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題名 腦島的功能性連結之年紀差異：基於小世界網路下的探討
Age-related differences on the functional connectivity of insular cortex: An approach based upon small-world theory
作者 林俊鴻
Lin, Jun Hong
貢獻者 蕭又新
Shiau, Yuo Hsien
林俊鴻
Lin, Jun Hong
關鍵詞 小世界網路
中樞自主神經系統
認知功能
多重攻擊策略
日期 2016
上傳時間 14-Nov-2016 16:15:24 (UTC+8)
摘要 近年來，功能性磁振造影技術發展迅速，使得大腦神經活動關聯性在腦神經科學中逐漸發展成熟。同時，網路理論的發展在近代也引起關注，在生物物理中，小世界網路(Small-World Network)被廣泛運用在大腦神經網路，其群聚性高、特徵路徑短之性質與大腦各個腦區間反應及高效率傳遞資訊的特性相似。有鑑於此，本論文藉由小世界網路的特性探討大腦的老化現象。
本研究以靜息態功能性磁振造影(Resting-state fMRI)量測年輕人及老年人大腦資料，並以右側腦島(Ins.R)作為核心，建構以腦島為核心的正及負相關網路。隨後，我們觀察在小世界特性明顯下的全域網路參數(Global Network Parameters)及區域網路參數(Regional Network Parameters)之老化現象。最後，我們利用多重攻擊策略模擬網路多點受損之情況，以了解網路之脆弱性。
我們研究結果指出，以腦島建立之負相關網路的常規化特徵路徑(Normalized Characteristic Path Length)會隨年紀而減短。並在區域網路參數所選出之重要網路樞紐中發現以腦島所建構之相關網路與認知功能(Cognitive Function)及中樞自主神經系統(Central Autonomic System)具有相關，且正相關網路中左側前扣帶和旁扣帶腦回(ACIN.L)及左側緣上回(SMG.L)隨著老化有顯著差異。期望可幫助醫學上了解中樞自主系統與認知功能在老化下之狀況。
參考文獻 參考文獻
[1]Re´ka Albert* and Albert-La´ szlo´ Baraba´ si,2002,.Statistical mechanics of complex networks
[2]Erdős, P., and A. Rényi. "On the evolution of random graphs." Selected Papers of Alfréd Rényi, vol 2 (1976): 482-525.
[3] Duncan J. Watts & Steven H. Strogatz 1998. Collective dynamics of ‘small-world’ networks. Nature 393, 440–442.

[4]Critchley, H.D., Harrison, N.A., 2013. Visceral influences on brain and behavior. Neuron 77, 624-638.
[5]Roser Sala-Llonch a,b, Carme Junqué a,b, Eider M. Arenaza-Urquijo a, Dídac Vidal-Piñeiro a,Cinta Valls-Pedret c, Eva M. Palacios a, Sara Domènech d, Antoni Salvà d, Nuria Bargalló e,David Bartrés-Faz a,b,2014,.Changes in whole-brain functional networks and memory performance in aging
[6]Song, X.-W., Dong, Z.-Y., Long, X.-Y., Li, S.-F., Zuo, X.-N., Zhu, C.-Z., He, Y., Yan, C.-G., Zang, Y.-F. 2011. REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PloS one 6(9), e25031.
[7]Chao-Gan, Y., Yu-Feng, Z. 2010. DPARSF: a MATLAB toolbox for “pipeline” data analysis of resting-state fMRI. Frontiers in systems neuroscience 4.
[8]Fox, M.D., Snyder, A.Z., Vincent, J.L., Corbetta, M., Van Essen, D.C., Raichle,M.E.2005. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences of the United States of America 102(27), 9673-8.
[9]Biswal, B., Zerrin Yetkin, F., Haughton, V.M., Hyde, J.S. 1995. Functional connectivity in the motor cortex of resting human brain using echo‐planar mri. Magnetic resonance in medicine 34(4), 537-41.
[10]Beissner, F., Meissner, K., Bär, K.-J., Napadow, V. 2013. The autonomic brain: an activation likelihood estimation meta-analysis for central processing of autonomic function. The Journal of Neuroscience 33(25), 10503-11.
