Default Mode Network of the Rat Brain

• Main Authors: Li-Ming Hsu, 許立明
• Other Authors: Ching-Po Lin
• Format: Others
• Language: en_US
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/15280679100575775269

博士 === 國立陽明大學 === 生物醫學影像暨放射科學系 === 104 === The human brain is one of the most complex systems in nature. Using non-invasive functional magnetic resonance imaging (fMRI) technology, researchers can explore the structural and functional brain networks on large scale. In human study, the default mode network (DMN) has been suggested to support a variety of self-referential functions, including recollection and imagination, conceptual processing, and autobiographical memory. Various neurological and psychiatric disorders including schizophrenia, Alzheimer’s disease, autism, and addiction have been demonstrated that linked to DMN dysregulation. The default mode network (DMN) has been suggested to support a variety of self-referential functions in humans. The human DMN has been fractionated into subsystems based on their distinct responses to cognitive tasks and functional connectivity architecture, which might reflect functional hierarchy and segregation within the network. Since preclinical models can be used in translational studies of neuropsychiatric disorders, partitioning of DMN in nonhuman species may inform both physiology and pathophysiology of the human DMN. In this study, we investigate constituents of the rat DMN using resting-state functional MRI (rs-fMRI) and diffusion tensor imaging (DTI). The DMN was identified using a group-level independent component analysis on the rs-fMRI data. Using modularity analyses, the rat DMN was fractionated into an anterior and a posterior subsystem, which were further segregated into five modules. Fiber density derived from DTI tractography demonstrates a close relationship with the functional connectivity between DMN regions, and provided anatomical evidence to support the detected DMN functional sub-systems. We also observed distinct modulation within and between these DMN subcomponents following acute sensorimotor stimulation and aged- related cognitive dysfunction, consistent with findings in the human DMN. Together, these results suggest that the rat DMN, like the analogous human DMN, can be partitioned into several subcomponents that may be associated with distinct functions. Further investigation into the neurobiological implications of the DMN organization in both healthy and pathological preclinical models is warranted. In summary, our work provides the architecture of rat DMN using modularity analysis of re-sfMRI data and associated this with the underlying structural connectivity obtained with diffusion tensor imaging (DTI) tractography. Together, our findings on the rat DMN and its organization provide a platform to explore the physiological basis and behavioral functions of this prominent, large-scale network.