Development of interaction measures based on adaptive non-linear time series analysis of biomedical signals

Biomedizinische Technik

Volumn 51, Issue 2, 2006, Pages 64-69

  Leistritz, Lutz ^a   Hesse, Wolfram ^a   Arnold, Matthias ^a   Witte, Herbert ^a  

^a FRIEDRICH SCHILLER UNIVERSITY JENA   (Germany)

Author keywords

Granger causality; Interaction measures; MVAR models; SETAR models

Indexed keywords

ADAPTIVE SYSTEMS; COMPUTER SIMULATION; NONLINEAR SYSTEMS; TIME SERIES ANALYSIS;

GRANGER CAUSALITY; INTERACTION MEASURES; MVAR MODELS; SETAR MODELS;

BIOMEDICAL ENGINEERING;

ARTICLE; BIOMEDICAL ENGINEERING; BLOOD OXYGENATION; MULTIVARIATE ANALYSIS; NONLINEAR SYSTEM; REGRESSION ANALYSIS; SIGNAL PROCESSING; SIMULATION; TIME SERIES ANALYSIS;

ALGORITHMS; ANIMALS; ARTIFICIAL INTELLIGENCE; BIOMEDICAL ENGINEERING; COMPUTER SIMULATION; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; LINEAR MODELS; MODELS, BIOLOGICAL; NONLINEAR DYNAMICS; PATTERN RECOGNITION, AUTOMATED; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 33747323358     PISSN: 00135585     EISSN: None     Source Type: Journal    
DOI: 10.1515/BMT.2006.012     Document Type: Article

References (22)

1. Arnold M, Günther R. Adaptive parameter estimation in multivariate self-exciting threshold autoregressive models. Commun Stat Simul Comput 2001; 30: 257.
2. Arnold M, Möller U, Witte H. Nonlinear time-series modelling by means of self-exciting threshold AR models. Theory Biosci 1999; 118: 261.
3. Baccala LA, Sameshima K. Partial directed coherence: a new concept in neural structure determination. Biol Cybern 2001; 84: 463.
4. Buxton RB, Frank LR. A model for the coupling between cerebral blood flow and oxygen metabolism during neural stimulation. J Cereb Blood Flow Metab 1997; 17: 64.
5. Chen HH, Quo L. Identification and stochastic adaptive control. Boston: Birkhäuser 1998.
6. Dahlhaus R, Eichler M. Causality and graphical models for multivariate time series and point processes. In: Proceedings of the 2nd European Medical and Biological Engineering Conference, Vienna, Part 2, 2002: 1430.
7. Eichler M. Graphical modelling of dynamic relationships in multivariate time series. In: Winterhalder M, Schelter B, Timmer J, editors. Handbook of time series analysis. Wiley-VCH 2006: Berlin. In press.
8. Eichler M. On the evaluation of information flow in multivariate systems by the directed transfer function. Technical report 2005. Biol Cybern 2006; 94: 469.
9. Eichler M, Dahlhaus R, Sandkuhler J. Partial correlation analysis for the identification of synaptic connections. Biol Cybern 2003; 89: 289.
10. Feucht M, Möller U, Witte H, et al. Nonlinear dynamics of 3 Hz spike-and-wave discharges recorded during typical absence seizures in children. Cereb Cortex 1998; 8: 524.
11. Florens JP, Mouchart M. A note on noncausality. Econometrica 1982; 50: 583-591.
12. Fristen KJ, Mechelli A, Turner R, Price CJ. Nonlinear responses in fMRI: the balloon model, volterra kernels, and other hemodynamics. Neuroimage 2000; 12: 466.
13. Geweke J. Measurement of linear dependence and feedback between multiple time-series. J Am Stat Assoc 1982; 77: 304.
14. Granger CWJ. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 1969; 37: 424.
15. Granger CWJ. Testing for causality - a personal viewpoint. J Econ Dyn Control 1980; 2: 329.
16. Hesse W, Möller E, Arnold M, Schack B. The use of time-variant EEG Granger causality for inspecting directed interdependencies of neural assemblies. J Neurosci Meth 2003; 124: 27.
17. Hosoya Y. On the Granger condition for non-causality. Econometrica 1977; 45: 1735.
18. Kaminski M, Blinowska K, Szelenberger W. Topographic analysis of coherence and propagation of EEG activity during sleep and wakefulness. Electroencephalogr Clin Neurophysiol 1997; 102: 216.
19. Möller E, Schack B, Vath N, Witte H. Fitting of one ARMA model to multiple trials increases the time resolution of instantaneous coherence. Biol Cybern 2003; 89: 303.
20. Rasch D. Mathematische Statistik: eine Einführung für Studenten der Mathematik, Statistik, Biometrie und Naturwissenschaften. Heidelberg, Leipzig: Johann Ambrosius Barth Verlag 1995.
21. Tong H. Non-linear time series. Oxford: Oxford University Press 1990.
22. Winterhalder M, Schelter B, Hesse W, et al. Comparison directed of linear signal processing techniques to infer interactions in multivariate neural systems. Signal Process 2005; 85: 2137.