NCT07033923

Brief 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.

Trial Health

77
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
588

participants targeted

Target at P75+ for not_applicable depression

Timeline
39mo left

Started Jul 2024

Longer than P75 for not_applicable depression

Geographic Reach
1 country

2 active sites

Status
recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Progress36%
Jul 2024Jul 2029

Study Start

First participant enrolled

July 18, 2024

Completed
7 months until next milestone

First Submitted

Initial submission to the registry

February 26, 2025

Completed
4 months until next milestone

First Posted

Study publicly available on registry

June 24, 2025

Completed
3.1 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

July 18, 2028

Expected
1 year until next milestone

Study Completion

Last participant's last visit for all outcomes

July 18, 2029

Last Updated

June 24, 2025

Status Verified

June 1, 2025

Enrollment Period

4 years

First QC Date

February 26, 2025

Last Update Submit

June 13, 2025

Conditions

Keywords

cognitive neurosciencepatient-specific modellingpsychiatrymood disordersaffective disorderscomputational modellingcomputational psychiatryprognosispredictive medicine

Outcome Measures

Primary Outcomes (1)

  • Computational phenotypes of daily mood fluctuations in the 3 groups

    Computational phenotypes of daily mood fluctuations obtained from daily collection of mood data and daily life events via the mobile application.

    From enrolment to Month 12

Secondary Outcomes (7)

  • Short-term computational phenotypes of mood

    Month 0

  • Correlation of computational phenotypes of mood at short and long-term

    From enrollment to Month 12

  • Basal fMRI signal characteristics of the vmPFC and aIns in each group

    Month 0

  • Neural correlates from functional MRI (fMRI)

    Month 0

  • Effect of mood on decision-making at short and long-term

    From enrolment to Month 12

  • +2 more secondary outcomes

Study Arms (1)

BD Group: patients with bipolar disorder

EXPERIMENTAL

Patients with: * a diagnosis of bipolar mood disorder (F31) according to ICD-10 criteria, made by a psychiatrist * a thymic episode (F31.0 - F31.6) diagnosed in the past 12 months by a psychiatrist

Diagnostic Test: Brain magnetic resonance imaging (MRI) with structural (anatomical) and functional sequences (optional)Behavioral: Computerized cognitive testsDevice: Daily longitudinal monitoring by mobile MOODELING application

Interventions

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.

BD Group: patients with bipolar disorder

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.

BD Group: patients with bipolar disorder

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

BD Group: patients with bipolar disorder

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Common between groups (DD, BD, control and GP):
  • Having given informed and written consent
  • Being covered by social security
  • For patients with depressive disorder (DD):
  • Having been diagnosed with characterized depressive episode (F32, F33, F34) according to the ICD-10, by a psychiatrist, or having presented this diagnosis during the past 12 months
  • For patients with bipolar disorder (BD):
  • Presenting a diagnosis of bipolar mood disorder (F31) according to ICD-10, by a psychiatrist
  • Having presented a mood episode (F31.0 - F31.6) diagnosed during the past 12 months by a psychiatrist

You may not qualify if:

  • Common between groups (DD, BD, control and GP):
  • Inability to carry out daily monitoring on mobile application for 12 months
  • legal protection measure (guardianship or curatorship)
  • For control group:
  • Current diagnosis of psychiatric disorder in ICD-10 (F20-F98) or prescription of psychotropic treatment
  • History of depression (F32)
  • Syndrome of dependence on a psychoactive substance other than tobacco
  • Neurological history (in particular history of stroke, coma, epilepsy, neuro- inflammatory, or neuro-degenerative disease)
  • Inability to carry out daily monitoring on mobile application for 12 months
  • For patients and healthy volunteers for whom an MRI (without injection of contrast agent) is proposed
  • Contraindication to MRI: cardiac pacemaker not compatible with MRI, heart valve implant, implant or metallic foreign body
  • Pregnant woman (at the time of MRI)

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (2)

- Groupe hospitalo-universitaire Paris Psychiatrie et Neurosciences

Paris, Paris, 75014, France

RECRUITING

Assistance Publique - Hôpitaux de Paris GH Pitié-Salpêtrière

Paris, 75651, France

RECRUITING

Related Publications (7)

  • Rutledge RB, Moutoussis M, Smittenaar P, Zeidman P, Taylor T, Hrynkiewicz L, Lam J, Skandali N, Siegel JZ, Ousdal OT, Prabhu G, Dayan P, Fonagy P, Dolan RJ. Association of Neural and Emotional Impacts of Reward Prediction Errors With Major Depression. JAMA Psychiatry. 2017 Aug 1;74(8):790-797. doi: 10.1001/jamapsychiatry.2017.1713.

