source: NeuroImage

DOI: 10.1016/j.neuroimage.2016.01.005

Authors: Heung-Il Suk, Chong-Yaw Wee, Seong-Whan Lee, Dinggang Shen

Institutions: Korea University, National University of Singapore, University of North Carolina at Chapel Hill

Language: English

Topic: Functional Brain Connectivity Studies

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Research Foundation of Korea, National Institutes of Health, Institute for Information and Communications Technology Promotion, National Institute on Aging, National Institute of Biomedical Imaging and Bioengineering

Awards: G2686953907, G3258782064, Assessing Large-scale Brain Connectivities in Mild Cognitive Impairment, G4798393751, Quantifying Brain Abnormality by Multimodality Neuroimage Analysis, Diagnosis of Alzheimer's Disease Using Dynamic High-Order Brain Networks, Longitudinal Mapping of Human Brain Development in the First Years of Life, Fast, Robust Analysis of Large Population Data, G5874234525, Imaging Genomics Based Brain Disease Prediction, G6575006414, Development of Robust Brain Measurement Tools Informed by Ultrahigh Field 7T MRI, G8437567545, G93323634

OpenAlex ID: W2238108400

FWCI: 22.04

Cites: 67

Cited by: 311

Related to: 10