Neuro-computational Study of Thymic Fluctuations in Mood Disorders

Summary

Depression and bipolar disorder are frequent, debilitating conditions. Both are thought to be primarily caused by an impaired regulation of mood, which is why they are sometimes referred to as "mood disorders". However, the biological basis of mood remains poorly understood, which is a major limitation for the development of new treatments.

Recent work that combines neuroscience with mathematical models are promising to better understand mood and to link it to its biological basis, but they don't have any medical application yet. Can these models describe mood in a way that is relevant to mood disorders, and help doctors and psychologists predict subsequent clinical evolution? With the objective of extending this framework to real-life fluctuations and to assess its clinical relevance, this study will combine a neuroimaging session with a smartphone-based, longitudinal follow-up. Three groups of 96 subjects each will be recruited: depressive disorder, bipolar disorder and healthy controls. They will have their mood fluctuations assessed first in the lab (in the neuroimaging experiment), then in their daily lives (by providing a few ratings and choices every day on the smartphone app).

This study will allow to better understand the differences in how patients' mood reacts to daily events, as compared to people who don't suffer from depression or bipolar disorder. The combination of the two steps will allow to assess whether a short neuroimaging evaluation can be useful to predict subsequent clinical evolution during the following months.

The investigators wanted to add two optional ancillary studies. The first uses a mobile application for implicit, passive, and longitudinal mood assessments through emotion tracking. Indeed, it seems relevant to add this type of evaluation alongside explicit assessments to more accurately detect mood fluctuations.

The second study uses a mobile application that allows voice recordings. The analysis of these vocal parameters will help to characterize a specific linguistic and vocal profile within the three groups, as well as to identify specific symptoms of conditions such as depression and bipolar disorder.

These ancillary studies will be offered to both patients and the control group.

Conditions

• Depression
• Bipolar Disorder
• Recurrent Depression
• Mood Disorders

Interventions

DIAGNOSTIC_TEST

Brain magnetic resonance imaging (MRI) with structural (anatomical) and functional sequences (optional)

Brain MRI with structural (anatomical) and functional sequences (without contrast injection) will be collected. The cognitive tests will be carried out during the recording of the functional MRI (optional) in order to highlight the neural correlates of mood variations.

BEHAVIORAL

Computerized cognitive tests

Cognitive tests can be administered during the recording of a functional MRI, in order to highlight the neural correlates of mood variations. Cognitive data from a computerized experimental psychology experiment: this test involves different tests on a computer or tablet, including a test evaluating the minimal variations in the subject's mood and motivational state during the task, as well as its decision-making abilities.

DEVICE

Daily longitudinal monitoring by mobile MOODELING application

Daily longitudinal monitoring by mobile MOODELING application (mood, energy, events) with self-monitoring tools (calendar, mood curve) at home. Follow-up duration on the application: 12 months

Sponsors & Collaborators

• Institut du Cerveau et de la Moelle (ICM Institute)

  collaborator UNKNOWN

• Centre Hospitalier St Anne

  lead OTHER

Principal Investigators

• Fabien Vinckier, Dr · GHU Paris Psychiatry & Neurosciences

Study Design

Allocation

NA

Purpose

BASIC_SCIENCE

Masking

NONE

Model

SINGLE_GROUP

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2024-07-18

Primary Completion

2028-07-18

Completion

2029-07-18

Countries

• France

Study Locations