ArticleNeuroinformatics2020
Zeffiro User Interface for Electromagnetic Brain Imaging: a GPU Accelerated FEM Tool for Forward and Inverse Computations in Matlab.
Article in Neuroinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Inferring neural sources from electroencephalography: foundations and frontiers.Journal of neural engineering · 2026Review
- Editorial: Forward and inverse solvers in multi-modal electric and magnetic brain imaging: theory, implementation, and application.Frontiers in human neuroscience · 2025Article
- CutFEM-based MEG forward modeling improves source separability and sensitivity to quasi-radial sources: A somatosensory group study.Human brain mapping · 2024Review
- Lattice layout and optimizer effect analysis for generating optimal transcranial electrical stimulation (tES) montages through the metaheuristic L1L1 method.Frontiers in human neuroscience · 2024Article
- The SESAMEEG package: a probabilistic tool for source localization and uncertainty quantification in M/EEG.Frontiers in human neuroscience · 2024Article
- Brainstorm-DUNEuro: An integrated and user-friendly Finite Element Method for modeling electromagnetic brain activity.NeuroImage · 2023Article
- CutFEM forward modeling for EEG source analysis.Frontiers in human neuroscience · 2023Article
- Multi-compartment head modeling in EEG: Unstructured boundary-fitted tetra meshing with subcortical structures.PloS one · 2023Article
- A comprehensive study on electroencephalography and magnetoencephalography sensitivity to cortical and subcortical sources.Human brain mapping · 2021Article
- Article
- Parametrizing the Conditionally Gaussian Prior Model for Source Localization with Reference to the P20/N20 Component of Median Nerve SEP/SEF.Brain sciences · 2020Article
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3 authors.
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Abstract
This article introduces the Zeffiro interface (ZI) version 2.2 for brain imaging. ZI aims to provide a simple, accessible and multimodal open source platform for finite element method (FEM) based and graphics processing unit (GPU) accelerated forward and inverse computations in the Matlab environment. It allows one to (1) generate a given multi-compartment head model, (2) to evaluate a lead field matrix as well as (3) to invert and analyze a given set of measurements. GPU acceleration is applied in each of the processing stages (1)-(3). In its current configuration, ZI includes forward solvers for electro-/magnetoencephalography (EEG) and linearized electrical impedance tomography (EIT) as well as a set of inverse solvers based on the hierarchical Bayesian model (HBM). We report the results of EEG and EIT inversion tests performed with real and synthetic data, respectively, and demonstrate numerically how the inversion parameters affect the EEG inversion outcome in HBM. The GPU acceleration was found to be essential in the generation of the FE mesh and the LF matrix in order to achieve a reasonable computing time. The code package can be extended in the future based on the directions given in this article.
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