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Evaluation of Default Mode Network In Mild Cognitive Impairment and Alzheimer's Disease Individuals
Hichem Metmer, QingHua Zhao, Chong Ji, Junwei Xiao, Jianfeng Lu
Pages - 1 - 12     |    Revised - 31-12-2016     |    Published - 31-01-2017
Volume - 11   Issue - 1    |    Publication Date - February 2017  Table of Contents
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KEYWORDS
Alzheimer's Disease, Mild Cognitive Impairment, Functional Magnetic Resonance Imaging, Independent Component Analysis, Default Mode Network.
ABSTRACT
Although progressive functional brain network disorders has been one of the indication of Alzheimer's disease, The current research on aging and dementia focus on diagnostics of the cognitive changes of normal aging and Alzheimer Disease (AD), these changes known as Mild Cognitive Impairment (MCI). The default mode network (DMN) is a network of interacting brain regions known to have activity highly correlated with each other and distinct from other networks in the brain, the default mode network is active during passive rest and consists of a set of brain areas that are tightly functionally connected and distinct from other systems within the brain. Anatomically, the DMN includes the posterior cingulated cortex (PCC), dorsal and ventral medial prefrontal cortex, the lateral parietal cortex, and the medial temporal lobes. DMN involves multiple anatomical networks that converge on cortical hubs, such as the PCC, ventral medial prefrontal, and inferior parietal cortices. The aim of this study was to evaluate the default mode network functional connectivity in MCI patients. While no treatments are recommended for MCI currently, Mild Cognitive Impairment is becoming a very important subject for researchers and deserves more recognition and further study, In order to increase the ability to recognize earlier symptoms of Alzheimer's disease.
1 Google Scholar 
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Bookheimer SY, Strojwas MH, Cohen MS, Saunders AM, Pericak-Vance MA, Mazziotta JC, Small GW. 2000. Patterns of brain activation in people at risk for Alzheimer's disease. New England Journal of Medicine 343:450-456 DOI 10.1056/NEJM200008173430701.
Bradford C. Dickerson, Reisa A. Sperling, Large-scale functional brain network abnormalities in Alzheimer's disease:Insights from functional neuroimaging, 2009, 5, Behavioural Neurology 21 (2009) 63-75 63, DOI 10.3233/BEN-2009-0227. IOS Press.
Broyd SJ, Demanuele C, Debener S, Helps SK, James CJ, Sonuga-Barke EJ. 2009. Default-mode brain dysfunction in mental disorders: a systematic review. Neuroscience and Biobehavioral Reviews 33:279-296 DOI 10.1016/j.neubiorev.2008.09.002.
De Luca M, Beckmann CF, De Stefano N, Matthews PM, Smith SM (2006) NeuroImage 29:1359-1367.
De Luca M, Beckmann CF, De Stefano N, Matthews PM, Smith SM (2006) NeuroImage 29:1359-1367.
De Martino F, Gentile F, Esposito F, Balsi M, Di Salle F, Goebel R, Formisano E. 2007. Classification of fMRI independent components using IC-fingerprints and support vector machine classifiers. Neuroimage 34(1):177-194DOI .1016/j.neuroimage.2006.08.041.
Dickerson BC, Salat DH, Greve DN, Chua EF, Rand-Giovannetti E, Rentz DM, Bertram L, Mullin K, Tanzi RE, Blacker D, et al. (2005) Neurology 65:404- Martin R. Farlow, Sujuan Gao, Tamiko R. MaGee, Brenna C. McDonald, Darren P. O'Neill, Shannon L. Risacher, Andrew J. Saykin, Yang Wang, John D. West, Journal of Alzheimer's disease.
Eun Hyun Seo, Dong Young Lee, Jong-Min Lee, Jun-Sung Park, Bo Kyung Sohn, Dong Soo Lee, Young Min Choe, Jong Inn Woo, Whole-brain Functional Networks in Cognitively Normal, Mild Cognitive Impairment and Alzheimer's Disease20134-10, 8(1)e53922, Doi:10.1371/journal.pone.0053922.
Jack CR Jr, Petersen RC, Xu YC et al. Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment. Neurology 1999; 52: 1397-403.
