A5089030889- Functional Brain Connectivity Studies
- Neural dynamics and brain function
- Advanced Neuroimaging Techniques and Applications
- EEG and Brain-Computer Interfaces
- Advanced MRI Techniques and Applications
- Advanced Memory and Neural Computing
- Migration, Health and Trauma
- Neural Networks and Applications
- Epilepsy research and treatment
- Parallel Computing and Optimization Techniques
- Healthcare Systems and Reforms
- Global Public Health Policies and Epidemiology
- Health and Conflict Studies
- stochastic dynamics and bifurcation
- Global Maternal and Child Health
- Influenza Virus Research Studies
- Low-power high-performance VLSI design
- Neurological disorders and treatments
- Bayesian Methods and Mixture Models
- Scientific Computing and Data Management
- COVID-19 epidemiological studies
- COVID-19 Pandemic Impacts
- Ferroelectric and Negative Capacitance Devices
- Pharmaceutical Practices and Patient Outcomes
- Gaussian Processes and Bayesian Inference
Institut de Neurosciences des Systèmes
2014-2024
Inserm
2013-2024
Aix-Marseille Université
2014-2024
Office of the United Nations High Commissioner for Refugees
2017-2022
Institut National de Recherche en Santé Publique
2021
Intel (United States)
2018
Louisiana State University Health Sciences Center New Orleans
2011
Centre National de la Recherche Scientifique
2010-2011
Institut de Neurobiologie de la Méditerranée
2011
Florida Atlantic University
2010
We present TheVirtualBrain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different scales that underlie generation macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from backgrounds can benefit an integrative software supporting framework data management (generation, organization,...
Precise estimates of epileptogenic zone networks (EZNs) are crucial for planning intervention strategies to treat drug-resistant focal epilepsy. Here, we present the virtual epileptic patient (VEP), a workflow that uses personalized brain models and machine learning methods estimate EZNs aid surgical strategies. The structural scaffold patient-specific whole-brain network model is constructed from anatomical T1 diffusion-weighted magnetic resonance imaging. Each node equipped with...
Despite the importance and frequent use of Bayesian frameworks in brain network modeling for parameter inference model prediction, advanced sampling algorithms implemented probabilistic programming languages to overcome difficulties have received relatively little attention this context. In technical note, we propose a framework, namely Virtual Epileptic Patient (BVEP), which relies on fusion structural data individuals infer spatial map epileptogenicity personalized large-scale epilepsy...
Given the large burden of non-communicable diseases (NCDs) among both Syrian refugees and host communities within which they are settled, humanitarian actors government Lebanon face immense challenges in addressing health needs. This study assessed status, unmet needs, utilization services Lebanon.A cross-sectional survey was conducted using a two-stage cluster design with probability proportional to size sampling. To obtain information on chronic NCDs, respondents were asked series...
The Virtual Brain (TVB) is now available as open-source services on the cloud research platform EBRAINS (ebrains.eu). It offers software for constructing, simulating and analysing brain network models including TVB simulator; magnetic resonance imaging (MRI) processing pipelines to extract structural functional networks; combined simulation of large-scale networks with small-scale spiking automatic conversion user-specified model equations into fast code; simulation-ready patients healthy...
Abstract Objective The virtual epileptic patient (VEP) is a large‐scale brain modeling method based on technology, using stereoelectroencephalography (SEEG), anatomical data (magnetic resonance imaging [MRI] and connectivity), computational neuronal model to provide computer simulations of patient's seizures. VEP has potential interest in the presurgical evaluation drug‐resistant epilepsy by identifying regions most likely generate We aimed assess performance approach estimating...
Whole-brain modeling of epilepsy combines personalized anatomical data with dynamical models abnormal activities to generate spatio-temporal seizure patterns as observed in brain imaging data. Such a parametric simulator is equipped stochastic generative process, which itself provides the basis for inference and prediction local global dynamics affected by disorders. However, calculation likelihood function at whole-brain scale often intractable. Thus, likelihood-free algorithms are required...
Surgical interventions in epileptic patients aimed at the removal of epileptogenic zone have success rates only 60-70%. This failure can be partly attributed to insufficient spatial sampling by implanted intracranial electrodes during clinical evaluation, leading an incomplete picture spatio-temporal seizure organization regions that are not directly observed. Utilizing partial observations spreading through brain network, complemented assumption seizures spread along structural connections,...