    PMID: 28678984BACKGROUND
  • Eldar E, Rutledge RB, Dolan RJ, Niv Y. Mood as Representation of Momentum. Trends Cogn Sci. 2016 Jan;20(1):15-24. doi: 10.1016/j.tics.2015.07.010. Epub 2015 Nov 3.

    PMID: 26545853BACKGROUND
  • Eldar E, Niv Y. Interaction between emotional state and learning underlies mood instability. Nat Commun. 2015 Jan 21;6:6149. doi: 10.1038/ncomms7149.

    PMID: 25608088BACKGROUND
  • Heerema R, Carrillo P, Daunizeau J, Vinckier F, Pessiglione M. Mood fluctuations shift cost-benefit tradeoffs in economic decisions. Sci Rep. 2023 Oct 24;13(1):18173. doi: 10.1038/s41598-023-45217-w.

    PMID: 37875525BACKGROUND
  • Pessiglione M, Heerema R, Daunizeau J, Vinckier F. Origins and consequences of mood flexibility: a computational perspective. Neurosci Biobehav Rev. 2023 Apr;147:105084. doi: 10.1016/j.neubiorev.2023.105084. Epub 2023 Feb 9.

    PMID: 36764635BACKGROUND
  • Vinckier F, Rigoux L, Oudiette D, Pessiglione M. Neuro-computational account of how mood fluctuations arise and affect decision making. Nat Commun. 2018 Apr 26;9(1):1708. doi: 10.1038/s41467-018-03774-z.

    PMID: 29700303BACKGROUND
  • Rutledge RB, Skandali N, Dayan P, Dolan RJ. A computational and neural model of momentary subjective well-being. Proc Natl Acad Sci U S A. 2014 Aug 19;111(33):12252-7. doi: 10.1073/pnas.1407535111. Epub 2014 Aug 4.

    PMID: 25092308BACKGROUND

Related Links

MeSH Terms

Conditions

DepressionBipolar DisorderMood Disorders

Interventions

Magnetic Resonance Imaging

Condition Hierarchy (Ancestors)

Behavioral SymptomsBehaviorBipolar and Related DisordersMental Disorders

Intervention Hierarchy (Ancestors)

TomographyDiagnostic ImagingDiagnostic Techniques and ProceduresDiagnosis

Study Officials

  • Fabien Vinckier, Dr

    GHU Paris Psychiatry & Neurosciences

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Study Design

Study Type
interventional
Phase
not applicable
Allocation
NA
Masking
NONE
Purpose
BASIC SCIENCE
Intervention Model
SINGLE GROUP
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

February 26, 2025

First Posted

June 24, 2025

Study Start

July 18, 2024

Primary Completion (Estimated)

July 18, 2028

Study Completion (Estimated)

July 18, 2029

Last Updated

June 24, 2025

Record last verified: 2025-06

Data Sharing

IPD Sharing
Will share

The data obtained from medical visits (clinical informations, biological assessments, cognitive data) and brain MRIs will be kept, coded and archived for a period of two years after the last publication of the research results or until the final research report is signed. These can be used later for collaborative research (academic and/or industrial partners) in the European Union (EU) and/or abroad exclusively for scientific purposes.

Shared Documents
STUDY PROTOCOL, SAP, ICF, CSR, ANALYTIC CODE
Time Frame
The data obtained from medical visits (clinical informations, biological assessments, neurocognitive data)and brain MRIs will be kept, coded and archived for a period of two years after the last publication of the research results or until the final research report is signed.
Access Criteria
The data can be used for collaborative research (academic and/or industrial partners) in the European Union (EU) and/or abroad exclusively for scientific purposes. Any party must contact the sponsor, who has full property of the data. In case of requested transfer of the anonymized database resulting from this research abroad (outside the EU), the sponsor will request information regarding data storage and management, to make sure that the other party will be able to ensure a level of security equivalent to French or European Union law.

Locations