CRSNS: Development of EEG/MEG Source Reconstruction with Fast Multipole Method

CRSNS：使用快速多极方法进行 EEG/MEG 源重建的开发

基本信息

批准号：
10835137
负责人：
Sergey N Makaroff
金额：
$ 19.41万
依托单位：
WORCESTER POLYTECHNIC INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-22 至 2027-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10835137
关键词：
Acceleration Address Affect Algorithms Anatomy Antidepressive Agents Anxiety Area Biological Sciences Biomedical Technology Boundary Elements Brain Charge Complex Computer software Coupling Data Development Diagnosis Disease Documentation Dryness Electrodes Electroencephalography Engineering Evaluation Feeling suicidal Fingers Finland Germany Goals Head Health Human Activities Institution International Language Location Lymphocytic choriomeningitis virus Measurement Measures Mental Depression Mental Health Methods Modality Modeling Motivation Motor National Institute of Biomedical Imaging and Bioengineering Neurons Pathologic Pathology Patients Population Problem Solving Public Health Pythons Reporting Research Resolution Schools Source Speed Strategic Planning Students Surface System Technology Thumb structure Time Universities Well in self Work Youth analysis pipeline cognitive neuroscience density design electric field experimental study finger movement gray matter health assessment improved indexing innovation insight magnetic resonance imaging/electroencephalography median nerve neural neuroimaging patient response physical science reconstruction response somatosensory source localization speech processing tool undergraduate student verification and validation volunteer young adult

Acceleration Address Affect Algorithms Anatomy Antidepressive Agents Anxiety Area Biological Sciences Biomedical Technology Boundary Elements Brain Charge Complex Computer software Coupling Data Development Diagnosis Disease Documentation Dryness Electrodes Electroencephalography Engineering Evaluation Feeling suicidal Fingers Finland Germany Goals Head Health Human Activities Institution International Language Location Lymphocytic choriomeningitis virus Measurement Measures Mental Depression Mental Health Methods Modality Modeling Motivation Motor National Institute of Biomedical Imaging and Bioengineering Neurons Pathologic Pathology Patients Population Problem Solving Public Health Pythons Reporting Research Resolution Schools Source Speed Strategic Planning Students Surface System Technology Thumb structure Time Universities Well in self Work Youth analysis pipeline cognitive neuroscience density design electric field experimental study finger movement gray matter health assessment improved indexing innovation insight magnetic resonance imaging/electroencephalography median nerve neural neuroimaging patient response physical science reconstruction response somatosensory source localization speech processing tool undergraduate student verification and validation volunteer young adult

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项目摘要

This proposal entitled “Development of EEG/MEG Source Reconstruction with Fast Multipole Method” will address the currently unmet need for significantly more accurate, near real-time EEG/MEG source localization tools. The result will be the construction of an entirely new, high-speed, high-resolution EEG/MEG source localization pipeline that includes: (i) field solution using the charge-based Boundary Element Method (BEM) with Fast Multipole acceleration; (ii) inverse problem solution algorithm utilizing the circuital reciprocity theorem and global cortical basis functions with an unlimited number of cortical sources; (iii) precisely segmented head models and; (iv) precise MEG compatible EEG hardware, verification and validation experiments and their documentation. If successful, the developed technology will be adaptable to any branch of cognitive neuroscience diagnosis (EEG and MEG), providing enhanced understanding of a patient’s response during antidepressant treatments and greater insight into overall mental well-being. Aim 1 Algorithm for EEG/MEG source reconstruction with fast multipole method Aim 1A Algorithm construction and development (WPI Worcester and MPI Leipzig) Aim 1B Preliminary results (WPI Worcester and MGH) Aim 2 Integration with high density dry-electrode EEG system. EEG/MEG Measurements Aim 2A Design a 256 channel MEG-compatible dry-electrode system (TU Ilmenau) Aim 2B Perform MRI/EEG/MEG verification measurements (MPI Leipzig & TU Ilmenau) Aim 2C Verify, modify and improve BEM-FMM based source reconstruction software (MPI Leipzig, WPI Worcester, TU Ilmenau) Coupling high-resolution algorithms with the finest yet robust and easy-to-use EEG hardware is one major proposal goal. Such coupling could make an advanced high-density dry-electrode EEG very accurate.

该建议名为“用快速多极方法开发EEG/MEG来源重建”将解决目前对更准确的未满足的需求，接近实时的脑电图/MEG源本地化工具。结果将是建造一个全新的高速，高分辨率 EEG/MEG源定位管道包括：（i）使用基于电荷的边界的现场解决方案元素方法（BEM）具有快速多极加速度；（ii）使用逆问题解决方案算法利用电路互惠定理和全球皮质基函数，具有无限数量的皮质来源；（iii）精确分段的头模型和；（iv）精密MEG兼容的EEG硬件，验证和验证实验及其文档。如果成功，已经发达的技术将适应认知神经科学诊断（EEG和MEG）的任何分支，提供了增强了解抗抑郁治疗期间患者的反应，并更深入地了解总体心理健康。 EEG/MEG源重建的AIM 1算法使用快速多极方法 AIM 1A算法建设与开发（WPI Worcester和MPI Leipzig） AIM 1B初步结果（WPI伍斯特和MGH） AIM 2与高密度干电极EEG系统的集成。 EEG/MEG测量 AIM 2A设计256通道MEG兼容的干电极系统（TU ILMENAU） AIM 2B执行MRI/EEG/MEG验证测量（MPI Leipzig＆Tu Ilmenau） AIM 2C验证，修改和改进基于BEM-FMM的源重建软件（MPI Leipzig，WPI 伍斯特，tu Ilmenau）将高分辨率算法与最好且易于使用的EEG硬件耦合是一个主要提案目标。这种耦合可以使高级高密度干电极EEG非常准确。