Salīdzināt metodes

	eLORETA	Ar notikumiem saistīto potenciālu analīze	MEG avoto lokalizācija
Nozare	Neiroattēlveidošana	Neiroattēlveidošana	Neiroattēlveidošana
Saime	Process / pipeline	Process / pipeline	Process / pipeline
Izcelsmes gads	2002	1969	1972
Autors	Roberto D. Pascual-Marqui	George Sutherland	David Cohen
Tips	EEG/MEG source localization algorithm	Time-locked EEG analysis pipeline	MEG neuroimaging analysis pipeline
Pirmavots	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.	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.
Citi nosaukumi	Exact LORETA, eLORETA source reconstruction	ERP, evoked potential, averaged EEG	MEG localization, magnetic source imaging, MSI
Saistītās	2	3	3
Kopsavilkums	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.	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.