Σύγκριση μεθόδων

	Ανάλυση Προκλητών Δυναμικών (Event-Related Potential Analysis)	eLORETA	Εντοπισμός πηγών MEG
Πεδίο	Νευροαπεικόνιση	Νευροαπεικόνιση	Νευροαπεικόνιση
Οικογένεια	Process / pipeline	Process / pipeline	Process / pipeline
Έτος προέλευσης	1969	2002	1972
Δημιουργός	George Sutherland	Roberto D. Pascual-Marqui	David Cohen
Τύπος	Time-locked EEG analysis pipeline	EEG/MEG source localization algorithm	MEG neuroimaging analysis pipeline
Θεμελιώδης πηγή	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.
Εναλλακτικές ονομασίες	ERP, evoked potential, averaged EEG	Exact LORETA, eLORETA source reconstruction	MEG localization, magnetic source imaging, MSI
Συναφείς	3	2	3
Σύνοψη	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.