ArticleFrontiers in neurology2015
The Virtual Brain: Modeling Biological Correlates of Recovery after Chronic Stroke.
Article in Frontiers in neurology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- HONeD-in on Brain Activity: Deconvolving Passive Diffusion on the Structural Network from Functional Brain Signals.bioRxiv : the preprint server for biology · 2026Article
- Capturing the emergent dynamical structure in biophysical neural models.PLoS computational biology · 2025Article
- Mapping global brain reconfigurations following local targeted manipulations.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Recent Progress in Brain Network Models for Medical Applications: A Review.Health data science · 2024Review
- Using causal methods to map symptoms to brain circuits in neurodevelopment disorders: moving from identifying correlates to developing treatments.Journal of neurodevelopmental disorders · 2022Review
- Task effects on functional connectivity measures after stroke.Experimental brain research · 2022Article
- Structure-function models of temporal, spatial, and spectral characteristics of non-invasive whole brain functional imaging.Frontiers in neuroscience · 2022Review
- Whole-Brain Modelling: Past, Present, and Future.Advances in experimental medicine and biology · 2022Article
- A new era for executive function research: On the transition from centralized to distributed executive functioning.Neuroscience and biobehavioral reviews · 2021Review
- Investigating the network consequences of focal brain lesions through comparisons of real and simulated lesions.Scientific reports · 2021Article
- Bridging Scales in Alzheimer's Disease: Biological Framework for Brain Simulation With The Virtual Brain.Frontiers in neuroinformatics · 2021Review
- Dynamical Mechanisms of Interictal Resting-State Functional Connectivity in Epilepsy.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2020Article
- Revisiting 'brain modes' in a new computational era: approaches for the characterization of brain-behavioural associations.Brain : a journal of neurology · 2020Article
- Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience.Frontiers in systems neuroscience · 2020Article
- Optimization of surgical intervention outside the epileptogenic zone in the Virtual Epileptic Patient (VEP).PLoS computational biology · 2019Article
- Linking Molecular Pathways and Large-Scale Computational Modeling to Assess Candidate Disease Mechanisms and Pharmacodynamics in Alzheimer's Disease.Frontiers in computational neuroscience · 2019Article
- Subject specificity of the correlation between large-scale structural and functional connectivity.Network neuroscience (Cambridge, Mass.) · 2019Article
- Differentiation of Alzheimer's disease based on local and global parameters in personalized Virtual Brain models.NeuroImage. Clinical · 2018Article
- Increased Modularity of Resting State Networks Supports Improved Narrative Production in Aphasia Recovery.Brain connectivity · 2016Article
- A new neuroinformatics approach to personalized medicine in neurology: The Virtual Brain.Current opinion in neurology · 2016Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
There currently remains considerable variability in stroke survivor recovery. To address this, developing individualized treatment has become an important goal in stroke treatment. As a first step, it is necessary to determine brain dynamics associated with stroke and recovery. While recent methods have made strides in this direction, we still lack physiological biomarkers. The Virtual Brain (TVB) is a novel application for modeling brain dynamics that simulates an individual's brain activity by integrating their own neuroimaging data with local biophysical models. Here, we give a detailed description of the TVB modeling process and explore model parameters associated with stroke. In order to establish a parallel between this new type of modeling and those currently in use, in this work we establish an association between a specific TVB parameter (long-range coupling) that increases after stroke with metrics derived from graph analysis. We used TVB to simulate the individual BOLD signals for 20 patients with stroke and 10 healthy controls. We performed graph analysis on their structural connectivity matrices calculating degree centrality, betweenness centrality, and global efficiency. Linear regression analysis demonstrated that long-range coupling is negatively correlated with global efficiency (P = 0.038), but is not correlated with degree centrality or betweenness centrality. Our results suggest that the larger influence of local dynamics seen through the long-range coupling parameter is closely associated with a decreased efficiency of the system. We thus propose that the increase in the long-range parameter in TVB (indicating a bias toward local over global dynamics) is deleterious because it reduces communication as suggested by the decrease in efficiency. The new model platform TVB hence provides a novel perspective to understanding biophysical parameters responsible for global brain dynamics after stroke, allowing the design of focused therapeutic interventions.
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