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Year 2006, Volume: 19 Issue: 1, 6 - 12, 26.06.2015

Abstract

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References

  • 1. Karakaş S, Erzengin ÖU, Başar E. A new strategy involving multiple cognitive paradigms demonstrates that ERP components are determined by the superposition of oscillatory responses. Clin Neurophysiol 2000; 111: 1719-1732
  • 2. Başar E. EEG-Brain Dynamics: Relation between EEG and Brain Evoked-Potentials. Amsterdam: Elsevier Publication,1980.
  • 3. Brandt ME, Jansen BH. The relationship between prestimulus alpha amplitude and visual evoked potential amplitude. Int J Neurosci 1991; 61: 261-8.
  • 4. Jervis BW, Nichols MJ, Johnson TE, Allen, Hudson NR. A fundamental investigation of the composition of auditory evoked potentials. IEEE Trans Biomed Eng 1983; 30: 43-49.
  • 5. Kolev V, Yordanova J. Analysis of phase-locking is informative for studying event-related EEG activity. Biol Cybern 1997; 96: 229-235.
  • 6. Parvin C, Torres F, Johnson E. Synchronization of single evoked response components: Estimation and interrelation of reproducibility measures. In Rhythmic EEG Activities and Cortical Functioning. Amsterdam: Elsevier, 1980.
  • 7. Röschke J, Mann K, Riemann D, Frank C, Fell J. Sequential analysis of the brain’s transfer properties during consecutive REM periods. Electroencephalogr Clin Neurophysiol 1995; 96: 390-397.
  • 8. Solodovnikov VV. Introduction to the Statistical Dynamics of Automatic Control Systems. New York: Dover Publications 1960.
  • 9. Başar E. Brain Function and Oscillations I: Brain Oscillations. Principles and Approaches Heidelberg: Springer-Verlag 1998.
  • 10. Başar E. Brain Function and Oscillations II: Integrative Brain Function. Neurophysiology and Cognitive Processes. Heidelberg: Springer-Verlag 1999.
  • 11. Cohen L. Time-frequency distributions: A review. Proc IEEE 1989; 77 (7): 941-81.
  • 12. Demiralp T, Ademoğlu A, Schürmann M, Başar E. Wavelet analysis of brain waves. In: Başar E, editor. Brain Function and Oscillations: I. Brain Oscillations. Principles and Approaches. Heidelberg: Springer-Verlag 1998.
  • 13. Demiralp T, Ademoğlu A, Schürmann M, Başar-Eroğlu C, Başar E. Detection of P300 in single trials by the wavelet transform (WT). Brain Lang 1999; 66: 108-128.
  • 14. Özdemir AK., Karakaş S, Çakmak ED, Tüfekçi Dİ., Arıkan O. Time-frequency component analyser and its application to brain oscillatory activity. Journal of Neuroscience Methods 2005; 145: 107-125.
  • 15. Rosso OA, Blanco S, Yordanova J, Kolev V, Figliola A, Schürmann M, Başar E. Wavelet entropy: A new tool for analysis of short-duration brain electrical signals. J Neurosci Methods 2001; 105: 65-75.
  • 16. Samar VJ, Bobardikar A, Rao R, Swartz K. Wavelet analysis of neuroelectric waveforms: A conceptual tutorial. Brain and Lang 1999; 66: 7-60.
  • 17. Tağluk, M.E., Çakmak, E.D., Karakaş, S. Analysis of time-varying energy of brain responses to an oddball paradigm using short-term smoothed Wigner-Ville distribution. Journal of Neuroscience Methods 2005; 143: 197-208.
  • 18. Yordonova J, Kolev V, Rosso OA, et al. Wavelet entropy analysis of event-related potentials indicates modality of independent theta dominance. J Neurosci Methods 2002; 117: 99-109.
  • 19. Farwell LA, Martinerie JM, Bashore TR, Rapp PE, Goddard PH. Optimal digital filters for long-latency components of the event-related brain potential. Psychophysiology 1993; 30: 306-315.
  • 20. Cook III. EW, Miller GA. Digital filtering: Background and tutorial for psychophysiologists. Psychophysiology 1992; 29: 350-367.
  • 21. Box GEP, Jenkins GM, Reinsel GC. Time Series Analysis, Forecasting and Control, 3rd ed. NJ: Prentice Hall 1994.
  • 22. Demiralp T, Başar E. Theta rhytmicities following expected visual and auditory targets. Int J Psychophysiol 1992; 13: 147-160

