Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive neuroimaging technique that utilizes spontaneous low-frequency fluctuations of blood-oxygenation-level dependent (BOLD) signals to examine resting-state functional connectivity in the brain. In the past two decades, this technique has been increasingly utilized to investigate properties of large-scale functional neural networks as well as their alterations in various cognitive and disease states. However, much less is known about large-scale functional neural networks of the rodent brain, particularly in the awake state. Therefore, we attempted to unveil local and global functional connectivity in awake rat through a combination of seed-based analysis, independent component analysis and graph-theory analysis. In the current studies, we revealed elementary local networks and their global organization in the awake rat brain. We further systematically compared the functional neural networks in awake and anesthetized states, revealing that the rat brain was locally reorganized while maintaining global topological properties from awake to anesthetized states. Furthermore, specific neural circuitries of the rat brain were examined using resting-state fMRI. First anticorrelated functional connectivity between infralimbic cortex and amygdala were found to be evident with different preprocessing methods (global signal regression, regression of ventricular and white matter signal and no signal regression). Secondly the thalamocortical connectivity was mapped for individual thalamic groups, revealing group-specific functional cortical connections that were generally consistent with known anatomical connections in rat. In conclusion, large-scale neural networks can be robustly and reliably studied using rs-fMRI in awake rat, and with this technique we established a baseline of local and global neural networks in the awake rat brain as well as their alterations in the anesthetized condition.
| Identifer | oai:union.ndltd.org:umassmed.edu/oai:escholarship.umassmed.edu:gsbs_diss-1657 |
| Date | 01 May 2013 |
| Creators | Liang, Zhifeng |
| Publisher | eScholarship@UMassChan |
| Source Sets | University of Massachusetts Medical School |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Morningside Graduate School of Biomedical Sciences Dissertations and Theses |
| Rights | Copyright is held by the author, with all rights reserved. |
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