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

定量白色物质成像方法如扩散张量成像（DTI）、磁化传递成像（MTI）和髓磷脂水成像（MWI）比常规MRI方法对脑微结构的变化更敏感。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，量化受试者间差异和/或白色结构纵向变化的数据分析方法保持相对静态。*特别地，对人类白色物质MRI数据的分析传统上采用两种方法中的一种。逐体素分析具有高空间分辨率的优点，因此能够检测小的局部白色物质变化。然而，如果白色物质变化的大小或位置在个体之间不同，则这种方法在跨受试者分析中受到很大影响，因此不适合对患有创伤性脑损伤或白色物质疾病（如多发性硬化症）的患者进行分组分析。另一方面，感兴趣区域（ROI）分析从较大的预定脑区域提取数据，从而允许受试者之间的病变尺寸和位置的小差异（即，只要它们在所选择的ROI内的某个地方），代价是对小的局部变化的敏感性。然而，这些ROI方法还需要关于选择哪个大脑区域（或区域集）以及每个ROI应该有多大的先验假设，从而导致固有的灵敏度与特异性的权衡。为了解决这些局限性，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色物质图谱;*2.开发新的基于束的分析方法以测量沿着白色物质ROI;以及 *3.使用上述地图集和基于轨迹的分析方法，结合功能磁共振成像和认知测试，研究结构连接，功能连接和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（即，第一个目标有2名硕士生，第二个和第三个目标各有1名博士生）。* 最后，通过这项研究获得的知识将进一步阐明大脑结构，大脑功能和认知能力之间的复杂关系;由于由此产生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具有广泛的应用，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.**