Task fMRI data analysis based on supervised stochastic coordinate coding

[1]  J. Lv,et al.  Assessing effects of prenatal alcohol exposure using group-wise sparse representation of fMRI data , 2015, Psychiatry Research: Neuroimaging.

[2]  Jieping Ye,et al.  Holistic Atlases of Functional Networks and Interactions Reveal Reciprocal Organizational Architecture of Cortical Function , 2015, IEEE Transactions on Biomedical Engineering.

[3]  Heng Huang,et al.  Sparse representation of whole-brain fMRI signals for identification of functional networks , 2015, Medical Image Anal..

[4]  Qingyang Li,et al.  Stochastic Coordinate Coding and Its Application for Drosophila Gene Expression Pattern Annotation , 2014, ArXiv.

[5]  Abraham Z. Snyder,et al.  Function in the human connectome: Task-fMRI and individual differences in behavior , 2013, NeuroImage.

[6]  L. Pessoa Beyond brain regions: Network perspective of cognition–emotion interactions , 2012, Behavioral and Brain Sciences.

[7]  Sungho Tak,et al.  A Data-Driven Sparse GLM for fMRI Analysis Using Sparse Dictionary Learning With MDL Criterion , 2011, IEEE Transactions on Medical Imaging.

[8]  Degang Zhang,et al.  Complex span tasks and hippocampal recruitment during working memory , 2011, NeuroImage.

[9]  N. Kanwisher Functional specificity in the human brain: A window into the functional architecture of the mind , 2010, Proceedings of the National Academy of Sciences.

[10]  J. Duncan The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour , 2010, Trends in Cognitive Sciences.

[11]  Guillermo Sapiro,et al.  Online Learning for Matrix Factorization and Sparse Coding , 2009, J. Mach. Learn. Res..

[12]  Yann LeCun,et al.  What is the best multi-stage architecture for object recognition? , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[13]  Stephen M Smith,et al.  Correspondence of the brain's functional architecture during activation and rest , 2009, Proceedings of the National Academy of Sciences.

[14]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.

[15]  Allen Y. Yang,et al.  Robust Face Recognition via Sparse Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  Marc Teboulle,et al.  A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..

[17]  N. Logothetis What we can do and what we cannot do with fMRI , 2008, Nature.

[18]  K. Lange,et al.  Coordinate descent algorithms for lasso penalized regression , 2008, 0803.3876.

[19]  Bruno A Olshausen,et al.  Sparse coding of sensory inputs , 2004, Current Opinion in Neurobiology.

[20]  R. Tibshirani,et al.  REJOINDER TO "LEAST ANGLE REGRESSION" BY EFRON ET AL. , 2004, math/0406474.

[21]  R. Tibshirani,et al.  Least angle regression , 2004, math/0406456.

[22]  Stephen M. Smith,et al.  General multilevel linear modeling for group analysis in FMRI , 2003, NeuroImage.

[23]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[24]  D. Heeger,et al.  In this issue , 2002, Nature Reviews Drug Discovery.

[25]  David J. Field,et al.  Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.

[26]  E. Bizzi,et al.  The Cognitive Neurosciences , 1996 .

[27]  R. Tibshirani Regression Shrinkage and Selection via the Lasso , 1996 .

[28]  Karl J. Friston,et al.  Statistical parametric maps in functional imaging: A general linear approach , 1994 .