博碩士論文 101331020 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:62 、訪客IP:3.236.147.122
姓名 洪百泉(Pai-Chuan Hung)  查詢紙本館藏   畢業系所 生物醫學工程研究所
論文名稱 利用同步腦電圖與功能性磁振造影探討睡眠階段之大腦活動
(Investigating Brain Oscillations across Sleep Stages using Simultaneous EEG-fMRI Recording)
相關論文
★ 應用希爾伯特黃轉換於功能性磁振造影之非穩態信號分析★ 評估生理雜訊對於靜息態功能性磁振造影之影響
★ 瀕死狀態下大腦功能性聯結之動態變化:觀察氯化鉀注射後大鼠之生理反應★ 探討同步功能性磁振造影與腦電圖於夜間睡眠研究
★ 以腦電圖觀察大腦恢復清醒的動態歷程★ 探討區域性大腦網路恢復於睡眠遲惰研究
★ 中風復健與大腦的神經可塑性變化: 縱貫性功能性磁振造影研究★ 以功能性磁振造影初探分心於創意醞釀之影響
★ 以靜息態功能性磁振造影探討頸動脈支架手術對於頸動脈狹窄病患大腦功能之影響★ 運用石墨烯射頻線圈增進7T磁振造影訊雜比之研究
★ 睡眠遲惰期間警覺網路於執行警覺任務下的動態恢復歷程
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 睡眠對於許多動物來說是不可或缺的生理節律,其功能除了調整生理狀態外,亦會重整大腦的認知功能,例如情緒及專注力調節;先前文獻亦指出深層睡眠(非快速動眼期第三階段)更與記憶鞏固息息相關。但過往睡眠相關研究大多專注於特定睡眠階段或是特定睡眠指標進行探討,鮮少有跨睡眠階段之全頻帶研究。因此為了了解睡眠中大腦網路的動態變化,我們首次嘗試使用同步腦電圖與功能性磁振造影來觀察正常受試者大腦網路在清醒狀態與非快速動眼睡眠(尤其是深層睡眠)間之差異。本論文著重於兩大目標:(1)探討腦波各頻帶在跨睡眠階段的頻率能量以及其網路連結之變化,以及(2)觀察有無深層睡眠對大腦活動的潛在影響。結果發現,腦波各頻帶在不同睡眠階段中有其特定的空間分佈以及功能性連結變化的差異;例如低頻Delta波在睡眠深度越深時除了能量逐漸增強外,其網路連結亦會從清醒時的縱向連結逐漸轉變為橫向連結。此外,缺少深層睡眠發現對清醒後的頻譜能量與橫向連結並無顯著影響,但對清醒後的縱向連結有顯著變化,暗示慢波睡眠的功用可能著重在改變大腦網路的縱向連結。不過在腦電圖以及功能性磁振造影都的結果中都發現頻率表現和網路連結不見得會呈現相同趨勢。整體而言,本論文證明腦波各頻帶在不同睡眠階段具有頻率響應及網路連結的動態特異性,而深層睡眠不僅在大腦網路調節上扮演著重要角色,有可能也會對甦醒後的腦部活動產生衝擊。
摘要(英) Sleep is an important physiological rhythm for many creatures, not only associated with physical regulation but also associated with mental reorganization. It has been proven that sleep correlates with lots of cognitive functions such as the emotion regulation, memory consolidation and attention. Previous sleep studies were typically conducted using electroencephalography (EEG), targeting on the changes of specific frequency bands or certain sleep stage; however, dynamic changes was rarely reported across all frequency bands and sleep stages. Therefore, to reveal the dynamicity within sleeping brain, we first investigate the sleeping EEG power and connectivity across frequency bands and non-rapid-eye-movement (NREM) sleep stages using simultaneous EEG-fMRI. Our second goal is to observe the impact of slow wave sleep (SWS) on brain activity and connectivity. Our results indicated spectral and regional disparities in EEG power and connectivity analysis across sleep stages. For example, the delta band showed increasing power along with deep sleep stages, meanwhile the delta connectivity pattern converted from waking longitudinal connection into a transverse connection during sleep. Secondly, the low-frequency bands did not show significant SWS effect on awakening in both power and transverse connectivity, but presented strong changes in longitudinal connectivity, which implied that slow wave sleep modulates the brain longitudinal connectivity. Furthermore, it should be noted that both EEG and fMRI presented a dissimilar mismatch between the spectral power and functional connectivity across sleep stages. Conclusively, this study indicate that during NREM sleep, EEG frequency bands had their own dynamic features in both power and connectivity, and lack of slow wave sleep might affect the consecutive functional connectivity upon awakening.
