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Evaluation of EEG Source Localization Algorithms with Multiple Cortical Source
Evaluation of EEG Source Localization Algorithms with Multiple Cortical Source
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Figshare
2016-01-19 更新
2026-04-08 收录
脑电源定位
神经影像算法评估
数据链接:
https://figshare.com/articles/dataset/Evaluation_of_EEG_Source_Localization_Algorithms_with_Multiple_Cortical_Source/1053095/1
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资源简介:
Data to accompany the PLoS One article
应用场景:
提供机构:
Yao, Jun; Bradley, Allison; Claus-Peter Richter; Jules Dewald
创建时间:
2014-06-11
相关数据集
Linear distributed methods considered in this study.
脑电源定位
神经影像学方法
First column: abbreviations of the methods’ names: (W)MNE = (weighted) minimum norm estimate, LORETA = low resolution electrical tomography, LORETA* = LORETA without weighting. Second column: correspo
NIAID Data Ecosystem
7
0
4 source cdr
脑电源定位
神经信号重建
Current source density reconstructions for four sources of equal strength.
Figshare
2016-01-19 更新
4
0
Summary of the maximum values of the scalp electrostatic potential ( V ) and GM electric field (magnitude, E , and normal component, E n ) induced in all the source distributions used in the realistic head model.
脑电源定位
神经电生理
For each quantity, two dipole densities are considered: 0.5 and 1.0 nAm/mm2.
NIAID Data Ecosystem
3
0
Benchmark data for sulcal pits extraction algorithms
脑沟底点提取
神经影像算法评估
This article contains data related to the research article “G. Auzias, L. Brun, C. Deruelle, O. Coulon, Deep sulcal landmarks: Algorithmic and conceptual improvements in the definition and extraction
DataONE
2019-11-18 更新
5
0
MNI coordinates of the maximum estimated sLORETA activity values corresponding to the P1 and P2 ERP components.
脑电源定位
事件相关电位
MNI coordinates of the maximum estimated sLORETA activity values corresponding to the P1 and P2 ERP components.
NIAID Data Ecosystem
4
0
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