Conditional entropy-based evaluation of information dynamics in physiological systems

Understanding Complex Systems

Volumn , Issue , 2014, Pages 61-86

  Faes, Luca ^a   Porta, Alberto ^b  

^a UNIVERSITY OF TRENTO   (Italy)

^b UNIVERSITY OF MILAN   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84901769257     PISSN: 18600832     EISSN: 18600840     Source Type: Book Series    
DOI: 10.1007/978-3-642-54474-3_3     Document Type: Article

References (47)

1. Bullmore, E., Sporns, O.: Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10, 186 (2009)
2. Bashan, A., Bartsch, R.P., Kantelhardt, J.W., Havlin, S., Ivanov, P.C.: Network physiology reveals relations between network topology and physiological function. Nat. Communicat. 3 (2012)
3. Lizier, J.T.: The local information dynamics of distributed computation in complex systems. Springer, Heidelberg (2013)
4. Faes, L., Nollo, G.: Multivariate frequency domain analysis of causal interactions in physiological time series. In: Laskovski, A.N. (ed.) Biomedical Engineering, Trends in Electronics, Communications and Software. In Tech, Rijeka (2011)
5. Pincus, S.M.: Approximate Entropy As A Measure of System-Complexity. Proc. Natl. Acad. Sci. USA 88, 2297-2301 (1991)
6. Richman, J.S., Moorman, J.R.: Physiological time-series analysis using approximate entropy and sample entropy. Am. J. Physiol. Heart Circ. Physiol. 278, H2039-H2049 (2000) (Pubitemid 30439218)
7. Porta, A., Baselli, G., Liberati, D., Montano, N., Cogliati, C., Gnecchi-Ruscone, T., Malliani, A., Cerutti, S.: Measuring regularity by means of a corrected conditional entropy in sympathetic outflow. Biol. Cybern. 78, 71-78 (1998) (Pubitemid 128636376)
8. Paluš, M., Komárek, V., Hrnčíř, Z., Štěrbová, K.: Synchronization as adjustment of information rates: detection from bivariate time series. Phys. Rev. E 63, 046211 (2001)
9. Porta, A., Baselli, G., Lombardi, F., Montano, N., Malliani, A., Cerutti, S.: Conditional entropy approach for the evaluation of the coupling strength. Biol. Cybern. 81, 119-129 (1999) (Pubitemid 129538430)
10. Schreiber, T.: Measuring information transfer. Phys. Rev. Lett. 85, 461-464 (2000)
11. Lizier, J.T., Pritam, S., Prokopenko, M.: Information Dynamics in Small-World Boolean Networks. Artificial Life 17, 293-314 (2011)
12. Chicharro, D., Ledberg, A.: Framework to study dynamic dependencies in networks of interacting processes. Phys. Rev. E 86, 041901 (2012)
13. Porta, A., Guzzetti, S., Montano, N., Pagani, M., Somers, V., Malliani, A., Baselli, G., Cerutti, S.: Information domain analysis of cardiovascular variability signals: evaluation of regularity, synchronisation and co-ordination. Med. Biol. Eng. Comput. 38, 180-188 (2000) (Pubitemid 30192992)
14. Nollo, G., Faes, L., Porta, A., Pellegrini, B., Ravelli, F., Del Greco, M., Disertori, M., Antolini, R.: Evidence of unbalanced regulatory mechanism of heart rate and systolic pressure after acute myocardial infarction. Am. J. Physiol. Heart Circ. Physiol. 283, H1200-H1207 (2002)
15. Porta, A., Faes, L., Mase, M., D'Addio, G., Pinna, G.D., Maestri, R., Montano, N., Furlan, R., Guzzetti, S., Nollo, G., Malliani, A.: An integrated approach based on uniform quantization for the evaluation of complexity of short-term heart period variability: Application to 24 h Holter recordings in healthy and heart failure humans. Chaos 17, 015117 (2007)
16. Porta, A., Gnecchi-Ruscone, T., Tobaldini, E., Guzzetti, S., Furlan, R., Montano, N.: Progressive decrease of heart period variability entropy-based complexity during graded head-up tilt. J. Appl. Physiol. 103, 1143-1149 (2007) (Pubitemid 47605947)
17. Faes, L., Nollo, G., Porta, A.: Information domain approach to the investigation of cardio-vascular, cardio-pulmonary, and vasculo-pulmonary causal couplings. Front. Physiol. 2, 1-13 (2011)
18. Faes, L., Nollo, G., Porta, A.: Information-based detection of nonlinear Granger causality in multivariate processes via a nonuniform embedding technique. Phys. Rev. E 83, 051112 (2011)
19. Faes, L., Nollo, G., Porta, A.: Non-uniform multivariate embedding to assess the information transfer in cardiovascular and cardiorespiratory variability series. Comput. Biol. Med. 42, 290-297 (2012)
20. Faes, L., Nollo, G., Porta, A.: Compensated transfer entropy as a tool for reliably estimating information transfer in physiological time series. Entropy 15, 198-219 (2013)
21. Cover, T.M., Thomas, J.A.: Elements of information theory. Wiley, New York (2006)
22. Kaiser, A., Schreiber, T.: Information transfer in continuous processes. Physica D 166, 43-62 (2002) (Pubitemid 34732166)
