Viktor Jirsa's research while affiliated with Aix-Marseille Université and other places

Publications (427)

Article
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Deep brain stimulation (DBS) is a technique commonly used both in clinical and fundamental neurosciences. Classically, brain stimulation requires an implanted and wired electrode system to deliver stimulation directly to the target area. Although techniques such as temporal interference (TI) can provide stimulation at depth without involving any im...
Article
Full-text available
Brain pathologies are characterized by microscopic changes in neurons and synapses that reverberate into large scale networks altering brain dynamics and functional states. An important yet unresolved issue concerns the impact of patients’ excitation/inhibition profiles on neurodegenerative diseases including Alzheimer’s Disease, Frontotemporal Dem...
Preprint
Whole brain ionic and metabolic imaging has potential as a powerful tool for the characterization of brain diseases. In this study we combined sodium MRI ( ²³ Na MRI) and ¹ H-MR Spectroscopic Imaging ( ¹ H-MRSI) and compared ionic/metabolic changes probed by this multimodal approach to intracerebral stereotactic-EEG (SEEG) recordings. We applied a...
Preprint
A bstract Deep brain stimulation (DBS) within the subcallosal cingulate cortex (SCC) alleviates symptoms of depression through an unclear therapeutic mechanism. Precise stimulation of SCC white matter (SCCwm) is thought to be necessary to achieve therapeutic response, and clinical recordings can now be used to test this hypothesis. In this paper we...
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The possibility to identify subjects from their brain activity was met enthusiastically, as it bears the possibility to individualize brain analyses. However, the nature of the processes generating subject-specific features remains unknown, as the literature does not point to specific mechanisms. In particular, most of the current literature uses t...
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The functional organization of the brain is usually presented with a back-to-front gradient of timescales, reflecting regional specialization with sensory areas (back) processing information faster than associative areas (front), which perform information integration. However, cognitive processes require not only local information processing but al...
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Coupling neural simulators operating on different scales enhances the explanatory power of models in neuroscience. Individual regions of interest can be simulated on the cellular level to address mechanistic questions, while the remaining network is efficiently simulated on the population level. To offer this new co-simulation capability in neurosc...
Article
Addressing the multiscale organization of the brain, which is fundamental to the dynamic repertoire of the organ, remains challenging. In principle, it should be possible to model neurons and synapses in detail and then connect them into large neuronal assemblies to explain the relationship between microscopic phenomena, large-scale brain functions...
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The reconfiguration of large-scale interactions among multiple brain regions underpins complex behavior. It manifests in bursts of activations, called neuronal avalanches, which can be tracked non-invasively as they expand across the brain. Responding to a new task requires brain regions to appropriately reconfigure their interactions, which might...
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Whole-brain network modeling of epilepsy is a data-driven approach that combines personalized anatomical information with dynamical models of abnormal brain activity to generate spatio-temporal seizure patterns as observed in brain imaging signals. Such a parametric simulator is equipped with a stochastic generative process, which itself provides t...
Article
Electrical stimulation of peripheral nerves is a cornerstone of bioelectronic medicine. Effective ways to accomplish peripheral nerve stimulation noninvasively without surgically implanted devices is enabling for fundamental research and clinical translation. Here we demonstrate how relatively high frequency sine‐wave carriers (3 kHz) emitted by tw...
Article
Objective: The virtual epileptic patient (VEP) is a large-scale brain modeling method based on virtual brain technology, using stereoelectroencephalography (SEEG), anatomical data (magnetic resonance imaging [MRI] and connectivity), and a computational neuronal model to provide computer simulations of a patient's seizures. VEP has potential intere...
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Introduction: Computational brain network modeling using The Virtual Brain (TVB) simulation platform acts synergistically with machine learning (ML) and multi-modal neuroimaging to reveal mechanisms and improve diagnostics in Alzheimer's disease (AD). Methods: We enhance large-scale whole-brain simulation in TVB with a cause-and-effect model lin...
Preprint
Neurostimulation applied from deep brain stimulation (DBS) electrodes is an effective therapeutic intervention in patients suffering from intractable drug-resistant epilepsy when resective surgery is contraindicated or failed. Inhibitory DBS to suppress seizures and associated epileptogenic biomarkers could be performed with high-frequency stimulat...
