Title
Fine-granularity functional interaction signatures for characterization of brain conditions.
Abstract
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.
Year
DOI
Venue
2013
10.1007/s12021-013-9177-2
Neuroinformatics
Keywords
Field
DocType
fine granularity,mci,rs-fmri,sz,dti,functional interaction,brain mapping,oxygen,schizophrenia,magnetic resonance imaging
Brain mapping,Population,Neuroscience,Diffusion MRI,Functional magnetic resonance imaging,Computer science,Nerve net,Human brain,Granularity,Magnetic resonance imaging
Journal
Volume
Issue
ISSN
11
3
1559-0089
Citations 
PageRank 
References 
4
0.41
21
Authors
9
Name
Order
Citations
PageRank
Xintao Hu111813.53
Dajiang Zhu232036.72
Peili Lv3142.31
Kaiming Li438530.92
Junwei Han53501194.57
Lihong Wang61205.34
Dinggang Shen77837611.27
Lei Guo81661142.63
Tianming Liu91033112.95