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Annonce

6 février 2019

Stage [6-9 mois, 2 offres] Hybrid modeling of personalized brain stimulation methods in the kHz range


Catégorie : Stagiaire


Two internship positions (6-9 months) are available at the LTSI and IETR labs (Rennes University) to contribute on a project entitled "Hybrid modeling of personalized brain stimulation methodes in the kHz range". One internship position will involve the use of computational models of epileptiform activity under brain stimulation, and the other position will involve the computation of detailed electric/magnetic field calculations at the brain level following brain stimulation. The internships can start immediately, and finish on October 15 at the latest. Please contact Julien Modolo (CR Inserm, LTSI, France, Email: Julien.modolo@inserm.fr) or Maxime Zhabodov (CR CNRS, IETR, France, Email: maxim.zhadobov@univ-rennes1.fr) for more information.

Topic: Hybrid modeling of personalized brain stimulation methods in the kHz range

(supported by CominLabs)

Background

Brain stimulation is a technique of increasing importance consisting in inducing changes in brain activity, mainly using electric or magnetic fields delivered invasively (intracranial) or non-invasively (scalp electrodes). The main applications of brain stimulation are diagnostic and therapeutic. In the case of epilepsy, a disease with a prevalence of approx. 60 millions of patients worldwide, a third of patients are drug-refractory (> 150,000 in France), and are therefore left of therapeutic options. For those patients, brain stimulation could represent an alternative. However, the brain stimulation protocols that have been investigated so far are mostly empirical, with little guidance from neurophysiological and biophysical consideration, and lack of mechanistic understanding, which is a major roadblock to provide novel therapeutic solutions to epileptic drug-refractory patients. Here, we propose a hybrid approach combining a careful description of the electromagnetic fields associated with brain stimulation and realistic dynamics of the neuronal networks close to the electrode.

Detail

The research project proposes a hybrid approach consisting in detailed dosimetry of the electromagnetic fields associated with brain stimulation on the one hand, coupled with biologically grounded computational models of neurons generating epileptiform activity on the other hand. This hybrid approach will offer individualized stimulation parameters optimizing the electric field induced in brain tissue, in terms of spatial extent, magnitude and dynamics.

-Objective: The general objective is to provide a new hybrid tool combining a realistic model of neuronal activity with a detailed calculation of electromagnetic fields induced in brain tissue by kHz-range stimulation.

-Data: Model data will be used to quantify the impact of brain stimulation in the kHz range. More specifically, the simulated electrical activity will include epileptiform activity, and its modulation by stimulation (duration and occurrence of epileptiform, events) will be quantified.

-Methods: We will extend a previously developed Hodgkin-Huxley model that simulates epileptiform activity at the single neuron level. The model will be modified to account for the contribution of an applied extracellular electric field, which will have a depolarizing (resp. hyperpolarizing) effect on neuron membranes). Also, full-wave time- and frequency-domain solvers will be used for computing the electric field induced in the brain models of increasing complexity.

Candidate profile

The project involves biophysics and computational modeling, at the Master level or last year of Engineering School level. Experience in biomedical engineering would be an asset, or in scientific computing and electrical engineering. The interns will join a multidisciplinary team including research scientists in biomedical engineering, signal processing, modeling and electrophysiology.

Location in the city of Rennes, France. LTSI and IETR laboratory, University of Rennes.

Contact

Julien Modolo (CR Inserm, LTSI, France, Email: Julien.modolo@inserm.fr)
Maxime Zhabodov (CR CNRS, IETR, France, Email:
maxim.zhadobov@univ-rennes1.fr)

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