參考文獻 |
〔1〕 吳孟潔, 腦中風怎麼復健?如何快速辨別腦中風,後遺症與復健歷程, 2019, https://drbao.org/stroke3/
〔2〕 朱芷君, 6觀念,中風復健不再難, 康健雜誌 第187期, 2014,https://www.commonhealth.com.tw/article/article.action?nid=68459
〔3〕 魏大森, 腦中風患者的復健治療, 2010, https://www1.cch.org.tw/knowledge/knowledge_1_1_det ail.aspx?oid=785&no=1&pID=57&sNO=145
〔4〕 Quinn TJ, Dawson J, Walters M . "Dr John Rankin; his life, legacy, and the 50th anniversary of the Rankin Stroke Scale". Scott Med J. 53 (1): 44–7, 2008
〔5〕 Farrell B, Godwin J, Richards S, Warlow C, et al. European ". J Neurol Neurosurg Psychiatry. 54 (12): 1044–1054, 1991
〔6〕 Pang, M.Y., J.E. Harris, and J.J. Eng, A community-based upper-extremity group exercise program improves motor function and performance of functional activities in chronic stroke: a randomized controlled trial. Arch Phys Med Rehabil. 87(1): 1-9,2006
〔7〕 Ogawa, S., Lee, T.M., Nayak, A.S., and Glynn, P. Oxygenation-sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields. Magn Reson Med 14, 68-78,1990
〔8〕 Rorden, C., & Brett, M. Stereotaxic Display of Brain Lesions. Behavioural Neurology, 12(4), 191–200, 2000
〔9〕 Chao-Gan, Y. and Z. Yu-Feng, DPARSF: A MATLAB Toolbox for "Pipeline" Data Analysis of Resting-State fMRI. Front Syst Neurosci. 4: p. 13, 2010
〔10〕 William D. Penny, K.J.F., John T. Ashburner, Stefan J. Kiebel, Thomas E. Nichols, Statistical Parametric Mapping: The Analysis of Functional Brain Images. 2011: Elsevier.
〔11〕 Tzourio-Mazoyer, N., et al., Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage. 15(1): p. 273-89, 2002
〔12〕 Song, X.W., et al., REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PLoS One6(9): p. e25031, 2011.
〔13〕 Xilin Shen, et al., Using connectome-based predictive modeling to predict individual behavior from brain connectivity, Nature protocols ,vol.12(3),p.506-508,2017
〔14〕 Stephanie Fountain-Zaragoza ,et al, Connectome-based models predict attentional control in aging adults, NeuroImage,186,1-13, 2019
〔15〕 Emily S. Finn, et al., Functional connectome fingerprinting: Identifying individuals based on patterns of brain connectivity, Nat Neurosci. , 18(11): 1664–1671, 2015
〔16〕 Chunliang Feng, Connectome-based individualized prediction of loneliness, Social Cognitive and Affective Neuroscience, 353–365, 2019
〔17〕 Monlca D.Rosenberg , et al ,Connectome-based Models Predict Separable Components of Attention in Novel Individuals, Journal of Cognitive Neuroscience,2017
〔18〕 Gibbons, J.D. & Chakraborti, S. Nonparametric Statistical Inference, Springer, 2011
〔19〕 Holland, P.W. & Welsch, R.E. Robust regression using iteratively reweighted least-squares. Commun. Stat.-Theory Methods 6, 813–827, 1977
〔20〕 Sarah W. Yip, Ph.D., Connectome-Based Prediction of Cocaine Abstinence, Am J Psychiatry 176:2, 2019
〔21〕 N Ramnani, Nature Reviews Neuroscience, 7: 511-522, 2006
〔22〕 Martijn et al., European Neuropsychopharmacology, 20: 519-534, 2010
〔23〕 J. L. Rodgers and W. A. Nicewander , Thirteen ways to look at the correlation coefficient. The American Statistician, 42(1):59–66, February ,1988
〔24〕 Wikipedia, Partial correlation, https://en.wikipedia.org/wiki/Partial_correlation
〔25〕 Taghreed Al-Said et al, The Logistic Regression Models and the Accuracy Measures in Analyzing Medical Data, IJSBAR, Vol 38 No2, 2018
〔26〕 M. Xia, J. Wang, and Y. He, “BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics,” Public Library of Science, vol. 8, no. 7, p. 068910, 4 July ,2013.
