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Exploring brain communication pathways by combining diffusion based quantitative structural connectivity and EEG source imaging : application to physiological and epileptic networks

Applicant Hagmann Patric
Number 170873
Funding scheme Sinergia
Research institution Département de radiologie médicale Centre Hospitalier Universitaire Vaudois University of Lausanne
Institution of higher education University of Lausanne - LA
Main discipline Interdisciplinary
Start/End 01.03.2017 - 28.02.2021
Approved amount 2'127'144.00
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All Disciplines (3)

Discipline
Interdisciplinary
Information Technology
Neurophysiology and Brain Research

Keywords (8)

diffusion MRI; effective connectivity; communication through coherence; connectome; electrical source imaging; functional dynamics; epilepsy; microstructural imaging

Lay Summary (French)

Lead
Explorer les mécanismes sous-jacents à la communication et au traitement de l’information dans le cerveau de manière non-invasive nécessite non seulement le développement d’outils combinant la capacité à caractériser la structure et mesurer l’activité neuronale mais également de nouveaux modèles neurophysiologiques basé sur l’expérimentation avec ces outils. Le projet se propose de réaliser ces développements.
Lay summary

Il existe un faisceau de preuve que la communication et le traitement de l’information dans le cerveau sont médiées par les fluctuations dynamiques de l’organisation d’un ensemble d’entités neuronales en un réseau qui est à la fois connecté structurellement et affiche une activité électrique cohérente. Pouvoir caractériser ces réseaux par des techniques d’imagerie non-invasives est crucial afin de pouvoir explorer leur rôle dans la cognition, le comportement et la maladie.

Le projet s’attache, d’une part, à développer les méthodes d’analyse permettant d’observer ces réseaux in-vivo en combinant l’imagerie par résonance magnétique – permettant de cartographier les faisceaux d’axones – et la localisation de source par électro-encephalographie – permettant d’enregistrer localement l’activité électrique neuronale. D’autre part le projet vise à modéliser au niveau informatique la représentation de l’information et la communication neuronale dans le réseau cérébral en étudiant la propagation de l’activité neuronale lors de stimuli visuels et lors de la propagation de crise épileptiques focales. Ce projet doit in-fine mettre à disposition de la communauté scientifique un outil logiciel permettant d’étudier la communication et la représentation de l’information neurale dans le cerveau de manière non-invasive et fournir de nouveaux modèles expliquant les mécanismes sous-jacents.

 Le projet relève de la recherche en neurosciences fondamentale et clinique. Pour mieux comprendre les mécanismes sous-jacents à la cognition, au comportement et aux maladies cérébrales, il est nécessaire de disposer d’outils non invasifs et de modèles neurophysiologiques. Dans le domaine de l’épileptologie, la meilleure compréhension des interactions dans les réseaux neuronaux pathologiques pourrait ultérieurement améliorer le traitement des patients résistants aux médicamenteux anti-épileptiques et qui sont candidat à une résection chirurgicale de leur foyer épileptique.

Direct link to Lay Summary Last update: 03.02.2017

Responsible applicant and co-applicants

Employees

Project partner

Publications

Publication
Estimating EEG Source Dipole Orientation Based on Singular-value Decomposition for Connectivity Analysis
Rubega M., Carboni M., Seeber M., Pascucci D., Tourbier S., Toscano G., Van Mierlo P., Hagmann P., Plomp G., Vulliemoz S., Michel C. M. (2018), Estimating EEG Source Dipole Orientation Based on Singular-value Decomposition for Connectivity Analysis, in Brain Topography.
Automated diagnosis of temporal lobe epilepsy in the absence of interictal spikes
Verhoeven Thibault, Coito Ana, Plomp Gijs, Thomschewski Aljoscha, Pittau Francesca, Trinka Eugen, Wiest Roland, Schaller Karl, Michel Christoph, Seeck Margitta, Dambre Joni, Vulliemoz Serge, van Mierlo Pieter (2018), Automated diagnosis of temporal lobe epilepsy in the absence of interictal spikes, in NeuroImage: Clinical, 17, 10-15.
Automated long-term EEG analysis to localize the epileptogenic zone
van Mierlo Pieter, Strobbe Gregor, Keereman Vincent, Birot Gwénael, Gadeyne Stefanie, Gschwind Markus, Carrette Evelien, Meurs Alfred, Van Roost Dirk, Vonck Kristl, Seeck Margitta, Vulliémoz Serge, Boon Paul (2017), Automated long-term EEG analysis to localize the epileptogenic zone, in Epilepsia Open, 2(3), 322-333.

