Development and application of cognitive neuroimaging tools for quantitative white matter analyses

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Quantitative white matter imaging methods such as diffusion tensor imaging (DTI), magnetization transfer imaging (MTI), and myelin water imaging (MWI) are more sensitive than conventional MRI methods to changes in brain microstructure. However, despite advances in MRI hardware (e.g., higher magnetic field strengths and more receiver channels), improved data acquisition schemes (e.g., 3D pulse sequences and parallel imaging techniques), and the refinement of DTI, MTI and MWI acquisition parameters, data analysis approaches to quantify inter-subject differences and/or longitudinal changes in white matter structure have remained relatively static.******In particular, analyses of human white matter MRI data have traditionally taken one of two approaches. Voxel-wise analyses have the advantage of high spatial resolution and are therefore able to detect small, localized white matter changes. However, this approach suffers greatly in cross-subject analyses if sizes or locations of the white matter changes vary from one individual to the next, and are therefore not well-suited for group-wise analysis of patients with traumatic brain injuries or white matter disorders such as Multiple Sclerosis. On the other hand, region-of-interest (ROI) analyses extract data from larger pre-determined brain areas, thereby allowing for small differences in lesion sizes and locations across subjects (i.e., as long as they are somewhere within the chosen ROI) at the expense of sensitivity to small, localized changes. However, these ROI approaches also require a priori assumptions about which brain region (or set or regions) to choose and how large each ROI should be, leading to inherent sensitivity vs. specificity trade-offs.******In order to address several of these limitations, my group will pursue the following three interrelated research objectives:******1. Creating a set of functionally-defined white matter atlases using fMRI-guided DTI;***2. Developing novel tract-based analysis methods to measure along white matter ROIs; and***3. Using the aforementioned atlases and tract-based analysis methods in conjunction with fMRI and cognitive testing to study relationships between structural connectivity, functional connectivity and cognitive performance.******In total, 4 graduate students will be trained through the Biomedical Engineering and Physiology Graduate Programs (i.e., 2 MSc students for the first objective, and 1 PhD student each for the second and third objectives). ******Finally, the knowledge gained through this research will further elucidate the complex relationships between brain structure, brain function and cognitive performance; and since the resulting brain atlases and analysis software are likely to have wide-ranging applications throughout systems and cognitive neuroscience, we plan to freely distribute these tools so that they can be used by other neuroimaging researchers within Canada and abroad.**