Confounding effects of indirect connections on causality estimation

Journal of Neuroscience Methods

Volumn 184, Issue 1, 2009, Pages 152-160

  Vakorin, Vasily A ^a   Krakovska, Olga A ^b   McIntosh, Anthony R ^a,c  

^a ROTMAN RESEARCH INSTITUTE   (Canada)

^b YORK UNIVERSITY   (Canada)

^c UNIVERSITY OF TORONTO   (Canada)

Author keywords

Brain connectivity; Causality; Indirect effects; Model misspecification; Partial transfer entropy

Indexed keywords

ARTICLE; CONTROLLED STUDY; ENTROPY; FUNCTIONAL ANATOMY; HUMAN; HUMAN EXPERIMENT; INTERMETHOD COMPARISON; NERVE CELL NETWORK; NEUROPHYSIOLOGY; NEUROSCIENCE; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; SENSITIVITY ANALYSIS; SENSORIMOTOR INTEGRATION; STATISTICAL MODEL; STIMULUS RESPONSE;

ALGORITHMS; BRAIN; CAUSALITY; COMPUTER SIMULATION; ELECTROENCEPHALOGRAPHY; ENTROPY; ENVIRONMENT; HUMANS; MEMORY, SHORT-TERM; MODELS, STATISTICAL; NEUROPSYCHOLOGICAL TESTS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 70349233762     PISSN: 01650270     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2009.07.014     Document Type: Article

References (39)

