NDLI: Resting-State Multi-Spectrum Functional Connectivity Networks for Identification of MCI Patients

Content Provider	PubMed Central
Author	Wee, Chong-yaw Yap, Pew-thian Denny, Kevin Browndyke, Jeffrey N. Potter, Guy G. Welsh-bohmer, Kathleen A. Wang, Lihong Shen, Dinggang
Editor	He, Yong
Copyright Year	2012
Abstract	In this paper, a high-dimensional pattern classification framework, based on functional associations between brain regions during resting-state, is proposed to accurately identify MCI individuals from subjects who experience normal aging. The proposed technique employs multi-spectrum networks to characterize the complex yet subtle blood oxygenation level dependent (BOLD) signal changes caused by pathological attacks. The utilization of multi-spectrum networks in identifying MCI individuals is motivated by the inherent frequency-specific properties of BOLD spectrum. It is believed that frequency specific information extracted from different spectra may delineate the complex yet subtle variations of BOLD signals more effectively. In the proposed technique, regional mean time series of each region-of-interest (ROI) is band-pass filtered ( Hz) before it is decomposed into five frequency sub-bands. Five connectivity networks are constructed, one from each frequency sub-band. Clustering coefficient of each ROI in relation to the other ROIs are extracted as features for classification. Classification accuracy was evaluated via leave-one-out cross-validation to ensure generalization of performance. The classification accuracy obtained by this approach is 86.5%, which is an increase of at least 18.9% from the conventional full-spectrum methods. A cross-validation estimation of the generalization performance shows an area of 0.863 under the receiver operating characteristic (ROC) curve, indicating good diagnostic power. It was also found that, based on the selected features, portions of the prefrontal cortex, orbitofrontal cortex, temporal lobe, and parietal lobe regions provided the most discriminant information for classification, in line with results reported in previous studies. Analysis on individual frequency sub-bands demonstrated that different sub-bands contribute differently to classification, providing extra evidence regarding frequency-specific distribution of BOLD signals. Our MCI classification framework, which allows accurate early detection of functional brain abnormalities, makes an important positive contribution to the treatment management of potential AD patients.
Related Links	http://dx.doi.org/10.1371/journal.pone.0037828
Starting Page	37828
File Format	PDF
ISSN	19326203
e-ISSN	19326203
Journal	PLoS ONE
Issue Number	5
Volume Number	7
Language	English
Publisher	Public Library of Science
Publisher Date	2012-05-01
Access Restriction	Open
Rights Holder	Public Library of Science
Subject Keyword	Biochemistry, Genetics and Molecular Biology(all) Agricultural and Biological Sciences(all) Medicine(all) Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Altered Causal Connectivity of Resting State Brain Networks in Amnesic MCI

Resting State Functional Connectivity in Patients with Chronic Hallucinations

Resting State Functional Connectivity in Perfusion Imaging: Correlation Maps with BOLD Connectivity and Resting State Perfusion

Functional Connectivity Alterations in Epilepsy from Resting-State Functional MRI

Modulatory Interactions of Resting-State Brain Functional Connectivity

Resting-State Functional Connectivity between Fronto-Parietal and Default Mode Networks in Obsessive-Compulsive Disorder

Resting-State Functional Connectivity Patterns Predict Chinese Word Reading Competency

Acupuncture Modulates Resting State Hippocampal Functional Connectivity in Alzheimer Disease

Altered Functional Connectivity in Patients with Subcortical Vascular Cognitive Impairment—A Resting-State Functional Magnetic Resonance Imaging Study

Resting-State Multi-Spectrum Functional Connectivity Networks for Identification of MCI Patients

Similar Documents

Altered Causal Connectivity of Resting State Brain Networks in Amnesic MCI

Resting State Functional Connectivity in Patients with Chronic Hallucinations

Resting State Functional Connectivity in Perfusion Imaging: Correlation Maps with BOLD Connectivity and Resting State Perfusion

Functional Connectivity Alterations in Epilepsy from Resting-State Functional MRI

Modulatory Interactions of Resting-State Brain Functional Connectivity

Resting-State Functional Connectivity between Fronto-Parietal and Default Mode Networks in Obsessive-Compulsive Disorder

Resting-State Functional Connectivity Patterns Predict Chinese Word Reading Competency

Acupuncture Modulates Resting State Hippocampal Functional Connectivity in Alzheimer Disease

Altered Functional Connectivity in Patients with Subcortical Vascular Cognitive Impairment—A Resting-State Functional Magnetic Resonance Imaging Study

Resting-State Multi-Spectrum Functional Connectivity Networks for Identification of MCI Patients