請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66839
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 林發暄(Fa-Hsuan Lin) | |
dc.contributor.author | Yi-Tien Li | en |
dc.contributor.author | 李宜恬 | zh_TW |
dc.date.accessioned | 2021-06-17T01:09:17Z | - |
dc.date.available | 2020-01-21 | |
dc.date.copyright | 2020-01-21 | |
dc.date.issued | 2020 | |
dc.date.submitted | 2020-01-19 | |
dc.identifier.citation | REFERENCE
Bellgowan P, Saad Z, Bandettini P. (2003): Understanding neural system dynamics through task modulation and measurement of functional MRI amplitude, latency, and width. Proceedings of the National Academy of Sciences 100(3):1415-1419. Brainard DH, Vision S. (1997): The psychophysics toolbox. Spatial vision 10:433-436. Buxton RB, Wong EC, Frank LR. (1998): Dynamics of blood flow and oxygenation changes during brain activation: the balloon model. Magnetic resonance in medicine 39(6):855-864. Chang C, Glover GH. (2009): Effects of model-based physiological noise correction on default mode network anti-correlations and correlations. Neuroimage 47(4):1448-59. Chang C, Thomason ME, Glover GH. (2008): Mapping and correction of vascular hemodynamic latency in the BOLD signal. Neuroimage 43(1):90-102. Chu YH, Hsu YC, Lin FH. (2016): Simultaneous multi-slice inverse imaging for high temporal resolution fMRI. Proc Intl Soc Magn Reson Med:946. Descoteaux M, Collins DL, Siddiqi K. (2008): A geometric flow for segmenting vasculature in proton-density weighted MRI. Medical image analysis 12(4):497-513. Descoteaux M, Collins L, Siddiqi K. Geometric flows for segmenting vasculature in MRI: Theory and validation; 2004. Springer. p 500-507. Devonshire IM, Papadakis NG, Port M, Berwick J, Kennerley AJ, Mayhew JE, Overton PG. (2012): Neurovascular coupling is brain region-dependent. Neuroimage 59(3):1997-2006. Devor A, Dunn AK, Andermann ML, Ulbert I, Boas DA, Dale AM. (2003): Coupling of total hemoglobin concentration, oxygenation, and neural activity in rat somatosensory cortex. Neuron 39(2):353-359. Ekstrom A. (2010): How and when the fMRI BOLD signal relates to underlying neural activity: the danger in dissociation. Brain research reviews 62(2):233-244. Feinberg DA, Setsompop K. (2013): Ultra-fast MRI of the human brain with simultaneous multi-slice imaging. Journal of magnetic resonance 229:90-100. Fischl B, Rajendran N, Busa E, Augustinack J, Hinds O, Yeo BT, Mohlberg H, Amunts K, Zilles K. (2008): Cortical folding patterns and predicting cytoarchitecture. Cerebral cortex 18(8):1973-1980. Frangi AF, Niessen WJ, Vincken KL, Viergever MA. Multiscale vessel enhancement filtering; 1998. Springer. p 130-137. Friston KJ, Fletcher P, Josephs O, Holmes A, Rugg M, Turner R. (1998): Event-related fMRI: characterizing differential responses. Neuroimage 7(1):30-40. Gao JH, Miller I, Lai S, Xiong J, Fox PT. (1996): Quantitative assessment of blood inflow effects in functional MRI signals. Magnetic resonance in medicine 36(2):314-319. Gary H. Glover T-QLaR. (2000): Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magnetic Resonance in Medicine 44(1):162-167. Glover GH, Lemieux SK, Drangova M, Pauly JM. (1996): Decomposition of inflow and blood oxygen level‐dependent (BOLD) effects with dual‐echo spiral gradient‐recalled echo (GRE) fMRI. Magnetic resonance in medicine 35(3):299-308. Handwerker DA, Gazzaley A, Inglis BA, D'esposito M. (2007): Reducing vascular variability of fMRI data across aging populations using a breathholding task. Human brain mapping 28(9):846-859. Henson RN, Price CJ, Rugg MD, Turner R, Friston