Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

Xintao Hu, Dajiang Zhu, Peili Lv, Kaiming Li, Junwei Han, Lihong Wang, Dinggang Shen, Lei Guo, Tianming Liu
2013 Neuroinformatics  
In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via restingstate 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
more » ... xplored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork 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 interregional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures.
doi:10.1007/s12021-013-9177-2 pmid:23319242 pmcid:PMC4030009 fatcat:kuxqmt2z2rgklhhmj5b3qxhwym