Measuring granger causality between cortical regions from voxelwise fmRI BOLD signals with LASSO

PLoS Computational Biology

Volumn 8, Issue 5, 2012, Pages

  Tang, Wei ^a   Bressler, Steven L ^a   Sylvester, Chad M ^b   Shulman, Gordon L ^b   Corbetta, Maurizio ^b  

^a FLORIDA ATLANTIC UNIVERSITY   (United States)

^b WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN; FUNCTIONAL NEUROIMAGING; STATISTICAL TESTS; TIME SERIES; TIME SERIES ANALYSIS;

BLOOD OXYGEN LEVEL DEPENDENTS; BLOOD-OXYGEN-LEVEL DEPENDENTS; BRAIN NETWORKS; BRAIN REGIONS; CORTICAL REGIONS; FUNCTIONAL INTERACTION; FUNCTIONAL MAGNETIC RESONANCE IMAGING; GRANGER CAUSALITY; HUMAN COGNITION; SELECTION OPERATORS;

MAGNETIC RESONANCE IMAGING;

ALGORITHM; ARTICLE; BOLD SIGNAL; BRAIN REGION; CONTROLLED STUDY; CORRELATION COEFFICIENT; FUNCTIONAL ASSESSMENT; FUNCTIONAL MAGNETIC RESONANCE IMAGING; GRANGER CAUSALITY; LEAST ABSOLUTE SHRINKAGE ELECTION OPERATOR; PREDICTION; REGRESSION ANALYSIS; SIMULATION; STATISTICAL ANALYSIS; TIME SERIES ANALYSIS; VALIDATION PROCESS; ANIMAL; BIOLOGICAL MODEL; BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; HUMAN; METHODOLOGY; NERVE CELL NETWORK; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; STATISTICAL MODEL; SYNAPTIC TRANSMISSION;

ALGORITHMS; ANIMALS; BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; HUMANS; MAGNETIC RESONANCE IMAGING; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; NERVE NET; SYNAPTIC TRANSMISSION;

EID: 84863686049     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1002513     Document Type: Article

References (44)

