Analysing connectivity with Granger causality and dynamic causal modelling

Current Opinion in Neurobiology

Volumn 23, Issue 2, 2013, Pages 172-178

  Friston, Karl ^a   Moran, Rosalyn ^a   Seth, Anil K ^b  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY OF SUSSEX   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CAUSAL MODELING; CONNECTOME; DYNAMIC CAUSAL MODELING; ENTROPY; EVENT RELATED POTENTIAL; FUNCTIONAL ASSESSMENT; FUNCTIONAL MAGNETIC RESONANCE IMAGING; GRANGER CAUSALITY; HEMODYNAMICS; INDEPENDENT COMPONENT ANALYSIS; INFORMATION PROCESSING; INTEGRATION; NERVE CELL NETWORK; NEUROPHYSIOLOGY; POSTSYNAPTIC POTENTIAL; PRIORITY JOURNAL; REVIEW; VISUOMOTOR COORDINATION;

BRAIN; BRAIN MAPPING; CAUSALITY; COMPUTER SIMULATION; HUMANS; MODELS, NEUROLOGICAL; NERVE NET; NEURONS; NONLINEAR DYNAMICS;

EID: 84875866518     PISSN: 09594388     EISSN: 18736882     Source Type: Journal    
DOI: 10.1016/j.conb.2012.11.010     Document Type: Review

References (53)

