Cargando…
Robust Motion Regression of Resting-State Data Using a Convolutional Neural Network Model
Resting-state functional magnetic resonance imaging (rs-fMRI) based on the blood-oxygen-level-dependent (BOLD) signal has been widely used in healthy individuals and patients to investigate brain functions when the subjects are in a resting or task-negative state. Head motion considerably confounds...
Autores principales: | Yang, Zhengshi, Zhuang, Xiaowei, Sreenivasan, Karthik, Mishra, Virendra, Cordes, Dietmar |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6482337/ https://www.ncbi.nlm.nih.gov/pubmed/31057348 http://dx.doi.org/10.3389/fnins.2019.00169 |
Ejemplares similares
-
Disentangling time series between brain tissues improves fMRI data quality using a time-dependent deep neural network
por: Yang, Zhengshi, et al.
Publicado: (2020) -
Energy-Period Profiles of Brain Networks in Group fMRI Resting-State Data: A Comparison of Empirical Mode Decomposition With the Short-Time Fourier Transform and the Discrete Wavelet Transform
por: Cordes, Dietmar, et al.
Publicado: (2021) -
Performing Sparse Regularization and Dimension Reduction Simultaneously in Multimodal Data Fusion
por: Yang, Zhengshi, et al.
Publicado: (2019) -
Resting-State Static and Dynamic Functional Abnormalities in Active Professional Fighters With Repetitive Head Trauma and With Neuropsychological Impairments
por: Zhuang, Xiaowei, et al.
Publicado: (2020) -
Single-scale time-dependent window-sizes in sliding-window dynamic functional connectivity analysis: A validation study
por: Zhuang, Xiaowei, et al.
Publicado: (2020)