〔27〕 Kwakkel G, Kollen B, Twisk J. Impact of time on improvement of outcome after stroke. Stroke. 37:2348–53 , 2006
〔28〕 Öneş K., Yalçinkaya E.Y., Toklu B.Ç., Cağlar N. Effects of age, gender, and cognitive, functional and motor status on functional outcomes of stroke rehabilitation. NeuroRehabilitation.;25:241–249. ,2009
〔29〕 Mohmoud E., Mohammed A. Saud M., Effect of risk factors on functional outcome after stroke rehabilitation. Neurosciences: Vol 11 (1): 15- 20, 2006
〔30〕 Jiang T, He Y, Zang Y, Weng X. Modulation of functional connectivity during the resting state and the motor task. Hum Brain Mapp; 22: 63–71, 2004
〔31〕 Wang, L., et al., Dynamic functional reorganization of the motor execution network after stroke. Brain. 133(Pt 4): p. 1224-38, 2010
〔32〕 王馨世, 如何維持較佳的腦力與認知功能?, 康健雜誌 2019, https://www.commonhealth.com.tw/blog/3391
〔33〕 Zhu, Y., et al., Disrupted brain connectivity networks in acute ischemic stroke patients. Brain Imaging Behav. 11(2): p. 444-453 , 2017
〔34〕 Bournonville, C., et al., Identification of a specific functional network altered in poststroke cognitive impairment. Neurology. 90(21): p. e1879-e1888 , 2018
〔35〕 Dacosta-Aguayo R, Graña M, Savio A, Fernández-Andújar M, Millán M, et al. Prognostic value of changes in resting-state functional connectivity patterns in cognitive recovery after stroke: A 3T fMRI pilot study. Human Brain Mapping 35:3819–31. ,2014
〔36〕 Greicius MD, Srivastava G, Reiss AL, Menon V. Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: evidence from functional MRI. Proc Natl Acad Sci USA101(13):4637-42, 2004
〔37〕 GAO, Siyuan, et al. Combining multiple connectomes improves predictive modeling of phenotypic measures. Neuroimage, 2019, 201: 116038.
〔38〕 Hardoon, David R.; Szedmak, Sandor; Shawe-Taylor, John. Canonical correlation analysis: An overview with application to learning methods. Neural computation, 2004, 16.12: 2639-2664.
〔39〕 Marquardt, D. W., & Snee, R. D. (1975). Ridge regression in practice. The American Statistician, 29(1), 3-20.
〔40〕 Rosenberg, M. D., Finn, E. S., Scheinost, D., Papademetris, X., Shen, X., Constable, R. T., & Chun, M. M. (2016). A neuromarker of sustained attention from whole-brain functional connectivity. Nature neuroscience, 19(1), 165-171.
〔41〕 Jang, S. H. (2010). Prediction of motor outcome for hemiparetic stroke patients using diffusion tensor imaging: a review. NeuroRehabilitation, 27(4), 367-372.
〔42〕 Kusano, Y., Seguchi, T., Horiuchi, T., Kakizawa, Y., Kobayashi, T., Tanaka, Y., ... & Hongo, K. (2009). Prediction of functional outcome in acute cerebral hemorrhage using diffusion tensor imaging at 3T: a prospective study. American Journal of Neuroradiology, 30(8), 1561-1565.
〔43〕 維基百科:額葉,取自https://zh.wikipedia.org/wiki/%E9%A1%8D%E8%91%89 |