Spatial resolution for EEG source reconstruction—A simulation study on SEPs

Kalogianni, Konstantina; Munck, Jan C. de; Nolte, Guido; Vardy, Alistair N.; Helm, F.C.T. van der; Daffertshofer, Andreas

doi:10.1016/j.jneumeth.2018.02.016

Cited by 17 publications

(8 citation statements)

References 52 publications

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“…Therefore, a quantitative evaluation is needed to assess how much task-relevant cortical source activity and dynamics were captured in the VBMEG method. In this proof of principle study, we assessed the performance of EEG source localization and LCD modeling in the VBMEG method by the VAF (Vlaar et al, 2017 ; Kalogianni et al, 2018b ). The VAF is a summary of how much of the variability of the data can be explained by a fitted model.…”

Section: Discussionmentioning

confidence: 99%

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Dynamic Information Flow Based on EEG and Diffusion MRI in Stroke: A Proof-of-Principle Study

Filatova

Yang

Dewald

et al. 2018

Front. Neural Circuits

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In hemiparetic stroke, functional recovery of paretic limb may occur with the reorganization of neural networks in the brain. Neuroimaging techniques, such as magnetic resonance imaging (MRI), have a high spatial resolution which can be used to reveal anatomical changes in the brain following a stroke. However, low temporal resolution of MRI provides less insight of dynamic changes of brain activity. In contrast, electro-neurophysiological techniques, such as electroencephalography (EEG), have an excellent temporal resolution to measure such transient events, however are hindered by its low spatial resolution. This proof-of-principle study assessed a novel multimodal brain imaging technique namely Variational Bayesian Multimodal Encephalography (VBMEG), which aims to improve the spatial resolution of EEG for tracking the information flow inside the brain and its changes following a stroke. The limitations of EEG are complemented by constraints derived from anatomical MRI and diffusion weighted imaging (DWI). EEG data were acquired from individuals suffering from a stroke as well as able-bodied participants while electrical stimuli were delivered sequentially at their index finger in the left and right hand, respectively. The locations of active sources related to this stimulus were precisely identified, resulting in high Variance Accounted For (VAF above 80%). An accurate estimation of dynamic information flow between sources was achieved in this study, showing a high VAF (above 90%) in the cross-validation test. The estimated dynamic information flow was compared between chronic hemiparetic stroke and able-bodied individuals. The results demonstrate the feasibility of VBMEG method in revealing the changes of information flow in the brain after stroke. This study verified the VBMEG method as an advanced computational approach to track the dynamic information flow in the brain following a stroke. This may lead to the development of a quantitative tool for monitoring functional changes of the cortical neural networks after a unilateral brain injury and therefore facilitate the research into, and the practice of stroke rehabilitation.

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Section: Discussionmentioning

confidence: 99%

“…The accuracy of source localization and dynamic information flow estimation was evaluated by calculating the VAF (Vlaar et al, 2017 ; Kalogianni et al, 2018b ). For source localization, the estimated sources were used to generate an estimated EEG signal

, which was compared with collected EEG signal M .…”

Section: Methodsmentioning

confidence: 99%

Dynamic Information Flow Based on EEG and Diffusion MRI in Stroke: A Proof-of-Principle Study

Filatova

Yang

Dewald

et al. 2018

Front. Neural Circuits

View full text Add to dashboard Cite

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“…fMRI has high spatial resolution (at the millimetre level), but its low temporal resolution limits its ability to image transient neural activity (Eichele et al, 2005; Goldman et al, 2009; Walz et al, 2014; Iannaccone et al, 2015). EEG and its magnetic counterpart, MEG, have high temporal resolution (at the millisecond level) while their spatial resolution is low due to the inverse problem (Kalogianni et al, 2018): that is, the problem of extracting 3D source activity within the brain from 2D scalp recordings is ill-posed because different source configurations can generate the same electric potentials on the scalp (Helmholtz, 1853; Kalogianni et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Single-Trial EEG-fMRI Reveals the Generation Process of the Mismatch Negativity

Liu

Yuan

et al. 2019

Front. Hum. Neurosci.

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Although research on the mismatch negativity (MMN) has been ongoing for 40 years, the generation process of the MMN remains largely unknown. In this study, we used a single-trial electro-encephalography (EEG)-functional magnetic resonance imaging (fMRI) coupling method which can analyze neural activity with both high temporal and high spatial resolution and thus assess the generation process of the MMN. We elicited the MMN with an auditory oddball paradigm while recording simultaneous EEG and fMRI. We divided the MMN into five equal-durational phases. Utilizing the single-trial variability of the MMN, we analyzed the neural generators of the five phases, thereby determining the spatiotemporal generation process of the MMN. We found two distinct bottom-up prediction error propagations: first from the auditory cortex to the motor areas and then from the auditory cortex to the inferior frontal gyrus (IFG). Our results support the regularity-violation hypothesis of MMN generation.

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“…37,[40][41][42][43][44] Although these results cannot simply be correlated with human experiments, it suggests the brain's remaining activity may explain the NDE. 45,46 As mentioned earlier, we have found, from anecdotal observations, that occasionally, when teaching CP to students, they would relive their previous NDE experience during their CP. Hence, it became clear that the four attributes described by Moody 47,48 to NDEs also applied to SCEs.…”

Section: Ceeg For Nde and Scementioning

confidence: 55%

Continuous EEG of memories of Near-death and mystical experiences: Preliminary research

Machado¹,

Newberg²,

Machado³

et al. 2022

World J. Adv. Res. Rev.

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We recently recorded, processed, and published brain activity by quantitative electroencephalography (QEEG) and quantitative electroencephalography (QEEGt), comparing separate subjects remembering their near-death experience (NDE) and mystical experience. Our studies refer to a mystical experience as a spiritual contemplative experience (SCE). We found neural and Greyson Scale (GS) correlations between them. This study is a real-time enhancement of that study using the emerging technology of continuous EEG monitoring (CEEG), which intensive care unit (ICU) professionals use to identify malignant EEG patterns quickly and provide care effectively. EEG monitoring encompasses a wide range of technical and clinical issues in successfully monitoring critically ill patients to detect significant changes in cerebral function and prevent serious neuronal injury over time. Because the brain undergoes continuous and dynamic changes, CEEG was considered an important method for real-time monitoring of functional brain changes while remembering near-death experiences (NDE) and spiritual contemplative experience (SCE). The CEEG envelope showed an incremental amplitude coinciding with NDE and SCE remembering the time, but an increase of amplitude was greater for SCE. CEEG also demonstrated a greater amplitude in frontal lobes for SCE. Statistical increments of absolute power for alpha and gamma bands were demonstrated during both NDE and SCE. We conclude that CEEG is a useful method for continuously assessing dynamic changes while remembering NDE and SCE.

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Spatial resolution for EEG source reconstruction—A simulation study on SEPs

Cited by 17 publications

References 52 publications

Dynamic Information Flow Based on EEG and Diffusion MRI in Stroke: A Proof-of-Principle Study

Dynamic Information Flow Based on EEG and Diffusion MRI in Stroke: A Proof-of-Principle Study

Single-Trial EEG-fMRI Reveals the Generation Process of the Mismatch Negativity

Continuous EEG of memories of Near-death and mystical experiences: Preliminary research

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