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Epilepsies caused by genetic mutations: signal processing and computational modeling

18 Octobre 2024

Catégorie : Post-doctorant

Post-doc or Research Engineer position offer (ref: RHU2024-MICRO)

Epilepsies caused by genetic mutations: signal processing and computational modeling

Context. Developmental and epileptic encephalopathies (DEEs) are a group of severe rare diseases where the combined effect of seizures, most often drug resistant, and the non-seizures consequences of the disease etiology, often genetic, entail a debilitating encephalopathy with drastic effects on the neurodevelopmental, psychiatric, and motor abilities of the patients. DEEs due to potassium channel mutations (K-DEEs) are emblematic of this disease presentation.

Rationale. The mechanisms underlying the relationship between i) the molecular effect of a gene mutation (KCNB1/KCNT1/KCNA2) on specific voltage gated potassium channel function, and ii) the patient-specific phenotypes observed in scalp-recorded EEG signals remain elusive. Computational models inspired from neuronal physiology is now recognized as a most efficient way to bridge the gap between i) changes occurring at the level of neurons and neuronal circuits and ii) electroencephalographic (EEG) signals recorded in patients containing markers of the underlying pathology.

 

Objective. The objective of the proposed research position is to design novel neuro-inspired models taking into account the molecular effect of a gene mutation on the specific voltage-gated potassium (K) channel function and the specific phenotypes observed in patients (scalp-recorded EEG signals) and in genetically-modified mice (local field potentials) in which downregulation or upregulation of K channels is induced.

Methods. Detailed multicompartment models (i.e. including dendrites, soma and axon) will be developed. They will be based on Hodgkin and Huxley's (HH) formalism. They will describe both passive (membrane capacitance, axial resistivity, leakage conductance, and membrane time constant) and active (voltage-gated and ligand-gated ion channels) membrane properties. The channel pathogenic variants of KCNB1/KCNT1/KCNA2 mutations identified in 2 other work packages (1 & 2) will be inserted in the membrane in order to study the impact of the channel mutation on the firing rate curves of considered neuron subtypes, typically pyramidal neurons (PYR), somatostatin (SST-), parvalbumin (PV-), and vasoactive intestinal polypeptide (VIP-) positive interneurons. Optimization methods will be developed for identifying optimal parameters minimizing the distance between real and simulated electrophysiological signals (LFPs). Models will use the Hodgkin & Huxley formalism. They will be developed in Python. They will extend already-existing models at cellular level. Strong background is available (https://perso.univ-rennes1.fr/fabrice.wendling/).

Scientific domains. Engineering (computational, biomedical); Neurophysiology; Neuroscience; Neurology; Computer Science (implementation of Python routines into an existing software application named COALIA).

Scientific environment. This research will benefit from an outstanding clinical research environment, centered around the largest curated K-DEE cohorts, coordinated by the Necker reference center for rare epilepsies (Prof. Rima Nabbout), and assembling an extensive group of experts from various specializations, including clinical, electrophysiological, psychological, computational, translational research, biotechnology and pharma industry.

Candidate profile. The research project is at the interface between biomathematics (neuro-inspired models) and neuroscience/neurology (epilepsy). The Post-doc/Engineer fellow (PhD level) will preferably have a strong background in computational neuroscience/systems biology or in electrical engineering with experience in bio-signal processing. Knowledge in electrophysiology and/or EEG analysis would be an asset.

Contract

The position will be opened November. 1st, 2024 (flexible). The contract is for 3 years (flexible). The employer is the University of Rennes. The competitive salary will be according to experience (2350 Euros net, minimum). The candidate will also have access to the French system benefits.

Location in the city of Rennes, France. LTSI-Inserm laboratory, University of Rennes. In addition, the hired person will have the opportunity to actively collaborate with other groups involved in the innov4epik RHU project (2024-2029), funded by the French National Research Agency (ANR).

Contact (please provide resume, cover letter and email of 2 references)

Pascal Benquet (Prof Univ Rennes, LTSI, France) Email: pascal.benquet@univ-rennes.fr

Fabrice Wendling (DR Inserm, LTSI, France) Email: fabrice.wendling@inserm.fr