臺灣博碩士論文加值系統

小腦在人類腦功能中扮演著重要的角色。除了傳統熟知的運動功能調節、平衡與學習複雜的連續動作。同時，小腦也牽涉在許多高階認知與情緒功能之中，像是語言能力、視覺空間處理、情緒調控等。因此，當小腦因疾病的發生而造成損害時，往往會導致步態、四肢或是眼球的運動失調與障礙，也更進一步的造成所謂的小腦認知與情緒症候群（cerebellar cognitive affective syndrome）。小腦型別多系統萎縮症（Multiple system atrophy of the cerebellar type ，MSA-C）是一種神經退化性疾病，伴隨著明顯的橋腦與小腦白質萎縮。在本論文中，我們邀請了18位MSA-C病患與19位年齡與性別相仿的健康受測者，收集其磁振T1權重影像（T1-weighted images）與擴散張量影像（diffusion tensor images），來探討橋腦與小腦白質萎縮所導致的局部結構與全腦功能的改變。
本論文旨在透過MSA-C疾病，來討論小腦在腦部結構與功能中所扮演的角色。我們將觀察橋腦與小腦白質萎縮存在的情況下，局部型態與全腦結構網路是如何被改變，包含：
1）小腦與大腦在白質體積與型態上的改變；
2）局部白質完整性的變異，以及全腦神經追蹤的變化；
3）小世界網路結構（small-world architecture）的改變，以及局部網路拓譜參數（topological properties）的變化；
4）結構網路連結的模組結構（modular stucture）變異。
同時透過局部結構與形態學的量測，以及從全腦的網路架構、模組結構改變，來探討橋腦與小腦白質萎縮所造成的影響，能讓我們更為完整的了解小腦的結構與功能，以及其在全腦結構網路中所扮演的角色。
本論文的結果呈現出，橋腦與小腦白質萎縮破壞了小腦與大腦間連結的迴路（cerebello-ponto-cerebral loops）。進而導致全腦網路中，各腦區間訊息傳遞與交換的效率下降。同時在小腦中，白質與灰質的交界面（inner cortical surface）也呈現出腦渠（sulci）的表面積有隨著橋腦與小腦白質體積線性下降的趨勢。特別是在小腦的下後頁（infero-posterior lobe）有相較於小腦蚓部（vermis）更為快速的萎縮速率，隱含著小腦受損所導致的運動障礙與認知情緒功能受損，可能呈現不一樣的模式。
我們總結，從MSA-C所引發的橋腦與小腦白質萎縮，會導致局部表面構造與全腦結構網路效能瓦解。由此可知，橋腦與小腦白質的完整性，可能藉由神經纖維束的張力來維持皮質表面皺褶的型態；而橋腦與小腦白質的完整性，也反映出完整的神經纖維網路，包含充足的神經纖維數量與其訊號傳導能力，藉以確保全腦結構網路的訊息傳遞效能。

The cerebellum involves diverse functions from motor coordination to higher cognitive functions. Impairment of the cerebellum can cause ataxia and cerebellar cognitive affective syndrome. Multiple system atrophy of the cerebellar type (MSA-C) is a neurodegenerative disorder with atrophy of pontocerebellar white matter (WM). We acquired T1-weighted and diffusion tensor images for 18 patients with MSA-C and 19 normal controls.
This thesis explores the role of cerebellum in the presence of the pontocerebellar WM atrophy from the perspective of local structures to global functions, including
1) the volumetric and morphological changes of the white matter in cerebellum and cerebrum;
2) the destruction of local WM integrity and whole-brain fiber tracking;
3) the alteration of the global small-world architecture and regionally topological properties;
4) the variation in modular structure of the structural connectivity.
The concurrent use of the measures of local morphology and properties of global network based on graph theory and modular organization for both MSA-C and healthy groups can offer a more complete view to understand the structure and function of cerebellum.
The results showed that pontocerebellar WM degeneration caused the destruction of cerebello-ponto-cerebral loops, resulting in reduced communication efficiency between regions in the whole-brain network. In addition, the sulcal area of the inner cortical surface in the cerebellum decreased linearly with the pontocerebellar WM volume, and the inferoposterior lobe exhibited a steeper atrophy rate than that of vermis regions. We concluded that the integrity of pontocerebellar WM is critical in sustaining the local morphology and the global functions of the whole-brain fiber network.

