Low-density EEG for Source Activity Reconstruction using Partial Brain Models

Andres Felipe Soler, Eduardo Giraldo, Marta Molinas

2020

Abstract

Brain mapping studies have shown that the source reconstruction performs with high accuracy by using high-density EEG montages, however, several EEG devices in the market provide low-density configurations and thus source reconstruction is considered out of the scope of those devices. In this work, our aim is to use a few numbers of electrodes to reconstruct the neural activity using partial brain models, therefore, we presented a pipeline to estimate the brain activity using a low-density EEG on brain regions of interest, the partial brain model formulation and several criteria for channel selection. Two regions have been considered to be studied, the occipital region and motor cortex region. For the presented study synthetic EEG signals were generated simulating the activation of sources with a frequency in the beta range at the occipital region, and mu rhythm range at the motor cortex areas. Novel methods for electrode reduction and models for specific brain areas are presented. We assessed the quality of the reconstructions by measuring the localization error, obtaining a mean localization error below 7 mm and 16 mm with sLORETA and MSP methods respectively, by using a low-density EEG with eight channels and partial brain models.

Paper Citation

in Harvard Style

Soler A., Giraldo E. and Molinas M. (2020). Low-density EEG for Source Activity Reconstruction using Partial Brain Models. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 2: BIOIMAGING; ISBN 978-989-758-398-8, SciTePress, pages 54-63. DOI: 10.5220/0008972500540063

in Bibtex Style

@conference{bioimaging20,
author={Andres Felipe Soler and Eduardo Giraldo and Marta Molinas},
title={Low-density EEG for Source Activity Reconstruction using Partial Brain Models},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 2: BIOIMAGING},
year={2020},
pages={54-63},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008972500540063},
isbn={978-989-758-398-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 2: BIOIMAGING
TI - Low-density EEG for Source Activity Reconstruction using Partial Brain Models
SN - 978-989-758-398-8
AU - Soler A.
AU - Giraldo E.
AU - Molinas M.
PY - 2020
SP - 54
EP - 63
DO - 10.5220/0008972500540063
PB - SciTePress