A5047727568- Neural dynamics and brain function
- Functional Brain Connectivity Studies
- EEG and Brain-Computer Interfaces
- Advanced Neuroimaging Techniques and Applications
- stochastic dynamics and bifurcation
- Advanced MRI Techniques and Applications
- Nonlinear Dynamics and Pattern Formation
- Neuroscience and Neuropharmacology Research
- Motor Control and Adaptation
- Neuroscience and Neural Engineering
- Neurological disorders and treatments
- Photoreceptor and optogenetics research
- Action Observation and Synchronization
- Neural Networks and Applications
- Advanced Memory and Neural Computing
- Epilepsy research and treatment
- Mental Health Research Topics
- Transcranial Magnetic Stimulation Studies
- Visual perception and processing mechanisms
- Health, Environment, Cognitive Aging
- Balance, Gait, and Falls Prevention
- Bioinformatics and Genomic Networks
- Multiple Sclerosis Research Studies
- Neuroscience and Music Perception
- Cell Image Analysis Techniques
Aix-Marseille Université
2016-2025
Inserm
2016-2025
Institut de Neurosciences des Systèmes
2016-2025
National Tsing Hua University
2023-2024
University of Campania "Luigi Vanvitelli"
2022
Sapienza University of Rome
2022
Institute of Applied Science and Intelligent Systems
2022
National Research Council
2022
Astronomical Observatory of Capodimonte
2022
Monash University
2022
A growing body of neuroimaging research has documented that, in the absence an explicit task, brain shows temporally coherent activity. This so-called "resting state" activity or, more explicitly, default-mode network, been associated with daydreaming, free association, stream consciousness, or inner rehearsal humans, but similar patterns have also found under anesthesia and monkeys. Spatiotemporal network are both complex consistent, which raises question whether they expression interesting...
Seizures can occur spontaneously and in a recurrent manner, which defines epilepsy; or they be induced normal brain under variety of conditions most neuronal networks species from flies to humans. Such universality raises the possibility that invariant properties exist characterize seizures different physiological pathological conditions. Here, we analysed seizure dynamics mathematically established taxonomy based on first principles. For predominant class developed generic model called...
The ongoing activity of the brain at rest, i.e., under no stimulation and in absence any task, is astonishingly highly structured into spatiotemporal patterns. These patterns, called resting state networks, display low-frequency characteristics (<0.1 Hz) observed typically BOLD-fMRI signal human subjects. We aim here to understand origins through modeling via a global spiking attractor network brain. This approach offers realistic mechanistic model level each single area based on neurons...
Traditionally brain function is studied through measuring physiological responses in controlled sensory, motor, and cognitive paradigms. However, even at rest, the absence of overt goal-directed behavior, collections cortical regions consistently show temporally coherent activity. In humans, these resting state networks have been shown to greatly overlap with functional architectures present during consciously directed activity, which motivates interpretation rest activity as day dreaming,...
Functional connectivity (FC) sheds light on the interactions between different brain regions. Besides basic research, it is clinically relevant for applications in Alzheimer's disease, schizophrenia, presurgical planning, epilepsy, and traumatic injury. Simulations of whole-brain mean-field computational models with realistic determined by tractography studies enable us to reproduce accuracy aspects average FC resting state. Most studies, however, did not address prominent non-stationarity...
In a network of neuronal oscillators with time-delayed coupling, we uncover phenomenon enhancement neural synchrony by time delay: stable synchronized state exists at low coupling strengths for significant delays. By formulating master stability equation networks Hindmarsh-Rose neurons, show that there is always an extended region synchronous activity corresponding to strengths. Such could be achieved in the undelayed system only much higher This enhanced delay has important implications,...
In the human brain, spontaneous activity during resting state consists of rapid transitions between functional network states over time but underlying mechanisms are not understood. We use connectome based computational brain modeling to reveal fundamental principles how generates large-scale observable by noninvasive neuroimaging. used structural and neuroimaging data construct whole- models. With this novel approach, we that operates at maximum metastability, i.e. in a switching. addition,...
A semiquantitative nonlinear field theory of the brain is presented derived from quasimicroscopic conversion properties neural populations. Realistic anatomical connectivity conditions like long range excitation and short inhibition are used. Predictions our equation checked against experimental MEG results.
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,...
In this article, we describe the mathematical framework of computational model at core tool The Virtual Brain (TVB), designed to simulate collective whole brain dynamics by virtualizing structure and function, allowing simultaneous outputs a number experimental modalities such as electro- magnetoencephalography (EEG, MEG) functional Magnetic Resonance Imaging (fMRI). implementation allows for systematic exploration manipulation every underlying component large-scale network (BNM), neural...
Various methods have been proposed to characterize the functional connectivity between nodes in a network measured with different modalities (electrophysiology, magnetic resonance imaging etc.). Since measures of yield results for same dataset, it is important assess when and how they can be used. In this work, we provide systematic framework evaluating performance large range – based upon comprehensive portfolio models generating measurable responses. Specifically, benchmarked 42 using...
See Lytton (doi:10.1093/awx018) for a scientific commentary on this article.Neural network oscillations are fundamental mechanism cognition, perception and consciousness. Consequently, perturbations of activity play an important role in the pathophysiology brain disorders. When structural information from non-invasive imaging is merged with mathematical modelling, then generative models constitute personalized silico platforms exploration causal mechanisms function clinical hypothesis...
Brain function is thought to emerge from the interactions among neuronal populations. Apart traditional efforts reproduce brain dynamics micro- macroscopic scales, complementary approaches develop phenomenological models of lower complexity. Such typically generate only a few selected-ideally functionally relevant-aspects dynamics. Importantly, they often allow an understanding underlying mechanisms beyond computational reproduction. Adding detail these will widen their ability broader range...
Information processing in the brain is thought to rely on convergence and divergence of oscillatory behaviors widely distributed areas. This information flow captured its simplest form via concepts synchronization desynchronization related metrics. More complex forms are transient synchronizations multi-frequency with metrics cross-frequency coupling (CFC). It supposed that CFC plays a crucial role organization large-scale networks functional integration across large distances. In this...
The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based network model that integrates individual structural and functional data with neural population dynamics to support multi-scale inference. Simulated populations were linked by connectivity and, as novelty, driven electroencephalography (EEG) source activity. Simulations not only predicted subjects' resting-state magnetic resonance imaging...
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...