Virtual brain twins: from basic neuroscience to clinical use.

Virtual brain twins are personalized, generative and adaptive brain models based on data from an individual's brain for scientific and clinical use. After a description of the key elements of virtual brain twins, we present the standard model for personalized whole-brain network models. The personalization is accomplished using a subject's brain imaging data by three means: (1) assemble cortical and subcortical areas in the subject-specific brain space; (2) directly map connectivity into the brain models, which can be generalized to other parameters; and (3) estimate relevant parameters through model inversion, typically using probabilistic machine learning. We present the use of personalized whole-brain network models in healthy ageing and five clinical diseases: epilepsy, Alzheimer's disease, multiple sclerosis, Parkinson's disease and psychiatric disorders. Specifically, we introduce spatial masks for relevant parameters and demonstrate their use based on the physiological and pathophysiological hypotheses. Finally, we pinpoint the key challenges and future directions.

Information overload in the context of COVID-19 pandemic: A repeated cross-sectional study.

OBJECTIVES: To assess the psychometric properties of the Coronavirus Information Overload scale (CovIO) and explore relationships between CovIO, its predictors and several health behaviours related to the COVID-19 pandemic, using Cancer Information Overload (CIO) scale results as a reference for comparison. METHODS: 2003 participants representative of the French adult population answered a self-administered questionnaire over two waves of polling (N1(June 2020)= 1003, N2(January 2021)= 1000). Respondents were randomized to fill CovIO or CIO scale. Psychometric properties of scales were evaluated with Confirmatory Factor Analysis (CFA). Predictors were assessed using multivariate linear regression. RESULTS: CovIO scale showed satisfactory psychometric properties (α=0.86, ω=0.86, RMSEA=0.050) without any measurement invariance issue. CovIO increased between waves of sampling and was significantly linked to education, health literacy and trust in institutions among other variables. A negative relationship between information overload and preventive behaviours was also observed. CONCLUSION: The CovIO scale is a valid tool for assessing COVID-19 information overload. The dynamical formation of information overload and links with theorised predictors, especially, health literacy are confirmed. PRACTICE IMPLICATIONS: Longitudinal designs could help better understand the potential detrimental effect of information overload and improving public health campaigns. Interventions to reduce the degree of overload are needed.

Recommendations of the treatment-resistant depression expert center network for promoting tobacco smoking cessation based on the results from the real-world FACE-TRD national cohort.

BACKGROUND: Tobacco smoking has been associated with suicide, impulsivity and depression in non-clinical populations with differences across sexes. OBJECTIVE: To determine the role of tobacco smoking in Treatment-Resistant Depression (TRD) according to sex in a precision-medicine approach. METHOD: The FACE-TRD cohort is a national cohort of TRD patients recruited in 13 resistant depression expert centers between 2014 and 2021 and followed-up at 6 months. A standardized one-day long comprehensive battery was carried out, including trained-clinician and patient-reported outcomes, and patients were reevaluated at 6 months on their smoking and psychiatric hospitalization outcomes. RESULTS: 355 TRD participants were included (222 women). The smoking rate was much higher in TRD women compared to the French general population (34% vs 24%) while it was comparable for men (approximately 29%). In multivariate analyses, compared to non-smoking women, female smokers had significantly increased number of lifetime psychiatric hospitalizations (standardized beta B = 0.232, p = 0.014) and electro-convulsive therapy (adjusted odds ratio (aOR) = 2.748, p = 0.005), increased suicidal ideations (aOR = 4.047, p = 0.031), history of suicide attempt (aOR = 1.994, p = 0.033), and increased impulsivity (B = 0.210, p = 0.006) and were more frequently treated by benzodiazepines (aOR = 1.848, p = 0.035) and third- or fourth-line TRD treatments (antipsychotics aOR = 2.270, p = 0.006, mood stabilizers aOR = 2.067 p = 0.044). Tobacco smoking at baseline was predictive of psychiatric hospitalization within 6 months in persistent smoking women (aOR = 2.636, p = 0.031). These results were not replicated in men, for whom tobacco smoking was only associated with increased clinician-rated and self-reported depressive symptoms (respectively B = 0.207, p = 0.022 and B = 0.184, p = 0.048). The smoking cessation rate at 6 months was higher in women than in men (12% vs. 7%). No patient was administered nicotine substitute or varenicline at the two timepoints. INTERPRETATION: Combining these results and those of the literature, we recommend that active tobacco cessation should be promoted in TRD to improve depression, suicide and impulsivity especially in women. Female smokers appear as a specific population with heavier mental health outcomes that should be specifically addressed.

Cancer information overload: Association between a brief version of the CIO scale and multiple cancer risk management behaviours.

OBJECTIVES: To demonstrate the best psychometric properties of the revised 5-item Cancer Information Overload (CIO) scale over the 10- and 8-item versions, for both English and French native speakers, and to explore the relationships between CIO and several cancer risk management behaviours in a large sample of caregivers, cancer survivors and healthy subjects. METHODS: 2809 participants (2568 from France, 241 from Australia) from two cancer survivor networks answered a self-administered questionnaire. After assessing the psychometric properties we studied the impact of CIO on health behaviours using multivariate logistic regression. RESULTS: Internal consistency assessment and Confirmatory Factor Analysis (CFA) showed satisfactory results (α = 0.87 and 0.83, ω = 0.87 and 0.83, RMSEA = 0.078 and 0.081 for the 8-item and 5-item versions respectively), as well as multi-group CFA where measurement invariance was partial for one item only in each version. CIO was independently associated with smoking, sunburns, and rare skin checks, but not with alcohol misuse. CONCLUSION: The 5-item version of the CIO scale showed adequate psychometric properties and discriminant association with multiple prevention behaviours. PRACTICE IMPLICATIONS: The 5-item CIO scale is valid and can help push research forward in the domain of disease prevention and message acceptance. Its role in clinical practice remains to be determined.