Connectome-based modeling of large-scale brain network dynamics enables causal in silico interrogation the brain’s structure-function relationship, necessitating close integration diverse neuroinformatics fields. Here we extend open-source simulation software The Virtual Brain (TVB) to whole mouse based on individual diffusion magnetic resonance imaging (dMRI)-based or tracer-based detailed connectomes. We provide practical examples how use Mouse (TVMB) simulate activity, such as seizure...
Several automated parcellation atlases of the human brain have been developed over past decades, based on various criteria, and applied in basic clinical research. : Here we present Virtual Epileptic Patient (VEP) atlas that offers a new region labeling, which has for specific use domains epileptology functional neurosurgery is able to apply at individual patient’s level. It comprises 162 regions, including 73 cortical 8 subcortical regions per hemisphere. We demonstrate successful...
Individualized anatomical information has been used as prior knowledge in Bayesian inference paradigms of whole-brain network models. However, the actual sensitivity to such personalized priors is still unknown. In this study, we introduce use fully criteria and leave-one-out cross-validation technique on subject-specific assess different epileptogenicity hypotheses regarding location pathological brain areas based a priori from dynamical system properties. The Virtual Epileptic Patient...
Abstract Connectome-based models, also known as virtual brain models (VBMs), have been well established in network neuroscience to investigate pathophysiological causes underlying a large range of diseases. The integration an individual’s imaging data VBMs has improved patient-specific predictivity, although Bayesian estimation spatially distributed parameters remains challenging even with state-of-the-art Monte Carlo sampling. imply latent nonlinear state space driven by noise and input,...
Network neuroscience has proven essential for understanding the principles and mechanisms underlying complex brain (dys)function cognition. In this context, whole-brain network modeling—also known as virtual modeling—combines computational models of dynamics (placed at each node) with individual imaging data (to coordinate connect nodes), advancing our its neurobiological underpinnings. However, there remains a critical need automated model inversion tools to estimate control (bifurcation)...
Focal drug resistant epilepsy is a neurological disorder characterized by seizures caused abnormal activity originating in one or more regions together called as epileptogenic zone. Treatment for such patients involves surgical resection of affected regions. Epileptogenic zone typically identified using stereotactic EEG recordings from the electrodes implanted into patient's brain. Identifying challenging problem due to spatial sparsity electrode implantation. We propose probabilistic...
Abstract The process of making inference on networks spiking neurons is crucial to decipher the underlying mechanisms neural computation. Mean-field theory simplifies interactions between produce macroscopic network behavior, facilitating study information processing and computation within brain. In this study, we perform a mean-field model gain insight into likely parameter values, uniqueness degeneracies, also explore how well statistical relationship parameters maintained by traversing...
Current clinical methods often overlook individual variability by relying on population-wide trials, while mechanism-based trials remain underutilized in neuroscience due to the brain's complexity. A Virtual Brain Twin (VBT) is a personalized digital replica of an individual's brain, integrating structural and functional brain data into advanced computational models inference algorithms. By bridging gap between molecular mechanisms, whole-brain dynamics, imaging data, VBTs enhance...
TheVirtualBrain (TVB) is a neuroinformatics Python package representing theconvergence of clinical, systems, and theoretical neuroscience in the analysis,visualization modeling neural neuroimaging dynamics. TVB iscomposed flexible simulator for dynamics measured across scalesfrom local populations to large-scale byelectroencephalography (EEG), magnetoencephalography (MEG) functionalmagnetic resonance imaging (fMRI), core analytic visualizationfunctions, all accessible through web browser...
Graphics workloads are highly dynamic in nature, using multi-threaded SIMD execution units (EUs), fixed-function units, samplers, and media accelerators to provide ever-increasing amounts of graphics performance. These often limited by power thermal constraints, requiring voltage/frequency scaling (DVFS) the processor (GPU). This coarse-grain DVFS, driven a power-management IC (PMIC) setting shared rail voltage (V <inf xmlns:mml="http://www.w3.org/1998/Math/MathML"...
Abstract The brain at rest exhibits a spatio-temporally rich dynamics which adheres to systematic behaviours that persist in task paradigms but appear altered disease. Despite this hypothesis, many state do not act directly upon the and therefore cannot confirm hypotheses about its mechanisms. To address challenge, we combined transcranial magnetic stimulation (TMS) electroencephalography (EEG) study brain’s relaxation toward following transient perturbation. Specifically, TMS targeted...