Understanding DCM: Ten simple rules for the clinician

NeuroImage

Volumn 83, Issue , 2013, Pages 542-549

  Kahan, Joshua ^a   Foltynie, Tom ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BAYES THEOREM; BEHAVIOR; BOLD SIGNAL; BRAIN REGION; DYNAMIC CAUSAL MODELING; ELECTROENCEPHALOGRAM; FUNCTIONAL MAGNETIC RESONANCE IMAGING; FUNCTIONAL NEUROIMAGING; HUMAN; INFORMATION PROCESSING; MAGNETOENCEPHALOGRAPHY; MATHEMATICAL ANALYSIS; NERVE CELL NETWORK; NERVE FUNCTION; NEUROSCIENCE; NOTE; PRIORITY JOURNAL; STIMULUS RESPONSE; THEORETICAL STUDY; VISUAL STIMULATION; ACTION POTENTIAL; ALGORITHM; ANIMAL; BIOLOGICAL MODEL; BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; NOMENCLATURE; PHYSIOLOGY; PROCEDURES;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; HUMANS; MODELS, NEUROLOGICAL; NERVE NET; TERMINOLOGY AS TOPIC;

EID: 84881236250     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2013.07.008     Document Type: Note

References (58)

1. Abutalebi J., et al. Bilingual aphasia and language control: a follow-up fMRI and intrinsic connectivity study. Brain Lang. 2009, 109(2-3):141-156. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/19427522 [Accessed May 18, 2012]).
2. Anon. How experts communicate. Nat. Neurosci. 2000, 3(2):97. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/10649559 [Accessed June 10, 2012]).
3. Bastos A.M.M., et al. Canonical microcircuits for predictive coding. Neuron 2012, 76(4):695-711. (Available at: http://linkinghub.elsevier.com/retrieve/pii/S0896627312009592 [Accessed November 21, 2012]).
4. Biswal B., et al. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn. Reson. Med. 1995, 34(4):537-541. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/8524021 [Accessed July 13, 2012]).
5. Buxton R.B., Wong E.C., Frank L.R. Dynamics of blood flow and oxygenation changes during brain activation: the balloon model. Magn. Reson. Med. 1998, 39(6):855-864. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/9621908 [Accessed September 1, 2011]).
6. Damoiseaux J.S., et al. Consistent resting-state networks across healthy subjects. Proc. Natl. Acad. Sci. U. S. A. 2006, 103(37):13848-13853. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1564249&tool=pmcentrez&rendertype=abstract [Accessed March 12, 2013]).
7. Daunizeau J., David O., Stephan K.E. Dynamic causal modelling: a critical review of the biophysical and statistical foundations. NeuroImage 2011, 58(2):312-322. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/19961941 [Accessed March 3, 2013]).
8. Daunizeau Jean, et al. Optimizing experimental design for comparing models of brain function. PLoS Comput. Biol. 2011, 7(11):e1002280. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3219623&tool=pmcentrez&rendertype=abstract [Accessed May 31, 2013]).
9. Daunizeau J., Lemieux L., et al. An electrophysiological validation of stochastic DCM for fMRI. Front. Comput. Neurosci. 2012, 6(January):103. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3548242&tool=pmcentrez&rendertype=abstract [Accessed March 12, 2013]).
10. Daunizeau J., Stephan K.E., Friston K.J. Stochastic dynamic causal modelling of fMRI data: should we care about neural noise?. NeuroImage 2012, 62(1):464-481. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/22579726 [Accessed October 11, 2012]).
11. David Olivier, Harrison Lee, Friston Karl J. Modelling event-related responses in the brain. NeuroImage 2005, 25(3):756-770. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/15808977 [Accessed March 5, 2013]).
12. David Olivier, et al. Dynamic causal modeling of evoked responses in EEG and MEG. NeuroImage 2006, 30(4):1255-1272. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/16473023 [Accessed March 12, 2013]).
13. David Olivier, et al. Identifying neural drivers with functional MRI: an electrophysiological validation. PLoS Biol. 2008, 6(12):2683-2697. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2605917&tool=pmcentrez&rendertype=abstract [Accessed July 15, 2011]).
14. Do C.B., Batzoglou S. What is the expectation maximization algorithm?. Nat. Biotechnol. 2008, 26(8):897-899. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/18688245).
15. Douglas R.J., Martin K.a.C., Whitteridge D. A canonical microcircuit for neocortex. Neural Comput. 1989, 1(4):480-488. (Available at: http://www.mitpressjournals.org/doi/abs/10.1162/neco.1989.1.4.480).
16. Felleman D.J., Van Essen D.C. Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1991, 1(1):1-47. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/1822724 [Accessed March 27, 2013]).
17. Friston Karl J. Functional and effective connectivity in neuroimaging: a synthesis. Hum. Brain Mapp. 1994, 2(1-2):56-78. (Available at: http://doi.wiley.com/10.1002/hbm.460020107).