Knowledge transfer events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
 One-day Workshop on Open, Reproducible and Replicatable Neuroscience with Connectome Mapper 3 training Workshop 06.10.2018 Lausanne, Switzerland


Awards

Title Year
Dr Bernd Vorderwülbecke, a German neurologist from the Charité, Berlin, will join our group for a 2-year research fellowship funded by the Deutsche Forschungsgemeinschaft (DFG). He will work on EEG-based connectivity and contribute to the Sinergia consortium with clinical and EEG expertise. Salary for a 1 year Post-doc with Prof Vulliemoz. 2019
Joint ReproNim/International Neuroscience Coordinating Facilities (INCF) Fellowship 2019 Travel grant we do not know how much yet. 2019
Presenter’s travel award, Cosyne 2019 2019

Associated projects

Number Title Start Funding scheme
156874 Quantitative characterization of the connectome in the progression of psychosis 01.05.2015 Project funding (Div. I-III)
157063 Towards micro-structure-based tractography for quantitative brain connectivity analysis 01.10.2014 Project funding (Div. I-III)
144529 Fast Global Tractography for Sensitive MR Connectomics 01.10.2012 Project funding (Div. I-III)
159705 Temporal dynamics of whole-brain neuronal networks 01.05.2015 Project funding (Div. I-III)
175974 Regularized Linear Inverse Problems in Diffusion Magnetic Resonance and Ultrasound Imaging 01.11.2017 Project funding (Div. I-III)
130090 Imaging the connectome in the early phase of psychosis 01.01.2011 Project funding (Div. I-III)

Abstract

BACKGROUND Traditionally explorations of the structural connectivity patterns of the brain have been kept separate from the studies of brain functional dynamics and connectivity probably because the fields of expertise are quite different. However there are strong reasons to have those fields merge in a common framework. Indeed, neuronal assemblies are distributed networks of physically connected neurons transiently coupled by temporally coherent activity. They are of strong interest because they are believed to encode elementary cognitive acts or more generally produce temporal windows for neuronal communication. In epilepsy patients, the axonal scaffold sets the premises of seizure onset and shapes the patterns of seizure propagation. The critical and metastable state of brain functional activity is largely related to the underlying connectome architecture, as computational models show. Electrical Source Imaging (ESI), can map neuronal activity over the entire brain at appropriate temporal resolution but suffers from limited localization power and alone has strong limitations when studying neuronal assemblies or seizures onset and propagation since physical connectedness between sources is unknown. Furthermore functional coupling metrics derived from ESI are heavily influenced by assumptions on conduction delays. On the other hand diffusion MRI (dMRI) allows mapping the large-scale structural brain connectivity network, including length of fiber pathways and has the potential, in combination with additional MRI techniques, to inform on axonal diameter distribution and myelination. Those elements are essential to map propagation routs and conduction speed. Beyond the technical challenge of combining structural connectivity data derived from MRI with ESI, the analysis of the complex interplay between those two dimensions, namely structure and function, is not trivial and has only been partially addressed. Accordingly, in addition to the fusion of structural and functional data, there is a need for a new framework encompassing simultaneously the dynamic non-stationary nature of brain functional oscillations and the physical constraints on propagation through axonal connections to identify and follow across time and space information or seizure propagation. AIM OF THE PROJECT •Develop a reconstruction framework, which will provide, from ESI and dMRI data, a brain network representation. To each node, representing a cortical region, an electrical source will be associated (time series). Each edge will represent an existing fiber tract to which information of length, size, axonal diameter distribution and myelination will be associated.•Develop new methods to constrain ESI sources by using structural connectivity information.•Determine the connection specific propagation delays by combining microstructural information and phase lags in well-defined visual stimulus paradigms and intracranial electrophysiology.•Fit new computational models of spontaneous activity and epilepsy to study criticality in the brain. •Develop a dedicated analysis framework to follow and characterize the propagation of spatio-temporal coupling with a dynamic network model.•Explore with this framework mechanisms of connectome constrained functional connectivity in the visual system and associated feed-forward and -backward mechanisms.•Explore with this framework the mechanisms of seizure onset, propagation and inter-ictal resting activity in epileptic patients.EXPECTED IMPACT Providing a mapping and analysis framework enabling to follow at high spatial and temporal resolution the propagation of neuronal electrical activity through the connectome is of highest utility to a large community of systems, cognitive and clinical neuroscientists. In addition our expected contributions to the understanding of neuronal information flow during vision and characterization of seizure propagation through experimentation and modeling is expected to advance those specific fields significantly.
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