EEG TEMELLİ OLAY-İLİŞKİ BEYİN DALGALARININ İSTATİSTİKSEL ZAMAN SERİLERİ İLE MODELLENMESİ

Year 2006, Volume: 19 Issue: 1, 6 - 12, 26.06.2015

Abstract

Amaç: Çalışmanın amacı beyinin olay ilişki aktivesinin alfa osilasyonlarının Otoregresif Bütünleşik
Hareketli Ortalama - ARIMA – modeli ile açıklamaktır.
Yöntem: Çalışan örneklem 17 (11 erkek, 6 kadın) sağ elini kullanan, sağlıklı gönüllülerden oluşmuştur. Olay
ilişkili aktivite, atlanmış uyarıcı paradigması altında kaydedilmiştir. Alfa tepkisi sayısal filtreyle elde
edilmiştir. Her katılımcının alfa tepksi ayrı ayrı analiz edilmiştir.
Bulgular: Yapılan çalışma göstermektedir ki her bir katılımcının atlanmış uyarıcı paradigması için alfa
tepkisi, ARIMA (0,2,1) tipindeki zaman serisiyle en iyi modellenebilmektedir.
Sonuç: Yapılan çalışma atlanmış uyarıcı paradigması altında elde edilmiş, bir katılımcının alfa tepkilerinin
en iyi ARIMA (0, 2, 1) zaman serisiyle modellendiğini göstermiştir.

References

  • 1. Karakaş S, Erzengin ÖU, Başar E. A new strategy involving multiple cognitive paradigms demonstrates that ERP components are determined by the superposition of oscillatory responses. Clin Neurophysiol 2000; 111: 1719-1732
  • 2. Başar E. EEG-Brain Dynamics: Relation between EEG and Brain Evoked-Potentials. Amsterdam: Elsevier Publication,1980.
  • 3. Brandt ME, Jansen BH. The relationship between prestimulus alpha amplitude and visual evoked potential amplitude. Int J Neurosci 1991; 61: 261-8.
  • 4. Jervis BW, Nichols MJ, Johnson TE, Allen, Hudson NR. A fundamental investigation of the composition of auditory evoked potentials. IEEE Trans Biomed Eng 1983; 30: 43-49.
  • 5. Kolev V, Yordanova J. Analysis of phase-locking is informative for studying event-related EEG activity. Biol Cybern 1997; 96: 229-235.
  • 6. Parvin C, Torres F, Johnson E. Synchronization of single evoked response components: Estimation and interrelation of reproducibility measures. In Rhythmic EEG Activities and Cortical Functioning. Amsterdam: Elsevier, 1980.
  • 7. Röschke J, Mann K, Riemann D, Frank C, Fell J. Sequential analysis of the brain’s transfer properties during consecutive REM periods. Electroencephalogr Clin Neurophysiol 1995; 96: 390-397.
  • 8. Solodovnikov VV. Introduction to the Statistical Dynamics of Automatic Control Systems. New York: Dover Publications 1960.
  • 9. Başar E. Brain Function and Oscillations I: Brain Oscillations. Principles and Approaches Heidelberg: Springer-Verlag 1998.
  • 10. Başar E. Brain Function and Oscillations II: Integrative Brain Function. Neurophysiology and Cognitive Processes. Heidelberg: Springer-Verlag 1999.
  • 11. Cohen L. Time-frequency distributions: A review. Proc IEEE 1989; 77 (7): 941-81.
  • 12. Demiralp T, Ademoğlu A, Schürmann M, Başar E. Wavelet analysis of brain waves. In: Başar E, editor. Brain Function and Oscillations: I. Brain Oscillations. Principles and Approaches. Heidelberg: Springer-Verlag 1998.
  • 13. Demiralp T, Ademoğlu A, Schürmann M, Başar-Eroğlu C, Başar E. Detection of P300 in single trials by the wavelet transform (WT). Brain Lang 1999; 66: 108-128.
  • 14. Özdemir AK., Karakaş S, Çakmak ED, Tüfekçi Dİ., Arıkan O. Time-frequency component analyser and its application to brain oscillatory activity. Journal of Neuroscience Methods 2005; 145: 107-125.
  • 15. Rosso OA, Blanco S, Yordanova J, Kolev V, Figliola A, Schürmann M, Başar E. Wavelet entropy: A new tool for analysis of short-duration brain electrical signals. J Neurosci Methods 2001; 105: 65-75.
  • 16. Samar VJ, Bobardikar A, Rao R, Swartz K. Wavelet analysis of neuroelectric waveforms: A conceptual tutorial. Brain and Lang 1999; 66: 7-60.
  • 17. Tağluk, M.E., Çakmak, E.D., Karakaş, S. Analysis of time-varying energy of brain responses to an oddball paradigm using short-term smoothed Wigner-Ville distribution. Journal of Neuroscience Methods 2005; 143: 197-208.
  • 18. Yordonova J, Kolev V, Rosso OA, et al. Wavelet entropy analysis of event-related potentials indicates modality of independent theta dominance. J Neurosci Methods 2002; 117: 99-109.
  • 19. Farwell LA, Martinerie JM, Bashore TR, Rapp PE, Goddard PH. Optimal digital filters for long-latency components of the event-related brain potential. Psychophysiology 1993; 30: 306-315.
  • 20. Cook III. EW, Miller GA. Digital filtering: Background and tutorial for psychophysiologists. Psychophysiology 1992; 29: 350-367.
  • 21. Box GEP, Jenkins GM, Reinsel GC. Time Series Analysis, Forecasting and Control, 3rd ed. NJ: Prentice Hall 1994.
  • 22. Demiralp T, Başar E. Theta rhytmicities following expected visual and auditory targets. Int J Psychophysiol 1992; 13: 147-160
There are 22 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Ömer Erzengin This is me

