title: Improved FastICA algorithm in fMRI data analysis using the sparsity property of the sources.
abstract: BACKGROUND
  As a blind source separation technique, independent component analysis (ICA) has many applications in functional magnetic resonance imaging (fMRI). Although either temporal or spatial prior information has been introduced into the constrained ICA and semi-blind ICA methods to improve the performance of ICA in fMRI data analysis, certain types of additional prior information, such as the sparsity, has seldom been added to the ICA algorithms as constraints.
  
  
  METHODS
  In this study, we proposed a SparseFastICA method by adding the source sparsity as a constraint to the FastICA algorithm to improve the performance of the widely used FastICA. The source sparsity is estimated through a smoothed ℓ0 norm method. We performed experimental tests on both simulated data and real fMRI data to investigate the feasibility and robustness of SparseFastICA and made a performance comparison between SparseFastICA, FastICA and Infomax ICA.
  
  
  RESULTS
  Results of the simulated and real fMRI data demonstrated the feasibility and robustness of SparseFastICA for the source separation in fMRI data.
  
  
  METHODS
  Both the simulated and real fMRI experimental results showed that SparseFastICA has better robustness to noise and better spatial detection power than FastICA. Although the spatial detection power of SparseFastICA and Infomax did not show significant difference, SparseFastICA had faster computation speed than Infomax.
  
  
  CONCLUSIONS
  SparseFastICA was comparable to the Infomax algorithm with a faster computation speed. More importantly, SparseFastICA outperformed FastICA in robustness and spatial detection power and can be used to identify more accurate brain networks than FastICA algorithm.
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; College of Information Science and Technology, Beijing Normal University, Beijing 100875, China; Non-Invasive Neurostimulation Therapies (NINET) Laboratory, Department of Psychiatry, Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 2A1, Canada.
authors.forename: Ruiyang
authors.initials: R
authors.lastname: Ge
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
authors.forename: Yubao
authors.initials: Y
authors.lastname: Wang
authors.affiliation: College of Information Science and Technology, Beijing Normal University, Beijing 100875, China.
authors.forename: Jipeng
authors.initials: J
authors.lastname: Zhang
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; College of Information Science and Technology, Beijing Normal University, Beijing 100875, China.
authors.forename: Li
authors.initials: L
authors.lastname: Yao
authors.affiliation: Paul C. Lauterbur Research Centers for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
authors.forename: Hang
authors.initials: H
authors.lastname: Zhang
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China. Electronic address: friskying@163.com.
authors.forename: Zhiying
authors.initials: Z
authors.lastname: Long
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000098:blood supply / Q000000981:diagnostic imaging*; D001931:Brain Mapping; D003198:Computer Simulation; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D010100:Oxygen / Q000097:blood; D025341:Principal Component Analysis; D011597:Psychomotor Performance; D012372:ROC Curve; D012146:Rest; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult
chemical_list: D010100:Oxygen
keywords: FastICA; Functional magnetic resonance imaging (fMRI); Independent component analysis (ICA); Sparse