Assessing causality in brain dynamics and cardiovascular control

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

Volumn 371, Issue 1997, 2013, Pages

  Porta, Alberto ^a   Faes, Luca ^b  

^a UNIVERSITY OF MILAN   (Italy)

^b UNIVERSITY OF TRENTO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ANIMAL; ARTICLE; BIOLOGICAL MODEL; BIOMEDICAL ENGINEERING; BIOPHYSICS; BRAIN; COMPLEXITY; COMPUTATIONAL PHYSICS; COMPUTER SIMULATION; FEEDBACK SYSTEM; HEART; HUMAN; MATHEMATICAL MODELLING; NERVE CELL NETWORK; PHYSIOLOGY; STATISTICAL PHYSICS;

BIOMEDICAL ENGINEERING; BIOPHYSICS; COMPLEXITY; COMPUTATIONAL PHYSICS; MATHEMATICAL MODELLING; STATISTICAL PHYSICS;

ALGORITHMS; ANIMALS; BRAIN; COMPUTER SIMULATION; FEEDBACK, PHYSIOLOGICAL; HEART; HUMANS; MODELS, BIOLOGICAL; NERVE NET;

EID: 84880530244     PISSN: 1364503X     EISSN: None     Source Type: Journal    
DOI: 10.1098/rsta.2012.0517     Document Type: Review

References (26)