致 謝 I
摘 要 III
Abstract V
Content VII
List of Figures IX
List of Tables XI
Chapter 1 Introduction 1
1.1 Background and Motivation 1
1.2 The Structure and Function of Cerebellum 3
1.3 The Tension-based Theory of Morphogenesis in Brain 4
1.4 Small-world Architecture and Brain Structure Network 5
1.5 Multiple System Atrophy of the Cerebellar Type 7
1.6 Dissertation Purposes and Contributions 8
Chapter 2 Material and Methods 10
2.1 Demography of Participants 10
2.2 Image Acquisition 11
2.3 Image Preprocessing 11
2.3.1 Image normalization 11
2.3.2 Image segmentation and WM volume estimation 13
2.4 Surface Morphology 13
2.5 Construction of Brain Network 15
2.6 Small-world Properties Based on Graph Theory 16
2.6.1 Small-worldness and global network properties 16
2.6.2 Topological properties of each node 17
2.7 Modular Structure Analysis 18
2.7.1 Hierarchical modularity 18
2.7.2 Node roles 19
2.7.2 The similarity between two modular partitions 21
2.7.3 Hierarchical clustering 22
2.8 Statistical Analysis 23
Chapter 3 Results 25
3.1 The pontocerebellar WM images for NC and MSA-C 25
3.2 The pontocerebellar WM volume decreased as the MSA-C progressed 26
3.3 Area of pontocerebellar sulci reduced as the WM volume decreased 27
3.4 The cerebellar-ponto-cerebral fiber tracts were disrupted for MSA-C patients 29
3.5 Small-worldness of WM networks 31
3.6 Significantly decreased network efficiency in MSA-C, particularly in the cerebellum 31
3.7 Decreased pontocerebellar WM volume reduced the whole-brain network efficiency 32
3.8 Alteration of nodal characteristics in MSA-C from the cerebellum to whole brain 33
3.9 Network properties correlation with the SARA scores of MSA-C 37
3.10 The pontocerebellar sulcal area was correlated to whole-brain network properties 39
3.11 The modular structure of WM network 39
3.12 The modular structure as a feature to classify the NC and MSA-C groups 41
3.13 The alteration of node character in modular structure for MSA-C 42
Chapter 4 Discussion 44
4.1 The volumetric change of pontocerebellar WM in MSA-C 44
4.2 The surface morphology change in cerebellum for MSA-C 45
4.3 The destruction of cerebello-ponto-cerebral tract and brain network in MSA-C 46
4.4 MSA-C altered small-world architecture in WM networks 47
4.5 Nodal characteristics revealed changes in the WM network from the cerebellum to the cerebrum in MSA-C 48
4.6 Disruption of vermis-related WM was distinct from cerebellar lobules in MSA-C 49
4.7 The loss of fiber tension altered surface morphology and network organization 53
Chapter 5 Conclusions and Future Works 54
Appendix 56
References 60
List of Publications and Vitae 70

Achard S, Bullmore E (2007) Efficiency and Cost of Economical Brain Functional Networks. PLoS Comput Biol 3:e17.
Alexander-Bloch A, Lambiotte R, Roberts B, Giedd J, Gogtay N, Bullmore E (2012) The discovery of population differences in network community structure: New methods and applications to brain functional networks in schizophrenia. NeuroImage 59:3889-3900.
Apps R, Garwicz M (2005) Anatomical and physiological foundations of cerebellar information processing. Nat Rev Neurosci 6:297-311.
Armstrong RA, Cairns NJ, Lantos PL (2007) A quantitative study of the pathological changes in white matter in multiple system atrophy. Neuropathology 27:221-227.
Beg MF, Miller MI, Trouvé A, Younes L (2005) Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms. International Journal of Computer Vision 61:139-157.
Benjamini Y, Hochberg Y (1995) Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B (Methodological) 57:289-300.
Bloedel JR (1992) Functional heterogeneity with structural homogeneity: How does the cerebellum operate? Behavioral and Brain Sciences 15:666-678.
Blondel V, Guillaume J-L, Lambiotte R, Lefebvre E (2008) Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment 2008:P10008.
Brenneis C, Boesch SM, Egger KE, Seppi K, Scherfler C, Schocke M, Wenning GK, Poewe W (2006) Cortical atrophy in the cerebellar variant of multiple system atrophy: A voxel-based morphometry study. Movement Disorders 21:159-165.
