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FAMILIAL PSYCHIATRIC DISORDERS & SCHIZOPHRENIA

FAMILIAL PSYCHIATRIC DISORDERS & SCHIZOPHRENIA
家族性精神疾病
批准号:
6123576
负责人:
ROBERT F ASARNOW
金额:
$0.77万
依托单位国家:
美国
项目类别:
财政年份:
1999
资助国家:
美国
项目状态:
已结题
起止时间:
1999-08-01 至 2000-07-31

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中文摘要
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英文摘要
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.
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