Applying stochastic spike train theory for high-accuracy human MEG/EEG
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Neuroscience Methods"
DOI: 10.1016/j.jneumeth.2020.108743
Abstract: BACKGROUND The accuracy of electroencephalography (EEG) and magnetoencephalography (MEG) in measuring neural evoked responses (ERs) is challenged by overlapping neural sources. This lack of accuracy is a severe limitation to the application of ERs to… read more here.
Keywords: meg eeg; theory; neural sources; accuracy ... See more keywords
Neural sources of prediction errors detect unrealistic VR interactions
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/ac69bc
Abstract: Objective. Neural interfaces hold significant promise to implicitly track user experience. Their application in virtual and augmented reality (VR/AR) simulations is especially favorable as it allows user assessment without breaking the immersive experience. In VR,… read more here.
Keywords: neural sources; prediction errors; eeg sources; sources prediction ... See more keywords
Ear-EEG sensitivity modeling for neural sources and ocular artifacts
Sign Up to like & getrecommendations! Published in 2023 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2022.997377
Abstract: The ear-EEG has emerged as a promising candidate for real-world wearable brain monitoring. While experimental studies have validated several applications of ear-EEG, the source-sensor relationship for neural sources from across the brain surface has not… read more here.
Keywords: neural sources; ear eeg; ocular artifacts; eeg sensitivity ... See more keywords