A5054717552- Neural dynamics and brain function
- Functional Brain Connectivity Studies
- Nonlinear Dynamics and Pattern Formation
- EEG and Brain-Computer Interfaces
- Advanced Neuroimaging Techniques and Applications
- Advanced MRI Techniques and Applications
- stochastic dynamics and bifurcation
- Health, Environment, Cognitive Aging
- Neural Networks and Applications
- Photoreceptor and optogenetics research
- Health disparities and outcomes
- Mental Health Research Topics
- Cell Image Analysis Techniques
- Complex Systems and Time Series Analysis
- Neuroscience and Neural Engineering
- Influenza Virus Research Studies
- COVID-19 epidemiological studies
- Scientific Computing and Data Management
- Neurological disorders and treatments
- Visual perception and processing mechanisms
- Heart Rate Variability and Autonomic Control
- Slime Mold and Myxomycetes Research
- COVID-19 Pandemic Impacts
- Neuroscience and Music Perception
- Stroke Rehabilitation and Recovery
Institut de Neurosciences des Systèmes
2016-2025
Inserm
2016-2025
Aix-Marseille Université
2016-2025
Institut National de Recherche en Santé Publique
2021
Centre National de la Recherche Scientifique
2016
Ulsan National Institute of Science and Technology
2016
Institut des Sciences du Mouvement Etienne-Jules Marey
2016
Institut des Sciences Moléculaires
2016
Lancaster University
2011-2014
Saints Cyril and Methodius University of Skopje
2008
Abstract Urban-living individuals are exposed to many environmental factors that may combine and interact influence mental health. While individual of an urban environment have been investigated in isolation, no attempt has made model how complex, real-life exposure living the city relates brain health, this is moderated by genetic factors. Using data 156,075 participants from UK Biobank, we carried out sparse canonical correlation analyses investigate relationships between environments...
ABSTRACT Virtual brain twins are personalized, generative and adaptive models based on data from an individual’s for scientific clinical use. After a description of the key elements virtual twins, we present standard model personalized whole-brain network models. The personalization is accomplished using subject’s imaging by three means: (1) assemble cortical subcortical areas in subject-specific space; (2) directly map connectivity into models, which can be generalized to other parameters;...
Information transmission in the human brain is a fundamentally dynamic network process. In partial epilepsy, this process perturbed and highly synchronous seizures originate local network, so-called epileptogenic zone (EZ), before recruiting other close or distant regions. We studied patient-specific models of 15 drug-resistant epilepsy patients with implanted stereotactic electroencephalography (SEEG) electrodes. Each personalized model was derived from structural data magnetic resonance...
The timing of activity across brain regions can be described by its phases for oscillatory processes, and is crucial importance functioning. structure the constrains dynamics through delays due to propagation strengths white matter tracts. We use self-sustained delay-coupled, non-isochronous, nonlinearly damped chaotic oscillators study how spatio-temporal organization governs phase lags between coherent regions. In silico results network model demonstrate a robust switching from in-...
Abstract That attention is a fundamentally rhythmic process has recently received abundant empirical evidence. The essence of temporal attention, however, to flexibly focus in time. Whether this function constrained by an underlying neural mechanism unknown. In six interrelated experiments, we behaviourally quantify the sampling capacities periodic during auditory or visual perception. We reveal presence limited attentional capacities, with optimal rate ~1.4 Hz audition and ~0.7 vision....
Drug-resistant focal epilepsy is a large-scale brain networks disorder characterized by altered spatiotemporal patterns of functional connectivity (FC), even during interictal resting state (RS). Although RS-FC-based metrics can detect these changes, results from RS magnetic resonance imaging (RS-fMRI) studies are unclear and difficult to interpret, the underlying dynamical mechanisms still largely unknown. To better capture dynamics, we phenomenologically extended neural mass model partial...
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...
Model-based data analysis of whole-brain dynamics links the observed to model parameters in a network neural masses. Recently, studies focused on role regional variance parameters. Such analyses however necessarily depend properties preselected mass model. We introduce method infer from functional both representing and region- subject-specific while respecting known structure. apply human resting-state fMRI. find that underlying can be described as noisy fluctuations around single fixed...
Abstract Structural connectivity of the brain at different ages is analyzed using diffusion-weighted magnetic resonance imaging (MRI) data. The largest decrease streamlines found in frontal regions and for long inter-hemispheric links. average length tracts also decreases, but clustering unaffected. From functional MRI we identify age-related changes dynamic (dFC) spatial covariation features (FC) links captured by metaconnectivity. They indicate more stable dFC, wider range variance MC,...
