Characterization of the resting-state brain network topology in the 6-hydroxydopamine rat model of Parkinson’s diseaseReport as inadecuate




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Resting-state functional MRI rsfMRI is an imaging technology that has recently gained attention for its ability to detect disruptions in functional brain networks in humans, including in patients with Parkinson’s disease PD, revealing early and widespread brain network abnormalities. This methodology is now readily applicable to experimental animals offering new possibilities for cross-species translational imaging. In this context, we herein describe the application of rsfMRI to the unilaterally-lesioned 6-hydroxydopamine 6-OHDA rat, a robust experimental model of the dopamine depletion implicated in PD. Using graph theory to analyse the rsfMRI data, we were able to provide meaningful and translatable measures of integrity, influence and segregation of the underlying functional brain architecture. Specifically, we confirm that rats share a similar functional brain network topology as observed in humans, characterised by small-worldness and modularity. Interestingly, we observed significantly reduced functional connectivity in the 6-OHDA rats, primarily in the ipsilateral lesioned hemisphere as evidenced by significantly lower node degree, local efficiency and clustering coefficient in the motor, orbital and sensorimotor cortices. In contrast, we found significantly, and bilaterally, increased thalamic functional connectivity in the lesioned rats. The unilateral deficits in the cortex are consistent with the unilateral nature of this model and further support the validity of the rsfMRI technique in rodents. We thereby provide a methodological framework for the investigation of brain networks in other rodent experimental models of PD, as well as of animal models in general, for cross-comparison with human data.



Author: Robert Westphal , Camilla Simmons, Michel B. Mesquita, Tobias C. Wood, Steve C. R. Williams, Anthony C. Vernon, Diana Cash

Source: http://plos.srce.hr/



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