Boundary Element Fast Multipole Method for Enhanced Modeling of Neurophysiological Recordings
Year: 2020
Type: article
Abstract: OBJECTIVE: A new numerical modeling approach is proposed which provides forward-problem solutions for both noninvasive recordings (EEG/MEG) and higher-resolution intracranial recordings (iEEG). METHODS: 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. RESULTS: 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. CONCLUSION: 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. SIGNIFICANCE: 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.
Language: English
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
Funders: National Institutes of Health, National Institute of Mental Health, National Institute on Deafness and Other Communication Disorders, National Institute of Neurological Disorders and Stroke, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institute of Biomedical Imaging and Bioengineering, U.S. National Library of Medicine
Awards: Non-invasive integrated system for brain stimulation and magnetocorticography, Modeling TMS-induced Cortical Network Activity, Mapping the intrinsic functional organization of auditory cortex in individual subjects using 7T MRI, Modeling TMS-induced Cortical Network Activity, Non-invasive measures of multisensory cortical feedforward and feedback influences, On-Body Passive-RFID Antenna Array and Testbed to Assess Changes in Bone Structure, Human Neocortical Neurosolver, Integrated multichannel system for transcranial magnetic stimulation and parallel magnetic resonance imaging, Decoding parametric attributes of auditory working memories from human brain activity, Brain and Human Body Modeling Conference – from Fast and Accurate Computational Modeling to Clinical Practice, Visible Human Project Full Body Finite-Element Phantom and Workflow, Scalable and Sensor-Agnostic Software for Distributed Processing and Visualization of Multi-Site MEG/EEG Datasets
OpenAlex ID: W3033356004