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MEG源定位×eLORETA×
领域神经影像神经影像
方法族Process / pipelineProcess / pipeline
起源年份19722002
提出者David CohenRoberto D. Pascual-Marqui
类型MEG neuroimaging analysis pipelineEEG/MEG source localization algorithm
开创性文献Hauk, O., Friston, K. J., & Leff, A. (2019). Functional neuroimaging of language: understanding the complex relationships between localization and function. Journal of Neurolinguistics, 50, 236–250. link ↗Pascual-Marqui, R. D. (2002). Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods & Findings in Experimental & Clinical Pharmacology, 24(S-D), 5–12. link ↗
别名MEG localization, magnetic source imaging, MSIExact LORETA, eLORETA source reconstruction
相关32
摘要Magnetoencephalography (MEG) source localization is the inverse problem of estimating where in the brain neural currents originate from magnetic field measurements at the scalp. Introduced by David Cohen in 1972, MEG offers superior temporal resolution (milliseconds) and spatial specificity compared to EEG, as magnetic fields are less distorted by tissue conductivity, enabling researchers to pinpoint neural activity with high precision.Exact Low-Resolution Electromagnetic Tomography (eLORETA) is a non-parametric solution to the inverse problem in EEG and MEG source localization. Developed by Roberto D. Pascual-Marqui in 2002, eLORETA reconstructs three-dimensional maps of electrical brain activity from scalp electrode recordings, offering zero localization error under ideal noise-free conditions.
ScholarGate数据集
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  2. 2 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED

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ScholarGate方法对比: MEG Source Localization · eLORETA. 于 2026-06-17 检索自 https://scholargate.app/zh/compare