A5014429750- Neural dynamics and brain function
- Functional Brain Connectivity Studies
- Complex Network Analysis Techniques
- Topological and Geometric Data Analysis
- Opinion Dynamics and Social Influence
- Nonlinear Dynamics and Pattern Formation
- Epilepsy research and treatment
- Advanced Neuroimaging Techniques and Applications
- Neuroscience and Neuropharmacology Research
- Neural Networks and Applications
- stochastic dynamics and bifurcation
- Slime Mold and Myxomycetes Research
- Gene Regulatory Network Analysis
- Infectious Encephalopathies and Encephalitis
- EEG and Brain-Computer Interfaces
- Advanced Memory and Neural Computing
- Extracellular vesicles in disease
- Neural Networks Stability and Synchronization
- Surgical Simulation and Training
- Distributed and Parallel Computing Systems
- Theoretical and Computational Physics
- Insect Pheromone Research and Control
- Olfactory and Sensory Function Studies
- Distributed Control Multi-Agent Systems
- Simulation Techniques and Applications
Amsterdam University Medical Centers
2020-2024
Vrije Universiteit Amsterdam
2020-2024
Universidad de Granada
2015-2024
Amsterdam Neuroscience
2021-2023
The higher-order interactions of complex systems, such as the brain are captured by their simplicial structure and have a significant effect on dynamics. However, existing dynamical models defined complexes make strong assumption that dynamics resides exclusively nodes. Here we formulate Kuramoto model which describes between oscillators placed not only nodes but also links, triangles, so on. We show can lead to an explosive synchronization transition using adaptive coupling dependent...
Recent studies on Alzheimer's disease (AD) suggest that tau proteins spread through the brain following neuronal connections. Several mechanisms could be involved in this process: spreading between regions interact strongly (functional connectivity); pattern of anatomical connections (structural or simple diffusion. Using magnetoencephalography (MEG), we investigated which pathways influence protein by modelling propagation process using an epidemic model. We compared modelled depositions...
Recently there is a surge of interest in network geometry and topology. Here we show that the spectral dimension plays fundamental role establishing clear relation between topological geometrical properties its dynamics. Specifically explore determining synchronization Kuramoto model. We synchronized phase can only be thermodynamically stable for dimensions above four entrainment oscillators found greater than two. numerically test our analytical predictions on recently introduced model...
The dynamics of networks neuronal cultures has been recently shown to be strongly dependent on the network geometry and in particular their dimensionality. However, this phenomenon so far mostly unexplored from theoretical point view. Here we reveal rich interplay between synchronization coupled oscillators context a simplicial complex model manifolds called Complex Network Manifold. generated by combine small world properties (infinite Hausdorff dimension) high modular structure with finite...
Abstract How to best define, detect and characterize network memory, i.e. the dependence of a network’s structure on its past, is currently matter debate. Here we show that memory temporal inherently multidimensional, introduce mathematical framework for defining efficiently estimating microscopic shape which characterises how activity each link intertwines with activities all other links. We validate our methodology range synthetic models, then study real-world networks spanning social,...
Abstract Triadic interactions in the brain are general mechanisms by which a node, e.g. neuron or glia cell such as astrocyte, can regulate directly link, synapse between other two nodes. The regulation takes place familiar way either depressing facilitating synaptic transmission. Such ubiquitous neural systems, accounting both for axo-axonic and tripartite synapses mediated astrocytes, instance, have been related to neuronal processes at different time-scales, including short- long-term...
Abstract Seizures represent a frequent symptom in gliomas and significantly impact patient morbidity quality of life. Although the pathogenesis tumor-related seizures is not fully understood, accumulating evidence indicates key role peritumoral microenvironment. Brain cancer cells interact with neurons by forming synapses them releasing exosomes, cytokines, other small molecules. Strong interactions among often lead to synchronization their activity. In this paper, we used an vitro model...
Triadic interactions are higher-order which occur when a set of nodes affects the interaction between two other nodes. Examples triadic present in brain glia modulate synaptic signals among neuron pairs or interneuron axo-axonic synapses enable presynaptic inhibition and facilitation, ecosystems one more species can affect species. On random graphs, percolation has been recently shown to turn into fully fledged dynamical process size giant component undergoes route chaos. However, many real...
Universality is one of the key concepts in understanding critical phenomena. However, for interacting inhomogeneous systems described by complex networks a clear relevant parameters universality still missing. Here we discuss role fundamental network parameter universality, spectral dimension. For this purpose, construct model where probability bond between two nodes proportional to power law nodes' distances. By explicit computation prove that dimension can be tuned continuously from $1$...
