Open Access
EPJ Nonlinear Biomed Phys
Volume 3, Number 1, December 2015
Article Number 4
Number of page(s) 35
Published online 10 April 2015
  1. Kroger JK, Elliott L, Wong TN, Lakey J, Dang H, George J. Detecting mental commands in high frequency EEG: Faster brain-machine interfaces. In: Proc. of the 2006 Biomedical Engineering Society Annual Meeting, Chicago, 2006. [Google Scholar]
  2. Watkins C, Kroger J, Kwong N, Elliott L, George J. Exploring high-frequency EEG as a faster medium of brain-machine communication. In: Proceedings Institute of Biological Engineering 2006 Annual Meeting, Tucson. [Google Scholar]
  3. Jovanović A, Perović A. Brain computer interfaces - some technical remarks. Int J Bioelectromagn. 2007;9(3):191–203. [Google Scholar]
  4. Jovanovic A, Perovic A, Borovcanin M. Brain connectivity measures: computations and comparisons. EPJ Nonlinear Biomed Phys. 2013;1:2. [Google Scholar]
  5. Perović A, Dordević Z, Paškota M, Takači A, Jovanović A. Automatic recognition of features in spectrograms based on some image analysis methods. Acta Polytechnica Hungarica. 2013;10:2. [Google Scholar]
  6. Jovanovic A, Kasum O, Peric N, Perovic A. Enhancing microscopic imaging for better object and structural detection, insight and classification. In: Mendez-Vilas A, editor. Microscopy: advances in scientific research and education, FORMATEX Microscopy series N6, vol. 2. 2014. [Google Scholar]
  7. Liu L, Arfanakis K, Ioannides A. Visual field influences functional connectivity pattern in a face affect recognition task. Int J Bioelectromagnetism. 2007;9:4. [Google Scholar]
  8. Aoyama A, Honda S, Takeda T. Magnetoencephalographic study of auditory feature analysis associated with visually based prediction. Int J Bioelectromagn. 2009;11(3):144–8. [Google Scholar]
  9. Grierson M. Composing with brainwaves: Minimal trial P300b recognition as an indication of subjective preference for the control of a musical instrument. Proceedings of the ICMC, Belfast. 2008. [Google Scholar]
  10. Granger CWJ. Investigating causal relations by econometric models and cross-spectral methods. Econometrica. 1969;37:424. [Google Scholar]
  11. Granger CWJ. Testing for causality: a personal viewpoint. J Econ Dyn Contr. 1980;2:329. [Google Scholar]
  12. Granger CWJ, Morris MJ. Time series modelling and interpretation. J R Stat Soc Ser A. 1976;139:246. [Google Scholar]
  13. Geweke J. Measurement of linear dependence and feedback between multiple time series. J Am Stat Assoc. 1982;77:304. [Google Scholar]
  14. Geweke J. Measures of conditional linear dependence and feedback between time series. J Am Stat Assoc. 1984;79:907. [Google Scholar]
  15. Kaminski M, Blinowska K. A new method of the description of the information flow in the brain structures. Biol Cybern. 1991;65:203. [Google Scholar]
  16. Kaminski M, Ding M, Truccolo W, Bressler S. Evaluating causal relations in neural systems: Granger causality, directed transfer function and statistical assessment of significance. Biol Cybern. 2001;85:145. [Google Scholar]
  17. Sameshima K, Baccala LA. Using partial directed coherence to describe a neuronal assembly interactions. J Neurosci Meth. 1999;94:93. [Google Scholar]
  18. Baccala L, Sameshima K. Partial directed coherence: a new concept in neural structure determination. Biol Cybern. 2001;84:463. [Google Scholar]
  19. Chen Y, Bressler SL, Ding M. Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data. J Neurosci Methods. 2006;150:228. [Google Scholar]
  20. Schelter B, Winterhalder M, Eichler M, Peifer M, Hellwig B, Guschlbauer B, et al. Testing for directed influences among neural signals using partial directed coherence. J Neurosci Meth. 2005;152:210. [Google Scholar]
  21. Takahashi DS, Baccala LA, Sameshima K. Information theoretic interpretation of frequency domain connectivity measures. Biol Cybern. 2010;103:463–9. 28. [Google Scholar]
  22. Shi J, Tomasi C. Good Features to Track, preprint, [Google Scholar]
  23. Welch G, Bishop G. An Introduction to the Kalman Filter. Chapter Hill: University of North Carolina at Chapter Hill; 2004. TR 95-014, April 5. [Google Scholar]
  24. Baccala L, Sameshima K. Overcoming the limitations of correlation analysis for many simultaneously processed neural structures, Chapter 3, M.A.L. In: Nicolelis ed. Progress in brain research, vol 130, Elsevier Sc; 2001. p. 1–15. [Google Scholar]
  25. Takahashi DY, Baccalá LA, Sameshima K. Partial directed coherence asymptotics for VAR processes of infinite order. Int J Bioelectromagn. 2008;10(1):31–6. [Google Scholar]
  26. Blinowska K. Review of the methods of determination of directed connectivity from multichannel data. Med Biol Eng Comput. 2011;49:521. doi: 10.1007/s11517-011-0739-x. [Google Scholar]
  27. Blinowska K, Kus R, Kaminski M, Janiszewska J. Transmission of brain activity during cognitive task. Brain Topogr. 2010;23:205. doi: 10.1007/s10548-010-0137-y. [Google Scholar]
  28. Brzezicka A, Kaminski M, Kaminski J, Blinowska K. Information transfer during a transitive reasoning task. Brain Topogr. 2011;24:1. doi: 10.1007/s10548-010-0158-6. [Google Scholar]
  29. Kus R, Blinowska K, Kaminski M, Basinska-Starzycka A. Transmission of information during continuous attention test. Acta Neurobiol Exp. 2008;68:103. [Google Scholar]
  30. Blinowska K. Methods for localization of time-frequency specific activity and estimation of information transfer in brain. Int J Bioelectromagn. 2008;10(1):2–16. [Google Scholar]
  31. Dhamala M, Rangarajan G, Ding M. Estimating Granger causality from Fourier and wavelet transforms of time series data. Phys Rev Lett. 2008;100(018701):1. [Google Scholar]
  32. Singh H, Li Q, Hines E, Stocks N. Classification and feature extraction strategies for multi channel multi trial BCI data. Int J Bioelectromagn. 2007;9(4):233. [Google Scholar]

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