MODELS OF NORMAL & POSTSTROKE HEMISPHERIC INTERACTIONS

正常模型

• 批准号: 6529198
• 负责人: JAMES A REGGIA
• 金额: $ 25.52万
• 依托单位: UNIV OF MARYLAND, COLLEGE PARK
• 依托单位国家: 美国
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-09-20 至 2005-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6529198
• 关键词: association learning; brain interhemispheric activity; cerebral dominance; computational neuroscience; corpus callosums; disease /disorder model; experimental brain lesion; human data; interhemispheric transfer; learning transfer; neural plasticity; stroke

Current understanding of the origins of cerebral specialization and of hemispheric interactions is fairly limited. For example, it is unclear which recognized cortical asymmetries lead to lateralization, whether the net influence of one hemisphere on the other is excitatory or inhibitory, and to the extent to which the intact contralateral hemisphere contributes to recovery following a cortical lesion such as a stroke. The long-term goal of this work is to gain a better understanding of these issues by developing and studying neural models of emergent hemispheric lateralization and of hemispheric interactions as those models recover from simulated cortical lesions. The models consist of networks of paired left and right cortical regions connected by a simulated corpus callosum. The specific aims are: 1. to test the hypothesis that models have excitatory callosal connections and indirect interhemispheric competition can better explain data from biological/behavioral experiments than previous models; 2. to determine how learning one behavioral task can influence the direction/extent of another task's lateralization; 3. to determine how multiple underlying hemispheric asymmetries in a single model interact, altering the direction/extent of lateralization produced by each alone; and 4. to examine lateralization and post-lesion hemispheric interactions in a neurobiologically-grounded model of associative word learning that is directly comparable to behavioral, clinical and functional imaging data. This is the first systematic attempt to better understand cerebral specialization and transcallosal diaschisis using computational models. The results will directly relate to ongoing experimental work, have important implications for current theories of the mechanisms underlying hemispheric functional asymmetries and post-stroke recovery, and may suggest new therapeutic concepts for stroke patients.

目前对大脑专门化和半球相互作用的起源的理解相当有限。 例如，目前还不清楚哪些公认的皮质不对称性会导致偏侧化，一个半球对另一个半球的净影响是兴奋性的还是抑制性的，以及完整的对侧半球在多大程度上有助于中风等皮质病变后的恢复。 这项工作的长期目标是通过开发和研究新兴半球偏侧化和半球相互作用的神经模型（当这些模型从模拟皮质损伤中恢复时），更好地理解这些问题。 该模型由成对的左右皮质区域网络组成，通过模拟胼胝体连接。 具体目标是： 1. 检验模型具有兴奋性胼胝体连接和间接半球间竞争能够比之前的模型更好地解释生物/行为实验数据的假设； 2. 确定学习一项行为任务如何影响另一项任务侧化的方向/程度； 3. 确定单个模型中多个潜在半球不对称性如何相互作用，从而改变每个模型单独产生的偏侧化的方向/程度； 4. 在基于神经生物学的联想词学习模型中检查偏侧化和损伤后半球相互作用，该模型可直接与行为、临床和功能成像数据进行比较。 这是利用计算模型更好地理解大脑特化和胼胝体神经联系联系分离的首次系统尝试。 结果将直接与正在进行的实验工作相关，对当前半球功能不对称和中风后恢复机制的理论具有重要意义，并可能为中风患者提出新的治疗概念。