To carry out their activities, Research Teams of the Frédéric Joliot Institute for Life Sciences have developed high-profile technological platforms in many areas : biomedical imaging, structural biology, metabolomics, High-Throughput screening, level 3 microbiological safety laboratory...
All the news of the Institute of life sciences Frédéric Joliot
NEUROIMAGING SIGNATURES OF BRAIN DISORDERS
My research focuses on the design of cutting-edge machine learning and statistical models to uncover neural signatures that can predict psychiatric disorders. Our goal is to harness the power of data by overseeing the effective management of multiple large-scale national and European initiatives. This will allow us to train and refine AI models to their fullest potential.
Artificial Intelligence (AI) combined with neuroimaging opens up possibilities for personalized medicine. With this long-term objective, we developed four lines of research:
We investigated new predictive linear models that integrate prior biological knowledge to force the solution to adhere to biological priors, producing more plausible interpretable signatures. These models have been used to uncover an anatomical pattern of schizophrenia and a functional pattern for hallucinations. We embraced the applied mathematic challenge of creating scalable optimization solvers [for high-dimensional neuroimaging data while being flexible enough to integrate various priors.
Thanks to the award of a Chair in AI (2020-2025), we proposed new weakly-supervised deep neural networks that are pre-trained on large datasets of controls, using auxiliary information such as “age” to improve theembedded representation of the general variability. Models are then transferred to smaller samples of patients to reveal the specific signal associated with psychiatric disorders .
with shared etiologies for individualized therapeutic strategy.
Learning models require collecting more and better data (wide and deep phenotyping). First, we tackled the “big data challenge” by aggregating open datasets (UKB, ABCD, HBN) into an interoperable database. Second, we actively contributed and will continue to play a major role to the emergence of deeply phenotyped datasets by leading the data management and analysis of several large European and national projects( PEPR PROPSY, RHUs FAME and PsyCARE, European project R-LiNK).
CEA is a French government-funded technological research organisation in four main areas: low-carbon energies, defense and security, information technologies and health technologies. A prominent player in the European Research Area, it is involved in setting up collaborative projects with many partners around the world.