關鍵字(中) ★ 非快速動眼睡眠
★ 腦波
★ 頻率
★ 網路連結
關鍵字(英)
論文目次 中文摘要 V
Abstract VI
Contents VII
List of Figures IX
List of Tables X
Chapter 1. Introduction 1
1.1 Research Purpose 1
1.2 Hypothesis and Aim 2
Chapter 2. Background 3
2.1 Sleep in EEG recording 3
2.2 Simultaneous EEG and fMRI 5
Chapter 3. Material and Methods 6
3.1 Participants preparation 6
3.2 Experiment Design and Protocol 8
3.2.1 Experiment Design 8
3.2.2 EEG Protocol 10
3.2.3 fMRI Protocol 11
3.3 Data Preprocessing 13
3.3.1 EEG noise removal and preprocessing 13
3.3.2 fMRI preprocessing 13
3.4 Data Analysis 14
3.4.1 Spectral analysis 14
3.4.2 EEG connectivity analysis 15
3.4.3 Statistical analysis 17
Chapter 4. Optimization of EEG Artifact-removal Strategies 18
4.1 Gradient field artifacts removal 19
4.2 Ballistocardiographic artifacts removal 21
4.3 Comparison between Analyzer and EEGLAB 23
4.3.1 Consistency in time series 24
4.3.2 Comparison using spectral analysis 25
4.3.3 Comparison using time-frequency analysis 27
Chapter 5. Results 30
5.1 Sleep scoring 30
5.2 Changes of spontaneous brain activity in multiple sleep stages 33
5.2.1 Spectral changes across multiple sleep stages 33
5.2.2 Topography of EEG connectivity across sleep stages 37
5.3 Changes of spontaneous brain activity in lack of deep sleep 41
5.3.1 Comparison between Pre-sleep & Awakening: Spectral Power 41
5.3.2 Comparison between Pre-sleep & Awakening: EEG connectivity 47
Chapter 6. Discussion 53
6.1 Spectrum and topography distribution 53
6.1.1 Delta dominated in anterior and posterior regions 53
6.1.2 Theta dominated in anterior and posterior regions 54
6.1.3 Alpha dominated in posterior regions 54
6.1.4 Beta dominated in anterior and posterior regions 55
6.2 Topography of EEG connectivity 55
6.2.1 Increased transverse connection in delta band during sleep 55
6.2.2 Decreased transverse connectivity in theta band upon awakening in without-N3 group 56
6.2.3 Higher anterior/posterior connectivity in alpha/beta band 57
6.4 Comparison between EEG and fMRI results 57
6.4.1 fMRI results across sleep stages 57
6.4.2 Comparison between pre-sleep and awakening in fMRI 63
6.4 Limitation 66
Chapter 7. Conclusion 67
References 68
參考文獻 1. Asplund, C.L. and M.W.L. Chee, Time-on-task and sleep deprivation effects are evidenced in overlapping brain areas. NeuroImage, 2013. 82: p. 326-335.
2. Prince, T.-M., et al., Sleep deprivation during a specific 3-hour time window post-training impairs hippocampal synaptic plasticity and memory. Neurobiology of Learning and Memory, 2014. 109: p. 122-130.
3. Motomura, Y., et al., Sleep Debt Elicits Negative Emotional Reaction through Diminished Amygdala-Anterior Cingulate Functional Connectivity. PLOS ONE, 2013. 8(2).
4. Bronzino, J.D., et al., Power spectral analysis of the EEG following protein malnutrition. Brain Research Bulletin, 1980. 5(1): p. 51-60.
5. Cai, Z.-J., An integrative analysis to sleep functions. Behavioural Brain Research, 1995. 69(1-2): p. 187-194.
6. Davis, H., et al., CHANGES IN HUMAN BRAIN POTENTIALS DURING THE ONSET OF SLEEP. Science, 1937. 86(2237): p. 448-450.
7. Aserinsky, E. and N. Kleitman, Regularly occurring periods of eye motility, and concomitant phenomena, during sleep. J Neuropsychiatry Clin Neurosci, 1953. 15(4): p. 454-455.
8. Rechtschaffen, A. and Kales A, A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects. . 1968.
9. Bryant, P.A., J. Trinder, and N. Curtis, SICK AND TIRED:DOES SLEEP HAVE A VITAL ROLE IN THE IMMUNE SYSTEM? NATURE REVIEWS IMMUNOLOGY, 2004. 4: p. 457-467.
