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Tumors in the central nervous system (CNS) can produce significant behavior deficits. These deficits significantly reduce the quality of life of long-term brain tumor survivors. Motor deficits can be the main presenting symptoms that brings a brain tumor patient into the hospital. Additionally, motor deficits can either improve or worsen after treatment. Its poorly understood how tumor phenotype (e.g infiltrative or circumscribed) contributes to the development and evolution of motor deficits. Resting state functional connectivity magnetic resonance imaging (rsfc-MRI) could help determine a relationship between brain function and tumor phenotype. rsfc-MRI provides measurements of functional connectivity (FC), which is a measure of brain activity and has been shown to correlate with neurological function (e.g. cognitive and motor deficit) in many disease states. Additional studies are needed before rsfc-MRI can be included in the standard of care for brain tumor patients because it is largely unknown how important clinical factors, such as tumor location and tumor burden (e.g. tumor volume), modulate the association between FC measurements and neurological performance. However, human studies are unlikely to have the statistical power to determine the relationships between FC, clinical factors, and neurological function because it is difficult to enroll many human subjects while controlling for a factor. Fortunately, mice can be used to control for a factor in many genetically identical specimens. Therefore, FC assessments need to be applied to studies in mouse models of brain tumors to assess the interactions be specific clinical factors, FC measurements and neurological function. FC measurements are infrequently obtained in mouse models because it is technically difficult to perform rsfc-MRI on the small mouse brain. Fortunately, functional connectivity optical intrinsic signal imaging (fcOISI) can be used obtain FC measurements in mice. In this study, we investigated how tumor phenotype modulates the relationship between tumor burden measures and motor function. We injected in two groups of mice with human brain tumor cell lines that exhibit different growth phenotypes. We assessed the motor function of the mice by their performance on a battery of sensorimotor tests. We determined tumor burden with bioluminescence and MRI and assessed FC with fcOISI. Lastly, we performed linear regression analysis to determine how these measured factors interact in the prediction of performance on the motor tests.
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