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High-speed simulation of developmental motor disorders

发育性运动障碍的高速模拟

基本信息

批准号：
7845875
负责人：
Terence D Sanger
金额：
$ 33.74万
依托单位：
UNIVERSITY OF SOUTHERN CALIFORNIA
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-02-01 至 2013-12-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): When the brain is injured during development, there is an effect not only on immediate brain function but also on the future ability to learn and acquire skills. We propose to create and simulate multi-scale computational models of the effect of early structural injury on future motor function of the cortex and spinal cord. We will use programmable chips (FPGA's) and the new mathematical theory of "Likelihood Calculus" to build simulations of 300,000 neurons that run 500 times faster than real-time. The model will be fitted to electromyographic and kinematic data from children at two visits spaced one year apart, and predictions will be tested by comparison to a third visit one year later. High speed simulation of the effect of early injury has the potential to revolutionize the treatment of developmental neurological deficits because it can, in one week, simulate 10 years of future change. In doing so, it allows prediction of disease progression, prediction of the future effects of treatments, and detailed understanding of the interaction between brain injury and resulting disorders of movement, perception, and behavior. Because of these predictions, we can intervene much earlier with treatments customized to each patient's disease profile. With early intervention, it may be possible to attenuate or block the natural progression of their disease. With over 750,000 US children and adults affected by developmental brain disorders, early acquired brain injury, or childhood progressive brain disease, the applicability and potential impact of an early intervention and disease prediction technique are significant.

描述(申请人提供)：当大脑在发育过程中受到损伤时，不仅会影响即刻的大脑功能，还会影响未来的学习和获得技能的能力。我们建议建立和模拟早期结构损伤对未来皮质和脊髓运动功能的影响的多尺度计算模型。我们将使用可编程芯片(FPGA)和新的数学理论“似然微积分”来模拟30万个神经元，这些神经元的运行速度比实时运行速度快500倍。该模型将适用于间隔一年进行两次访问的儿童的肌电和运动学数据，并将通过与一年后第三次访问进行比较来检验预测。对早期损伤影响的高速模拟有可能给发育性神经缺陷的治疗带来革命性的变化，因为它可以在一周内模拟未来10年的变化。通过这样做，它可以预测疾病的进展，预测治疗的未来效果，并详细了解脑损伤与由此导致的运动、感知和行为障碍之间的相互作用。由于这些预测，我们可以更早地根据每个患者的疾病特征定制治疗方法进行干预。通过早期干预，有可能减缓或阻止他们疾病的自然发展。超过75万名美国儿童和成人受到发育性脑疾病、早期获得性脑损伤或儿童进行性脑疾病的影响，早期干预和疾病预测技术的适用性和潜在影响是显著的。