KJ. (2002): Detecting latency differences in event-related BOLD responses: application to words versus nonwords and initial versus repeated face presentations. Neuroimage 15(1):83-97. Hinds OP, Rajendran N, Polimeni JR, Augustinack JC, Wiggins G, Wald LL, Rosas HD, Potthast A, Schwartz EL, Fischl B. (2008): Accurate prediction of V1 location from cortical folds in a surface coordinate system. Neuroimage 39(4):1585-1599. Hsu Y-C, Chu Y-H, Tsai S-Y, Kuo W-J, Chang C-Y, Lin F-H. (2017): Simultaneous multi-slice inverse imaging of the human brain. Scientific reports 7(1):17019. Huo B-X, Smith JB, Drew PJ. (2014): Neurovascular coupling and decoupling in the cortex during voluntary locomotion. Journal of Neuroscience 34(33):10975-10981. Kastrup A, Krüger G, Glover GH, Moseley ME. (1999): Assessment of cerebral oxidative metabolism with breath holding and fMRI. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine 42(3):608-611. Keilholz SD, Silva AC, Raman M, Merkle H, Koretsky AP. (2006): BOLD and CBV-weighted functional magnetic resonance imaging of the rat somatosensory system. Magnetic Resonance in Medicine 55(2):316-324. Kleiner M, Brainard D, Pelli D, Ingling A, Murray R, Broussard C. (2007): What’s new in Psychtoolbox-3. Perception 36(14):1. Lee AT, Glover GH, Meyer CH. (1995): Discrimination of large venous vessels in time‐course spiral blood‐oxygen‐level‐dependent magnetic‐resonance functional neuroimaging. Magnetic Resonance in Medicine 33(6):745-754. Leonard BE. (2002): Neuropsychopharmacology—The fifth generation of progress. Edited by K. L. Davis, D. Charney, J. T. Coyle, C. Nemeroff. Lippincott, Williams and Wilkins: Philadelphia, 2002. ISBN: 0-7817-2837-1. Price: $189. Pages: 2080. Human Psychopharmacology: Clinical and Experimental 17(8):433-433. Li Y-T, Lin J-FL, Wu P-Y, Tsai KW-K, Lin F-H. 2017. Characterize the Effect of Regional Variations in Venule Vasculature Related to temporal variability of hemodynamic responses latency at the human primary visual cortex. The ISMRM 25th Annual Meeting & Exhibition. Hawaii Convention Center, Honolulu, HI, USA: Yi-Tien Li. Lin F-H, Polimeni JR, Lin J-FL, Tsai KW-K, Chu Y-H, Wu P-Y, Li Y-T, Hsu Y-C, Tsai S-Y, Kuo W-J. (2018): Relative latency and temporal variability of hemodynamic responses at the human primary visual cortex. Neuroimage 164:194-201. Lin F-H, Witzel T, Raij T, Ahveninen J, Tsai KW-K, Chu Y-H, Chang W-T, Nummenmaa A, Polimeni JR, Kuo W-J. (2013): fMRI hemodynamics accurately reflects neuronal timing in the human brain measured by MEG. Neuroimage 78:372-384. Lin FH, Huang TY, Chen NK, Wang FN, Stufflebeam SM, Belliveau JW, Wald LL, Kwong KK. (2005): Functional MRI using regularized parallel imaging acquisition. Magnetic resonance in medicine 54(2):343-353. Lin FH, Kwong KK, Belliveau JW, Wald LL. (2004): Parallel imaging reconstruction using automatic regularization. Magnetic Resonance in Medicine 51(3):559-567. Liu H-L, Huang J-C, Wu C-T, Hsu Y-Y. (2002): Detectability of blood oxygenation level-dependent signal changes during short breath hold duration. Magnetic resonance imaging 20(9):643-648. Liu HL, Wei PS, Wai YY, Kuan WC, Huang CM, Wu CW, Buckle C, Wan YL, Gao JH. (2008): Inflow effects on hemodynamic responses characterized by event‐related using gradient‐echo EPI sequences. Medical physics 35(10):4300-4307. Logothetis NK, Pauls J, Augath M, Trinath T, Oeltermann A. (2001): Neurophysiological investigation of the basis of the fMRI signal. Nature 412(6843):150. Mandeville JB, Marota JJ, Ayata C, Zaharchuk G, Moskowitz MA, Rosen BR, Weisskoff