Brooks DJ, Seppi K (2009) Proposed neuroimaging criteria for the diagnosis of multiple system atrophy. Movement Disorders 24:949-964.
Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10:186-198.
Chen H, Zhang T, Guo L, Li K, Yu X, Li L, Hu X, Han J, Hu X, Liu T (2012) Coevolution of Gyral Folding and Structural Connection Patterns in Primate Brains. Cerebral Cortex.
Gilman S, Wenning GK, Low PA, Brooks DJ, Mathias CJ, Trojanowski JQ, Wood NW, Colosimo C, Dürr A, Fowler CJ, Kaufmann H, Klockgether T, Lees A, Poewe W, Quinn N, Revesz T, Robertson D, Sandroni P, Seppi K, Vidailhet M (2008) Second consensus statement on the diagnosis of multiple system atrophy. Neurology 71:670-676.
Gong G, He Y, Concha L, Lebel C, Gross DW, Evans AC, Beaulieu C (2009) Mapping Anatomical Connectivity Patterns of Human Cerebral Cortex Using In Vivo Diffusion Tensor Imaging Tractography. Cerebral Cortex 19:524-536.
Guimerà R, Amaral LA (2005) Cartography of complex networks: modules and universal roles. Journal of statistical mechanics (Online) 2005:nihpa35573.
Habas C, Kamdar N, Nguyen D, Prater K, Beckmann CF, Menon V, Greicius MD (2009) Distinct Cerebellar Contributions to Intrinsic Connectivity Networks. The Journal of Neuroscience 29:8586-8594.
Habas PA, Scott JA, Roosta A, Rajagopalan V, Kim K, Rousseau F, Barkovich AJ, Glenn OA, Studholme C (2012) Early Folding Patterns and Asymmetries of the Normal Human Brain Detected from in Utero MRI. Cerebral Cortex 22:13-25.
Hagmann P, Kurant M, Gigandet X, Thiran P, Wedeen VJ, Meuli R, Thiran J-P (2007) Mapping Human Whole-Brain Structural Networks with Diffusion MRI. PLoS ONE 2:e597.
Hagmann P, Cammoun L, Gigandet X, Meuli R, Honey CJ, Wedeen VJ, Sporns O (2008) Mapping the Structural Core of Human Cerebral Cortex. PLoS Biol 6:e159.
Harris AD, Pereira RS, Mitchell JR, Hill MD, Sevick RJ, Frayne R (2004) A comparison of images generated from diffusion-weighted and diffusion-tensor imaging data in hyper-acute stroke. Journal of Magnetic Resonance Imaging 20:193-200.
Hauser T-K, Luft A, Skalej M, Nägele T, Kircher TTJ, Leube DT, Schulz JB (2006) Visualization and quantification of disease progression in multiple system atrophy. Movement Disorders 21:1674-1681.
Hilgetag CC, Barbas H (2006) Role of Mechanical Factors in the Morphology of the Primate Cerebral Cortex. PLoS Comput Biol 2:e22.
Holmes G (1939) The cerebellum of man. Brain 62:1-30.
Hu H-H, Chen H-Y, Hung C-I, Guo W-Y, Wu Y-T Shape and curvedness analysis of brain morphology using human fetal magnetic resonance images in utero. Brain Struct Funct In press.
Hu H-H, Guo W-Y, Chen H-Y, Wang P-S, Hung C-I, Hsieh J-C, Wu Y-T (2009) Morphological regionalization using fetal magnetic resonance images of normal developing brains. European Journal of Neuroscience 29:1560-1567.
Humphries MD, Gurney K (2008) Network ‘Small-World-Ness’: A Quantitative Method for Determining Canonical Network Equivalence. PLoS ONE 3:e0002051.
Inoue M, Yagishita S, Ryo M, Hasegawa K, Amano N, Matsushita M (1997) The distribution and dynamic density of oligodendroglial cytoplasmic inclusions (GCIs) in multiple system atrophy: a correlation between the density of GCIs and the degree of involvement of striatonigral and olivopontocerebellar systems. Acta Neuropathologica 93:585-591.
Ito M, Watanabe H, Kawai Y, Atsuta N, Tanaka F, Naganawa S, Fukatsu H, Sobue G (2007) Usefulness of combined fractional anisotropy and apparent diffusion coefficient values for detection of involvement in multiple system atrophy. Journal of Neurology, Neurosurgery &; Psychiatry 78:722-728.
