Critical comments on dynamic causal modelling

NeuroImage

Volumn 59, Issue 3, 2012, Pages 2322-2329

  Lohmann, Gabriele ^a   Erfurth, Kerstin ^a,b   Müller, Karsten ^a   Turner, Robert ^a  

^a MAX PLANCK INSTITUTE FOR HUMAN COGNITIVE AND BRAIN SCIENCES   (Germany)

^b LEIPZIG UNIVERSITY OF APPLIED SCIENCES   (Germany)

Author keywords

Combinatorial explosion; Dynamic causal modelling; Model validation

Indexed keywords

ACCURACY; BAYES THEOREM; DYNAMIC CAUSAL MODELLING; INTERMETHOD COMPARISON; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; NOTE; PREDICTION; PRIORITY JOURNAL; PROBABILITY; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICAL PARAMETERS; VALIDATION STUDY; VALIDITY;

ADULT; ALGORITHMS; BAYES THEOREM; BRAIN; CAUSALITY; ELECTROENCEPHALOGRAPHY; HUMANS; LINEAR MODELS; MAGNETIC RESONANCE IMAGING; MAGNETOENCEPHALOGRAPHY; MODELS, STATISTICAL; REPRODUCIBILITY OF RESULTS; SELECTION BIAS;

EID: 84855419311     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2011.09.025     Document Type: Note

References (65)

