Trial reportFrontiers in neural circuits2018
Dynamic Information Flow Based on EEG and Diffusion MRI in Stroke: A Proof-of-Principle Study.
Trial report in Frontiers in neural circuits, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 22 citations in OpenAlex.
- The Role of Hemispheric Sensory Shifts: Impacts on Stretch Reflex and Motor Plasticity Post-Stroke.Medical hypotheses · 2025Article
- How the Somatosensory System Adapts to the Motor Change in Stroke: A Hemispheric Shift?Medical hypotheses · 2024Article
- Alteration of Cortical Somatosensory Feedback in Post-Stroke Movement Control.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2024Article
- Cortical Reorganization of Early Somatosensory Processing in Hemiparetic Stroke.Journal of clinical medicine · 2022Article
- Structure supports function: Informing directed and dynamic functional connectivity with anatomical priors.Network neuroscience (Cambridge, Mass.) · 2022Article
- Nonlinear Modeling of Cortical Responses to Mechanical Wrist Perturbations Using the NARMAX Method.IEEE transactions on bio-medical engineering · 2021Article
- Limited capacity for ipsilateral secondary motor areas to support hand function post-stroke.The Journal of physiology · 2020Article
- Determining the Online Measurable Input Variables in Human Joint Moment Intelligent Prediction Based on the Hill Muscle Model.Sensors (Basel, Switzerland) · 2020Article
- MEG Source Imaging and Group Analysis Using VBMEG.Frontiers in neuroscience · 2019Article
Corrections and comments
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Authors and funding
9 authors at 6 institutions in 4 countries.
Funding
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.