2020-02865 - Post-Doctoral Research Visit F/M Tractography and connectivity analysis from advanced diffusion MRI for early depression diagnosis and characterization
Le descriptif de l’offre ci-dessous est en Anglais

Type de contrat : CDD

Contrat renouvelable : Oui

Niveau de diplôme exigé : Thèse ou équivalent

Fonction : Post-Doctorant

A propos du centre ou de la direction fonctionnelle

The Inria Rennes - Bretagne Atlantique Centre is one of Inria's eight centres and has more than thirty research teams. The Inria Center is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative PMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc.

Contexte et atouts du poste

Within the collaboration between Empenn Inria team and Inserm U1000 (Paris), funded by the Fondation de France

Mission confiée

Context

Psychiatric diseases, among which depression is major one, are still not fully understood. The exact mechanisms and brain modifications related to those diseases are especially complex to explain. Recent research advances have shown major changes but the connectivity alteration remains to be explained. Advanced MRI techniques including multi-shell diffusion imaging have shown a great potential to highlight subtle changes of microstructure in the brain. We are therefore looking at how these advanced MRI techniques may allow a better definition of the brain change patterns in major fiber bundles that are related to classical pathways involved in depression.

The Empenn research team is currently involved with the Rennes university hospital EA4712 in a multi-site project lead by Inserm U1000 in Paris, France. The goal of this project is to evaluate how the brains differ between healthy subjects and patients suffering from drug resistant and non-drug resistant depression. In turn the long-term goal of this study will be to evaluate from early imaging how young patients suffering from depression may be susceptible to become drug resistant. To do so, advanced MRI acquisitions are being performed both In Paris and in Rennes with advanced diffusion, and soon relaxometry data from which myelin information will also be extracted.

Principales activités

Scientific objectives

The major scientific objective for this post-doctoral position will be to develop and evaluate new methodologies to quantify microstructure changes along major fiber tracts of the brain using advanced diffusion models from diffusion MRI. To do so, the post-doctoral fellow will first evaluate methodologies to extract reliable brain fibers from diffusion MRI data as this is a major problem identified in the literature. Then he will propose new methods to compare brain fiber tracts, their associated microstructure information and brain connectivity inferred from those tracts. For these tasks, the post-doctoral fellow will build on previous works from the team on those topics as well as a literature review.

The post-doctoral researcher will then apply the developed tools to the databases acquired among the project. This includes the IMAGEN database acquired in Paris with over 100 patients each with advanced multi-shell diffusion MRI; the local databases from Rennes on depression that also include advanced diffusion MRI (CUSP sequence). From all this data, he will develop pipelines to analyze the data and evaluate the interest of diffusion MRI in depression early diagnosis.

In terms of methodology, the following domains will be covered in this post-doctoral position:

  • Advanced multi-shell diffusion MRI (multi-compartment models)
  • Fiber tractography from multi-compartment models
  • Analysis of fiber tracts and associated microstructure information
  • Connectivity analysis in controls and patients suffering from depression
  • Statistical comparison between groups of patients and/or controls

Compétences

This position will require strong knowledge both in applied mathematics (optimization, representations in Riemannian manifolds, statistics…) and in advanced image processing (tractography, tract-based analysis…). A PhD defended close to one of those domains will therefore be required. A good knowledge of computer science aspects is also mandatory, especially in object-oriented programming (C++), Python and Matlab.

Avantages

  • Subsidized meals
  • Partial reimbursement of public transport costs

Rémunération

Monthly gross salary amounting to 2653 euros