[11]Lixia Tian, Jinhui Wang, Chaogan Yan, Yong He .,2010 .Hemisphere- and gender-related differences in small-world brain networks: A resting-state functional MRI study
[12]Rajesh Kumar,2015,. Reduced Regional Brain Cortical Thickness in Patients with Heart Failure
[13]Yihai Zhu, Yan (Lindsay) Sun2012 ,,Load Distribution Vector Based Attack Strategies against Power Grid Systems
[14]M. E. J. Newman,2004, “Scientific collaboration networks. II. shortest paths, weighted networks, and centrality,” Phys. Rev. E., vol. 64, 016132]
[15]Xiaoxi He,2013,.Age-related decrease in functional connectivity of the right fronto-insular cortex with the central executive and default-mode networks in adults from young to middle age
[16]Francis L. Stevens, Ph.D., Robin A. Hurley, M.D., Katherine H. Taber, Ph.D.,2011,.Anterior Cingulate Cortex: Unique Role in Cognition and Emotion
[17]Cornelia Stoeckel1, Patricia M. Gough2,3, Kate E. Watkins1,2, and Joseph T.Devlin4,2009,Supramarginal gyrus involvement in visual word recognition
[18]Tononi, G., Sporns, O., Edelman, G.M., 1994. A measure for brain complexity: relating functional segregation and integration in the nervous system. Proc. Natl Acad. Sci. USA 91, 5033–5037.

[19]Elizabeth A Phelps2004,.Human emotion and memory: interactions of the amygdala and hippocampal complex
[20]Adam Hampshire, Samuel R. Chamberlain, Martin M. Monti , John Duncan , Adrian M. Owen 2010,.The role of the right inferior frontal gyrus: inhibition and attentional control
[21]Amanda V. Utevsky,1,2 David V. Smith,3 and Scott A. Huettel1,2 ,.2014,Precuneus Is a Functional Core of the Default-Mode Network
[22] Grady, C., Springer, M., Hongwanishkul, D., McIntosh, A., Winocur, G., 2006. Age-related changes in brain activity across the adult lifespan. Journal of Cognitive Neuroscience 18, 227-241.
[23]Hotta, H., Uchida, S., 2010. Aging of the autonomic nervous system and possible improvements in autonomic activity using somatic afferent stimulation. Geriatrics & gerontology international 10, S127-S136.
[24]Kelly, A.C., Uddin, L.Q., Biswal, B.B., Castellanos, F.X., Milham, M.P., 2008. Competition between functional brain networks mediates behavioral variability. Neuroimage 39, 527-537.
[25]Lowe, M., Mock, B., Sorenson, J. 1998. Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations. Neuroimage 7(2), 119-32.
[26]Alireza Salami,Sara Pudas, Lars Nyberg,.2014,.Elevated hippocampal resting-state connectivity underlies deficient neurocognitive function in aging
描述 碩士
國立政治大學
應用物理研究所
103755003
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0103755003
資料類型 thesis
dc.contributor.advisor 蕭又新zh_TW
dc.contributor.advisor Shiau, Yuo Hsienen_US
dc.contributor.author (Authors) 林俊鴻zh_TW
