ISSN : 1226-9654
In contrast to the task-based fMRI, the resting-state fMRI (rs-fMRI) doesn’t require a specific task, since data are obtained during rest for a relatively short scan time (about 10 min). Therefore, rs-fMRI provides advantages in studying individual differences not associated with the task, and in obtaining data from a large population of various groups (clinical or normal healthy). In the current review, we introduced several analyzing techniques for rs-fMRI. These techniques allow us to identify the functional connectivity among specific regions (seed-based functional connectivity analysis, independent component analysis), a network pattern composed of nodes (graph-based network analysis), or the spontaneous activity pattern (regional homogeneity, analysis of low-frequency fluctuation) during rest. The individual differences found during rest with these techniques have been shown to be related to individual differences (e.g., personality traits) or clinical diseases, such as depression, Alzheimer’s diseases, and autism. Choosing an optimal research technique for a specific study question would be possible only with a deep understanding of these analysis techniques.
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