Geri Dön

Analysis of brain activity during the sleep-wake cycles of rodents and humans with symbolic dynamic analysis of the electroencephalogram

Başlık çevirisi mevcut değil.

PDF İndir

  1. Tez No: 544612
  2. Yazar: PINAR DENİZ TOSUN
  3. Danışmanlar: Dr. DANIEL ABASOLO, Dr. RAPHAELLE WINSKY SOMMERER
  4. Tez Türü: Doktora
  5. Konular: Makine Mühendisliği, Mechanical Engineering
  6. Anahtar Kelimeler: Belirtilmemiş.
  7. Yıl: 2018
  8. Dil: İngilizce
  9. Üniversite: University of Surrey
  10. Enstitü: Yurtdışı Enstitü
  11. Ana Bilim Dalı: Belirtilmemiş.
  12. Bilim Dalı: Belirtilmemiş.
  13. Sayfa Sayısı: 203

Özet

Özet yok.

Özet (Çeviri)

Sleep is an essential physiological phenomenon which is regulated by fundamental sleep-wake cycles. Sleep is formed of non-rapid-eye-movement (NREM) and REM stages where NREM and REM sleep stages alternate with wakefulness in a whole night sleep (i.e., typically consists of several sleep-wake cycles). During sleep, brain is active and the activity also alters with changing vigilance states (VS). Furthermore, physiological or external changes in the brain structure might influence brain activity during sleep. Effects of ageing, sex differences, and pharmacological manipulations have been widely investigated in sleep research using Fourier Transferim. However, the use of non-linear analysis techniques might be more suitable in analysing non-linear and non-stationary signals (e.g., electroencephalogram (EEG)). Therefore, non-linear analysis has been used within this PhD with the hypothesis that these methods might reveal hidden characteristics in the changing brain signals that are difficult to detect with traditional EEG power spectral density analysis. The use of non-linear analysis techniques (e.g., symbolic dynamic analysis (SDA)) will allow to further dissect the physiological significance of activity-dependent changes of neuronal networks across sleep-wake cycles, as well as the significance of brain activity patterns during waking, sleep, sleep deprivation (SD), or induced by sleep-promoting drugs and pharmacological treatments. In this PhD, rodent and human sleep EEG recordings were analysed using SDA methods: Lempel-Ziv complexity (LZC), Permutation Entropy (PE) and Permutation Lempel-Ziv complexity (PLZC). All the methods were able characterise different VS with wakefulness and REM sleep resulting in higher measures of complexity compared to NREM sleep suggesting an active state of the brain in these VS. This was measured in all datasets which assists the usability of these techniques in sleep research by providing at least the minimum requirement for sleep analysis (i.e., characterisation of VS). In addition to this, SD significantly reduced complexity in the following sleep period which supports the compensation process for the lost sleep by increased slow wave activity which was reflected as reduced complexity in this study. Furthermore, a low dose tiagabine administration's sleep compensation promoting effect was found in mice. Moreover, ageing was identified as a main effect on changes in brain activity. These changes were more pronounced in the old age where complexity was significantly lower compared to young age. On the one hand, this was found with all three methods contributing to the hypothesis that these techniques reveal structural dynamic changes due to physiological alterations. On the other hand, no significant differences in complexity across genders were found suggesting the underlying mechanisms that maintain sleep-wake cycles are similar for men and women. This finding with further investigation might corroborate to question the need to use both genders in drug trials. Furthermore, significant changes in brain activity were found at different times of the sleep period highlighting the changes occurring within VS as sleep progresses. This also has an impact on the way sleep stages are scored and investigated which are influenced by different brain activity levels within each VS throughout the entire sleep. All in all, this study achieved to support its hypothesis of determining the changes in brain activity as a complexity measure by characterising sleep under physiological and pharmacologically induced EEG datasets in mice and in humans. The study was a novel application to analyse sleep in these conditions. However, with further analysis performed on larger datasets, its findings together with surrogate data analysis proved SDA techniques' robust usability which can complement the gold standard FT analysis in sleep research and may provide a more sustainable research approach. Declaration of Originality This thesis and the work to which it refers are the results of my own efforts. Any ideas, data, images or text resulting from the work of others (whether published or unpublished) are fully identified as such within the work and attributed to their originator in the text, bibliography or in footnotes. This thesis has not been submitted in whole or in part for any other academic degree or Professional qualification. I agree that the university has the right to submit my work to the plagiarism detection service TurnitinUK for originality checks. Whether or not drafts have been so-assessed, the University reserves the right to require an electronic version of the final document (as submitted) for the assessment as above.

Benzer Tezler

  1. Tez No

    384870

    Korteks davranışının vuru üreten hücre modeli ile incelenmesi

    Analysis of cortex behavior by a spiking neuron model

    YUSUF KUYUMCU

    Yüksek Lisans

    Türkçe

    Türkçe

    2014

    Elektrik ve Elektronik Mühendisliğiİstanbul Teknik Üniversitesi

    Elektronik ve Haberleşme Mühendisliği Ana Bilim Dalı

    DOÇ. NESLİHAN SERAP ŞENGÖR

  2. Tez No

    323940

    Sandviç kumaşların termal konfor özellikleri

    Thermal comfort properties of spacer fabrics

    SENA TERLİKSİZ

    Yüksek Lisans

    Türkçe

    Türkçe

    2012

    Tekstil ve Tekstil Mühendisliğiİstanbul Teknik Üniversitesi

    Tekstil Mühendisliği Ana Bilim Dalı

    PROF. DR. FATMA KALAOĞLU

    YRD. DOÇ. DR. SELİN HANİFE ERYÜRÜK

  3. Tez No

    663357

    Alternatif makine öğrenmesi teknikleriyle epileptik EEG zaman serilerinin sınıflandırılması

    Classification of epileptic EEG time series with alternativemachine learning techniques

    BEYDA ÇAĞLIYAN

    Yüksek Lisans

    Türkçe

    Türkçe

    2021

    Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve KontrolSüleyman Demirel Üniversitesi

    Bilgisayar Mühendisliği Ana Bilim Dalı

    DOÇ. DR. UTKU KÖSE

  4. Tez No

    198804

    Wireless functional optical imager

    Telsiz işlevsel optik görüntüleyici

    SERKAN KARACA

    Yüksek Lisans

    İngilizce

    İngilizce

    2005

    BiyomühendislikBoğaziçi Üniversitesi

    Elektronik Mühendisliği Ana Bilim Dalı

    YRD. DOÇ. ATA AKIN

  5. Tez No

    390654

    Small-World modelinde yeniden yapılandırma ve gürültülü sinaptik iletkenliğin talamokortikal yavaş dalgalar üzerindeki etkileri

    In Small-World model the effects of rewiring and noisy synaptic conductivity on talamocortical slow waves

    RAMAZAN TEKİN

    Doktora

    Türkçe

    Türkçe

    2015

    Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrolİnönü Üniversitesi

    Elektrik-Elektronik Mühendisliği Ana Bilim Dalı

    DOÇ. DR. MEHMET EMİN TAĞLUK

Geri Dön