Article
Full-text available
Simulating the resting-state brain dynamics via mathematical whole-brain models requires an optimal selection of parameters, which determine the model’s capability to replicate empirical data. Since the parameter optimization via a grid search (GS) becomes unfeasible for high-dimensional models, we evaluate several alternative approaches to maximiz...
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Understanding the human brain is a "Grand Challenge" for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by pr...
Article
Full-text available
Deep brain stimulation (DBS) of subcallosal cingulate white matter (SCCwm) alleviates symptoms of depression, but its mechanistic effects on brain dynamics remain unclear. In this study we used novel intracranial recordings (LFP) in n = 6 depressed patients stimulated with DBS around the SCCwm target, observing a novel dynamic oscillation (DOs). We...
Preprint
Healthy aging is accompanied by heterogeneous decline of cognitive abilities among individuals, especially during senescence. The mechanisms of this variability are not understood, but have been associated with the reorganization of white matter fiber tracts and the functional co-activations of brain regions. Here, we built a causal inference frame...
Preprint
The success of resective surgery for drug-resistant epilepsy patients hinges on the correct identification of the epileptogenic zone (EZ) consisting of the subnetwork of brain regions that underlies seizure genesis in focal epilepsy. The dynamic network biomarker (DNB) method is a dynamical systems-based network analysis approach for identifying su...
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Whole brain network models are now an established tool in scientific and clinical research, however their use in a larger workflow still adds significant informatics complexity. We propose a tool, RateML, that enables users to generate such models from a succinct declarative description, in which the mathematics of the model are described without s...
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Amyotrophic lateral sclerosis (ALS) is a multisystem disorder. This view is widely supported by clinical, molecular and neuroimaging evidence. As a consequence, predicting clinical features requires a comprehensive description of large-scale brain activity. Flexible dynamics is key to support complex adaptive responses. In health, brain activity re...
Preprint
The clinical connectome fingerprint (CCF) was recently introduced as a way to assess brain dynamics and used to predict the cognitive decline in preclinical Alzheimer's disease. In this paper we explore the performance of CCF in 47 Parkinson's disease (PD) patients and 47 healthy controls, under the hypothesis that patients would show reduced ident...
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In the field of computational epilepsy, neural field models helped to understand some large-scale features of seizure dynamics. These insights however remain on general levels, without translation to the clinical settings via personalization of the model with the patient-specific structure. In particular, a link was suggested between epileptic seiz...
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The majority of seizures recorded in humans and experimental animal models can be described by a generic phenomenological mathematical model, the Epileptor. In this model, seizure-like events (SLEs) are driven by a slow variable and occur via saddle-node (SN) and homoclinic bifurcations at seizure onset and offset, respectively. Here we investigate...
Article
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The Virtual Brain (TVB) is now available as open-source services on the cloud research platform EBRAINS. It offers software for constructing, simulating and analysing brain network models including the TVB simulator; magnetic resonance imaging (MRI) processing pipelines to extract structural and functional brain networks; combined simulation of lar...
Preprint
One-third of 50 million epilepsy patients worldwide suffer from drug resistant epilepsy and are candidates for surgery. Precise estimates of the epileptogenic zone networks (EZNs) are crucial for planning intervention strategies. Here, we present the Virtual Epileptic Patient (VEP), a multimodal probabilistic modeling framework for personalized end...
Article
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Networks in neuroscience determine how brain function unfolds, and their perturbations lead to psychiatric disorders and brain disease. Brain networks are characterized by their connectomes, which comprise the totality of all connections, and are commonly described by graph theory. This approach is deeply rooted in a particle view of information pr...
Article
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Neuroscience is home to concepts and theories with roots in a variety of domains including information theory, dynamical systems theory, and cognitive psychology. Not all of those can be coherently linked, some concepts are incommensurable, and domain-specific language poses an obstacle to integration. Still, conceptual integration is a form of und...
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A bstract Spontaneously fluctuating brain activity patterns emerge at rest and relate to brain functional networks involved in task conditions. Despite detailed descriptions of the spatio-temporal brain patterns, our understanding of their generative mechanism is still incomplete. Using a combination of computational modeling and dynamical systems...