1. Bressler SL, Menon V, (2010) Large-scale brain networks in cognition: Emerging methods and principles. Trends Cogn Sci 14: 277-290.
2. Greicius MD, Krasnow B, Reiss AL, Menon V, (2003) Functional connectivity in the resting brain: A network analysis of the default mode hypothesis. Proc Natl Acad Sci U S A 100: 253-258.
3. He BJ, Snyder AZ, Vincent JL, Epstein A, Shulman GL, et al. (2007) Breakdown of functional connectivity in frontoparietal networks underlies behavioral deficits in spatial neglect. Neuron 53: 905-918.
4. Hagmann P, Cammoun L, Gigandet X, Meuli R, Honey CJ, et al. (2008) Mapping the structural core of human cerebral cortex. PLoS Biol 6: e159.
5. Anderson JS, Ferguson MA, Lopez-Larson M, Yurgelun-Todd D, (2010) Topographic maps of multisensory attention. Proc Natl Acad Sci U S A 107: 20110-20114.
6. Zhang L, Zhong G, Wu Y, Vangel MG, Jiang B, et al. (2010) Using Granger-Geweke causality model to evaluate the effective connectivity of primary motor cortex (M1), supplementary motor area (SMA) and cerebellum. J Biomed Sci Eng 3: 848-860.
7. Wiener N, (1956) The theory of prediction. Modern Mathematics for the Engineer New York McGraw-Hill pp. 165-190.
8. Granger CWJ, (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37: 424-38.
9. Bernasconi C, Konig P, (1999) On the directionality of cortical interactions studied by structural analysis of electrophysiological recordings. Biol Cybern 81: 199-210.
10. Ding M, Bressler SL, Yang W, Liang H, (2000) Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modeling: data preprocessing, model validation, and variability assessment. Biol Cybern 83: 35-45.
11. Kaminski M, Ding M, Truccolo WA, Bressler SL, (2001) Evaluating causal relations in neural systems: Granger causality, directed transfer function and statistical assessment of significance. Biol Cybern 85: 145-157.
12. Hesse W, Moller E, Arnold M, Schack B, (2003) The use of time-variant EEG Granger causality for inspecting directed interdependencies of neural assemblies. J Neurosci Meth 124: 27-44.
13. Ding M, Chen Y, Bressler SL, (2006) Granger causality: Basic theory and application to neuroscience. In: Schelter S, Winterhalder M, Timmer J, editors. Handbook of time series analysis Wienheim Wiley pp. 438-460.
14. Bressler SL, Seth AK, (2011) Wiener-Granger Causality: A well established methodology. Neuroimage 58: 323-329.
15. Roebroeck A, Formisano E, Goebel R, (2005) Mapping directed influence over the brain using Granger causality and fMRI. Neuroimage 25: 230-242.
16. Deshpande G, Hu X, Stilla R, Sathian K, (2008) Effective connectivity during haptic perception: A study using Granger causality analysis of functional magnetic resonance imaging data. Neuroimage 40: 1807-1814.
17. Roebroeck A, Formisano E, Goebel R, (2011) The identification of interacting networks in the brain using fMRI: Model selection, causality and deconvolution. Neuroimage 58: 296-302.
18. Roebroeck A, Formisano E, Goebel R, (2011) Reply to Friston and David: After comments on: The identification of interacting networks in the brain using fMRI: Model selection, causality and deconvolution. Neuroimage 58: 310-311.
19. David O, Guillemain I, Saillet S, Reyt S, Deransart C, et al. (2008) Identifying neural drivers with functional MRI: An electrophysiological validation. PLoS Biol 6: 2683-2697.
20. Friston K, (2009) Causal modelling and brain connectivity in functional magnetic resonance imaging. PLoS Biol 7: e1000033.
21. Friston K, (2011) Functional and effective connectivity: A review. Brain Connect 1: 13-36.
22. Friston K, (2011) Dynamic causal modeling and Granger causality Comments on: The identification of interacting networks in the brain using fMRI: Model selection, causality and deconvolution. Neuroimage 58: 303-305.
23. David O, (2011) fMRI connectivity, meaning and empiricism Comments on: The identification of interacting networks in the brain using fMRI: Model selection, causality and deconvolution. Neuroimage 58: 306-309.
24. Bressler SL, Tang W, Sylvester CM, Shulman GL, Corbetta M, (2008) Top-down control of human visual cortex by frontal and parietal cortex in anticipatory visual spatial attention. J Neurosci 28: 10056-10061.
25. Geweke JF, (1984) Measures of conditional linear dependence and feedback between time series. J Amer Stat Assoc 79: 907-915.
26. Chen Y, Bressler S, Ding M, (2006) Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data. J Neurosci Meth 150: 228-237.
27. Seth AK, Edelman GM, (2007) Distinguishing causal interactions in neural populations. Neur Comp 19: 910-933.
28. Valdes-Sosa PA, Sanchez-Bornot JM, Lage-Castellanos A, Vega-Hernandez M, Bosch-Bayard J, et al. (2005) Estimating brain functional connectivity with sparse multivariate autoregression. Philos Trans Royal Soc B: Biol Sci 360: 969-981.
29. Tibshirani R, (2011) Regression shrinkage and selection via the lasso: A retrospective. J R Stat Soc B Stat Methodol 73: 273-282.
30. Arnold A, Liu Y, Abe N, (2007) Temporal causal modeling with graphical granger methods. pp. 66-75 In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; 12-15 August 2007; San Jose, California, United States.
31. Shojaie A, Michailidis G, (2010) Discovering graphical Granger causality using the truncating lasso penalty. Bioinf 26: i517-i523.
32. Sanchez-Bornot JM, Martinez-Montes E, Lage-Castellanos A, Vega-Hernandez M, Valdes-Sosa PA, (2008) Uncovering sparse brain effective connectivity: A voxel-based approach using penalized regression. Stat Sin 18: 1501-1518.
33. Garg R, Cecchi GA, Rao AR, (2011) Full-brain auto-regressive modeling (FARM) using fMRI. Neuroimage 58: 416-441.
34. Sylvester CM, Shulman GL, Jack AI, Corbetta M, (2007) Asymmetry of anticipatory activity in visual cortex predicts the locus of attention and perception. J Neurosci 27: 14424-14433.
35. Roebroeck A, Formisano E, Goebel R, (2005) Mapping directed influence over the brain using Granger causality and fMRI. Neuroimage 25: 230-242.
36. Cohen AL, Fair DA, Dosenbach NUF, Miezin FM, Dierker D, et al. (2008) Defining functional areas in individual human brains using resting functional connectivity MRI. Neuroimage 41: 45-57.
37. He Y, Chen ZJ, Evans AC, (2007) Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. Cereb Cortex 17: 2407-2419.
38. Gong G, He Y, Concha L, Lebel C, Gross DW, et al. (2009) Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography. Cereb Cortex 19: 524-536.
39. Tibshirani R, Saunders M, Rosset S, Zhu J, Knight K, (2005) Sparsity and smoothness via the fused lasso. J R Stat Soc Ser B Stat Methodol 67: 91-108.
40. Zou H, Hastie T, (2005) Regularization and variable selection via the elastic net. J R Stat Soc Ser B Stat Methodol 67: 301-320.
41. Yuan M, Lin Y, (2006) Model selection and estimation in regression with grouped variables. J R Stat Soc Ser B Stat Methodol 68: 49-67.
42. Hesterberg T, Choi NH, Meier L, Fraley C, (2008) Least angle and l1 penalized regression: A review. Statist Surv 2: 61-93.
43. Greene W, (2003) Least squares. Econometric Analysis Upper Saddle River, NJ Prentice Hall pp. 19-40.
44. Efron B, Hastie T, Johnstone I, Tibshirani R, (2004) Least angle regression. Ann Stat 32: 407-499.