Document Detail


Fine-granularity functional interaction signatures for characterization of brain conditions.
MedLine Citation:
PMID:  23319242     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity sub-network scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rs-fMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures.
Authors:
Xintao Hu; Dajiang Zhu; Peili Lv; Kaiming Li; Junwei Han; Lihong Wang; Dinggang Shen; Lei Guo; Tianming Liu
Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  Neuroinformatics     Volume:  11     ISSN:  1559-0089     ISO Abbreviation:  Neuroinformatics     Publication Date:  2013 Jul 
Date Detail:
Created Date:  2013-07-25     Completed Date:  2014-02-27     Revised Date:  2014-07-01    
Medline Journal Info:
Nlm Unique ID:  101142069     Medline TA:  Neuroinformatics     Country:  United States    
Other Details:
Languages:  eng     Pagination:  301-17     Citation Subset:  IM    
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Aged
Aged, 80 and over
Brain / blood supply*,  pathology
Brain Mapping*
Diffusion Magnetic Resonance Imaging
Humans
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Mild Cognitive Impairment / pathology*
Nerve Net / blood supply,  pathology*
Neural Pathways / physiology*
Oxygen / blood
Schizophrenia / pathology*
Grant Support
ID/Acronym/Agency:
AG041721/AG/NIA NIH HHS; EB008374/EB/NIBIB NIH HHS; EB009634/EB/NIBIB NIH HHS; K01 EB006878/EB/NIBIB NIH HHS; K23 AG028982/AG/NIA NIH HHS; K23 AG028982/AG/NIA NIH HHS; R01 AG041721/AG/NIA NIH HHS; R01 AG042599/AG/NIA NIH HHS; R01 DA033393/DA/NIDA NIH HHS; R01 DA033393/DA/NIDA NIH HHS; R01 EB006733/EB/NIBIB NIH HHS; R01 EB006733/EB/NIBIB NIH HHS; R01 EB008374/EB/NIBIB NIH HHS; R01 EB009634/EB/NIBIB NIH HHS; R01 HL087923-03S2/HL/NHLBI NIH HHS
Chemical
Reg. No./Substance:
S88TT14065/Oxygen
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  A graphics processing unit accelerated motion correction algorithm and modular system for real-time ...
Next Document:  Dysphagia after definitive radiotherapy for head and neck cancer : Correlation of dose-volume parame...