FAMILIAL PSYCHIATRIC DISORDERS & SCHIZOPHRENIA

大脑建模挑战。关于大脑结构的研究 和功能需要多种工具来创建。分析， 将大脑模型可视化，并与之交互。有一种快速的 对足够全面以代表大脑的大脑模型的需求日益增长 结构和功能随着时间的推移而变化。当他们改变的时候 在大量人群中、在不同的疾病状态下、在 不同年龄和性别的成像方式。甚至是跨物种的。 这要求开发3D和4D大脑模型，这些模型是 可适应多种应用。包括检测 以及对结构变化和异常的分析，在所有他们的 空间和时间的复杂性。的范围和复杂程度 这些战略将与将重点关注的广泛研究范围相匹配 对动态变化的大脑进行测绘和建模。 开发动态大脑建模工具，基于 2、3和4维的参数化，以表示和分析 大脑结构在不同疾病状态下的变化。横穿 大量人群，不同年龄和性别，不同成像方式， 以及跨物种的。计算大脑建模工具将是 创建用于跟踪和分析复杂的三和 不同运动状态下脑内四维结构的变化 神经发育和退行性疾病的过程。工具将 将结构指数与临床、行为数据库相关联 和神经精神测试数据，以扩大对大脑的研究 四个维度的结构-功能关系。 具体目标2.创建数学策略来分析 大脑皮层的结构，因为它在单个时间内变化 受试者和组。将开发新的计算机化方法 绘制大脑皮层发育和退化的时间模式 编码人类种群中的皮质变异模式，并 检测个别患者的异常脑回和脑沟模式 组。统计解剖学模型将绘制出四个大脑皮质的变化 测量和检测患者群体中的异常 阿尔茨海默氏症、精神分裂症和神经发育障碍。 具体目标3.开发和扩展自动提取软件 以及对脑结构模型的分析。解剖学的参数化 模型是比较神经解剖学的关键，因为它制造模型 在不同的时间点具有可比性。用于提取曲面的强大工具 一系列全面神经解剖结构的模型将 加快和扩大脑建模项目的范围和 脑结构模型必须满足以下条件的诊断应用 迅速而有力地创造出来。 具体目标4.开发脑图工具和数学图像 分析适应和借鉴三人档案的算法 四维神经解剖模型。海量的档案 由内部和协作产生的计算模型 建模项目将被组织起来，以便它们能够指导和告知 分析人类未来神经解剖学数据的数学算法 同样的类型。模型驱动工具将包括用于结构的软件 拔牙。结构变化和异常的圈定， 脑功能图像数据分析与非线性配准 将来自受试者和小组的大脑数据与大脑集成的工具 结构差异。

Brain Modeling Challenges. Investigations into brain structure and function require a diverse array of tools to create. analyze, visualize, and interact with models of the brain. There is a rapidly growing need for brain models comprehensive enough to represent brain structure and function as they change across time,. as they change vary across large populations, in different disease states, across imaging modalities, across age and gender. and even across species. This mandates the development of 3D and 4D brain models that are adaptable to a wide variety of applications. including the detection and analysis of structural change and abnormality, in all their spatial and temporal complexity. The range and sophistication of these strategies will match the broad scope of studies that will focus on mapping and modeling the dynamically changing brain. Develop dynamic brain modeling tools, based on the concept of parameterization in 2, 3, and 4 dimensions, to represent and analyze brain structure as it changes in different disease states. across large populations, across age and gender, across imaging modalities, and across species. Computational brain modeling tools will be created to track and analyze complex patterns of three-and four-dimensional structural change in the brain during a variety of neurodevelopmental and degenerative disease processes. Tools will correlate structural indices with databases of clinical, behavioral and neuropsychiatric test data, to expand investigations of brain structure-function relationships to four dimensions. Specific Aim 2. Create mathematical strategies to analyze the structure of the cerebral cortex, as it changes across time in single subjects and groups. Novel computerized approaches will be developed to map temporal patterns of cortical development and degeneration, to encode patterns of cortical variation in human populations, and to detect abnormal gyral and sulcal patterns in individual patients and groups. Statistical anatomic models will map cortical change in four dimensions and detect anomalies in patient populations with Alzheimer's Disease, schizophrenia, and neurodevelopmental disorders. Specific Aim 3. Develop and extend software for automated extraction and analysis of brain structure models. Parameterization of anatomic models is critical for comparative neuroanatomy, as it makes models comparable at different time-points. Robust tools to extract surface models for a comprehensive range of neuroanatomic structures will accelerate and expand the scope of brain modeling projects and diagnostic applications in which brain structure models must be created rapidly and robustly. Specific Aim 4. Develop brain mapping tools and mathematical image analysis algorithms that adapt and learn from archives of three and four-dimensional neuroanatomic models. Immense archives of computational models resulting from in-house and collaborative modeling projects will be structured so that they can guide and inform mathematical algorithms which analyze future neuroanatomic data of the same type. Model-driven tools will include software for structure extraction. delineation of structural change and abnormality, analysis of functional brain image data, and nonlinear registration tools that integrate brain data from subjects and groups with brain structure differences.