Parametrizing the Conditionally Gaussian Prior Model for Source Localization with Reference to the P20/N20 Component of Median Nerve SEP/SEF

Parametrizing the Conditionally Gaussian Prior Model for Source Localization with Reference to the P20/N20 Component of Median Nerve SEP/SEF

In this article, we focused on developing the conditionally Gaussian hierarchical Bayesian model (CG-HBM), which forms a superclass of several inversion methods for source localization of brain activity using somatosensory evoked potential (SEP) and field (SEF) measurements. The goal of this proof-o...

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Bibliographic Details
Main Authors: Atena Rezaei, Marios Antonakakis, MariaCarla Piastra, Carsten H. Wolters, Sampsa Pursiainen
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Brain Sciences
Subjects:
electroencephalography (EEG)
magnetoencephalography (MEG)
somatosensory evoked potentials
somatosensory evoked fields
P20/N20 component
hierarchical bayesian model
Online Access:https://www.mdpi.com/2076-3425/10/12/934

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