Assessing Topographic Structural Connectivity of the Human Basal Ganglia and Thalamus

Irtiza A. Gilani; Kader K. Oguz; Huseyin Boyaci; Katja Doerschner

As with any imaging technique, various sources of image distortion could hamper the quantification of probabilistic connectivity patterns using diffusion MRI. More specifically, motion, eddy-current, susceptibility, main magnetic field inhomogeneity, concomitant fields and any other types of distortions must be precisely corrected in order to ensure improved quantitative processing of the diffusion and structural MRI data. Due to the imperfect distortion correction, distant proximity of certain structures and dense crossing fibers, the relative frequencies of connectivity of some structures were not in the "high range" in our work, for example between STN and cortical areas, CN and STN, Pu and STN, SN and cortical areas, SN and Pu, etc. However, specifically optimized T 2 * sequences can be employed for visualizing the STN to make accurate identification and delineation of the nucleus and target the motor portion of the STN. Additionally, the performance of the employed manual segmentation may not be optimal. This factor may limit the detection of high probability connectivity pathways. As connections revealed through diffusion MRI represent the sum total of both afferents and efferents, the inability of determining the polarity of connections may be another limiting aspect of this study.