From social interactions to the human brain, higher-order networks are key describe underlying network geometry and topology of many complex systems. While it is well known that structure strongly affects its function, role has on emerging dynamical properties yet be clarified. In this perspective, spectral dimension plays a since determines effective for diffusion processes network. Despite relevance, theoretical understanding which mechanisms lead finite dimension, how can controlled,...
Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients. However, seizure-freedom currently achieved in only 2/3 patients after surgery. In this study we have developed an individualized computational model based on MEG brain networks to explore seizure propagation and efficacy different virtual resections. Eventually, goal obtain models optimize resection strategy outcome. We modelled as epidemic process using susceptible-infected (SI) individual derived from...
Abstract A fundamental question in neuroscience is how structure and function of neural systems are related. We study this interplay by combining a familiar auto-associative network with an evolving mechanism for the birth death synapses. feedback loop then arises leading to two qualitatively different types behaviour. In one, becomes heterogeneous dissasortative, system displays good memory performance; furthermore, optimised particular patterns stored during process. other, remains...
Abstract The success of epilepsy surgery in patients with refractory depends upon correct identification the epileptogenic zone (EZ) and an optimal choice resection area. In this study we developed individualized computational models based structural brain networks to explore impact different virtual resections on propagation seizures. seizures was modelled as epidemic process [susceptible-infected-recovered (SIR) model] individual derived from presurgical diffusion tensor imaging 19...
Nature exhibits countless examples of adaptive networks, whose topology evolves constantly coupled with the activity due to its function. The brain is an illustrative example a system in which dynamic complex network develops by generation and pruning synaptic contacts between neurons while memories are acquired consolidated. Here, we consider recently proposed developing model study how mechanisms responsible for evolution structure affect affected memory storage processes. Following recent...
Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients, but only leads to seizure freedom roughly two in three patients. To address this problem, we designed a patient-specific model combining large-scale magnetoencephalography (MEG) brain networks with an epidemic spreading model. This simple was enough reproduce stereo-tactical electroencephalography (SEEG) propagation patterns all patients (N = 15), when considering resection areas (RA) as seed. Moreover,...
Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients, but up to 50% patients continue have seizures one year after resection. In order aid presurgical planning and predict postsurgical outcome on a patient-by-patient basis, we developed framework individualized computational models that combines epidemic spreading with patient-specific connectivity epileptogeneity maps: Epidemic Spreading Seizure Surgery (ESSES). ESSES parameters were fitted in retrospective study (
The interplay between structure and function affects the emerging properties of many natural systems. Here we use an adaptive neural network model that couples activity topological dynamics reproduces experimental temporal profiles synaptic density observed in brain. We prove existence a transient period relatively high connectivity is critical for development system under noise circumstances, such resulting can recover stored memories. Moreover, show intermediate densities provide optimal...
Abstract Background Recent studies in Alzheimer’s disease (AD) suggest that tau proteins spread through the brain following neuronal connections. Several mechanisms could be involved this process: spreading between regions interact strongly (functionally connected); pattern of anatomical connections (structural connectivity); or simple diffusion to spatially adjacent (Euclidean distance (EC)). We investigated by modelling tau‐spreading process on these different networks, and compared...
Abstract BackgroundThe success of epilepsy surgery in patients with refractory depends upon correct identification the epileptogenic zone (EZ) and an optimal choice resection area. In this study we developed individualized computational models based structural brain networks to explore impact different virtual resections on propagation seizures.MethodsThe seizures was modelled as epidemic process (susceptible-infected-recovered (SIR) model) individual derived from presurgical diffusion...
Abstract Pathological hubs in the brain networks of epilepsy patients are hypothesized to drive seizure generation and propagation. In epilepsy-surgery patients, these have traditionally been associated with resection area: region removed during surgery goal stopping seizures, which is typically used as a proxy for epileptogenic zone. However, recent studies hypothesize that pathological may extend vicinity area, potentially complicating post-surgical control. Here we propose...
Triadic interactions are general mechanisms by which a node or neuron can regulate directly the link synapse between other two neurons. The regulation takes place in familiar way either depressing facilitating synaptic transmission. Such ubiquitous neural systems, accounting for axo-axonic synapses and tripartite mediated astrocytes, instance, have been related to neuronal processes at different time-scales, including short long-term plasticity. In field of network science, triadic shown...
Abstract Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients, but up to 50% patients continue have seizures one year after resection. In order aid presurgical planning and predict postsurgical outcome in a patient-by-patient basis, we developed framework individualized computational models that combine epidemic spreading with patient-specific connectivity epileptogeneity maps: Epidemic Spreading Seizure Surgery (ESSES). The ESSES parameters were fitted...