18. Friston K.J. Bayesian estimation of dynamical systems: an application to fMRI. NeuroImage 2002, 16(2):513-530. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/12030834 [Accessed November 16, 2012]).
19. Friston K. Causal modelling and brain connectivity in functional magnetic resonance imaging. PLoS Biol. 2009, 7(2):e33. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2642881&tool=pmcentrez&rendertype=abstract [Accessed March 21, 2012]).
20. Friston Karl J. Functional and effective connectivity: a review. Brain Connectivity 2011, 1(1):13-36. (Available at: http://www.liebertonline.com/doi/abs/10.1089/brain.2011.0008 [Accessed March 13, 2012]).
21. Friston K.J., et al. Nonlinear responses in fMRI: the Balloon model, Volterra kernels, and other hemodynamics. NeuroImage 2000, 12(4):466-477. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/10988040 [Accessed November 10, 2012]).
22. Friston K.J., Harrison L., Penny W. Dynamic causal modelling. NeuroImage 2003, 19(4):1273-1302. (Available at: http://linkinghub.elsevier.com/retrieve/pii/S1053811903002027 [Accessed March 1, 2012]).
23. Friston K., Moran R., Seth A.K. Analysing connectivity with Granger causality and dynamic causal modelling. Curr. Opin. Neurobiol. 2013, 23(2):172-178. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/23265964 [Accessed March 4, 2013]).
24. Goulden N., et al. Sample size estimation for comparing parameters using dynamic causal modeling. Brain Connectivity 2012, 2(2):80-90. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/22559836 [Accessed June 17, 2013]).
25. Greicius M.D., et al. Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol. Psychiatry 2007, 62(5):429-437. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2001244&tool=pmcentrez&rendertype=abstract [Accessed March 4, 2013]).
26. Hacker C.D., et al. Resting state functional connectivity of the striatum in Parkinson's disease. Brain 2012, 135(Pt 12):3699-3711. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/23195207 [Accessed March 3, 2013]).
27. Heeger D.J., Ress D. What does fMRI tell us about neuronal activity?. Nat. Rev. Neurosci. 2002, 3(2):142-151. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/11836522 [Accessed July 21, 2011]).
28. Jansen B.H., Rit V.G. Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns. Biol. Cybern. 1995, 73(4):357-366. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/7578475 [Accessed May 1, 2013]).
29. Jech R., et al. Levodopa increases functional connectivity in the cerebellum and brainstem in Parkinson's disease. Brain 2013, 1-2. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/23370091 [Accessed June 16, 2013]).
30. Kahan J., et al. Therapeutic Subthalamic Nucleus Deep Brain Stimulation Reverses Cortico-Thalamic Coupling during Voluntary Movements in Parkinson's Disease. PLoS ONE 2012, 7:e50270. 12, (Available at: http://dx.plos.org/10.1371/journal.pone.0050270 [Accessed January 2, 2013]). J.-C. Baron (Ed.).
31. Li B., Daunizeau J., Stephan K.E., Penny W., Hu D., Friston K. Generalised filtering and stochastic DCM for fMRI. NeuroImage 2011, 58(2):442-457. 10.1016/j.neuroimage.2011.01.085.
32. Litvak V., et al. EEG and MEG data analysis in SPM8. Comput. Intell. Neurosci. 2011, 852961. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3061292&tool=pmcentrez&rendertype=abstract [Accessed March 2, 2013]).
33. Logothetis N.K. What we can do and what we cannot do with fMRI. Nature 2008, 453(7197):869-878. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/18548064 [Accessed February 29, 2012]).
34. Lowe M.J., Mock B.J., Sorenson J.A. Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations. NeuroImage 1998, 7(2):119-132. (Available at: http://dx.doi.org/10.1006/nimg.1997.0315 [Accessed February 6, 2013]).
35. Marreiros a C., Kiebel S.J., Friston K.J. Dynamic causal modelling for fMRI: a two-state model. NeuroImage 2008, 39(1):269-278. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/17936017 [Accessed March 6, 2012]).
36. Marreiros A.C., et al. Basal ganglia-cortical interactions in Parkinsonian patients. NeuroImage 2012, 301-310. (null(null), Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3573233&tool=pmcentrez&rendertype=abstract [Accessed November 21, 2012]).
37. Moran R.J., et al. A neural mass model of spectral responses in electrophysiology. NeuroImage 2007, 37(3):706-720. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2644418&tool=pmcentrez&rendertype=abstract [Accessed March 12, 2013]).
38. Moran R.J., et al. Dynamic causal models of steady-state responses. NeuroImage 2009, 44(3):796-811. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2644453&tool=pmcentrez&rendertype=abstract [Accessed March 12, 2013]).
