مقایسهٔ روش‌ها

	مکان‌یابی منبع MEG	eLORETA	تحلیل پتانسیل‌های برانگیخته رویداد
حوزه	تصویربرداری عصبی	تصویربرداری عصبی	تصویربرداری عصبی
خانواده	Process / pipeline	Process / pipeline	Process / pipeline
سال پیدایش	1972	2002	1969
پدیدآور	David Cohen	Roberto D. Pascual-Marqui	George Sutherland
نوع	MEG neuroimaging analysis pipeline	EEG/MEG source localization algorithm	Time-locked EEG analysis pipeline
منبع بنیادین	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.	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.	Luck, S. J. (2005). An Introduction to the Event-Related Potential Technique. MIT Press.
نام‌های دیگر	MEG localization, magnetic source imaging, MSI	Exact LORETA, eLORETA source reconstruction	ERP, evoked potential, averaged EEG
مرتبط	3	2	3
خلاصه	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.	Event-Related Potential (ERP) analysis is a method for extracting stereotyped brain electrical responses time-locked to stimulus presentation or behavioral events from EEG recordings. Formalized in the cognitive neuroscience literature by researchers including Sutherland and Picton, ERP analysis enables millisecond-level temporal resolution of neural processing and has become foundational for studying perception, attention, memory, and decision-making.