1. Zeki S., Shipp S. The functional logic of cortical connections. Nature 1988, 335:311-317.
2. Friston K.J., Frith C.D., Liddle P.F., Frackowiak R.S. Functional connectivity: the principal-component analysis of large (PET) data sets. J Cereb Blood Flow Metab 1993, 13:5-14.
3. Breakspear M. Dynamic connectivity in neural systems-theoretical and empirical considerations. Neuroinformatics 2004, 2:205-225.
4. Bell A.J., Sejnowski T.J. An information maximisation approach to blind separation and blind de-convolution. Neural Comput 1995, 7:1129-1159.
5. Siegel M., Donner T.H., Engel A.K. Spectral fingerprints of large-scale neuronal interactions. Nat Rev Neurosci 2012, 13:131-134.
6. Granger C.W.J. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 1969, 37:424-438.
7. David O., Kiebel S., Harrison L., Mattout J., Kilner J.M., Friston K.J. Dynamic causal modeling of evoked responses in EEG and MEG. Neuroimage 2006, 30:1255-1272.
8. Garrido M.I., Kilner J.M., Kiebel S.J., Friston K.J. Evoked brain responses are generated by feedback loops. Proc Natl Acad Sci USA 2007, 104:20961-20966.
9. Kiebel S.J., Garrido M.I., Friston K.J. Dynamic causal modelling of evoked responses: the role of intrinsic connections. Neuroimage 2007, 36:332-345.
10. Garrido M.I., Kilner J.M., Kiebel S.J., Stephan K.E., Baldeweg T., Friston K.J. Repetition suppression and plasticity in the human brain. Neuroimage 2009, 48:269-279.
11. Moran R.J., Symmonds M., Stephan K.E., Friston K.J., Dolan R.J. An in vivo assay of synaptic function mediating human cognition. Curr Biol 2011, 21:1320-1325.
12. Boly M., Garrido M.I., Gosseries O., Bruno M.A., Boveroux P., Schnakers C., Massimini M., Litvak V., Laureys S., Friston K. Preserved feedforward but impaired top-down processes in the vegetative state. Science 2011, 332:858-862.
13. Gerstein G.L., Perkel D.H. Simultaneously recorded trains of action potentials: analysis and functional interpretation. Science 1969, 164:828-830.
14. Aertsen A.M., Gerstein G.L., Habib M.K., Palm G. Dynamics of neuronal firing correlation: modulation of "effective connectivity" J Neurophysiol 1989, 61:900-917.
15. Geweke J. Measures of conditional linear dependence and feedback between time series. J Am Stat Assoc 1984, 79:907-915.
16. Seth A.K. A MATLAB toolbox for Granger causal connectivity analysis. J Neurosci Meth 2010, 186:262-273.
17. Roebroeck A., Formisano E., Goebel R. The identification of interacting networks in the brain using fMRI: model selection, causality and deconvolution. Neuroimage 2011, 58:296-302.
18. Dhamala M., Rangarajan G., Ding M. Analyzing information flow in brain networks with nonparametric Granger causality. Neuroimage 2008, 41:354-362.
19. Schreiber T. Measuring information transfer. Phys Rev Lett 2000, 85:461-464.
20. Barnett L.C., Barrett A.B., Seth A.K. Granger causality and transfer entropy are equivalent for Gaussian variables. Phys Rev Lett 2009, 103:238701.
21. Gourévitch B., Bouquin-Jeannès R.L., Faucon G. Linear and nonlinear causality between signals: methods, examples, and neurophysiological applications. Biol Cybern 2006, 95:349-369.
22. Barrett A.B., Barnett L.C., Seth A.K. Multivariate Granger causality and generalized variance. Phys Rev E 2010, 81:041907.
23. Bernasconi C., Konig P. On the directionality of cortical interactions studies by structural analysis of electrophysiological recordings. Biol Cybern 1999, 81:199-210.
24. Ding M., Bressler S.L., Yang W., Liang H. Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modelling: data preprocessing, model validation, and variability assessment. Biol Cybern 2000, 83:35-45.
25. Brovelli A., Ding M., Ledberg A., Chen Y., Nakamura R., Bressler S.L. Beta oscillations in a large-scale sensorimotor cortical network: directional influences revealed by Granger causality. Proc Natl Acad Sci USA 2004, 101:9849-9854.
26. Bosman CA, Schoffelen J-M, Brunet N, Oostenveld R, Bastos AM, Womelsdorf T, Rubehn B, Stieglitz T, de Weerd P, Fries P: Attentional stimulus selection through selective synchronization between monkey visual areas. Neuron, in press.
27. Friston K.J. The free-energy principle: a rough guide to the brain?. Trends Cogn Sci 2009, 13:239-301.
28. Barrett A.B., Murphy M., Bruno M.-A., Noirhomme Q., Boly M., Laureys S., Seth A.K. Granger causality analysis of steady-state electroencephalographic signals during propofol-induced anaesthesia. PLoS One 2012, 7:e29072.
29. Murphy M., Bruno M.-A., Riedner B., Boveroux P., Noirhomme Q., Landsness E.C., Brichant J.F., Phillips C., Massimini M., Laureys S., et al. Propofol anesthesia and sleep: a high-density EEG study. Sleep 2011, 34:283-291.
30. David O., Guillemain I., Saillet S., Reyt S., Deransart C., Segebarth C., Depaulis A. Identifying neural drivers with functional MRI: an electrophysiological validation. PLoS Biol 2008, 6:2683-2697.
31. Roebroeck A., Formisano E., Goebel R. Mapping directed influences over the brain using Granger causality and fMRI. Neuroimage 2005, 25:230-242.
32. Wen X., Lau L., Liu Y., Ding M Causal interactions in attention networks predict behavioral performance. J Neurosci 2012, 32:1284-1292.
33. Bressler S., Tang W., Sylvester C.M., Shulman G.S., Corbetta M. Top-down control of human visual cortex by frontal and parietal cortex in anticipatory visual spatial attention. J Neurosci 2008, 28:10056-10061.
34. Schippers M.B., Roebroeck A., Renken R., Nanetti L., Keysers C. Mapping the information flow from one brain to another during gestural communication. Proc Natl Acad Sci USA 2010, 107:9388-9393.
35. Gaillard R., Dehaene S., Adam C., Clemenceau S., Hasboun D., Baulac M., Cohen L., Naccache L Convering intracranial markers of conscious access. PLoS Biol 2009, 7:e61.
36. Friston K.J., Harrison L., Penny W. Dynamic causal modelling. Neuroimage 2003, 19:1273-1302.
37. Stephan K.E., Weiskopf N., Dyrsdale P.M., Robinson P.A., Friston K.J. Comparing hemodynamic models with DCM. Neuroimage 2007, 39:387-401.
38. Penny W.D. Comparing dynamic causal models using AIC, BIC, and free energy. Neuroimage 2012, 59:319-330.
39. Marreiros A.C., Kiebel S.J., Daunizeau J., Harrison L.M., Friston K.J. Population dynamics under the Laplace assumption. Neuroimage 2009, 44:701-714.
40. Moran R.J., Jung F., Kumagai T., Endepols H., Graf R., Dolan R.J., Friston K.J., Stephan K.E., Tittgemeyer M. Dynamic causal models and physiological inference a validation study using isoflurane anaesthesia in rodents. PLoS One 2011, 6:e22790.
41. Daunizeau J., David O., Stephan K.E. Dynamic causal modelling: a critical review of the biophysical and statistical foundations. Neuroimage 2011, 58:312-322.
42. Bressler S., Seth A.K. Wiener-Granger causality: a well established methodology. Neuroimage 2011, 58:323-329.
43. Goebel R., Roebroeck A., Kim D.S., Formisano E. Investigating directed cortical interactions in time-resolved fMRI data using vector autoregressive modelling and Granger causality mapping. Magn Reson Imaging 2003, 21:1251-1261.
44. Seth A.K., Chorley P., Barnett L.C. Granger causality analysis of fMRI BOLD signals is invariant to hemodynamic convolution but not downsampling. Neuroimage 2013, 65:540-555.
45. Smith S.M., Miller K.L., Salimi-Khorshidi G., Webster M., Beckmann C.F., Nichols T.E., Ramsey J.D., Woolrich M.W. Network modelling methods for fMRI. Neuroimage 2011, 54:875-891.
46. Valdes-Sosa P.A., Roebroeck A., Daunizeau J., Friston K. Effective connectivity: influence, causality and biophysical modeling. Neuroimage 2011, 58:339-361.
47. Boly M., Moran R., Murphy M., Boveroux P., Bruno M.-A., Noirhomme Q., Ledoux D., Bonhomme V., Brichant J.-F., Tononi G., et al. Connectivity changes underlying spectral EEG changes during propofol-induced loss of consciousness. J Neurosci 2012, 32:7082-7090.
48. Li B., Daunizeau J., Stephan K.E., Penny W.D., Hu D., Friston K. Generalised filtering and stochastic DCM for fMRI. Neuroimage 2011, 58:442-457.
49. Stephan K.E., Kasper L., Harrison L., Daunizeau J., Den Ouden H., Breakspear M., Friston K.J. Nonlinear dynamic causal models for fMRI. Neuroimage 2008, 42:649-662.
50. Ryali S., Supekar K., Chen T., Menon V. Multivariate dynamical systems models for estimating causal interactions in fMRI. Neuroimage 2011, 54:807-823.
51. Valdes-Sosa P.A., Sanchez-Bornot J.M., Lage-Castellos A., Vega-Hernandez M., Bosch-Bayard J., Melie-Garcia L., Canales-Rodrigues E. Estimating brain functional connectivity with sparse multivariate regression. Philos Trans R Soc B 2005, 360:969-981.
52. Friston K.J., Penny W. Post hoc Bayesian model selection. Neuroimage 2011, 56:2089-2099.
53. Marreiros A.C., Kiebel S.J., Friston K.J. Dynamic causal model for fMRI: a two-state model. Neuroimage 2008, 39:269-278.