RM. (1999): Evidence of a cerebrovascular postarteriole windkessel with delayed compliance. Journal of Cerebral Blood Flow & Metabolism 19(6):679-689. Marrelec G, Bellec P, Benali H. (2006): Exploring large-scale brain networks in functional MRI. Journal of Physiology-Paris 100(4):171-181. Miezin FM, Maccotta L, Ollinger J, Petersen S, Buckner R. (2000): Characterizing the hemodynamic response: effects of presentation rate, sampling procedure, and the possibility of ordering brain activity based on relative timing. Neuroimage 11(6):735-759. Pelli DG. (1997): The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial vision 10(4):437-442. Puckett AM, Mathis JR, DeYoe EA. (2014): An investigation of positive and inverted hemodynamic response functions across multiple visual areas. Human brain mapping 35(11):5550-5564. Rogers BP, Morgan VL, Newton AT, Gore JC. (2007): Assessing functional connectivity in the human brain by fMRI. Magnetic resonance imaging 25(10):1347-1357. Schacter DL, Buckner RL, Koutstaal W, Dale AM, Rosen BR. (1997): Late onset of anterior prefrontal activity during true and false recognition: an event-related fMRI study. Neuroimage 6(4):259-269. Setsompop K, Gagoski BA, Polimeni JR, Witzel T, Wedeen VJ, Wald LL. (2012): Blipped‐controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g‐factor penalty. Magnetic resonance in medicine 67(5):1210-1224. Shih AY, Rühlmann C, Blinder P, Devor A, Drew PJ, Friedman B, Knutsen PM, Lyden PD, Mateo C, Mellander L. (2015): Robust and fragile aspects of cortical blood flow in relation to the underlying angioarchitecture. Microcirculation 22(3):204-218. Sodickson DK. (2000): Tailored SMASH image reconstructions for robust in vivo parallel MR imaging. Magnetic resonance in medicine 44(2):243-251. Thomason ME, Burrows BE, Gabrieli JD, Glover GH. (2005): Breath holding reveals differences in fMRI BOLD signal in children and adults. Neuroimage 25(3):824-837. Thomason ME, Foland LC, Glover GH. (2007): Calibration of BOLD fMRI using breath holding reduces group variance during a cognitive task. Human brain mapping 28(1):59-68. Vigneau‐Roy N, Bernier M, Descoteaux M, Whittingstall K. (2014): Regional variations in vascular density correlate with resting‐state and task‐evoked blood oxygen level‐dependent signal amplitude. Human brain mapping 35(5):1906-1920. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66839 | - |
dc.description.abstract | 血氧水平依賴(BOLD)信號反映了潛在的神經活動和內在腦血管反應性(CVR)的組合。因此,使用BOLD信號偵測神經活動同步性以及推斷腦區間因果關係可能是有偏差的。可以透過閉氣(BH)任務來估計血液動力學延遲時間,得到測量BOLD信號中的純血管(非神經)延遲時間來解決這個問題。
本研究使用快速功能性磁振造影(取樣頻率 = 10 Hz)量測當受試者參與視覺運動(VM)任務時視覺區和感覺運動區之間的BOLD時間差。透過減去由CVR引起的時間差來進一步校正腦區間的BOLD時間差,而CVR是透過相同受試者族群的BH任務量測的。同時,我們還透過高空間解析度磁敏感加權成像(立體像素大小 = 0.78 × 0.78 × 1mm3)估計了受試者族群內的靜脈機率(VP)圖。透過計算這些結構和生理測量之間的相關性,我們目標是要顯示區域性的靜脈血管分佈與BOLD信號的動態變化及其變異性是否有關聯。 結果顯示,校正CVR造成的延遲時間,會使腦區間時間差呈現顯著差異(外側膝狀體早於視覺區,視覺區早於感覺運動區)。透過CVR校正,消除了原先在VP和BOLD延遲時間以及延遲時間變異性的顯著相關性。此外,在校正後,受試者之間和受試者自身重複量測皆發現任務反應時間(428 ± 41 ms)與腦區間BOLD時間差(432 ± 149 ms)之間呈現顯著正相關。研究結果顯示可以透過校正個體的CVR來改善BOLD信號的時間穩定性,此結果可由受試者族群的VP與BOLD延遲時間以及延遲時間變異性在校正後呈現無相關來驗證。 | zh_TW |
dc.description.abstract | The blood-oxygen level dependent (BOLD) signal reflects the combination of both underlying neural activity and the intrinsic cerebral vascular reactivity (CVR). Thus detecting neuronal synchrony as well as inferring inter-regional causal modulation using BOLD signal can be biased. Mapping the hemodynamic latency using a breath-holding (BH) task provides a way to mitigate this issue by measuring the pure vascular (non-neural) latency component in the BOLD signal.