1. Arnhold J., Grassberger P., Lehnertz K., and Elger C.E. A robust method for detecting interdependences: application to intracranially recorded EEG. Physica D 134 4 (1999) 419-430
2. Baek EG, Brock WA. A general test for non-linar Granger causality: bibariate model, Working Paper, Iowa State University; 1992.
3. Blinowska K.J., Ku R., and Kamiski M. Granger causality and information flow in multivariate processes. Phys Rev E Stat Nonlin Soft Mat Phys 70 5 Pt 1 (2004) 050902
4. Bressler S.L. Understanding cognition through large-scale cortical networks. Curr Dir Psychol Sci 11 2 (2002) 58-61
5. Bressler S.L. Large-scale cortical networks and cognition. Brain Res Brain Res Rev 20 3 (1995) 288-304
6. Chavez M., Martinerie J., and Le Van Quyen M. Statistical assessment of nonlinear causality: application to epileptic eeg signals. J Neurosci Methods 124 2 (2003) 113-128
7. Cohen J.D., and Tong F. Neuroscience: the face of controversy. Science 293 5539 (2001) 2405-2407
8. Efron B., and Tibshirani R.J. An introduction to the bootstrap (1993), Chapman and Hall
9. Freiwald W.A., Valdes P., Bosch J., Biscay R., Jimenez J.C., Rodriguez L.M., et al. Testing non-linearity and directedness of interactions between neural groups in the macaque inferotemporal cortex. J Neurosci Methods 94 1 (1999) 105-119
10. Friston K.J. Functional and effective connectivity in neuroimaging: a synthesis. Hum Brain Mapp 2 1-2 (1994) 56-78
11. Friston K.J., Mechelli A., Turner R., and Price C.J. Nonlinear responses in fMRI: the balloon model, volterra kernels, and other hemodynamics. Neuroimage 12 4 (2000) 466-477
12. Friston K.J., Harrison L., and Penny W. Dynamic causal modelling. Neuroimage 19 4 (2003) 1273-1302
13. Gourvitch B., Bouquin-Jeanns R.L., and Faucon G. Linear and nonlinear causality between signals: methods, examples and neurophysiological applications. Biol Cybern 95 4 (2006) 349-369
14. Granger C.W.J. Investigating causal relations by econometric models and cross spectral methods. Econometrica 37 (1969) 428-438
15. Hiemstra C., and Jonathan J.D. Testing for linear and nonlinear granger causality in the stock price-volume relation. J Finance 49 5 (1994) 1639-1664
16. Hinrichs H., Heinze H.J., and Schoenfeld M.A. Causal visual interactions as revealed by an information theoretic measure and fMRI. Neuroimage 31 3 (2006) 1051-1060
17. In: Jirsa V.K., and McIntosh A.R. (Eds). Handbook of brain connectivity (2007), Springer-Verlag, Berlin/Heidelberg
18. Kaplan A.A. Non-stationary EEG: methodological and experimental analysis. Usp Physiol Nauk 29 (1998) 35-55
19. Kaplan A.Y.a., Fingelkurts AlA., Fingelkurts AnA., Borisov S.V., and Darkhovsky B.S. Nonstationary nature of the brain activity as revealed by EEG/MEG: methodological, practical and conceptual challenges. Signal Process 85 (2005) 2190-2212
20. Kim H.S., Eykholt R., and Slas J.D. Delay time window and plateau onset of the correlation dimention for small data sets. Phys Rev E 58 (1998) 5676-5682
21. Lai Y.C., and Lerner D. Effective scaling regime for computing the correlation dimention from chaotic time series. Physica D 115 (1998) 1-18
22. McIntosh A.R. Mapping cognition to the brain through neural interactions. Memory 7 5-6 (1999) 523-548
23. McIntosh A.R., and Gonzalez-Lima F. Structural equation modeling and its application to network analysis in functional brain imaging. Hum Brain Mapp 2 1-2 (1994) 2-22
24. Palus M., and Vejmelka M. Directionality from coupling between bivariate time series: how to avoid false causalities and missed connections. Phys Rev E 75 (2007) 056211
25. Palus M., Komarek V., Hrncir Z., and Sterbova K. Synchronization as adjustment of infomation rates: detection from bivariate time series. Phys Rev E 63 (2001) 046211
26. In: Pearl J. (Ed). Causality: models, reasoning, and inference (2000), Cambridge University Press
27. Prichard D., and Theiler J. Generralized redundancies for time series analysis. Physica D 84 (1995) 476-493
28. Protzner A.B., and McIntosh A.R. The interplay of stimulus modality and response latency in neural network organization for simple working memory tasks. J Neurosci 27 12 (2007) 3187-3197
29. Protzner A.B., Cortesec F., Alain C., and McIntosh A.R. The temporal interaction of modality specific and process specific neural networks supporting simple working memory tasks. Neuropsychologia 47 8-9 (2009)
30. Quiroga R.Q., Arnhold J., and Grassberger P. Learning driver-response relationships from synchronization patterns. Phys Rev E 61 5 Pt A (2000) 5142-5148
31. Riera J.J., Watanabe J., Kazuki I., Naoki M., Aubert E., Ozaki T., et al. A state-space model of the hemodynamic approach: nonlinear filtering of BOLD signals. Neuroimage 21 2 (2004) 547-567
32. Schreiber T. Measuring information transfer. Phys Rev Lett 85 2 (2000) 461-464
33. Silverman B.W. Density estimation for statistics and data analysis (1986), Chapman Hall, London
34. Small M., and Tse C.K. Optimal embedding parameters: a modeling paradigm. Physica D 194 (2004) 283-296
35. Stam C.J. Nonlinear dynamical analysis of EEG and MEG: review of an emerging field. Clin Neurophysiol 116 10 (2005) 2266-2301
36. Stam C.J., and van Dijk B.W. Synchronization likelihood: an unbiased measure of generalized synchronization in multivariate data sets. Physica D 163 3-4 (2002) 236-251
37. Vakorin VA, Krakovska OO, McIntosh AR. Time-reversed approach to compensate for complexity effect in estimating mutual interdependencies; under review.
38. Vakorin V.A., Krakovska O.O., Borowsky R., and Sarty G.E. Inferring neural activity from BOLD signals through nonlinear optimization. Neuroimage 38 2 (2006) 248-260
39. Valds-Sosa P.A., Snchez-Bornot J.M., Lage-Castellanos A., Vega-Hernndez M., Bosch-Bayard J., Melie-Garca L., et al. Estimating brain functional connectivity with sparse multivariate autoregression. Philos Trans R Soc Lond B Biol Sci 360 1457 (2005) 969-981