Feature Selection and Combination of Information in the Functional Brain Connectome for Discrimination of Mild Cognitive Impairment and Analyses of Altered Brain Patterns

Frontiers in Aging Neuroscience
Xiaowen XuPeijun Wang

Abstract

Mild cognitive impairment (MCI) is often considered a critical time window for predicting early conversion to Alzheimer's disease (AD). Brain functional connectome data (i.e., functional connections, global and nodal graph metrics) based on resting-state functional magnetic resonance imaging (rs-fMRI) provides numerous information about brain networks and has been used to discriminate normal controls (NCs) from subjects with MCI. In this paper, Student's t-tests and group-least absolute shrinkage and selection operator (group-LASSO) were used to extract functional connections with significant differences and the most discriminative network nodes, respectively. Based on group-LASSO, the middle temporal, inferior temporal, lingual, posterior cingulate, and middle frontal gyri were the most predominant brain regions for nodal observation in MCI patients. Nodal graph metrics (within-module degree, participation coefficient, and degree centrality) showed the maximum discriminative ability. To effectively combine the multipattern information, we employed the multiple kernel learning support vector machine (MKL-SVM). Combined with functional connectome information, the MKL-SVM achieved a good classification performance (area under the...Continue Reading

References

Apr 6, 1999·Archives of Neurology·R C PetersenE Kokmen
Jan 21, 2004·Archives of Neurology·Michael GrundmanUNKNOWN Alzheimer's Disease Cooperative Study
Jul 13, 2004·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·M E J Newman
Aug 21, 2004·Neuroinformatics·Olaf Sporns, Jonathan D Zwi
Aug 25, 2004·Journal of Internal Medicine·R C Petersen
Aug 1, 2006·Lancet·Kaj BlennowHenrik Zetterberg
Oct 10, 2006·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·M E J Newman
Feb 6, 2007·PLoS Computational Biology·Sophie Achard, Ed Bullmore
Feb 27, 2008·Annals of Neurology·Jennifer J ManlyRichard Mayeux
Feb 5, 2009·Nature Reviews. Neuroscience·Ed Bullmore, Olaf Sporns
Oct 13, 2009·NeuroImage·Mikail Rubinov, Olaf Sporns
Dec 25, 2009·Radiology·Arun L W BokdeHarald Hampel
Feb 24, 2010·Proceedings of the National Academy of Sciences of the United States of America·Bharat B BiswalMichael P Milham
Jul 6, 2010·NeuroImage·Andrew ZaleskyEdward T Bullmore
Jan 22, 2011·Annals of the New York Academy of Sciences·Olaf Sporns
Oct 5, 2011·Cerebral Cortex·Xi-Nian ZuoMichael P Milham
Nov 22, 2011·Neuron·Jonathan D PowerSteven E Petersen
Dec 15, 2011·Journal of Clinical and Experimental Neuropsychology·María QuintanaUNKNOWN Neuronorma Study Team
Mar 8, 2013·Brain Structure & Function·Chong-Yaw WeeDinggang Shen
Aug 26, 2014·Frontiers in Aging Neuroscience·Heung-Ii SukUNKNOWN Alzheimers Disease Neuroimaging Initiative
Sep 30, 2014·Neurobiology of Aging·Gautam PrasadUNKNOWN Alzheimer's Disease Neuroimaging Initiative (ADNI)
May 16, 2015·Handbook of Experimental Pharmacology·John Talpos, Mohammed Shoaib
Jul 16, 2015·Frontiers in Human Neuroscience·Jinhui WangYong He
Dec 15, 2015·Journal of Cerebral Blood Flow and Metabolism : Official Journal of the International Society of Cerebral Blood Flow and Metabolism·Ting-Yu ChangHo-Ling Liu
Feb 4, 2016·Alzheimer Disease and Associated Disorders·Eek-Sung LeeUNKNOWN Alzheimer’s Disease Neuroimaging Initiative
Jun 28, 2016·Behavioural Brain Research·Ali KhazaeeUNKNOWN Alzheimer’s Disease Neuroimaging Initiative
Aug 4, 2016·NeuroImage·Lishan QiaoDinggang Shen
Nov 5, 2016·NeuroImage. Clinical·Djalel-Eddine MeskaldjiDimitri Van De Ville
Apr 9, 2017·Neuroscience and Biobehavioral Reviews·Xuhong LiaoYong He
Apr 14, 2017·The Neuroscientist : a Review Journal Bringing Neurobiology, Neurology and Psychiatry·Jon delEtoile, Hojjat Adeli
Jun 10, 2017·Journal of Alzheimer's Disease : JAD·Kim N H DillenGereon R Fink
Jun 28, 2017·Journal of Cognitive Neuroscience·Camarin E RolleAdam Gazzaley
Sep 16, 2017·Computational Intelligence and Neuroscience·Wenjia NiuJianchuan Bai
Oct 24, 2017·Frontiers in Aging Neuroscience·Alessia SaricaAldo Quattrone
May 11, 2018·Molecular Psychiatry·Massimo FilippiFederica Agosta
Dec 2, 2018·Frontiers in Neurology·Charalambos ThemistocleousDimitrios Kokkinakis
Dec 16, 2018·Neurobiology of Aging·Zhengjia DaiHuali Wang

❮ Previous
Next ❯

Citations

Oct 27, 2020·Frontiers in Neuroscience·Lulu ZhangUNKNOWN Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Dec 8, 2020·Frontiers in Neuroscience·Guokai ZhangWenliang Che

❮ Previous
Next ❯

Software Mentioned

SLEP
MKL
Data Processing Assistant for Resting - State fMRI ( DPARSF )
Statistical Parametric Mapping ( SPM8
MATLAB
group
LASSO
BrainNet Viewer
Graph Theoretical Network Analysis Toolbox ( GRETNA )
LOOCV

Related Concepts

Related Feeds

Alzheimer's Disease: Neuroimaging

Neuroimaging can help identify pathological hallmarks of Alzheimer's disease (AD). Here is the latest research on neuroimaging modalities, including magnetic resonance imaging and positron emission tomography, in AD.

Related Papers

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Nina ChengBaiying Lei
Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Min WangJiehui Jiang
© 2021 Meta ULC. All rights reserved