1. Biswal B., et al. Toward discovery science of human brain function. Proc. Natl. Acad. Sci. U.S.A. 2010, 107:4734-4739.
2. Box G. Sampling and Bayes' inference in scientific modelling and robustness. J. R. Stat. Soc. 1980, 143:383-430. (Part A).
3. Box G., Draper N. Empirical Model-Building and Response Surfaces 1987, Wiley, (iSBN 0471810339).
4. Breakspear M., Terry J., Friston K. Modulation of excitatory synaptic coupling facilitates synchronization and complex dynamics in a biophysical model of neuronal dynamics. Netw. Comput. Neural Syst. 2003, 14:703-732.
5. Bressler S., Seth A. Wiener granger causality: a well established methodology. NeuroImage 2011, 58(2):323-329.
6. Büchel C., Friston K. Modulation of connectivity in visual pathways by attention: cortical interactions evaluated with structural equation modelling and fMRI. Cereb. Cortex 1997, 7:768-778.
7. Bullmore E., Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 2009, 10:186-198.
8. Buxton R., Wong E., Frank L. Dynamics of blood flow and oxygenation changes during brain activation: the Balloon model. MRM 1998, 39:855-864.
9. Daunizeau J., Friston K., Kiebel S. Variational Bayesian identification and prediction of stochastic nonlinear dynamic causal models. Phys. D 2009, 238:2089-2118.
10. Daunizeau J., David O., Stephan K. Dynamic causal modelling: a critical review of the biophysical and statistical foundations. NeuroImage 2011, 58(2):312-322.
11. David O. fMRI connectivity, meaning and empiricism. comments on: Roebroeck et al. the identification of interacting networks in the brain using fMRI: model selection, causality and deconvolution. NeuroImage 2011, 58(2):306-309.
12. David O., Kiebel S., Harrison L., Mattout J., Kilner J., Friston K. Dynamic causal modeling of evoked responses in EEG and MEG. NeuroImage 2006, 30(4):1255-1272.
13. 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(12):2683-2697.
14. Evans M., Moshonov H. Checking for prior-data conflict. Bayesian Analysis 2006, 1(4):893-914.
15. Frigg R., Hartmann S. Models in science. The Stanford Encyclopedia of Philosophy 2009, http://plato.stanford.edu/archives/sum2009/entries/models-science/.
16. Friston K. Dynamic causal modeling and granger causality. Dynamic causal modeling and granger causality comments on: the identification of interacting networks in the brain using fMRI: model selection, causality and deconvolution. NeuroImage 2011, 58(2):303-305.
17. Friston, K., (Epub ahead of print). Functional and effective connectivity: a review. Brain Connectivity.
18. Friston K., Harrison L., Penny W. Dynamic causal modeling. NeuroImage 2003, 19:1273-1302.
19. Friston K., Li B., Daunizeau J., Stephan K. Network discovery with DCM. NeuroImage 2011, 56(3):1202-1221.
20. Fukunaga M., Horovitz S., de Zwart J., van Gelderen P., Balkin T., Braun A., Duyn J. Metabolic origin of BOLD signal fluctuations in the absence of stimuli. J. Cereb. Blood Flow Metab. 2008, 28(7):1377-1387.
21. Geweke J. Bayesian model comparison and validation. Am. Econ. Rev. 2007, 97(2):60-64.
22. Geyer S., Weiss M., Reimann K., Lohmann G., Turner R. Microstructural parcellation of the human cerebral cortex from Brodmann's post-mortem map to in vivo mapping with high-field magnetic resonance imaging. Front. Hum. Neurosci. 2011, (Feb). 10.3389/fnhum.2011.00019.
23. Goncalves M., Hall D. Connectivity analysis with structural equation modelling: an example of the effects of voxel selection. NeuroImage 2003, 20:1455-1467.
24. Goodwin C. Research in Psychology: Methods and Design 2010, John Wiley & Sons. 6th Edition.
25. Grueschow M., Rieger J., Stadler J., Tempelmann C., Heinze H., Speck O., Haynes J. Topography of responses to colour and luminance in human subcortical visual pathways as revealed by high-resolution fMRI at 7T. J. Vis. 2008, 8(6). 10.1167/8.6.959.
26. Haxby J., Gobbini M., Furey M., Ishai A., Schouten J., Pietrini P. Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science 2001, 293:2425-2430.
27. Haynes J., Rees G. Decoding mental states from brain activity in humans. Nat. Rev. Neurosci. 2006, 7:523-534.
28. Heidemann R., Porter D., Anwander A., Feiweier T., Heberlein K., Knoesche T., Turner R. Diffusion imaging in humans at 7T using readout-segmented EPI and GRAPPA. Magn. Reson. Med. 2010, 64(1):9-14.
29. Jaynes E. Probability Theory: The Logic of Science 2003, Cambridge University Press, Cambridge, England. 1st Edition.
30. Kiebel S., Klöppel S., Weiskopf N., Friston K. Dynamic causal modeling: a generative model of slice timing in fMRI. NeuroImage 2007, 34(4):1487-1496.
31. Kiebel S., Garrido M., Moran R., Chen C., Friston K. Dynamic causal modeling for EEG and MEG. Hum. Brain Mapp. 2009, 30(6):1866-1876.
32. Lee L., Friston K., Horwitz B. Large-scale neural models and dynamic causal modelling. NeuroImage 2006, 30:1243-1254.
33. Leff A., Schofield T., Stephan K., Crinion J., Friston K., Price C. The cortical dynamics of intelligible speech. J. Neurosci. 2008, 28(49):13209-13215.
34. Li B., Daunizeau J., Stephan K., Penny W., Hu D., Friston K. Generalised filtering and stochastic DCM for fMRI. NeuroImage 2011, 58(2):442-457.
35. Little R. Calibrated Bayes: a Bayes/frequentist roadmap. Am. Stat. 2006, 60(3).
36. Lohmann G., Hoehl S., Brauer J., Danielmeier C., Bornkessel-Schlesewski I., Bahlmann J., Turner R., Friederici A. Setting the frame: the human brain activates a basic low-frequency network for language processing. Cereb. Cortex 2010, 20(6):1286-1292. http://dx.doi.org/doi:10.1093/cercor/bhp190.
37. Lohmann G., Margulies D., Horstmann A., Pleger B., Lepsien J., Goldhahn D., Schloegl H., Stumvoll M., Villringer A., Turner R. Eigenvector centrality mapping for analyzing connectivity patterns in fMRI data of the human brain. PloS ONE 2010, 5(4):e10232.
38. Mackay D. Information Theory, Inference and Learning Algorithms 2003, Cambridge University Press, Cambridge, England. 1st Edition.
39. Marreiros A., Kiebel S., Friston K. Dynamic causal modelling for fMRI: a two-state model. NeuroImage 2008, 39(1):269-278.
40. Marreiros A.C., Stephan K., Friston K. Dynamic causal modeling. Scholarpedia 2010, 5(7):9568.
41. Mitchell T., Hutchinson R., Niculescu R., Pereira F., Wang X. Learning to decode cognitive states from brain images. Mach. Learn. 2004, 57:145-175.
42. Neumann J., Lohmann G., Zysset S., von Cramon D. Within-subject variability of BOLD response dynamics. NeuroImage 2003, 19(3):784-796.
43. Penny W., Stephan K., Mechelli A., Friston K. Comparing dynamic causal models. NeuroImage 2004, 22(3):1157-1172.
44. Penny W., Stephan K., Daunizeau J., Rosa M., Friston K., Schofield T., Leff A. Comparing families of dynamic causal models. PLoS Comput. Biol. 2010, 6(3):e1000709.
45. Poirier D. Posterior odds analysis when all competing models are false. Econ. Lett. 1981, 8:135-140.
46. Polimeni J., Fischl B., Greve D., Wald L. Laminar analysis of 7T BOLD using an imposed spatial activation pattern in human V1. NeuroImage 2010, 52(4):1334-1346.
47. Polimeni J., Fujimoto K., Fischl B., Greve D., Wald L. Retinotopically organized left to right hemisphere functional connectivity in human V1 using high-resolution FMRI at 7T. Proc. Intl. Soc. Mag. Reson. Med. 2010, ISMRM, Stockholm, (May, 1-7).
48. Protzner A., McIntosh A. Testing effective connectivity changes with structural equation modeling: what does a bad model tell us?. Hum. Brain Mapp. 2006, 27:935-947.
49. Ramsey J., Hanson S., Hanson C., Halchenko Y., Poldrack R., Glymour C. Six problems for causal inference from fMRI. NeuroImage 2010, 49(2):1545-1558.
50. Reyt S., Picq C., Sinniger V., Clarencon D., Bonaz B., David O. Dynamic causal modelling and physiological confounds: a functional MRI study of vagus nerve stimulation. NeuroImage 2010, 52(4):1456-1464.
51. Riera J.J., Watanabe J., Kazuki I., Naoki M., Aubert E., Ozaki T., Kawashima R. A state-space model of the hemodynamic approach: nonlinear filtering of BOLD signals. NeuroImage 2004, 21(2):547-567.
52. Roebroeck A., Formisano E., Goebel R. The identification of interacting networks in the brain using fMRI: model selection, causality and deconvolution. NeuroImage 2011, 58(2):296-302.
53. Roebroeck A., Formisano E., Goebel R. Reply to Friston and David: after comments on: the identification of interacting networks in the brain using fMRI: model selection, causality and deconvolution. NeuroImage 2011, 58(2):310-311.
54. Schuyler B., Ollinger J., Oakes T., Johnstone T., Davidson R. Dynamic causal modeling applied to fMRI data shows high reliability. NeuroImage 2010, 49(1):603-611.
55. Shmuel A., Chaimow D., Raddatz G., Ugurbil K., Yacoub E. Mechanisms underlying decoding at 7T: ocular dominance columns, broad structures, and macroscopic blood vessels in V1 convey information on the stimulated eye. NeuroImage 2010, 49(3):1957-1964.
56. SPM8 data set http://www.fil.ion.ucl.ac.uk/spm/data/attention.
57. SPM8 manual http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf.
58. Sporns O. Networks of the Brain 2011, MIT Press, Cambridge, Mass.
59. Stephan K., Weiskopf N., Drysdale P., Robinson P., Friston K. Comparing hemodynamic models with DCM. NeuroImage 2007, 38(3):387-401.
60. Stephan K., Kasper L., Harrison L., Daunizeau J., den Ouden H., Breakspear M., Friston K. Nonlinear dynamic causal models for fMRI. NeuroImage 2008, 42:649-662.
61. Stephan K., Penny W., Moran R., den Ouden H., Daunizeau J., Friston K. Ten simple rules for dynamic causal modeling. NeuroImage 2010, 49(4):3099-3109.
62. Trampel R., Schäfer A., Heidemann R., Ivanov D., Lohmann G., Geyer S., Turner R. High resolution functional mapping of primary motor cortex and primary somatosensory cortex in humans at 7T. Proc. Intl. Soc. Mag. Reson. Med. 2011, Vol. 19. ISMRM, Montreal, (p. No.3586).
63. Trampel R., Ott D., Turner R. Do the congenitally blind have a stria of Gennari?. First intracortical insights in vivo. Cereb. Cortex 2011, 21(9):2075-2081.
64. Valdes-Sosa P., Sanchez-Bornot J., Sotero R., Iturria-Medina Y., Aleman-Gomez Y., Bosch-Bayard J., Carbonell F., Ozaki T. Model driven EEG/fMRI fusion of brain oscillations. Hum. Brain Mapp. 2009, 30(9):2701-2721.
65. Valdes-Sosa P., Roebroeck A., Daunizeau J., Friston K. Effective connectivity: influence, causality and biophysical modeling. NeuroImage 2011, 58(2):339-361.