Neuro-computational Study of Thymic Fluctuations in Mood Disorders - MOODELING
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 588
- 试验地点
- 2
- 主要终点
- Computational phenotypes of daily mood fluctuations in the 3 groups
研究概览
简要总结
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.
详细描述
Mood disorders are common diseases that represent the first psychiatric cause of morbidity and mortality, and a major public health and medico-economic issue at the national and international level.
Although effective treatments exist, understanding of the pathophysiology of these diseases remains largely incomplete. The assessment is entirely clinical, without any reliable biological marker which has serious consequences in terms of morbidity.
Neurocomputational approaches, which consist of describing the cognitive mechanisms underlying the symptoms on which the clinic is based, so as to better articulate them with their biological substrates, are proving promising in the field.
The first mood models mathematically describe the intuitive idea that positive events have a positive impact on mood, and vice versa for negative events. More recent work has developed models to characterize the interaction of mood with decision-making. They describe how mood affects the perception of events and influences the resulting decisions: when mood is high, subjects tend to overestimate potential gains and underestimate losses, and vice versa when mood is low.
The investigators recently replicated these results and identified the neural bases of this phenomenon by showing, using a functional MRI (fMRI) study in healthy volunteers, that mood was encoded in the activity of two brain regions, the ventromedial prefrontal cortex (vmPFC) and the anterior insula (aIns). The activity of these regions in turn modulated the participants attitude towards risky choices. The investigators recently replicated this result in an intracerebral stereo-electroencephalogram (sEEG) study.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Basic Science
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •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
排除标准
- •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)
研究组 & 干预措施
BD Group: patients with bipolar disorder
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
干预措施: Brain magnetic resonance imaging (MRI) with structural (anatomical) and functional sequences (optional) (Diagnostic Test)
BD Group: patients with bipolar disorder
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
干预措施: Computerized cognitive tests (Behavioral)
BD Group: patients with bipolar disorder
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
干预措施: Daily longitudinal monitoring by mobile MOODELING application (Device)
结局指标
主要结局
Computational phenotypes of daily mood fluctuations in the 3 groups
时间窗: From enrolment to Month 12
Computational phenotypes of daily mood fluctuations obtained from daily collection of mood data and daily life events via the mobile application.
次要结局
- Short-term computational phenotypes of mood(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)
- Sensitivity of decision-making parameters to predict clinical relapses(Month 0, Month 3, Month 6, Month 9, Month 12)
- Correlation of computational phenotypes of mood at short and long-term(From enrollment to Month 12)
- Number of hour per day of sunshine(From enrolment to Month 12)
- Basal fMRI signal characteristics of the vmPFC and aIns in each group(Month 0)