The Bipolar Bayesian Brain at 7T: Mood disturbances in bipolar disorder studied with ultra-high field MRI – B37T

Bipolar disorder (BD) is a chronic mood disorder characterized by emotional hyperresponsiveness during acute periods (i.e., mania and depression), as well as during periods of remission (i.e., euthymia). Current neurocognitive models suggest that lack of cognitive control may be responsible for these symptoms, but do not explain the recurrence of mood cycles in BD. The objective of this project is to clarify the cognitive mechanisms responsible for extreme mood variations in BD and to identify the underlying cerebral correlate. We assume that patients with BD would exhibit an early perceptual bias when processing emotions, that would also be congruent with their mood. On the one hand, regardless of their mood, patients would tend to "over-predict" emotions, leading to "top-down" prediction errors and abnormal connectivity between the amygdala, the orbito-frontal cortex, and the visual system. On the other hand, the valence of this expectation bias would depend on their mood state and would be underpinned by an imbalance of connectivity between the amygdala, the hippocampus, and the nucleus accumbens. We will use ultra-high field MRI (7 Tesla) which, thanks to a very high spatial resolution and a very high signal-to-noise ratio, will allow us to precisely measure the connectivity of these regions. We will employ a dimensional approach, including 60 patients in different mood states: euthymic, depressed, or hypomanic, as well as 30 healthy controls. We will use ecological momentary assessment (EMA) to characterize as precisely as possible the mood of the patients at the time of the MRI scan. From the theoretical perspective, this project will contribute to the modeling of the neurocognitive processes involved in the regulation of mood. From a clinical and societal perspective, it will help to improve the diagnosis of mood disorders and will open new perspectives for the treatment of patients with BD.