Vildan Sümbüloğlu This is me

Sirel Karakaş This is me

Publication Date June 26, 2015
Published in Issue Year 2006 Volume: 19 Issue: 1

Cite

APA Erzengin, Ö., Sümbüloğlu, V., & Karakaş, S. (2015). EEG TEMELLİ OLAY-İLİŞKİ BEYİN DALGALARININ İSTATİSTİKSEL ZAMAN SERİLERİ İLE MODELLENMESİ. Marmara Medical Journal, 19(1), 6-12.
AMA Erzengin Ö, Sümbüloğlu V, Karakaş S. EEG TEMELLİ OLAY-İLİŞKİ BEYİN DALGALARININ İSTATİSTİKSEL ZAMAN SERİLERİ İLE MODELLENMESİ. Marmara Med J. August 2015;19(1):6-12.
Chicago Erzengin, Ömer, Vildan Sümbüloğlu, and Sirel Karakaş. “EEG TEMELLİ OLAY-İLİŞKİ BEYİN DALGALARININ İSTATİSTİKSEL ZAMAN SERİLERİ İLE MODELLENMESİ”. Marmara Medical Journal 19, no. 1 (August 2015): 6-12.
EndNote Erzengin Ö, Sümbüloğlu V, Karakaş S (August 1, 2015) EEG TEMELLİ OLAY-İLİŞKİ BEYİN DALGALARININ İSTATİSTİKSEL ZAMAN SERİLERİ İLE MODELLENMESİ. Marmara Medical Journal 19 1 6–12.
IEEE Ö. Erzengin, V. Sümbüloğlu, and S. Karakaş, “EEG TEMELLİ OLAY-İLİŞKİ BEYİN DALGALARININ İSTATİSTİKSEL ZAMAN SERİLERİ İLE MODELLENMESİ”, Marmara Med J, vol. 19, no. 1, pp. 6–12, 2015.
ISNAD Erzengin, Ömer et al. “EEG TEMELLİ OLAY-İLİŞKİ BEYİN DALGALARININ İSTATİSTİKSEL ZAMAN SERİLERİ İLE MODELLENMESİ”. Marmara Medical Journal 19/1 (August 2015), 6-12.
JAMA Erzengin Ö, Sümbüloğlu V, Karakaş S. EEG TEMELLİ OLAY-İLİŞKİ BEYİN DALGALARININ İSTATİSTİKSEL ZAMAN SERİLERİ İLE MODELLENMESİ. Marmara Med J. 2015;19:6–12.
MLA Erzengin, Ömer et al. “EEG TEMELLİ OLAY-İLİŞKİ BEYİN DALGALARININ İSTATİSTİKSEL ZAMAN SERİLERİ İLE MODELLENMESİ”. Marmara Medical Journal, vol. 19, no. 1, 2015, pp. 6-12.
Vancouver Erzengin Ö, Sümbüloğlu V, Karakaş S. EEG TEMELLİ OLAY-İLİŞKİ BEYİN DALGALARININ İSTATİSTİKSEL ZAMAN SERİLERİ İLE MODELLENMESİ. Marmara Med J. 2015;19(1):6-12.