期刊
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
卷 2014, 期 -, 页码 -出版社
HINDAWI LTD
DOI: 10.1155/2014/864979
关键词
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资金
- Natural Science Foundation of China [81422022, 81271553, 81201155, 81171328, 61131003, 61378092, 81401402]
- Jinling Hospital [2011061]
- 12.5 Key Grant [BWS11J063, 10z026]
Examining the resting-state networks (RSNs) may help us to understand the neural mechanism of the frontal lobe epilepsy (FLE). Resting-state functional MRI (fMRI) data were acquired from 46 patients with FLE (study group) and 46 age-and gender-matched healthy subjects (control group). The independent component analysis (ICA) method was used to identify RSNs from each group. Compared with the healthy subjects, decreased functional connectivity was observed in all the networks; however, in some areas of RSNs, functional connectivity was increased in patients with FLE. The duration of epilepsy and the seizure frequency were used to analyze correlation with the regions of interest (ROIs) in the nine RSNs to determine their influence on FLE. The functional network connectivity (FNC) was used to study the impact on the disturbance and reorganization of FLE. The results of this study may offer new insight into the neuropathophysiological mechanisms of FLE.
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