39. Moran Rosalyn J., et al. An in vivo assay of synaptic function mediating human cognition. Curr. Biol. 2011, 21(15):1320-1325. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3153654&tool=pmcentrez&rendertype=abstract [Accessed March 9, 2013]).
40. Moran Rosalyn J., et al. Alterations in brain connectivity underlying beta oscillations in parkinsonism. PLoS Comput. Biol. 2011, 7(8):e1002124. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3154892&tool=pmcentrez&rendertype=abstract [Accessed August 14, 2011]).
41. Moran R., Pinotsis D.A., Friston K. Neural masses and fields in dynamic causal modeling. Frontiers in Computational Neuroscience 2013, 7. (Available at: http://www.frontiersin.org/Computational_Neuroscience/10.3389/fncom.2013.00057/full [Accessed July 17, 2013]). 10.3389/fncom.2013.00057.
42. Mori S., Zhang J. Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 2006, 51(5):527-539. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/16950152 [Accessed February 28, 2013]).
43. Penny W.D., et al. Comparing dynamic causal models. NeuroImage 2004, 22(3):1157-1172. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/15219588 [Accessed July 18, 2012]).
44. Penny Will D., et al. Comparing families of dynamic causal models. PLoS Comput. Biol. 2010, 6(3):e1000709. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2837394&tool=pmcentrez&rendertype=abstract [Accessed March 6, 2013]).
45. Rehme A.K., et al. Dynamic causal modeling of cortical activity from the acute to the chronic stage after stroke. NeuroImage 2011, 55(3):1147-1158. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/21238594 [Accessed July 24, 2012]).
46. Rowe James B. Connectivity analysis is essential to understand neurological disorders. Front. Syst. Neurosci. 2010, 4(September):1-13. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2953412&tool=pmcentrez&rendertype=abstract [Accessed October 9, 2012]).
47. Rowe J.B., et al. Dynamic causal modelling of effective connectivity from fMRI: are results reproducible and sensitive to Parkinson's disease and its treatment?. NeuroImage 2010, 52(3):1015-1026. (Available at: http://www.sciencedirect.com/science/article/pii/S105381190901369X [Accessed August 25, 2011]).
48. Seghier M.L., et al. Identifying abnormal connectivity in patients using dynamic causal modeling of FMRI responses. Front. Syst. Neurosci. 2010, 4. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2936900&tool=pmcentrez&rendertype=abstract [Accessed June 23, 2011]).
49. Smith Stephen M. The future of FMRI connectivity. NeuroImage 2012, 62(2):1257-1266. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/22248579 [Accessed October 26, 2012]).
50. Sonty S.P., et al. Altered effective connectivity within the language network in primary progressive aphasia. Neuroscience J. Neurosci. Off. J. Soc. Neurosci. 2007, 27(6):1334-1345. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/17287508 [Accessed June 10, 2013]).
51. Stephan Klaas Enno, et al. Nonlinear dynamic causal models for fMRI. NeuroImage 2008, 42(2):649-662. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2636907&tool=pmcentrez&rendertype=abstract [Accessed November 14, 2012]).
52. Stephan Klaas Enno, Penny Will D., et al. Bayesian model selection for group studies. NeuroImage 2009, 46(4):1004-1017. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2703732&tool=pmcentrez&rendertype=abstract [Accessed July 22, 2012]).
53. Stephan Klaas Enno, Tittgemeyer M., et al. Tractography-based priors for dynamic causal models. NeuroImage 2009, 47(4):1628-1638. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2728433&tool=pmcentrez&rendertype=abstract [Accessed March 8, 2013]).
54. Stephan K.E., et al. Ten simple rules for dynamic causal modeling. NeuroImage 2010, 49(4):3099-3109. (Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2825373&tool=pmcentrez&rendertype=abstract [Accessed June 15, 2011]).
55. Urner M., et al. Early visual learning induces long-lasting connectivity changes during rest in the human brain. NeuroImage 2013, 77:148-156. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/23558105 [Accessed April 6, 2013]).
56. Vossel S., et al. Deconstructing the architecture of dorsal and ventral attention systems with dynamic causal modeling. J. Neurosci. 2012, 32(31):10637-10648. (Available at: [Accessed August 2, 2012]). 10.1523/JNEUROSCI.0414-12.2012.
57. Wu T., et al. Changes of functional connectivity of the motor network in the resting state in Parkinson's disease. Neurosci. Lett. 2009, 460(1):6-10. (Available at: http://www.ncbi.nlm.nih.gov/pubmed/19463891 [Accessed July 26, 2011]).
58. Zhang D., Raichle M.E. Disease and the brain's dark energy. Nat. Rev. Neurol. 2010, 6(1):15-28. Available at: http://www.ncbi.nlm.nih.gov/pubmed/20057496 [Accessed February 28, 2013].