dc.contributor.author (Authors) Lin, Jun Hongen_US
dc.creator (作者) 林俊鴻zh_TW
dc.creator (作者) Lin, Jun Hongen_US
dc.date (日期) 2016en_US
dc.date.accessioned 14-Nov-2016 16:15:24 (UTC+8)-
dc.date.available 14-Nov-2016 16:15:24 (UTC+8)-
dc.date.issued (上傳時間) 14-Nov-2016 16:15:24 (UTC+8)-
dc.identifier (Other Identifiers) G0103755003en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/103992-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 應用物理研究所zh_TW
dc.description (描述) 103755003zh_TW
dc.description.abstract (摘要) 近年來，功能性磁振造影技術發展迅速，使得大腦神經活動關聯性在腦神經科學中逐漸發展成熟。同時，網路理論的發展在近代也引起關注，在生物物理中，小世界網路(Small-World Network)被廣泛運用在大腦神經網路，其群聚性高、特徵路徑短之性質與大腦各個腦區間反應及高效率傳遞資訊的特性相似。有鑑於此，本論文藉由小世界網路的特性探討大腦的老化現象。
本研究以靜息態功能性磁振造影(Resting-state fMRI)量測年輕人及老年人大腦資料，並以右側腦島(Ins.R)作為核心，建構以腦島為核心的正及負相關網路。隨後，我們觀察在小世界特性明顯下的全域網路參數(Global Network Parameters)及區域網路參數(Regional Network Parameters)之老化現象。最後，我們利用多重攻擊策略模擬網路多點受損之情況，以了解網路之脆弱性。
我們研究結果指出，以腦島建立之負相關網路的常規化特徵路徑(Normalized Characteristic Path Length)會隨年紀而減短。並在區域網路參數所選出之重要網路樞紐中發現以腦島所建構之相關網路與認知功能(Cognitive Function)及中樞自主神經系統(Central Autonomic System)具有相關，且正相關網路中左側前扣帶和旁扣帶腦回(ACIN.L)及左側緣上回(SMG.L)隨著老化有顯著差異。期望可幫助醫學上了解中樞自主系統與認知功能在老化下之狀況。		zh_TW
dc.description.tableofcontents 中文摘要 ii
Abstract iv
Chapter 1 導論 1
1.1 網路 1
1.2 腦島與老化 2
Chapter 2 方法 7
2.1 資料來源與預處理 7
2.2 腦島之相關網路的建構 10
2.2.1 皮爾森相關性矩陣(Pearson Correlational Matrix) 10
2.2.2 最小生成樹(Minimum Spanning Tree) 14
2.3 網路參數 17
2.3.1 全域網路參數 17
2.3.2 區域網路參數 20
2.4 網路樞紐之定義 22
2.5 統計方法 23
2.5.1 雙樣本平均數差異T檢定 23
Chapter 3 網路分析 24
3.1 腦島之相關網路的全域網路特性 24
3.1.1小世界網路特性與效率 24
3.1.2 老化差異 31
3.2腦島之相關網路之區域網路特性 33
3.2.1網路樞紐 33
3.2.2 老化差異 36
3.3 網路圖 38
Chapter4中樞自主神經網路的多重攻擊策略 41
4.1 負載分佈向量(Load Distribution Vector) 41
4.2 基於負載分佈的多重攻擊策略流程 44
4.2 腦島之相關網路的多重攻擊策略 45
4.2.1 攻擊結點累計圖 47
4.2.2 腦島之相關網路之多重攻擊效率分析 49
Chapter5結論與討論 52
5.1腦島相關網路的小世界特性 52
5.2 腦島相關網路的常規化特徵路徑與老化的關聯 53
5.3 腦島相關網路的最小生成樹及區域網路特性與老化的關聯 54
5.4腦島之相關網路的多重攻擊策略 61
參考文獻 64		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0103755003en_US
dc.subject (關鍵詞) 小世界網路zh_TW
dc.subject (關鍵詞) 中樞自主神經系統zh_TW
dc.subject (關鍵詞) 認知功能zh_TW
dc.subject (關鍵詞) 多重攻擊策略zh_TW
dc.title (題名) 腦島的功能性連結之年紀差異：基於小世界網路下的探討zh_TW
dc.title (題名) Age-related differences on the functional connectivity of insular cortex: An approach based upon small-world theoryen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 參考文獻
[1]Re´ka Albert* and Albert-La´ szlo´ Baraba´ si,2002,.Statistical mechanics of complex networks
[2]Erdős, P., and A. Rényi. "On the evolution of random graphs." Selected Papers of Alfréd Rényi, vol 2 (1976): 482-525.
[3] Duncan J. Watts & Steven H. Strogatz 1998. Collective dynamics of ‘small-world’ networks. Nature 393, 440–442.

[4]Critchley, H.D., Harrison, N.A., 2013. Visceral influences on brain and behavior. Neuron 77, 624-638.
