This project studies markers for emotional regulation using MRI in a large sample of patients . The goal is to identify sub-categories of bipolar and emotional disorders according to the stage in the  disease’s progression, age of onset, presence of psychotic symptoms, association with psychiatric or somatic disorders, and clinical variables such as childhood stress.

Thanks to neuroimaging, several significant correlations between brain structures and clinical progression have been identified, which should lead very soon to the characterisation of a new marker for emotional regulation. The innovative multivariate analysis methods used make it possible to link clinical variables to brain function.

Drs Camille Piguet of the HUG in Geneva and Josselin Houenou at Neurospin & CHU Henri Mondor in Paris and their teams, combined their skills and shared their data. They are identifying correlations between MRI signal variability during rest periods and behaviour. This could lead to the identification of a new marker for emotion regulation in bipolar patients and would help to explain and better understand the discrepancies currently found in the scientific literature.

A manuscript presenting these results and a synthesis presenting the preliminary results were submitted to the Society of Biological Psychiatry’s annual conference (May 2018, New York).

Subsequently, the database of people with bipolar disorder will be extended to other diseases. The analysis of these data in “sub-groups” of patients will use artificial intelligence techniques such as machine learning. This approach will lead to a better understanding and therefore better targeting of the physiological mechanisms underlying emotional disorders with the prospect of rapidly developing new treatments for patients.