Iturria-Medina Y, Sotero RC, Canales-Rodríguez EJ, Alemán-Gómez Y, Melie-García L (2008) Studying the human brain anatomical network via diffusion-weighted MRI and Graph Theory. NeuroImage 40:1064-1076.
Jernigan TL, Archibald SL, Fennema-Notestine C, Gamst AC, Stout JC, Bonner J, Hesselink JR (2001) Effects of age on tissues and regions of the cerebrum and cerebellum. Neurobiology of Aging 22:581-594.
Kanazawa M, Shimohata T, Terajima K, Onodera O, Tanaka K, Tsuji S, Okamoto K, Nishizawa M (2004) Quantitative evaluation of brainstem involvement in multiple system atrophy by diffusion-weighted MR imaging. Journal of Neurology 251:1121-1124.
Kawai Y, Suenaga M, Takeda A, Ito M, Watanabe H, Tanaka F, Kato K, Fukatsu H, Naganawa S, Kato T, Ito K, Sobue G (2008) Cognitive impairments in multiple system atrophy. Neurology 70:1390-1396.
Kelly RM, Strick PL (2003) Cerebellar Loops with Motor Cortex and Prefrontal Cortex of a Nonhuman Primate. The Journal of Neuroscience 23:8432-8444.
Kochunov P, Mangin J-F, Coyle T, Lancaster J, Thompson P, Rivière D, Cointepas Y, Régis J, Schlosser A, Royall DR, Zilles K, Mazziotta J, Toga A, Fox PT (2005) Age-related morphology trends of cortical sulci. Human Brain Mapping 26:210-220.
Koenderink JJ, van Doorn AJ (1992) Surface shape and curvature scales. Image and Vision Computing 10:557-564.
Latora V, Marchiori M (2001) Efficient Behavior of Small-World Networks. Physical Review Letters 87:198701.
Le Gros Clark W (1945) Deformation patterns in the cerebral cortex: Essays on growth and form. London: Oxford University Press.
Lee Y-c, Liao Y-c, Wang P-s, Lee IH, Lin K-p, Soong B-w (2011) Comparison of cerebellar ataxias: A three-year prospective longitudinal assessment. Movement Disorders 26:2081-2087.
Li K, Guo L, Li G, Nie J, Faraco C, Cui G, Zhao Q, Miller LS, Liu T (2010) Gyral folding pattern analysis via surface profiling. NeuroImage 52:1202-1214.
Li Y, Liu Y, Li J, Qin W, Li K, Yu C, Jiang T (2009) Brain Anatomical Network and Intelligence. PLoS Comput Biol 5:e1000395.
Lindblad J (2005) Surface area estimation of digitized 3D objects using weighted local configurations. Image and Vision Computing 23:111-122.
Liu Y, Liang M, Zhou Y, He Y, Hao Y, Song M, Yu C, Liu H, Liu Z, Jiang T (2008) Disrupted small-world networks in schizophrenia. Brain 131:945-961.
Lu C-F, Soong B-W, Wu H-M, Teng S, Wang P-S, Wu Y-T Disrupted Cerebellar Connectivity Reduces Whole-Brain Network Efficiency in Multiple System Atrophy. Movement Disorders In press.
Mann HB, Whitney DR (1947) On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other. Annals of Mathematical Statistics 18:50-60.
Matsuo A, Akiguchi I, Lee GC, McGeer EG, McGeer PL, Kimura J (1998) Myelin Degeneration in Multiple System Atrophy Detected by Unique Antibodies. The American Journal of Pathology 153:735-744.
Meunier D, Lambiotte R, Fornito A, Ersche K, Bullmore ET (2009) Hierarchical modularity in human brain functional networks. Frontiers in Neuroinformatics 3.
Milgram S (1967) The small world problem. Psychology today 2:60-67.
Miyatake S, Mochizuki H, Naka T, Ugawa Y, Tanabe H, Kuzume D, Suzuki M, Ogata K, Kawai M (2010) Brain volume analyses and somatosensory evoked potentials in multiple system atrophy. Journal of Neurology 257:419-425.
Mori S, Crain BJ, Chacko VP, Van Zijl PCM (1999) Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Annals of Neurology 45:265-269.
Mori S, Wakana S, Nagae-Poetscher L, Zijl Pv (2006) MRI Atlas of Human White Matter. Amsterdam: Elsevier.
Mota B, Herculano-Houzel S (2012) How the cortex gets its folds: an inside-out, connectivity-driven model for the scaling of mammalian cortical folding. Frontiers in Neuroanatomy 6.