[5]Roser Sala-Llonch a,b, Carme Junqué a,b, Eider M. Arenaza-Urquijo a, Dídac Vidal-Piñeiro a,Cinta Valls-Pedret c, Eva M. Palacios a, Sara Domènech d, Antoni Salvà d, Nuria Bargalló e,David Bartrés-Faz a,b,2014,.Changes in whole-brain functional networks and memory performance in aging
[6]Song, X.-W., Dong, Z.-Y., Long, X.-Y., Li, S.-F., Zuo, X.-N., Zhu, C.-Z., He, Y., Yan, C.-G., Zang, Y.-F. 2011. REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PloS one 6(9), e25031.
[7]Chao-Gan, Y., Yu-Feng, Z. 2010. DPARSF: a MATLAB toolbox for “pipeline” data analysis of resting-state fMRI. Frontiers in systems neuroscience 4.
[8]Fox, M.D., Snyder, A.Z., Vincent, J.L., Corbetta, M., Van Essen, D.C., Raichle,M.E.2005. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences of the United States of America 102(27), 9673-8.
[9]Biswal, B., Zerrin Yetkin, F., Haughton, V.M., Hyde, J.S. 1995. Functional connectivity in the motor cortex of resting human brain using echo‐planar mri. Magnetic resonance in medicine 34(4), 537-41.
[10]Beissner, F., Meissner, K., Bär, K.-J., Napadow, V. 2013. The autonomic brain: an activation likelihood estimation meta-analysis for central processing of autonomic function. The Journal of Neuroscience 33(25), 10503-11.
[11]Lixia Tian, Jinhui Wang, Chaogan Yan, Yong He .,2010 .Hemisphere- and gender-related differences in small-world brain networks: A resting-state functional MRI study
[12]Rajesh Kumar,2015,. Reduced Regional Brain Cortical Thickness in Patients with Heart Failure
[13]Yihai Zhu, Yan (Lindsay) Sun2012 ,,Load Distribution Vector Based Attack Strategies against Power Grid Systems
[14]M. E. J. Newman,2004, “Scientific collaboration networks. II. shortest paths, weighted networks, and centrality,” Phys. Rev. E., vol. 64, 016132]
[15]Xiaoxi He,2013,.Age-related decrease in functional connectivity of the right fronto-insular cortex with the central executive and default-mode networks in adults from young to middle age
[16]Francis L. Stevens, Ph.D., Robin A. Hurley, M.D., Katherine H. Taber, Ph.D.,2011,.Anterior Cingulate Cortex: Unique Role in Cognition and Emotion
[17]Cornelia Stoeckel1, Patricia M. Gough2,3, Kate E. Watkins1,2, and Joseph T.Devlin4,2009,Supramarginal gyrus involvement in visual word recognition
[18]Tononi, G., Sporns, O., Edelman, G.M., 1994. A measure for brain complexity: relating functional segregation and integration in the nervous system. Proc. Natl Acad. Sci. USA 91, 5033–5037.

[19]Elizabeth A Phelps2004,.Human emotion and memory: interactions of the amygdala and hippocampal complex
[20]Adam Hampshire, Samuel R. Chamberlain, Martin M. Monti , John Duncan , Adrian M. Owen 2010,.The role of the right inferior frontal gyrus: inhibition and attentional control
[21]Amanda V. Utevsky,1,2 David V. Smith,3 and Scott A. Huettel1,2 ,.2014,Precuneus Is a Functional Core of the Default-Mode Network
[22] Grady, C., Springer, M., Hongwanishkul, D., McIntosh, A., Winocur, G., 2006. Age-related changes in brain activity across the adult lifespan. Journal of Cognitive Neuroscience 18, 227-241.
[23]Hotta, H., Uchida, S., 2010. Aging of the autonomic nervous system and possible improvements in autonomic activity using somatic afferent stimulation. Geriatrics & gerontology international 10, S127-S136.
[24]Kelly, A.C., Uddin, L.Q., Biswal, B.B., Castellanos, F.X., Milham, M.P., 2008. Competition between functional brain networks mediates behavioral variability. Neuroimage 39, 527-537.
[25]Lowe, M., Mock, B., Sorenson, J. 1998. Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations. Neuroimage 7(2), 119-32.
[26]Alireza Salami,Sara Pudas, Lars Nyberg,.2014,.Elevated hippocampal resting-state connectivity underlies deficient neurocognitive function in aging		zh_TW