Digital phenotype of mood disorders: A conceptual and critical review

BackgroundMood disorders are commonly diagnosed and staged using clinical features that rely merely on subjective data. The concept of digital phenotyping is based on the idea that collecting real-time markers of human behavior allows us to determine the digital signature of a pathology. This strategy assumes that behaviors are quantifiable from data extracted and analyzed through digital sensors, wearable devices, or smartphones. That concept could bring a shift in the diagnosis of mood disorders, introducing for the first time additional examinations on psychiatric routine care.ObjectiveThe main objective of this review was to propose a conceptual and critical review of the literature regarding the theoretical and technical principles of the digital phenotypes applied to mood disorders.MethodsWe conducted a review of the literature by updating a previous article and querying the PubMed database between February 2017 and November 2021 on titles with relevant keywords regarding digital phenotyping, mood disorders and artificial intelligence.ResultsOut of 884 articles included for evaluation, 45 articles were taken into account and classified by data source (multimodal, actigraphy, ECG, smartphone use, voice analysis, or body temperature). For depressive episodes, the main finding is a decrease in terms of functional and biological parameters [decrease in activities and walking, decrease in the number of calls and SMS messages, decrease in temperature and heart rate variability (HRV)], while the manic phase produces the reverse phenomenon (increase in activities, number of calls and HRV).ConclusionThe various studies presented support the potential interest in digital phenotyping to computerize the clinical characteristics of mood disorders

Physiopathologie du trouble obsessionnel-compulsif : une approche multimodale afin de confronter les preuves

Obsessive compulsive disorder is a serious disorder, understudied and considered as the 4th cause of disability in the world by the World Health Organization. Treatments exist such as antidepressants and cognitive-behavioral psychotherapies, but a significant number of patients do not respond to these usual treatments. Nowadays, great importance is given to personalized medicine and researchers are largely focusing their research in finding biomarkers in the field of psychiatry. In this context, the objective of my thesis work was to identify the brain regions that may be involved in obsessive-compulsive symptomatology in order to develop precision medicine. For this, after having carried out a synthesis of the neuroimaging data present in the literature, we looked for indirect evidences but also direct evidences with a strong biological causality in order to validate or invalidate pre-existing results. Finally, on the strength of these discoveries, our team has developed a new paradigm of metacognition, freeing itself from the measurement of obsessive-compulsive symptoms (provocative tasks) or even cognitive functions. This paradigm aims to go beyond the symptoms by capturing a cerebral signature in electroencephalography and the visual strategy adopted by each patient suffering from an obsessive-compulsive disorder.Le trouble obsessionnel compulsif est une maladie grave, peu étudiée et considérée par l’Organisation Mondiale de la Santé comme la 4ème cause de handicap dans le monde. Des traitements existent tels que les antidépresseurs et les psychothérapies de type cognitivo-comportementale mais un nombre non négligeable de patients ne répondent pas à ces traitements habituels. De nos jours, une grande importance est portée à la médecine personnalisée ainsi qu’à la recherche de biomarqueurs dans le domaine des maladies mentales. Dans ce contexte, l’objectif de ma thèse a été d’identifier les régions cérébrales pouvant être impliquées dans la symptomatologie obsessionnelle-compulsive afin de développer une médecine de précision. Pour cela, après avoir réalisé une synthèse des données de neuro-imagerie présentes dans la littérature, nous avons recherché des preuves indirectes mais également directes ayant une forte causalité biologique afin d’infirmer ou de confirmer les résultats préexistants. Enfin, fort de ces découvertes, notre équipe a développé un nouveau paradigme de métacognition, s’affranchissant de la mesure des symptômes obsessionnels compulsifs (tâches de provocation) ou encore de l’évaluation des fonctions cognitives. Ce paradigme a pour dessein d’aller au-delà du symptôme en capturant une signature cérébrale en électroencéphalographie et en étudiant la stratégie visuelle adoptée par chaque patient souffrant d’un trouble obsessionnel-compulsif

Physiopathologie du trouble obsessionnel-compulsif : une approche multimodale afin de confronter les preuves