Newman MEJ (2004) Detecting community structure in networks. Eur Phys J B 38:321-330.
Newman MEJ (2006) Modularity and community structure in networks. Proceedings of the National Academy of Sciences 103:8577-8582.
O'Reilly JX, Beckmann CF, Tomassini V, Ramnani N, Johansen-Berg H (2010) Distinct and Overlapping Functional Zones in the Cerebellum Defined by Resting State Functional Connectivity. Cerebral Cortex 20:953-965.
Ozawa T, Paviour D, Quinn NP, Josephs KA, Sangha H, Kilford L, Healy DG, Wood NW, Lees AJ, Holton JL, Revesz T (2004) The spectrum of pathological involvement of the striatonigral and olivopontocerebellar systems in multiple system atrophy: clinicopathological correlations. Brain 127:2657-2671.
Papp MI, Kahn JE, Lantos PL (1989) Glial cytoplasmic inclusions in the CNS of patients with multiple system atrophy (striatonigral degeneration, olivopontocerebellar atrophy and Shy-Drager syndrome). Journal of the neurological sciences 94:79-100.
Probst-Cousin S, Rickert CH, Schmid KW, Gullotta F (1998) Cell death mechanisms in multiple system atrophy. J Neuropathol Exp Neurol 57:814-821.
Quinn N (1989) Multiple system atrophy--the nature of the beast. Journal of Neurology, Neurosurgery &; Psychiatry 52:78-89.
Rajagopalan V, Scott J, Habas PA, Kim K, Corbett-Detig J, Rousseau F, Barkovich AJ, Glenn OA, Studholme C (2011) Local Tissue Growth Patterns Underlying Normal Fetal Human Brain Gyrification Quantified In Utero. The Journal of Neuroscience 31:2878-2887.
Ramnani N (2006) The primate cortico-cerebellar system: anatomy and function. Nature reviews Neuroscience 7:511-522.
Ramnani N, Behrens TEJ, Johansen-Berg H, Richter MC, Pinsk MA, Andersson JLR, Rudebeck P, Ciccarelli O, Richter W, Thompson AJ, Gross CG, Robson MD, Kastner S, Matthews PM (2006) The Evolution of Prefrontal Inputs to the Cortico-pontine System: Diffusion Imaging Evidence from Macaque Monkeys and Humans. Cerebral Cortex 16:811-818.
Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: Uses and interpretations. NeuroImage 52:1059-1069.
Schmahmann JD (1991) An emerging concept: The cerebellar contribution to higher function. Archives of Neurology 48:1178-1187.
Schmahmann JD (1996) From movement to thought: Anatomic substrates of the cerebellar contribution to cognitive processing. Human Brain Mapping 4:174-198.
Schmahmann JD (2000) The role of the cerebellum in affect and psychosis. Journal of Neurolinguistics 13:189-214.
Schmahmann JD (2004) Disorders of the Cerebellum: Ataxia, Dysmetria of Thought, and the Cerebellar Cognitive Affective Syndrome The Journal of Neuropsychiatry and Clinical Neurosciences 16:367-378.
Schmahmann JD, Pandya DN (1989) Anatomical investigation of projections to the basis pontis from posterior parietal association cortices in rhesus monkey. The Journal of Comparative Neurology 289:53-73.
Schmahmann JD, Sherman JC (1998) The cerebellar cognitive affective syndrome. Brain 121:561-579.
Schmitz-Hübsch T et al. (2006) Scale for the assessment and rating of ataxia. Neurology 66:1717-1720.
Shapiro SS, Wilk MB (1965) An Analysis of Variance Test for Normality (Complete Samples). Biometrika 52:591-611.
Shiga K, Yamada K, Yoshikawa K, Mizuno T, Nishimura T, Nakagawa M (2005) Local tissue anisotropy decreases in cerebellopetal fibers and pyramidal tract in multiple system atrophy. Journal of Neurology 252:589-596.
Specht K, Minnerop M, Müller-Hübenthal J, Klockgether T (2005) Voxel-based analysis of multiple-system atrophy of cerebellar type: complementary results by combining voxel-based morphometry and voxel-based relaxometry. NeuroImage 25:287-293.
Stefanova N, B?cke P, Duerr S, Wenning GK (2009) Multiple system atrophy: an update. The Lancet Neurology 8:1172-1178.
