Two-step paretial least square regression classifiers in brain-state decoding using functional magnetic resonance imaging
暂无分享,去创建一个
Li Yao | Yubao Wang | Zhiying Long | Xuanping Liu | L. Yao | Z. Long | Yubao Wang | Xuanping Liu
[1] Danh V. Nguyen,et al. Multi-class cancer classification via partial least squares with gene expression profiles , 2002, Bioinform..
[2] Charles D. Smith,et al. Partial least squares for discrimination in fMRI data. , 2012, Magnetic resonance imaging.
[3] Yeung Sam Hung,et al. Decoding Subjective Intensity of Nociceptive Pain from Pre-stimulus and Post-stimulus Brain Activities , 2016, Front. Comput. Neurosci..
[4] Russell T. Shinohara,et al. Approaches to Defining Common and Dissociable Neurobiological Deficits Associated With Psychopathology in Youth , 2019, Biological Psychiatry.
[5] F. Tong,et al. Decoding reveals the contents of visual working memory in early visual areas , 2009, Nature.
[6] Sunduz Keles,et al. Sparse Partial Least Squares Classification for High Dimensional Data , 2010, Statistical applications in genetics and molecular biology.
[7] Kai Wang,et al. Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI , 2018, EBioMedicine.
[8] Ravi Mathur,et al. Partial Least Squares (PLS) Applied to Medical Bioinformatics , 2011, Complex Adaptive Systems.
[9] Tahir Mehmood,et al. A review of variable selection methods in Partial Least Squares Regression , 2012 .
[10] S. Keleş,et al. Sparse partial least squares regression for simultaneous dimension reduction and variable selection , 2010, Journal of the Royal Statistical Society. Series B, Statistical methodology.
[11] N. Kanwisher,et al. The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception , 1997, The Journal of Neuroscience.
[12] M SwathiC,et al. Voxel Selection of fMRI Data using Multi- Voxel Pattern Analysis to Predict Neural Response , 2015 .
[13] Tom Michael Mitchell,et al. Predicting Human Brain Activity Associated with the Meanings of Nouns , 2008, Science.
[14] Philip A. Kragel,et al. Multivariate neural biomarkers of emotional states are categorically distinct. , 2015, Social cognitive and affective neuroscience.
[15] Vince D. Calhoun,et al. Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia , 2016, NeuroImage.
[16] Mark A. Elliott,et al. Impact of in-scanner head motion on multiple measures of functional connectivity: Relevance for studies of neurodevelopment in youth , 2012, NeuroImage.
[17] Li Yao,et al. Comparative Study of SVM Methods Combined with Voxel Selection for Object Category Classification on fMRI Data , 2011, PloS one.
[18] W. Art Chaovalitwongse,et al. Voxel Selection Framework in Multi-Voxel Pattern Analysis of fMRI Data for Prediction of Neural Response to Visual Stimuli , 2014, IEEE Transactions on Medical Imaging.
[19] Youngjo Lee,et al. Sparse partial least-squares regression and its applications to high-throughput data analysis , 2011 .
[20] Russell A. Epstein,et al. The Parahippocampal Place Area Recognition, Navigation, or Encoding? , 1999, Neuron.
[21] D. Hu,et al. Neurobiological basis of head motion in brain imaging , 2014, Proceedings of the National Academy of Sciences.
[22] W. Art Chaovalitwongse,et al. Multicriteria variable selection for classification of production batches , 2012, Eur. J. Oper. Res..
[23] P. Rodríguez,et al. Neural decoding of goal locations in spatial navigation in humans with fMRI , 2009, Human brain mapping.
[24] Vince D. Calhoun,et al. SimTB, a simulation toolbox for fMRI data under a model of spatiotemporal separability , 2012, NeuroImage.
[25] Sean M. Polyn,et al. Beyond mind-reading: multi-voxel pattern analysis of fMRI data , 2006, Trends in Cognitive Sciences.