Back to Search Start Over

Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods.

Authors :
Mikulan, Ezequiel
Russo, Simone
Parmigiani, Sara
Sarasso, Simone
Zauli, Flavia Maria
Rubino, Annalisa
Avanzini, Pietro
Cattani, Anna
Sorrentino, Alberto
Gibbs, Steve
Cardinale, Francesco
Sartori, Ivana
Nobili, Lino
Massimini, Marcello
Pigorini, Andrea
Source :
Scientific Data; 4/28/2020, Vol. 7 Issue 1, p1-8, 8p
Publication Year :
2020

Abstract

Precisely localizing the sources of brain activity as recorded by EEG is a fundamental procedure and a major challenge for both research and clinical practice. Even though many methods and algorithms have been proposed, their relative advantages and limitations are still not well established. Moreover, these methods involve tuning multiple parameters, for which no principled way of selection exists yet. These uncertainties are emphasized due to the lack of ground-truth for their validation and testing. Here we present the Localize-MI dataset, which constitutes the first open dataset that comprises EEG recorded electrical activity originating from precisely known locations inside the brain of living humans. High-density EEG was recorded as single-pulse biphasic currents were delivered at intensities ranging from 0.1 to 5 mA through stereotactically implanted electrodes in diverse brain regions during pre-surgical evaluation of patients with drug-resistant epilepsy. The uses of this dataset range from the estimation of in vivo tissue conductivity to the development, validation and testing of forward and inverse solution methods. Measurement(s) electrical fields induced by intracerebral stimulation • brain measurement Technology Type(s) electroencephalography (EEG) Factor Type(s) Source localization methods • Stimulation intensity • Stimulation location • EEG montage Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12017823 [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20524463
Volume :
7
Issue :
1
Database :
Complementary Index
Journal :
Scientific Data
Publication Type :
Academic Journal
Accession number :
142943117
Full Text :
https://doi.org/10.1038/s41597-020-0467-x