Jianchao Yang, Jiangping Wang, and Thomas Huang, LEARNING THE SPARSE REPRESENTATION FOR CLASSIFICATION, 4.
Jose Angel Pineda-Pardo, Pilar Garces, Maria Eugenia Lopez, Sara Aurtenetxe, Pablo Cuesta, Alberto Marcos, Pedro Montejo, Miguel Yus, Juan Antonio Hernandez-Tamames, Francisco del Pozo, James T. Becker, and Fernando Maestu. White Matter Damage Disorgani.
Julien Mairal, Francis Bach, Jean Ponce, and Guillermo Sapiro, "Online learning for matrix factorization and sparse coding," Journal of Machine Learning Research, vol. 11, pp. 19-60, 2010.
Korf ES, Wahlund LO, Visser PJ, Scheltens P. Medial temporal lobe atrophy on MRI predicts dementia in patients with mild cognitive impairment. Neurology. 2004;63:94-100.
Laia Farràs-Permanyer, Guàrdia-Olmosand, Maribel Peró-Cebollero, Mild cognitive impairment and fMRI studies of brain functional connectivity: the state of the art, 2015, 3-7, doi: 3389/fpsyg.2015.01095.
Larrieu S, Letenneur L, Orgogozo JM, et al. Incidence and outcome of mild cognitive impairment in a population-based prospective cohort. Neurology. 2002;59:1594-1599.
Morris JC, Heyman A, Mohs RC, Hughes JP, van Belle G, Fillenbaum G, Mellits ED, Clark C (1989) Neurology 39:1159-1165.
Morris JC, Storandt M, Miller JP, et al. Mild cognitive impairment represents early-stage Alzheimer's disease. Arch Neurol 2000; 58: 397-405.
Morris, J. C. (1993) Neurology 43, 2412-2414.11
Petersen RC, ed. Mild Cognitive Impairment: Aging to Alzheimer's disease. New York, NY: Oxford University Press.
Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: clinical characterization and outcome. Arch Neurol. 1999;56:303-308.
RC.PE TERSEN, Mild cognitive impairment as a diagnostic entity, 2004, 2-3, 2004 Blackwell.
Roberto Esposito, Alessandra Mosca, Valentina Pieramico, Filippo Cieri, Nicoletta Cera and Stefano L. Sensi, Characterization of resting state activity in MCI individuals. 2013, 3-4, DOI 10.7717/peerj.135
Rombouts SA, Barkhof F, Goekoop R, Stam CJ, Scheltens P (2005)Hum Brain Mapp 26:231-239.
Ronald C. Petersen, PhD, MD; John C. Morris, MD, Mild Cognitive Impairment as a Clinical Entity and Treatment Target, 200, 2, ARCH NEUROL/VOL 62, JULY 2005, The American Medical Association.
S.S. Bassett, D.M. Yousem, C. Cristinzio, I. Kusevic, M.A. Yassa, B.S. Caffo and S.L. Zeger, Familial risk for Alzheimer's disease alters fMRI activation patterns, Brain 129 (2006), 1229-1239.
Staffen, W., Ladurner, G., Höller, Y., Bergmann, J., Aichhorn, M., Golaszewski, S., et al. (2012). Brain activation disturbance for target detection in patients with mild cognitive impairment: an fMRI study. Neurobiol. Aging 33, 1002, e1-e16. doi: 10.1016/j.neurobiolaging.2011.09.002.
The Alzheimer's disease Neuroimaging Initiative: A review of papers published since its inception, 2013, 47-50, Alzheimer's Dement. 2013 September; 9(5):e111-e194.Doi:10.1016/j.
Wang, Y., Risacher, S. L., West, J. D., McDonald, B. C., Magee, T. R., Farlow, M. R., et al. (2013). Altered default mode network connectivity in older adults with cognitive complaints and amnestic mild cognitive impairment. J. Alzheimers Dis. 35, 751-760, doi: 10.3233/JAD-130080.
Mr. Hichem Metmer
NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY - China
hichemmetmer@qq.com
Mr. QingHua Zhao
School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing, 210094, Republic of China - China
Mr. Chong Ji
School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing, 210094, Republic of China - China
Dr. Junwei Xiao
School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing, 210094, Republic of China - China
Professor Jianfeng Lu
NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY - China