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

定量白质成像方法，如扩散张量成像（DTI）、磁化转移成像（MTI）和髓鞘水成像（MWI）比传统的MRI方法对大脑微观结构的变化更敏感。然而，尽管MRI硬件（例如，更高的磁场强度和更多的接收器通道），改进的数据采集方案（例如，3D脉冲序列和并行成像技术）以及DTI， MTI和MWI采集参数的细化，量化主体间差异和/或白质结构纵向变化的数据分析方法仍然相对静止。******特别是，对人类白质MRI数据的分析传统上采用两种方法之一。体素分析具有高空间分辨率的优势，因此能够检测到小的、局部的白质变化。然而，如果白质变化的大小或位置因人而异，这种方法在跨主题分析中会受到很大的影响，因此不适合对创伤性脑损伤或白质紊乱（如多发性硬化症）患者进行群体分析。另一方面，感兴趣区域（ROI）分析从较大的预先确定的大脑区域提取数据，从而允许受试者之间病变大小和位置的微小差异（即，只要它们在所选的ROI内），以牺牲对小的局部变化的敏感性为代价。然而，这些ROI方法也需要对选择哪个大脑区域（或一组或多个区域）以及每个ROI应该有多大进行先验假设，从而导致固有的敏感性与特异性权衡。******为了解决其中的一些限制，我的小组将追求以下三个相互关联的研究目标：******1。使用fmri引导的DTI创建一组功能定义的白质图谱；***2。开发新的基于束的分析方法来测量沿白质roi；和* * * 3。利用上述图谱和基于通道的分析方法，结合功能磁共振成像和认知测试，研究结构连接、功能连接与认知表现之间的关系。******总共有4名研究生将通过生物医学工程和生理学研究生课程接受培训（即，第一个目标是2名硕士研究生，第二个和第三个目标是1名博士研究生）。******最后，通过本研究获得的知识将进一步阐明大脑结构、大脑功能和认知表现之间的复杂关系；由于最终的大脑图谱和分析软件可能在整个系统和认知神经科学中有广泛的应用，我们计划免费分发这些工具，以便加拿大和国外的其他神经成像研究人员可以使用它们

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.**