Boundary Element Fast Multipole Method for Enhanced Modeling of Neurophysiological Recordings.
Boundary Element Fast Multipole Method for Enhanced Modeling of Neurophysiological Recordings.
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DOI：
10.1109/tbme.2020.2999271
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发表时间：
2021-01
期刊：
影响因子：
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通讯作者：
Nummenmaa A
中科院分区：
文献类型：
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作者：
Makarov SN;Hamalainen M;Okada Y;Noetscher GM;Ahveninen J;Nummenmaa A
提出了一种新的数值建模方法，为无创记录（EEG/MEG）和高分辨率颅内记录（iEEG）提供了正向问题解决方案。该算法是我们最近开发的边界元快速多极子方法或边界元FMM。它是基于集成的边界元制定的表面电荷密度和快速多极方法起源于它的发明者。该算法仍然具有传统边界元法的主要优点-速度快-但同时能够处理大量的基于表面的未知数。因此，可以实现前所未有的空间分辨率，这使得多尺度建模成为可能。对于非侵入性EEG/MEG，我们能够在1 - 2分钟内精确地解决前向问题，在给定数千个皮层偶极子的情况下，在皮层中具有约1 mm的解剖分辨率。针对高分辨率的iEEG，我们能够计算，第一次，一个完整的电磁响应的合奏（2,450）紧密包装的现实锥体新皮层神经元在一个完整的头部模型与0.6毫米的解剖皮层分辨率。神经元乔木由5.9 M的1.2 μ m长的基本偶极子组成。在一个标准的服务器上，计算需要约5分钟。我们的研究结果表明，BEM-FMM方法可能非常适合于支持现代高分辨率和亚毫米iEEG相关的数值多尺度建模。基于实现的速度和易用性，这种新算法代表了一种方法，将极大地促进跨各种应用程序的多尺度模拟。
A new numerical modeling approach is proposed which provides forward-problem solutions for both noninvasive recordings (EEG/MEG) and higher-resolution intracranial recordings (iEEG). The algorithm is our recently developed boundary element fast multipole method or BEM-FMM. It is based on the integration of the boundary element formulation in terms of surface charge density and the fast multipole method originating from its inventors. The algorithm still possesses the major advantage of the conventional BEM - high speed - but is simultaneously capable of processing a very large number of surface-based unknowns. As a result, an unprecedented spatial resolution could be achieved, which enables multiscale modeling. For non-invasive EEG/MEG, we are able to accurately solve the forward problem with approximately 1 mm anatomical resolution in the cortex within 1–2 min given several thousand cortical dipoles. Targeting high-resolution iEEG, we are able to compute, for the first time, an integrated electromagnetic response for an ensemble (2,450) of tightly packed realistic pyramidal neocortical neurons in a full-head model with 0.6 mm anatomical cortical resolution. The neuronal arbor is comprised of 5.9 M elementary 1.2 μm long dipoles. On a standard server, the computations require about 5 min. Our results indicate that the BEM-FMM approach may be well suited to support numerical multiscale modeling pertinent to modern high-resolution and submillimeter iEEG. Based on the speed and ease of implementation, this new algorithm represents a method that will greatly facilitate simulations at multi-scale across a variety of applications.