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- W2358906855 abstract "In view of the urgent need of looking for the biological indicators for the diagnosis and treatment of depression,as well as the growing maturity of fMRI data analysis and pattern classification techniques,this paper studies on the functional connectivity analysis and its application.It focuses on the various model-driven methods of resting state fMRI functional connectivity analysis using the fMRI collection of 28 healthy subjects and 38 patients with depression.It not only includes cross-correlation analysis and partial cross-correlation analysis in the time domain but also coherence analysis and mutual information analysis in the frequency domain.This demonstrates that the selection methods in the experiment are feasible and can distinguish the depression and the healthy.It places a certain role to establish the physiological indicator for the diagnosis and treatment of depression,thus it can better aid the clinical diagnosis and treatment." @default.
- W2358906855 created "2016-06-24" @default.
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- W2358906855 date "2013-01-01" @default.
- W2358906855 modified "2023-09-28" @default.
- W2358906855 title "Study and application of functional connectivity-analysis methods based on resting state fMRI" @default.
- W2358906855 hasPublicationYear "2013" @default.
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