Symonds LL, Archibald SL, Grant I, Zisook S, Jernigan TL (1999) Does an increase in sulcal or ventricular fluid predict where brain tissue is lost? Journal of neuroimaging : official journal of the American Society of Neuroimaging 9:201-209.
Takahashi E, Folkerth RD, Galaburda AM, Grant PE (2012) Emerging Cerebral Connectivity in the Human Fetal Brain: An MR Tractography Study. Cerebral Cortex 22:455-464.
Taniwaki T, Nakagawa M, Yamada T, Yoshida T, Ohyagi Y, Sasaki M, Kuwabara Y, Tobimatsu S, Kira J-i (2002) Cerebral metabolic changes in early multiple system atrophy: a PET study. Journal of the neurological sciences 200:79-84.
Thirion J-P, Gourdon A (1995) Computing the Differential Characteristics of Isointensity Surfaces. Computer Vision and Image Understanding 61:190-202.
Toro R, Burnod Y (2005) A Morphogenetic Model for the Development of Cortical Convolutions. Cerebral Cortex 15:1900-1913.
Trouillas P, Takayanagi T, Hallett M, Currier RD, Subramony SH, Wessel K, Bryer A, Diener HC, Massaquoi S, Gomez CM, Coutinho P, Hamida MB, Campanella G, Filla A, Schut L, Timann D, Honnorat J, Nighoghossian N, Manyam B (1997) International Cooperative Ataxia Rating Scale for pharmacological assessment of the cerebellar syndrome. Journal of the neurological sciences 145:205-211.
Tu P-h, Galvin JE, Baba M, Giasson B, Tomita T, Leight S, Nakajo S, Iwatsubo T, Trojanowski JQ, Lee VMY (1998) Glial cytoplasmic inclusions in white matter oligodendrocytes of multiple system atrophy brains contain insoluble α-synuclein. Annals of Neurology 44:415-422.
Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, Mazoyer B, Joliot M (2002) Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain. NeuroImage 15:273-289.
Van Essen DC (1997) A tension-based theory of morphogenesis and compact wiring in the central nervous system. Nature 385:313-318.
Voogd J, Glickstein M (1998) The anatomy of the cerebellum. Trends in cognitive sciences 2:307-313.
Wakabayashi K, Takahashi H (2006) Cellular pathology in multiple system atrophy. Neuropathology 26:338-345.
Wakabayashi K, Mori F, Nishie M, Oyama Y, Kurihara A, Yoshimoto M, Kuroda N (2005) An autopsy case of early (“minimal change”) olivopontocerebellar atrophy (multiple system atrophy-cerebellar). Acta Neuropathologica 110:185-190.
Watts DJ, Strogatz SH (1998) Collective dynamics of 'small-world' networks. Nature 393:440-442.
Wedeen VJ, Wang RP, Schmahmann JD, Benner T, Tseng WYI, Dai G, Pandya DN, Hagmann P, D'Arceuil H, de Crespigny AJ (2008) Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers. NeuroImage 41:1267-1277.
Wenning GK, Colosimo C, Geser F, Poewe W (2004) Multiple system atrophy. The Lancet Neurology 3:93-103.
Wishart D (1969) An Algorithm for Hierarchical Classifications. Biometrics 25:165-170.
Woods RP, Grafton ST, Holmes CJ, Cherry SR, Mazziotta JC (1998) Automated Image Registration: I. General Methods and Intrasubject, Intramodality Validation. Journal of Computer Assisted Tomography 22:139-152.
Wu Y-T, Shyu K-K, Jao C-W, Wang Z-Y, Soong B-W, Wu H-M, Wang P-S (2010) Fractal dimension analysis for quantifying cerebellar morphological change of multiple system atrophy of the cerebellar type (MSA-C). NeuroImage 49:539-551.
Wu Y-T, Shyu K-K, Jao C-W, Liao Y-L, Wang T-Y, Wu H-M, Wang P-S, Soong B-W (2012) Quantifying cerebellar atrophy in multiple system atrophy of the cerebellar type (MSA-C) using three-dimensional gyrification index analysis. NeuroImage 61:1-9.
Yan C, Gong G, Wang J, Wang D, Liu D, Zhu C, Chen ZJ, Evans A, Zang Y, He Y (2011) Sex- and Brain Size–Related Small-World Structural Cortical Networks in Young Adults: A DTI Tractography Study. Cerebral Cortex 21:449-458.