Learning structural equation models for fMRI

Advances in Neural Information Processing Systems

Volumn , Issue , 2007, Pages 1329-1336

  Storkey, Amos J ^a   Simonotto, Enrico ^a   Whalley, Heather ^a   Lawrie, Stephen ^a   Murray, Lawrence ^a   McGonigle, David ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CAUSAL MODEL; CONNECTIVITY ANALYSIS; CYCLIC GRAPH; FMRI DATA; GAUSSIANS; JOINT DISTRIBUTIONS; LEARNING NETWORK; STRUCTURAL EQUATION MODELS; STRUCTURAL EQUATIONS; STRUCTURE-LEARNING; TEMPORAL INFORMATION;

BAYESIAN NETWORKS;

EID: 51449086351     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. K. A. Bollen. Structural Equations with Latent Variables. John Wiley and Sons, 1989.
2. C. Buchel, J.T. Coull, and K.J. Friston. The preedictive value of changes in effective connectivity for human learning. Science, 283:1528-1541, 1999.
3. E. Bullmore, B. Howitz, G. Honey, M. Brammer, S. Williams, and T. Sharma. How good is good enough in path analysis of fMRI data? Neuroimage, 11:289-301, 2000.
4. D. Dash. Restructing dynamic causal systems in equilibrium. In Proc. Uncertainty in AI 2005, 2005.
5. K.J. Friston and C. Buchel. Attentional modulation of effective connectivity from V2 to V5/MT in humans. Proceedings of the National Academy of Sciecnes, 97:7591-7596, 2000.
6. K.J. Friston, L. Harrison, and W.D. Penny. Dynamic causal modelling. NeuroImage, 19:1273-1302, 2003.
7. T. Haavelmo. The statistical implications of a system of simultaneous equations. Econometrica, 11:1-12, 1943.
8. D. McGonigle, A. Howseman, B. Athwal, K.J. Friston, R. Frackowiak, and A. Holmes. Variability in fmri: An examination of intersession differences. Neuroimage, 11:708-734, 2000.
9. A. R. McIntosh and F. Gozales-Lima. Structural equation modelling and its application to network analysis in functional brain imaging. Human Brain Mapping, 2:2-22, 1994.
10. C. Glymour P. Spirtes and R. Scheines. Causation, Prediction and Search. MIT Press, 2 edition, 2001.
11. J. Pearl. Causality. Cambridge University Press, 2000.
12. W.D. Penny, K.E. Stephan, A. Mechelli, and K.J. Friston. Comparing dynamic causal models. Neuroimage, 22:1157-1172, 2004.
13. T. Richardson. A discovery algorithm for directed cyclic graphs. In Proceedings of the 12th Conference on Uncertainty in Artificial Intelligence, 1996.
14. J. Rowe, K.E. Stephan, K. Friston, R. Frackowiak, A. Lees, and R. Passingham. Attention to action in Parkinsons disease. Brain, 125:276-289, 2002.
15. R. Schlosser, T. Gesierich, B. Kauffman, G. Vucurevic, S. Hunsche, J. Gawehn, and P. Stoeter. Altered effective connectivity during working memory performance in schizophrenia: a study with fMRI and structural equation modeling. Neuroimage, 19:751-763, 2003.
16. G. Schwarz. Estimating the dimension of a model. Annals of Statistics, 6:461-464, 1978.
17. S.M.Smith, C.F. Beckmann, N. Ramnani, M.W. Woolrich, P.R. Bannister, M. Jenkinson, P.M. Matthews, and D. McGonigle. Variability in fMRI: A re-examination of intersession differences. Human Brain Mapping, 24:248-257, 2005.
18. P.A. Valdes Sosa, J.M. Sanchez-Bornot, A. Lage-Castellanos, M. Vega-Hernandez, J. Bosch Bayard, L. Melie-Garcia, and E. Canales-Rodriguez. Estimating brain functional connectiivty with sparse multivariate autoregression. Philosophical Transactions of the Royal Society onf London B Biological Sciences, 360:969-981, 2005.
19. H.C. Whalley, E. Simonotto, I. Marshall, D.G.C Owens, N.H. Goddard, E.C. Johnstone, and S.M. Lawrie. Functional disconnectivity in subjects at high genetic risk of schizophrenia. Brain, 128:2097-2108, 2005.
20. S. Wright. Correlation and causation. Journal of Agricultural Research, 20:557-585, 1921.
21. X. Zheng and J. C. Rajapakse. Learning functional structure from fMR images. Neuroimage, 31:1601-1613, 2006.