10. Stickgold, R., Sleep: off-line memory reprocessing. Trends in Cognitive Sciences, 1998. 2(12): p. 484-492.
11. Medicine, A.A.o.S. and C. Iber, The AASM manual for the scoring of sleep and associated events: rules, terminology and technical specifications. American Academy of Sleep Medicine, 2007.
12. Ogawa S, T.D., Menon R, Ellermann JM, Kim SG, Merkle H, Ugurbil K, Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci U S A., 1992. 89(13): p. 5951-5955.
13. Hung, C.-S., et al., Local Experience-Dependent Changes in the Wake EEG after Prolonged Wakefulness. SLEEP, 2013. 36(01): p. 59-72.
14. Zalesky, A., A. Fornito, and E. Bullmore, On the use of correlation as a measure of network connectivity. Neuroimage, 2012. 60(4): p. 2096-2106.
15. MARZANO, C., et al., ELECTROENCEPHALOGRAPHIC SLEEP INERTIA OF THE AWAKENING BRAIN. Neuroscience, 2011. 176(308-317).
16. Dang-Vu, T.T., et al., Spontaneous neural activity during human slow wave sleep. PNAS, 2008. 105(39): p. 15160-15165.
17. Xia, M., J. Wang, and Y. He, BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics. PLOS ONE, 2013. 8(7).
18. GmbH, B.P., BrainVision Analyzer User Manual. 2013.
19. Philip J. Allen, O.J., Robert Turner, Method for Removing Imaging Artifact from Continuous EEG Recorded during Functional MRI. NeuroImage, 2000. 12(2): p. 230-239.
20. Arnaud Delorme, S.M., EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 2004. 134(1): p. 9-21.
21. H, J., CORTICAL EXCITATORY STATE AND VARIABILITY IN HUMAN BRAIN RHYTHMS. Science, 1936. 83(2150): p. 259-260.
22. Norden E. Huang, et al., The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. 1998.
23. Finelli, L.A., A.A. Borbely, and P. Achermann, Functional topography of the human nonREM sleep electroencephalogram. European Journal of Neuroscience, 2001. 13(12): p. 2282-2290.
24. Massimini, M., et al., The Sleep Slow Oscillation as a Traveling Wave. The Journal of Neuroscience, 2004. 24(31): p. 6862-6870.
25. Aeschbach, D., et al., Evidence from the waking electroencephalogram that short sleepers live under higher homeostatic sleep pressure than long sleepers. Neuroscience, 2001. 102(3): p. 493-502.
26. Tinguely, G., et al., Functional EEG topography in sleep and waking: State-dependent and state-independent features. NeuroImage, 2006. 32(1): p. 283-292.
27. Gorgoni, M., et al., EEG topography during sleep inertia upon awakening after a period of increased homeostatic sleep pressure. Sleep Medicine, 2015. 16(7): p. 883-890.
28. GALLIAUD, E., et al., Sharp and sleepy: evidence for dissociation between sleep pressure and nocturnal performance. J. Sleep Res., 2008. 17(1): p. 11-15.
29. Klimesch, W., et al., Induced alpha band power changes in the human EEG and attention. Neurosci Lett, 1998. 244(2): p. 73-76.
30. Berger, H., Über das Elektrenkephalogramm des Menschen. Archiv für Psychiatrie und Nervenkrankheiten,, 1933.
31. Mantini, D., et al., Electrophysiological signatures of resting state networks in the human brain. PNAS, 2007. 104(32): p. 13170-13175.
32. Laufs, H., et al., Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest. PNAS, 2003. 100(19): p. 11053-11058.
33. Bernardi, G., et al., Neural and Behavioral Correlates of Extended Training during Sleep Deprivation in Humans: Evidence for Local, Task-Specific Effects. The Journal of Neuroscience, 2015. 35(11): p. 4487-4500.
34. Verweij, I.M., et al., Sleep deprivation leads to a loss of functional connectivity in frontal brain regions. BMC Neurosci, 2014. 15: p. 88-98.
35. Ko, Y.-T., Investigating Dynamic Brain Oscillation and Synchronization in Nocturnal Sleep using Simultaneous fMRI and EEG. 2014.
36. Tsai, P.-J., et al., Local awakening: Regional reorganizations of brain oscillations after sleep. NeuroImage, 2014. 102: p. 894-903
指導教授 吳昌衛 審核日期 2016-1-27
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明