A pooling-LiNGAM algorithm for effective connectivity analysis of fMRI data
暂无分享,去创建一个
Li Yao | Kewei Chen | Jiacai Zhang | Lele Xu | Xia Wu | Xiaojuan Guo | Tingting Fan | L. Yao | Lele Xu | Kewei Chen | Xia Wu | Xiaojuan Guo | Jia-cai Zhang | Tingting Fan
[1] Mark W. Woolrich,et al. Network modelling methods for FMRI , 2011, NeuroImage.
[2] David Heckerman,et al. Learning Gaussian Networks , 1994, UAI.
[3] Hongyan Chen,et al. Altered Effective Connectivity of the Default Mode Network in Resting-State Amnestic Type Mild Cognitive Impairment , 2013, Journal of the International Neuropsychological Society.
[4] Tom Burr,et al. Causation, Prediction, and Search , 2003, Technometrics.
[5] Karl J. Friston,et al. Effective Connectivity and Intersubject Variability: Using a Multisubject Network to Test Differences and Commonalities , 2002, NeuroImage.
[6] Shohei Shimizu,et al. Use of non-normality in structural equation modeling: Application to direction of causation , 2008 .
[7] Rainer Goebel,et al. Investigating directed cortical interactions in time-resolved fMRI data using vector autoregressive modeling and Granger causality mapping. , 2003, Magnetic resonance imaging.
[8] Vinod Menon,et al. Functional connectivity in the resting brain: A network analysis of the default mode hypothesis , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[9] Aapo Hyvärinen,et al. A Linear Non-Gaussian Acyclic Model for Causal Discovery , 2006, J. Mach. Learn. Res..
[10] D. Hibbs. On analyzing the effects of policy interventions : Box-Jenkins and Box-Tiao vs. structural equation models , 1977 .
[11] Terrence J. Sejnowski,et al. Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Subgaussian and Supergaussian Sources , 1999, Neural Computation.
[12] Karl J. Friston. Functional and effective connectivity in neuroimaging: A synthesis , 1994 .
[13] E. Formisano,et al. Functional connectivity as revealed by spatial independent component analysis of fMRI measurements during rest , 2004, Human brain mapping.
[14] J. Pearl. Causality: Models, Reasoning and Inference , 2000 .
[15] Shohei Shimizu,et al. Joint estimation of linear non-Gaussian acyclic models , 2011, Neurocomputing.
[16] J. Pekar,et al. A method for making group inferences from functional MRI data using independent component analysis , 2001, Human brain mapping.
[17] Wei Zhu,et al. Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data , 2007, Human brain mapping.
[18] Martin J. McKeown,et al. Dynamic Bayesian network modeling of fMRI: A comparison of group-analysis methods , 2008, NeuroImage.
[19] Erkki Oja,et al. Independent component analysis: algorithms and applications , 2000, Neural Networks.
[20] Pierre Comon,et al. Independent component analysis, A new concept? , 1994, Signal Process..
[21] B. Biswal,et al. Functional connectivity in the motor cortex of resting human brain using echo‐planar mri , 1995, Magnetic resonance in medicine.
[22] Seungjin Choi,et al. Independent Component Analysis , 2009, Handbook of Natural Computing.
[23] Jagath C. Rajapakse,et al. Learning functional structure from fMR images , 2006, NeuroImage.
[24] F. Gonzalez-Lima,et al. Structural equation modeling and its application to network analysis in functional brain imaging , 1994 .
[25] D. Chakrabarti,et al. A fast fixed - point algorithm for independent component analysis , 1997 .
[26] Martin J. McKeown,et al. A Multi-Subject, Dynamic Bayesian Networks (DBNS) Framework for Brain Effective Connectivity , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.
[27] R. Buxton,et al. Dynamics of blood flow and oxygenation changes during brain activation: The balloon model , 1998, Magnetic resonance in medicine.
[28] M. Greicius,et al. Default-Mode Activity during a Passive Sensory Task: Uncoupled from Deactivation but Impacting Activation , 2004, Journal of Cognitive Neuroscience.
[29] Ingrid S. Johnsrude,et al. Can Meaningful Effective Connectivities Be Obtained between Auditory Cortical Regions? , 2001, NeuroImage.
[30] Karl J. Friston,et al. Functional Connectivity: The Principal-Component Analysis of Large (PET) Data Sets , 1993, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[31] C. Robert Kenley,et al. Gaussian influence diagrams , 1989 .
[32] Stephen M. Smith,et al. Advances and Pitfalls in the Analysis and Interpretation of Resting-State FMRI Data , 2010, Front. Syst. Neurosci..
[33] Li Yao,et al. Temporal and instantaneous connectivity of default mode network estimated using Gaussian Bayesian network frameworks , 2012, Neuroscience Letters.
[34] David Heckerman,et al. A Tutorial on Learning with Bayesian Networks , 1999, Innovations in Bayesian Networks.
[35] Karl J. Friston,et al. Dynamic causal modelling , 2003, NeuroImage.
[36] J. Lynch,et al. Cortico-cortical networks and cortico-subcortical loops for the higher control of eye movements. , 2006, Progress in brain research.
[37] C. Stein,et al. Structural equation modeling. , 2012, Methods in molecular biology.
[38] S. Bressler,et al. Stochastic modeling of neurobiological time series: power, coherence, Granger causality, and separation of evoked responses from ongoing activity. , 2006, Chaos.