השוואת שיטות

	ניתוח פוטנציאלים הקשורים לאירוע	eLORETA	מיפוי מקורות MEG
תחום	הדמיה עצבית	הדמיה עצבית	הדמיה עצבית
משפחה	Process / pipeline	Process / pipeline	Process / pipeline
שנת המקור	1969	2002	1972
הוגה השיטה	George Sutherland	Roberto D. Pascual-Marqui	David Cohen
סוג	Time-locked EEG analysis pipeline	EEG/MEG source localization algorithm	MEG neuroimaging analysis pipeline
מקור מכונן	Luck, S. J. (2005). An Introduction to the Event-Related Potential Technique. MIT Press.	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.	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.
כינויים	ERP, evoked potential, averaged EEG	Exact LORETA, eLORETA source reconstruction	MEG localization, magnetic source imaging, MSI
קשורות	3	2	3
תקציר	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.	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.	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.