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Structural connectivity of the brain at different ages is analyzed using diffusion-weighted Magnetic Resonance Imaging (MRI) data. The largest decrease of the number and average length of stream- lines is found for the long inter-hemispheric links, with the strongest impact for frontal regions. From the BOLD functional MRI (fMRI) time series we ide...
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In epilepsy, the most frequent surgical procedure is the resection of brain tissue in the temporal lobe, with seizure-free outcomes in approximately two-thirds of cases. However, consequences of surgery can vary strongly depending on the brain region targeted for removal, as surgical morbidity and collateral damage can lead to significant complicat...
Preprint
Full-text available
Brain pathologies are based on microscopic changes in neurons and synapses that reverberate into large scale networks altering brain dynamics and functional states. An important yet unresolved issue concerns the impact of patients excitation/inhibition profiles on neurodegenerative diseases including Alzheimer's disease, Frontotemporal Dementia and...
Article
Full-text available
Foreword from the editors. We hosted four keynote speakers: Wolf Singer, Bill Bialek, Danielle Bassett, and Sonja Gruen. They enlightened us about computations in the cerebral cortex, the reduction of high-dimensional data, the emerging field of computational psychiatry, and the significance of spike patterns in motor cortex. From the submissions,...
Preprint
Full-text available
Electrical stimulation of peripheral nerves is a cornerstone of bioelectronic medicine. Effective ways to accomplish peripheral nerve stimulation noninvasively without surgically implanted devices is enabling for fundamental research and clinical translation. Here we demonstrate how relatively high frequency sine-wave carriers (3 kHz) emitted by tw...
Preprint
Full-text available
Simulating the resting-state brain dynamics via mathematical whole-brain models requires an optimal selection of parameters, which determine the model’s capability to replicate empirical data. Since the parameter optimization via a grid search (GS) becomes unfeasible for high-dimensional models, we evaluate several alternative approaches to maximiz...
Article
Over the past 15 years, deep brain stimulation (DBS) has been actively investigated as a groundbreaking therapy for patients with treatment-resistant depression (TRD); nevertheless, outcomes have varied from patient to patient, with an average response rate of ∼50%. The engagement of specific fiber tracts at the stimulation site has been hypothesiz...
Preprint
Deep brain stimulation (DBS) is a technique commonly used both in clinical and fundamental neurosciences. Classically, brain stimulation requires an implanted and wired electrode system to deliver stimulation directly to the target area. Although techniques such as temporal interference (TI) can provide stimulation at depth without involving any im...
Article
Full-text available
Focal drug resistant epilepsy is a neurological disorder characterized by seizures caused by 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 is typically identified using stereotactic EEG recordings from the el...
Preprint
Numerous network and whole brain modeling approaches make use of mean-field models. Their relative simplicity allows studying network dynamics at a large scale. They correspond to lumped descriptions of neuronal assemblies connected via synapses. mean-field models do not consider the ionic composition of the extracellular space, which can change in...
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Flexibility is a key feature of psychological health, allowing the individual to dynamically adapt to changing environmental demands, which is impaired in many psychiatric disorders like obsessive–compulsive disorder (OCD). Adequately responding to varying demands requires the brain to switch between different patterns of neural activity, which are...
Article
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At rest, mammalian brains display remarkable spatiotemporal complexity, evolving through recurrent functional connectivity (FC) states on a slow timescale of the order of tens of seconds. While the phenomenology of the resting state dynamics is valuable in distinguishing healthy and pathologic brains, little is known about its underlying mechanisms...
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Model-based data analysis of whole-brain dynamics links the observed data to model parameters in a network of neural masses. In recent years a special focus was placed on the role of regional variance of model parameters for the emergent activity. Such analyses however depend on the properties of the employed neural mass model, which is often obtai...
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Hallmarks of neural dynamics during healthy human brain states span spatial scales from neuromodulators acting on microscopic ion channels to macroscopic changes in communication between brain regions. Developing a scale-integrated understanding of neural dynamics has therefore remained challenging. Here, we perform the integration across scales us...
Article
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Dynamics underlying epileptic seizures span multiple scales in space and time, therefore, understanding seizure mechanisms requires identifying the relations between seizure components within and across these scales, together with the analysis of their dynamical repertoire. In this view, mathematical models have been developed, ranging from single...
