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Findings about LORETA Applied to High-Density EEG—A Review

Serena Dattola, Francesco Carlo Morabito, Nadia Mammone, Fabio La Foresta

2020Electronics47 citationsDOIOpen Access PDF

Abstract

Electroencephalography (EEG) is a non-invasive diagnostic technique for recording brain electric activity. The EEG source localization has been an area of research widely explored during the last decades because it provides helpful information about brain physiology and abnormalities. Source localization consists in solving the so-called EEG inverse problem. Over the years, one of the most employed method for solving it has been LORETA (Low Resolution Electromagnetic Tomography). In particular, in this review, we focused on the findings about the LORETA family algorithms applied to high-density EEGs (HD-EEGs), used for improving the low spatial resolution deriving from the traditional EEG systems. The results were classified according to their clinical application and some aspects arisen from the analyzed papers were discussed. Finally, suggestions were provided for future improvement. In this way, the combination of LORETA with HD-EEGs could become an even more valuable tool for noninvasive clinical evaluation in the field of applied neuroscience.

Topics & Concepts

ElectroencephalographyComputer scienceArtificial intelligenceLow resolutionInverse problemPattern recognition (psychology)NeurosciencePsychologyHigh resolutionMathematicsGeologyMathematical analysisRemote sensingEEG and Brain-Computer InterfacesFunctional Brain Connectivity StudiesAdvanced MRI Techniques and Applications