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Original Article

Exp Neurobiol 2019; 28(2): 300-310

Published online April 30, 2019

https://doi.org/10.5607/en.2019.28.2.300

© The Korean Society for Brain and Neural Sciences

Generation of Mouse Basal Ganglia Diffusion Tractography Using 9.4T MRI

Jae-Hyuk Shim, Sang-Jin Im, A-Yoon Kim, Yong-Tae Kim, Eun Bee Kim, and Hyeon-Man Baek*

Department of Health Sciences and Technology, GAIHST, Gachon University, Incheon 21999, Korea.

Correspondence to: *To whom correspondence should be addressed.
TEL: 82-32-899-6678, FAX: 82-32-899-6677
e-mail: hmbaek98@gachon.ac.kr

Received: January 9, 2019; Revised: March 5, 2019; Accepted: March 25, 2019

Over the years, diffusion tractography has seen increasing use for comparing minute differences in connectivity of brain structures in neurodegenerative diseases and treatments. Studies on connectivity between basal ganglia has been a focal point for studying the effects of diseases such as Parkinson's and Alzheimer's, as well as the effects of treatments such as deep brain stimulation. Additionally, in previous studies, diffusion tractography was utilized in disease mouse models to identify white matter alterations, as well as biomarkers that occur in the progression of disease. However, despite the extensive use of mouse models to study model diseases, the structural connectivity of the mouse basal ganglia has been inadequately explored. In this study, we present the methodology of segmenting the basal ganglia of a mouse brain, then generating diffusion tractography between the segmented basal ganglia structures. Additionally, we compare the relative levels of connectivity of connecting fibers between each basal ganglia structure, as well as visualize the shapes of each connection. We believe that our results and future studies utilizing diffusion tractography will be beneficial for properly assessing some of the connectivity changes that are found in the basal ganglia of various mouse models.

Graphical Abstract


Keywords: Mouse, Basal Ganglia, MRI, Diffusion tractography