Error-reduction in dipole-source localization models

偶极源定位模型中的误差减少

• 批准号: 6337409
• 负责人: Don L. Jewett
• 金额: $ 10.45万
• 依托单位: ABRATECH CORPORATION
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2003-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6337409
• 关键词: bioimaging /biomedical imaging; computer program /software; computer simulation; computer system design /evaluation; dipole moment; electroencephalography; evoked potentials; magnetoencephalography; mathematical model; model design /development

DESCRIPTION(Adapted from applicant's abstract): Multiple-channel brain evoked-response data is often recorded from the scalp, either electrically, or magnetically. The analysis of this multi-channel data commonly utilizes mathematical models, which assume that the neural generators of the evoked-response are dipoles. Such DSL can be accurate or inaccurate, depending upon many factors, most of which are not accessible to the researchers or clinicians who use the DSL. The problem is compounded by the fact that a given model may be accurate for dipoles in some locations, but not accurate for dipoles in other locations. Furthermore, the use of the least-square error by the DSL has been shown to increase dipole parameter errors. A method of evaluating whether insidious errors may be present in DSL analysis has been developed, based upon the fact that poor models show a sensitivity to neural-generator wave shape. The applicants have developed a proprietary, technically innovative method to utilize this sensitivity as an error-signal to allow adaptive-adjustment of model constants to reduce errors. The Phase I research will test this method using computer simulations. This research is health-related because DSL methods are widely used to analyze human brain activity, whether normal or abnormal. PROPOSED COMMERCIAL APPLICATION: The methodology will be incorporated into existing or future DSL software under license, since it would remove the present uncertainty of DSL results.

描述(改编自申请人的摘要)：多通道脑诱发反应数据通常从头皮记录， 要么是电的，要么是磁的。对该多通道数据的分析 通常利用数学模型，这些模型假设神经生成器 诱发反应中有偶极子。这种DSL可以是准确的或不准确的， 取决于许多因素，其中大多数因素对于使用DSL的研究人员或临床医生是不可访问的。 更复杂的是，给定的模型对于 偶极子在某些位置，但对其他位置的偶极子不准确。 此外，DSL对最小二乘误差的使用已被证明 增加偶极子参数误差。 一种评估DSL分析中是否存在潜在错误的方法 已经被开发出来了，基于这样一个事实，即糟糕的模型对 神经发生器的波形。申请者开发了一种专有的， 利用这种敏感度作为误差信号的技术创新方法 允许模型常量的自适应调整，以减少误差。 第一阶段的研究将使用计算机模拟来测试这种方法。 这项研究与健康有关，因为DSL方法被广泛用于分析 人类的大脑活动，无论是正常的还是异常的。 建议的商业应用： 该方法将在许可下被纳入现有或未来的DSL软件中，因为它将消除目前DSL结果的不确定性。