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Abstract #1716

Phenotyping assay of neuropathic pain models using resting state functional connectivity MRI and Graph theoretical analysis

Yuji Komaki1,2, Fumiko Seki1,2,3, Keigo Hikishima4, Masaya Nakamura2, and Hideyuki Okano2

1Laboratory Animal Research Department, Central Institute for Experimental Animals, Kawasaki, Japan, 2Keio University, Tokyo, Japan, 3Brain Science Institute, RIKEN, Saitama, Japan, 4Okinawa Institute of Science and Technology Graduate University (OIST), Japan

Resting state functional connectivity MRI was performed with neuropathic pain model mice.The functional network was constructed by temporal correlation analysis at the whole brain level based on the Allen brain atlas. Graph theoretical analysis was conducted to evaluate the feature of constructed networks. Compared with the intact model, degree and eigenvector centrality of neuropathic pain model showed a significant reduction in the primary somatosensory area. The clustering coefficient and local efficiency were significantly increased in the ACA. Significantly higher betweenness centrality was observed in the VPL. These results indicate that amount of information about connection to S1 was decreased. Neuropathic pain disrupt the pain matrix and the pain matrix that includes ACA and VPL may construct the complicated network. Integration of resting state functional connectivity MRI and graph theoretical analysis can evaluate the interactive complex networks of each region, not only existence or non-existence of activation region.

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