Abstract
So far, resting state functional connectivity (RSFC) has been performed mainly by seed correlation analysis (SCA) on functional MRI (fMRI) studies. In previous studies, the seeds are usually selected on the basis of prior anatomical information or previously performed activation maps. In this paper, we proposed a novel way to select the desired seeds by taking the natures of resting state data into account. The proposed approach is based on the measurement of regional homogeneity (ReHo) of brain regions. Using this technique, 2 locations showing higher ReHo in the cerebellum (i.e. the bilateral anterior inferior cerebellum, AICb) were identified and used as the seeds for RSFC patterns studies. We found that the bilateral AICb show significant functional connectivity with the bilateral thalamus, the bilateral hippocampus, the precuneus, the temporal lobe and the prefrontal lobe. Further, the differences of RSFC patterns between the bilateral AICb were ascertained by a random effect paired t-test. These findings may improve our understanding of cerebellar involvement in motor and a variety of non-motor functions.
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Keywords
- Functional Connectivity
- Rest State Functional Connectivity
- Prefrontal Lobe
- Bilateral Thalamus
- Bilateral Hippocampus
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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He, Y., Zang, Y., Jiang, T., Liang, M., Gong, G. (2004). Detecting Functional Connectivity of the Cerebellum Using Low Frequency Fluctuations (LFFs). In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30136-3_110
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DOI: https://doi.org/10.1007/978-3-540-30136-3_110
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