Le trouble obsessionnel compulsif est une maladie grave, peu étudiée et considérée par l’Organisation Mondiale de la Santé comme la 4ème cause de handicap dans le monde. Des traitements existent tels que les antidépresseurs et les psychothérapies de type cognitivo-comportementale mais un nombre non négligeable de patients ne répondent pas à ces traitements habituels. De nos jours, une grande importance est portée à la médecine personnalisée ainsi qu’à la recherche de biomarqueurs dans le domaine des maladies mentales. Dans ce contexte, l’objectif de ma thèse a été d’identifier les régions cérébrales pouvant être impliquées dans la symptomatologie obsessionnelle-compulsive afin de développer une médecine de précision. Pour cela, après avoir réalisé une synthèse des données de neuro-imagerie présentes dans la littérature, nous avons recherché des preuves indirectes mais également directes ayant une forte causalité biologique afin d’infirmer ou de confirmer les résultats préexistants. Enfin, fort de ces découvertes, notre équipe a développé un nouveau paradigme de métacognition, s’affranchissant de la mesure des symptômes obsessionnels compulsifs (tâches de provocation) ou encore de l’évaluation des fonctions cognitives. Ce paradigme a pour dessein d’aller au-delà du symptôme en capturant une signature cérébrale en électroencéphalographie et en étudiant la stratégie visuelle adoptée par chaque patient souffrant d’un trouble obsessionnel-compulsif.Obsessive compulsive disorder is a serious disorder, understudied and considered as the 4th cause of disability in the world by the World Health Organization. Treatments exist such as antidepressants and cognitive-behavioral psychotherapies, but a significant number of patients do not respond to these usual treatments. Nowadays, great importance is given to personalized medicine and researchers are largely focusing their research in finding biomarkers in the field of psychiatry. In this context, the objective of my thesis work was to identify the brain regions that may be involved in obsessive-compulsive symptomatology in order to develop precision medicine. For this, after having carried out a synthesis of the neuroimaging data present in the literature, we looked for indirect evidences but also direct evidences with a strong biological causality in order to validate or invalidate pre-existing results. Finally, on the strength of these discoveries, our team has developed a new paradigm of metacognition, freeing itself from the measurement of obsessive-compulsive symptoms (provocative tasks) or even cognitive functions. This paradigm aims to go beyond the symptoms by capturing a cerebral signature in electroencephalography and the visual strategy adopted by each patient suffering from an obsessive-compulsive disorder

Ecological Momentary Assessment Using Smartphones in Patients With Depression: Feasibility Study

International audienceBackground: Ecological momentary assessment (EMA) is a promising tool in the management of psychiatric disorders and particularly depression. It allows for a real-time evaluation of symptoms and an earlier detection of relapse or treatment efficacy. The generalization of the smartphone in the modern world offers a new, large-scale support for EMA.Objective: The main objective of this study was twofold: (1) to assess patients' compliance with an EMA smartphone app defined by the number of EMAs completed, and (2) to estimate the external validity of the EMA using a correlation between self-esteem/guilt/mood variables and Hamilton Depression Rating Scale (HDRS) score.Methods: Eleven patients at the Pitié-Salpêtrière Hospital, Paris, France, were monitored for 28 days by means of a smartphone app. Every patient enrolled in the study had two types of assessment: (1) three outpatient consultations with a psychiatrist at three different time points (days 1, 15, and 28), and (2) real-time data collection using an EMA smartphone app with a single, fixed notification per day at 3 pm for 28 days. The results of the real-time data collected were reviewed during the three outpatient consultations by a psychiatrist using a dashboard that aggregated all of the patients' data into a user-friendly format.Results: Of the 11 patients in the study, 6 patients attended the 3 outpatient consultations with the psychiatrist and completed the HDRS at each consultation. We found a positive correlation between the HDRS score and the variables of self-esteem, guilt, and mood (Spearman correlation coefficient 0.57). Seven patients completed the daily EMAs for 28 days or longer, with an average response rate to the EMAs of 62.5% (175/280). Furthermore, we observed a positive correlation between the number of responses to EMAs and the duration of follow-up (Spearman correlation coefficient 0.63).Conclusions: This preliminary study with a prolonged follow-up demonstrates significant patient compliance with the smartphone app. In addition, the self-assessments performed by patients seemed faithful to the standardized measurements performed by the psychiatrist. The results also suggest that for some patients it is more convenient to use the smartphone app than to attend outpatient consultations

Transcranial Magnetic Stimulation (rTMS) on the Precuneus in Alzheimer’s Disease: A Literature Review

The current literature review aimed to evaluate the effectiveness of rTMS on the precuneus as a potential treatment for Alzheimer’s disease (AD). Although the number of studies specifically targeting the precuneus is limited, the results from this review suggest the potential benefits of this approach. Future studies should focus on exploring the long-term effects of rTMS on the precuneus in Alzheimer’s disease patients, as well as determining the optimal stimulation parameters and protocols for this population. Additionally, investigating the effects of rTMS on the precuneus in combination with other brain regions implicated in AD may provide valuable insights into the development of effective treatment for this debilitating neurodegenerative disorder

Performance in delayed non-matching to sample task predicts the diagnosis of obsessive–compulsive disorder