Here we used fast fMRI measurements (sampling rate=10 Hz) to measure the BOLD timing difference between visual and sensorimotor areas when subjects engaged a visuomotor (VM) task. The inter-regional BOLD timing difference was further calibrated by subtracting the timing difference caused by CVR, which was measured by a BH task on the same subject group. Meanwhile, we also estimated a venous probability (VP) map within subject group by the high spatial resolution susceptibility-weighted image (voxel size=0.78×0.78×1mm3). Via the correlation between these structural and physiological measures, we aimed to reveal how the regional venous vasculature is related to the dynamics and variability of the BOLD signal. Calibrating the CVR led to the significant inter-regional BOLD timing difference (lateral geniculate nucleus before visual cortex, visual cortex before sensorimotor cortex). The significant correlation between VP and BOLD latencies as well as the latency variabilities were eliminated by CVR calibration. Further, significant positive correlation between task reaction time (428 ± 41 ms) and the within- as well as the cross-subject inter-regional BOLD timing difference (432 ± 149 ms) was revealed after calibration. The results supported that the temporal stability of BOLD signal can be empirically improved by calibrating individual’s CVR, which is underpinned by VP within the subject group. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T01:09:17Z (GMT). No. of bitstreams: 1 ntu-109-D05548015-1.pdf: 3724027 bytes, checksum: 42ca18b832627f36f42f49488ba90308 (MD5) Previous issue date: 2020 | en |
dc.description.tableofcontents | 口試委員會審定書 i
誌謝 ii 中文摘要 iii Abstract iv LIST OF FIGURES iii LIST OF TABLES v Chapter 1 Introduction 6 Chapter 2 Materials and Methods 10 2-1 Materials…............ 10 2-1.1 Subjects and the task 10 2-1.2 MRI data acquisition and reconstruction 10 2-1.3 Physiological monitoring 12 2-2 Data Analysis 12 2-2.1 BOLD latency estimation 12 2-2.2 Venous probability (VP) estimation 14 2-2.3 Linear regression relation between anatomical and physiological measures of vascular components 16 Chapter 3 Results 18 3-1 BOLD activation and latency results 18 3-2 The relationship between BOLD latency and venous vasculature 26 3-3 Relationship between BOLD latency and behavior data at visuomotor (VM) task 31 Chapter 4 Discussion 34 4-1 Behavior correlates of fMRI hemodynamic responses after calibrating the vascular contributions 34 4-2 Structural basis of fMRI hemodynamic responses related to venous vasculatures 36 4-3 Effect of the methodologies to generate latency map for latency calibration 39 Chapter 5 Conclusion 42 REFERENCE 43 | |
dc.language.iso | en | |
dc.title | 人腦血氧動態反應和行為的關聯與其結構基礎 | zh_TW |
dc.title | Behavioral Correlates and the Structural Basis of Hemodynamic Responses in the Human Brain | en |
dc.type | Thesis | |
dc.date.schoolyear | 108-1 | |
dc.description.degree | 博士 | |
dc.contributor.coadvisor | 黃義侑(Yi-You Huang) | |
dc.contributor.oralexamcommittee | 鍾孝文(Hsiao-Wen Chung),吳文超(Wen-Chau Wu),郭文瑞(Wen-Jui Kuo),蔡尚岳(Shang-Yueh Tsai) | |
dc.subject.keyword | 腦血管反應性,靜脈機率,閉氣任務,視覺運動任務,血液動力學延遲時間,延遲時間變異性,時間穩定性, | zh_TW |
dc.subject.keyword | cerebral vascular reactivity,venous probability,breath-holding task,visuomotor task,hemodynamic latency,latency variability,temporal stability, | en |
dc.relation.page | 46 | |
dc.identifier.doi | 10.6342/NTU202000123 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2020-01-20 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 醫學工程學研究所 | zh_TW |
顯示於系所單位: | 醫學工程學研究所 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-109-1.pdf 目前未授權公開取用 | 3.64 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。