23. Lizier, J.T., Prokopenko, M., Zomaya, A.Y.: Local measures of information storage in complex distributed computation. Information Sciences 208, 39-54 (2012)
24. Porta, A., Catai, A.M., Takahashi, A.C.M., Magagnin, V., Bassani, T., Tobaldini, E., Montano, N.: Information Transfer through the Spontaneous Baroreflex in Healthy Humans. Meth. Inf. Med. 49, 506-510 (2010)
25. Porta, A., Catai, A.M., Takahashi, A.C., Magagnin, V., Bassani, T., Tobaldini, E., de van, B.P., Montano, N.: Causal relationships between heart period and systolic arterial pressure during graded head-up tilt. Am. J. Physiol Regul. Integr. Comp. Physiol. 300, R378-R386 (2011)
26. Vicente, R., Wibral, M., Lindner, M., Pipa, G.: Transfer entropy-a model-free measure of effective connectivity for the neurosciences. Journal of Computational Neuroscience 30, 45-67 (2011)
27. Barnett, L., Barrett, A.B., Seth, A.K.: Granger causality and transfer entropy are equivalent for Gaussian variables. Phys. Rev. Lett. 103, 238701 (2009)
28. Amblard, P.O., Michel, O.J.: The relation between Granger causality and directed information theory: a review. Entropy 15, 113-143 (2013)
29. Vakorin, V.A., Krakovska, O.A., McIntosh, A.R.: Confounding effects of indirect connections on causality estimation. J. Neurosci. Methods 184, 152-160 (2009)
30. Williams, P.L.: Nonnegative decomposition of multivariate information. ArXiv, 1004.2515 (2010)
31. Schreiber, T.: Interdisciplinary application of nonlinear time series methods. Phys. Rep. 308, 1-64 (1999)
32. Takens, F.: Detecting strange attractors in fluid turbulence. In: Rand, D., Young, S.L. (eds.) Dynamical Systems and Turbulence. Springer, Berlin (1981)
33. Vlachos, I., Kugiumtzis, D.: Nonuniform state-space reconstruction and coupling detection. Phys. Rev. E 82, 016207 (2010)
34. Small, M.: Applied nonlinear time series analysis: applications in physics, physiology and finance. World Scientific (2005)
35. Runge, J., Heitzig, J., Petoukhov, V., Kurths, J.: Escaping the Curse of Dimensionality in Estimating Multivariate Transfer Entropy. Phys. Rev. Lett. 108, 258701 (2012)
36. Pincus, S.M.: Approximated entropy (ApEn) as a complexity measure. Chaos, 110-117 (1995)
37. Hlaváčková-Schindler, K., Paluš, M., Vejmelka, M., Bhattacharya, J.: Causality detection based on information-theoretic approaches in time series analysis. Phys. Rep. 441, 1-46 (2007)
38. Kugiumtzis, D., Tsimpiris, A.: Measures of Analysis of Time Series (MATS): A MATLAB Toolkit for Computation of Multiple Measures on Time Series Data Bases. J. Stat. Software 33, 1-30 (2010)
39. Wibral, M., Rahm, B., Rieder, M., Lindner, M., Vicente, R., Kaiser, J.: Transfer entropy in magnetoencephalographic data: Quantifying information flow in cortical and cerebellar networks. Progr. Biophys. Mol. Biol. 105, 80-97 (2011)
40. Lungarella, M., Pegors, T., Bulwinkle, D., Sporns, O.: Methods for quantifying the informational structure of sensory and motor data. Neuroinformatics 3, 243-262 (2005) (Pubitemid 41112872)
41. Porta, A., Castiglioni, P., Bari, V., Bassani, T., Marchi, A., Cividjian, A., Quintin, L., Di Rienzo, M.: K-nearest-neighbor conditional entropy approach for the assessment of the short-term complexity of cardiovascular control. Phys. Meas. 34, 17-33 (2013)
42. Faes, L., Nollo, G.: Decomposing the transfer entropy to quantify lag-specific Granger causality in cardiovascular variability. In: Proc. of the 35th Annual Int. Conf. IEEEEMBS, pp. 5049-5052 (2013)
43. Kugiumtzis, D.: Direct-coupling information measure from nonuniform embedding. Phys. Rev. E 87, 062918 (2013)
44. Porta, A., Guzzetti, S., Montano, N., Furlan, R., Pagani, M., Malliani, A., Cerutti, S.: Entropy, entropy rate, and pattern classification as tools to typify complexity in short heart period variability series. IEEE Trans. Biomed. Eng. 48, 1282-1291 (2001) (Pubitemid 32988569)
45. Viola, A.U., Tobaldini, E., Chellappa, S.L., Casali, K.R., Porta, A., Montano, N.: Short-Term Complexity of Cardiac Autonomic Control during Sleep: REM as a Potential Risk Factor for Cardiovascular System in Aging. PLoS One 6 (2011)
46. Porta, A., Castiglioni, P., Di Rienzo, M., Bari, V., Bassani, T., Marchi, A., Wu, M.A., Cividjian, A., Quintin, L.: Information domain analysis of the spontaneous baroreflex during pharmacological challenges. Auton. Neurosci. 178(1-2), 67-75 (2013)
47. Faes, L., Porta, A., Rossato, G., Adami, A., Tonon, D., Corica, A., Nollo, G.: Investigating the mechanisms of cardiovascular and cerebrovascular regulation in orthostatic syncope through an information decomposition strategy. Auton. Neurosci. 178(1-2), 76-82 (2013)