International audienceElectrical stimulation studies have recently evidenced the involvement of orbitofrontal cortex (OFC) in obsessive-compulsive disorder (OCD). In addition, lateral OFC is activated in healthy subjects during delayed non-matching-to-sample task (DNMS). In the present study, we hypothesized that OCD results from a specific defect of lateral OFC processing that can be evidenced via a DNMS task. To this end, we compared the DNMS performances of 20 OCD patients vs 20 demographically matched healthy controls. As predicted, our results showed that OCD patients performed worse than healthy controls at DNMS task. To test for the specificity of this behavioral impairment, we furthermore compared OCD patients and healthy subjects on a different task not involving directly the lateral OFC: the delayed match-to-sample task (DMS). As expected, OCD patients are more impaired for both the DNMS and the DMS task, compared with healthy subjects. Moreover, OCD patients tend statistically to perform worse for the DNMS task than for DMS task. Our results suggest the DNMS task specifically target the malfunctioning areas in OCD, such as the lateral OFC. In light of these results, lateral OFC should therefore be the focus of future therapeutic interventions

In Search of Digital Dopamine: How Apps Can Motivate Depressed Patients, a Review and Conceptual Analysis

Introduction: Depression is highly prevalent and causes considerable suffering and disease burden despite the existence of wide-ranging treatment options. Momentary assessment is a promising tool in the management of psychiatric disorders, and particularly depression. It allows for a real-time evaluation of symptoms and an earlier detection of relapse or treatment efficacy. Treating the motivational and hedonic aspects of depression is a key target reported in the literature, but it is time-consuming in terms of human resources. Digital Applications offer a major opportunity to indirectly regulate impaired motivational circuits through dopaminergic pathways. Objective: The main objective of this review was twofold: (1) propose a conceptual and critical review of the literature regarding the theoretical and technical principles of digital applications focused on motivation in depression, activating dopamine, and (2) suggest recommendations on the relevance of using these tools and their potential place in the treatment of depression. Material and Methods: A search for words related to “dopamine”, “depression”, “smartphone apps”, “digital phenotype” has been conducted on PubMed. Results: Ecological momentary interventions (EMIs) differ from traditional treatments by providing relevant, useful intervention strategies in the context of people’s daily lives. EMIs triggered by ecological momentary assessment (EMA) are called “Smart-EMI”. Smart-EMIs can mimic the “dopamine reward system” if the intervention is tailored for motivation or hedonic enhancement, and it has been shown that a simple reward (such as a digital badge) can increase motivation. Discussion: The various studies presented support the potential interest of digital health in effectively motivating depressed patients to adopt therapeutic activation behaviors. Finding effective ways to integrate EMIs with human-provided therapeutic support may ultimately yield the most efficient and effective intervention method. This approach could be a helpful tool to increase adherence and motivation. Conclusion: Smartphone apps can motivate depressed patients by enhancing dopamine, offering the opportunity to enhance motivation and behavioral changes, although longer term studies are still needed

Revisiting 'brain modes' in a new computational era: approaches for the characterization of brain-behavioural associations.

International audienceThe study of brain-function relationships is undergoing a conceptual and methodological transformation due to the emergence of network neuroscience and the development of multivariate methods for lesion-deficit inferences. Anticipating this process, in 1998 Godefroy and co-workers conceptualized the potential of four elementary typologies of brain-behaviour relationships named 'brain modes' (unicity, equivalence, association, summation) as building blocks able to describe the association between intact or lesioned brain regions and cognitive processes or neurological deficits. In the light of new multivariate lesion inference and network approaches, we critically revisit and update the original theoretical notion of brain modes, and provide real-life clinical examples that support their existence. To improve the characterization of elementary units of brain-behavioural relationships further, we extend such conceptualization with a fifth brain mode (mutual inhibition/masking summation). We critically assess the ability of these five brain modes to account for any type of brain-function relationship, and discuss past versus future contributions in redefining the anatomical basis of human cognition. We also address the potential of brain modes for predicting the behavioural consequences of lesions and their future role in the design of cognitive neurorehabilitation therapies

Digital Phenotyping: Data-Driven Psychiatry to Redefine Mental Health

International audienceThe term “digital phenotype” refers to the digital footprint left by patient-environment interactions. It has potential for both research and clinical applications but challenges our conception of health care by opposing 2 distinct approaches to medicine: one centered on illness with the aim of classifying and curing disease, and the other centered on patients, their personal distress, and their lived experiences. In the context of mental health and psychiatry, the potential benefits of digital phenotyping include creating new avenues for treatment and enabling patients to take control of their own well-being. However, this comes at the cost of sacrificing the fundamental human element of psychotherapy, which is crucial to addressing patients’ distress. In this viewpoint paper, we discuss the advances rendered possible by digital phenotyping and highlight the risk that this technology may pose by partially excluding health care professionals from the diagnosis and therapeutic process, thereby foregoing an essential dimension of care. We conclude by setting out concrete recommendations on how to improve current digital phenotyping technology so that it can be harnessed to redefine mental health by empowering patients without alienating them