Description du sujet de thèse

Mechanisms of neural adaptation after cervical spinal cord injury and synchronized stimulation as a therapeutic approach to prevent diaphragm atrophy: Longitudinal evaluation by MRI

Contexte de travail

Cervical spinal cord injuries (SCI) severely impair both motor and respiratory functions, often leaving patients dependent on mechanical ventilation (MV), which in turn worsens diaphragm dysfunction and limits recovery. A new non-invasive, breathing-synchronized stimulation system (rSynES), developed by Dr. Isabelle Vivodtzev, targets accessory respiratory muscles and has shown promising results in improving respiratory function. Suggesting that it may activate spinal networks.
This PhD project aims to investigate the underlying mechanisms of rSynES-induced recovery using a mouse model of cervical SCI, through longitudinal assessment of molecular and cellular changes. Advanced imaging techniques, including glutamate-sensitive CEST-MRI (gluCEST), developed by Dr. Julien Flament, will be used to monitor neuronal integrity and metabolic alterations at the lesion site.
In addition, we will study the mechanisms of neuroplasticity. For example, we will assess the reorganization and survival of motor neurons using synaptic markers and analyses of nerve fiber regrowth. Tracing techniques will allow us to observe the connections from the brain to the spinal cord. Inflammation will be measured using immunostaining and western blot."

We are looking for a student who has completed:
A Master's degree (M2) in Neuroscience or Physiology with an interest in imaging and programming
or
An engineering degree or Master's in Computer Science, Programming, Biomedical Engineering, Medical Imaging, or Biophysics, with a strong interest in neuroscience and/or respiratory physiology.

Informations complémentaires

A significant part of the is thesis (1 about year) will be carried out at the Molecular Imaging Research Center MIRCen-CEA located in Fontenay-aux-Roses, a multidisciplinary center situated at the interface between physics and biology. Consequently, the candidate must demonstrate skills and a strong interest in these two disciplines. Additionally, the candidate must show an aptitude for data processing and numerical simulation. Proficiency in programming tools (Matlab, Python, C++) is essential, and knowledge of NMR/MRI would be a valuable asset.