1. Porta A, Di Rienzo M, Wessel N, Kurths J. 2009 Addressing the complexity of cardiovascular regulation. Phil. Trans. R. Soc. A 367, 1215-1218. (doi:10.1098/rsta.2008.0292).
2. Wiener N. 1956 The theory of prediction. New York, NY: McGraw-Hill.
3. Granger CWJ. 1963 Economic processes involving feedback. Inf. Control 6, 28-48. (doi:10.1016/S0019-9958(63)90092-5).
4. Schreiber T. 2000 Measuring information transfer. Phys. Rev. Lett. 85, 461-464. (doi:10.1103/PhysRevLett.85.461).
5. Barnett L, Barrett AB, Seth AK. 2009 Granger causality and transfer entropy are equivalent for Gaussian variables. Phys. Rev. Lett. 103, 238701. (doi:10.1103/PhysRevLett.103.238701).
6. Hlavá̌cková-Schindler K. 2011 Equivalence of Granger causality and transfer entropy: A generalization. Appl. Math. Sci. 5, 3637-3648.
7. Magagnin V, Bassani T, Bari V, Turiel M, Maestri R, Pinna GD, Porta A. 2011 Non-stationarities significantly distort short-term spectral, symbolic and entropy heart rate variability indices. Physiol. Meas. 32, 1775-1786. (doi:10.1088/0967-3334/32/11/S05).
8. Granger CWJ. 1969 Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37, 424-438. (doi:10.2307/1912791).
9. Geweke J. 1984 Measurement of linear dependence and feedback between multiple time series. J. Am. Stat. Assoc. 77, 304-313. (doi:10.1080/01621459. 1982.10477803).
10. Porta A, Furlan R, Rimoldi O, Pagani M, Malliani A, van de Borne P. 2002 Quantifying the strength of linear causal coupling in closed loop interacting cardiovascular variability series. Biol. Cybern. 86, 241-251. (doi:10.1007/s00422-001-0292-z). (Pubitemid 135689574)
11. Faes L, Porta A, Nollo G. 2008 Mutual nonlinear prediction as a tool to evaluate coupling strength and directionality in bivariate time series: comparison among different strategies based on k nearest neighbors. Phys. Rev. E 78, 026201. (doi:10.1103/PhysRevE.78.026201).
12. Staniek M, Lehnertz K. 2008 Symbolic transfer entropy. Phys. Rev. Lett. 100, 158101. (doi:10.1103/PhysRevLett.100.158101). (Pubitemid 351549488)
13. Quiroga RQ, Arnhold J, Grassberger P. 2000 Learning driver-response relationship from synchronization patterns. Phys. Rev. E 61, 5142-5148. (doi:10.1103/PhysRevE.61.5142).
14. Romano MC, Thiel M, Kurths J, Grebogi C. 2007 Estimation of the direction of the coupling by conditional probabilities of recurrence. Phys. Rev. E 76, 036211. (doi:10.1103/Phys RevE.76.036211).
15. Eichler M. 2013 Causal inference with multiple time series: principles and problems. Phil. Trans. R. Soc. A 371, 20110613. (doi:10.1098/rsta.2011.0613) .
16. Porta A, Castiglioni P, Di Rienzo M, Bassani T, Bari V, Faes L, Nollo G, Cividjan A, Quintin L. 2013 Cardiovascular control and time domain Granger causality: insights from selective autonomic blockade. Phil. Trans. R. Soc. A 371, 20120161. (doi:10.1098/rsta.2012.0161).
17. Baccalá LA, de Brito CSN, Takahashi DY, Sameshima K. 2013 Unified asymptotic theory for all partial directed coherence forms. Phil. Trans. R. Soc. A 371, 20120158. (doi:10.1098/rsta.2012.0158).
18. Faes L, Erla S, Porta A, Nollo G. 2013 A framework for assessing frequency domain causality in physiological time series with instantaneous effects. Phil. Trans. R. Soc. A 371, 20110618. (doi:10.1098/rsta.2011.0618).
19. Wen X, Rangarajan G, Ding M. 2013 Multivariate Granger causality: an estimation framework based on factorization of the spectral density matrix. Phil. Trans. R. Soc. A 371, 20110610. (doi:10.1098/rsta.2011.0610).
20. Ramb R, Eichler M, Ing A, Thiel M, Weiller C, Grebogi C, Schwarzbauer C, Timmer J, Schelter B. 2013 The impact of latent confounders in directed network analysis in neuroscience. Phil. Trans. R. Soc. A 371, 20110612. (doi:10.1098/rsta.2011.0612).
21. Schulz S, Adochiei F-C, Edu I-R, Rico S, Hariton C, Bär K-J, Andreas V. 2013 Cardiovascular and cardiorespiratory coupling analyses: A review. Phil. Trans. R. Soc. A 371, 20120191. (doi:10.1098/rsta.2012.0191).
22. Marwan N, Zou Y, Wessel N, Riedl M, Kurths J. 2013 Estimating coupling directions in the cardiorespiratory system using recurrence properties. Phil. Trans. R. Soc. A 371, 20110624. (doi:10.1098/rsta.2011.0624).
23. Blinowska KJ, Kamí nski M, Brzezicka A, Kamí nski J. 2013 Application of directed transfer function and network formalism for the assessment of functional connectivity in working memory task. Phil. Trans. R. Soc. A 371, 20110614. (doi:10.1098/rsta.2011.0614).
24. Leistritz L, Pester B, Doering A, Schiecke K, Babiloni F, Astolfi L, Witte H. 2013 Time-variant partial directed coherence for analysing connectivity: A methodological study. Phil. Trans. R. Soc. A 371, 20110616. (doi:10.1098/rsta.2011.0616).
25. Iatsenko D, Bernjak A, Stankovski T, Shiogai Y, Owen-Lynch PJ, Clarkson PBM, McClintock PVE, Stefanovska A. 2013 Evolution of cardiorespiratory interactions with age. Phil. Trans. R. Soc. A 371, 20110622. (doi:10.1098/rsta.2011.0622).
26. Ramírez Ávila GM, Gapelyuk A, Marwan N, Walther T, Stepan H, Kurths J, Wessel N. 2013 Classification of cardiovascular time series based on different coupling structures using recurrence networks analysis. Phil. Trans. R. Soc. A 371, 20110623. (doi:10.1098/rsta.2011.0623).