Article
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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 information in priors is still unknown. In this study, we introduce the use of fully Bayesian information criteria and leave-one-out cross-validation technique on...
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Brain activity during rest displays complex, rapidly evolving patterns in space and time. Structural connections comprising the human connectome are hypothesized to impose constraints on the dynamics of this activity. Here, we use magnetoencephalography (MEG) to quantify the extent to which fast neural dynamics in the human brain are constrained by...
Preprint
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Over 15 million patients with epilepsy worldwide do not respond to medical therapy and may benefit from surgical treatment. In cases of focal epilepsy, surgical treatment requires complete removal or disconnection of the epileptogenic zone (EZ). However, despite detailed multimodal pre-operative assessment, surgical success rates vary and may be as...
Preprint
Two structurally connected brain regions are more likely to interact, with the lengths of the structural bundles, their widths, myelination, and the topology of the structural connectome influencing the timing of the interactions. We introduce an in vivo approach for measuring functional delays across the whole brain using magneto/electroencephalog...
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Dynamical system tools offer a complementary approach to detailed biophysical seizure modeling, with a high potential for clinical applications. This review describes the theoretical framework that provides a basis for theorizing certain properties of seizures and for their classification according to their dynamical properties at onset and offset....
Article
Full-text available
In patients with focal drug-resistant epilepsy, electrical stimulation from intracranial electrodes is frequently used for the localization of seizure onset zones and related pathological networks. The ability of electrically stimulated tissue to generate beta and gamma range oscillations, called rapid-discharges, is a frequent indication of an epi...
Article
Brain connectome fingerprinting is rapidly rising as a novel influential field in brain network analysis. Yet, it is still unclear whether connectivity fingerprints could be effectively used for mapping and predicting disease progression from human brain data. We hypothesize that dysregulation of brain activity in disease would reflect in worse sub...
Article
Full-text available
Dynamical system tools offer a complementary approach to detailed biophysical seizure modeling, with a high potential for clinical applications. This review describes the theoretical framework that provides a basis for theorizing certain properties of seizures and for their classification according to their dynamical properties at onset and offset....
Article
Large neuroimaging datasets, including information about structural connectivity (SC) and functional connectivity (FC), play an increasingly important role in clinical research, where they guide the design of algorithms for automated stratification, diagnosis or prediction. A major obstacle is, however, the problem of missing features [e.g., lack o...
Chapter
Because individual differences influence the outcome of treatment approaches, the customization of healthcare options for individual patients should improve treatment results. We describe a novel approach to customizing interventions, The Virtual Brian (TVB), which combines individual patient brain structure and connectivity with high-performance c...
Preprint
Full-text available
INTRODUCTION Computational brain network modeling using The Virtual Brain (TVB) simulation platform acts synergistically with machine learning and multi-modal neuroimaging to reveal mechanisms and improve diagnostics in Alzheimer’s disease. METHODS We enhance large-scale whole-brain simulation in TVB with a cause-and-effect model linking local Amy...
Article
Full-text available
Intracranial electroencephalography is a standard tool in clinical evaluation of patients with focal epilepsy. Various early electrographic seizure patterns differing in frequency, amplitude, and waveform of the oscillations are observed. The pattern most common in the areas of seizure propagation is the so-called theta-alpha activity (TAA), whose...
Preprint
Full-text available
Dynamical systems tools offer a complementary approach to detailed biophysical seizure modeling, with high potential for clinical applications. This review describes the theoretical framework, allowing theorizing certain properties of seizures and their classifications according to their dynamics properties at onset and offset. We describe various...
Article
Full-text available
Surgical interventions in epileptic patients aimed at the removal of the epileptogenic zone have success rates at only 60-70%. This failure can be partly attributed to the insufficient spatial sampling by the implanted intracranial electrodes during the clinical evaluation, leading to an incomplete picture of spatio-temporal seizure organization in...
Preprint
Full-text available
The Virtual Brain (TVB) is now available as open-source cloud ecosystem on EBRAINS, a shared digital research platform for brain science. It offers services for constructing, simulating and analysing brain network models (BNMs) including the TVB network simulator; magnetic resonance imaging (MRI) processing pipelines to extract structural and funct...