Abstract In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration modelling at multiple scales—from molecules to the whole brain. Major are emerging intersection of neuroscience with technology computing. This science combines high-quality research, across scales, culture multidisciplinary large-scale collaboration, translation into applications. As pioneered in Europe’s Human Brain Project...
We consider the Kuramoto model of an ensemble interacting oscillators allowing for arbitrary distribution frequencies and coupling strengths. define a family traveling wave states as stationary in rotating frame, derive general equations their parameters. suggest empirical stability conditions which, case incoherence, become exact. In addition to making new theoretical predictions, we show that many earlier results follow naturally from our framework. The are applicable scientific contexts...
The precise mechanisms underlying general anaesthesia pose important and still open questions. To address them, we have studied induced by the widely used (intravenous) propofol (inhalational) sevoflurane anaesthetics, computing cross-frequency coupling functions between neuronal, cardiac respiratory oscillations in order to determine their mutual interactions. phase domain function reveals form of defining mechanism an interaction, as well its strength. Using a method based on dynamical...
Architecture of phase relationships among neural oscillations is central for their functional significance but has remained theoretically poorly understood. We use phenomenological model delay-coupled oscillators with increasing degree topological complexity to identify underlying principles by which the spatio-temporal structure brain governs lags between oscillatory activity at distant regions. Phase relations and regions stability are derived numerically confirmed two networks randomly...
Two structurally connected brain regions are more likely to interact, with the lengths of structural bundles, their widths, myelination, and topology connectome influencing timing interactions. We introduce an in vivo approach for measuring functional delays across whole humans (of either sex) using magneto/electroencephalography (MEG/EEG) integrating them bundles. The resulting topochronic map delays/velocities shows that larger bundles have faster velocities. estimated multiple sclerosis...
The mechanisms of cognitive decline and its variability during healthy aging are not fully understood, but have been associated with reorganization white matter tracts functional brain networks. Here, we built a network modeling framework to infer the causal link between structural connectivity architecture consequent in aging. By applying in-silico interhemispheric degradation connectivity, reproduced process dedifferentiation Thereby, found global modulation dynamics by increase age, which...
We introduce a generalization of the Kuramoto model by explicit consideration time-dependent parameters. The oscillators' natural frequencies and/or couplings are supposed to be influenced external, time-dependant fields, with constant or randomly-distributed strengths. As result, dynamics an external system is being imposed on top autonomous one, scenario that cannot treated adequately previous (adiabatic) approaches. now propose analysis which describes faithfully overall system.
Network couplings of oscillatory large-scale systems, such as the brain, have a space-time structure composed connection strengths and signal transmission delays. We provide theoretical framework, which allows treating spatial distribution time delays with regard to synchronization, by decomposing it into patterns therefore reducing stability analysis tractable problem finite set delay-coupled differential equations. analyze delay-structured networks phase oscillators we find that, depending...
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)...
Synchronization is fundamental for information processing in oscillatory brain networks and strongly affected by time delays via signal propagation along long fibers. Their effect, however, less evident spiking neural given the discrete nature of spikes. To bridge gap between these different modeling approaches, we study synchronization conditions, dynamics underlying synchronization, role delay a two-dimensional network model composed adaptive exponential integrate-and-fire neurons. Through...
Whole-brain simulations are a valuable tool for gaining insight into the multiscale processes that regulate brain activity. Due to complexity of brain, it is impractical include all microscopic details in simulation. Hence, researchers often simulate as network coupled neural masses, each described by mean-field model. These models capture essential features neuronal populations while approximating most biophysical details. However, may be important certain parameters significantly impact...
Whole-brain simulations are a valuable tool for gaining insight into the multiscale processes that regulate brain activity. Due to complexity of brain, it is impractical include all microscopic details in simulation. Hence, researchers often simulate as network coupled neural masses, each described by mean-field model. These models capture essential features neuronal populations while approximating most biophysical details. However, may be important certain parameters significantly impact...
The functioning of brain networks can be broadly categorized as an interplay two main contributors, namely the neurological processes dictating local dynamics and patterns anatomical connections that enable interactions between various processes, resulting in a global emergent behavior. Using Brain Network Modeling we describe constraints structure upon resting state human brain. We identify low-dimensional representation states, Resting State Manifold (RSM), leveraging network degeneracy...