Publications by authors named "Jean-Luc Martinot"

Increases in impulsivity and negative affect (e.g., neuroticism) are common during adolescence and are both associated with risk for alcohol-use initiation and other risk behaviors.

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The study of cortical geometry and connectivity is prevalent in human brain research. However, these two aspects of brain structure are usually examined separately, leaving the essential connections between the brain's folding patterns and white matter connectivity unexplored. In this study, we aim to elucidate the fundamental links between cortical geometry and white matter tract connectivity.

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Chronic pain is a leading cause of disability, yet its underlying susceptibility traits remain unclear. Disorders like chronic pain may stem from extreme neural types, or archetypes, optimized for specific cognitive strategies and reflected in patterns of resting-state networks. Here, we examined a sample from the general population ( = 892) and three clinical samples with subacute back pain ( = 76), chronic back pain ( = 30), and treatment-resistant depression ( = 24).

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Substance use disorder (SUD) stands as a critical public health concern, contributing to substantial morbidity, mortality and societal costs. The effects of SUD on structural brain changes have been well documented. However, the neural mechanisms underlying SUD and the spatial-temporal volumetric changes associated with SUD remained underexplored.

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Resilience to developing emotional disorders is critical for adolescent mental health, especially following childhood trauma. Yet, brain markers of resilience remain poorly understood. By analyzing brain responses to angry faces in a large-scale longitudinal adolescent cohort (IMAGEN), we identified two functional networks located in the orbitofrontal and occipital regions.

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Background: The COVID-19 pandemic has impacted various aspects of daily life, leading to increased psychological symptoms and changes in alcohol use, yet little is known about their specific interactions, particularly early stages during the pandemic. We examined the relationship between psychological symptoms and alcohol-related behaviors associated with COVID-19, and determined whether associations shifted already early during the pandemic and whether changes in psychological symptoms from the pre- to during COVID-19 impacted changes in alcohol consumption.

Methods: Participants were young adults from a longitudinal cohort (N=435, age: 22-25) from two time points.

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Importance: Psychiatric diagnoses are not defined by neurobiological measures hindering the development of therapies targeting mechanisms underlying mental illness. Research confined to diagnostic boundaries yields heterogeneous biological results, whereas transdiagnostic studies often investigate individual symptoms in isolation.

Objective: To develop a framework that groups clinical symptoms compatible with ICD-10 and DSM-5 according to their covariation and shared brain mechanisms.

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Substance use disorder (SUD) stands as a critical public health concern, contributing to substantial morbidity, mortality and societal costs. The effects of SUD on structural brain changes have been well documented. However, the neural mechanisms underlying SUD and the spatial-temporal volumetric changes associated with SUD remained underexplored.

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The excitation-inhibition ratio is a key functional property of cortical microcircuits which changes throughout an individual's lifespan. Adolescence is considered a critical period for maturation of excitation-inhibition ratio. This has primarily been observed in animal studies.

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Background: Copy number variants (CNVs) may increase the risk for neurodevelopmental conditions. The neurobiological mechanisms that link these high-risk genetic variants to clinical phenotypes are largely unknown. An important question is whether brain abnormalities in individuals who carry CNVs are associated with their degree of penetrance.

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Importance: Psychiatric comorbidity is the norm. Identifying transdiagnostic risk factors will inform our understanding of developmental pathways and early intervention targets.

Objective: We recently reported that many psychiatric outcomes are predicted by a three-factor model composed of adolescent externalizing (EXT) behaviors, early life adversity, and dopamine autoreceptor availability.

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The study of cortical geometry and connectivity is prevalent in research on the human brain. However, these two aspects of brain structure are usually examined separately, leaving the essential connections between the brain's folding patterns and white matter connectivity unexplored. In this study, we aimed to elucidate fundamental links between cortical geometry and white matter tract connectivity.

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Background: Cannabis use is common, particularly during emerging adulthood when brain development is ongoing, and its use is associated with harmful outcomes for a subset of people. An improved understanding of the neural mechanisms underlying risk for problem-level use is critical to facilitate the development of more effective prevention and treatment approaches.

Methods: In the current study, we applied a whole-brain, data-driven, machine learning approach to identify neural features predictive of problem-level cannabis use in a nonclinical sample of college students (n = 191, 58% female) based on reward task functional connectivity data.

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Laboratory studies show brain maturation involves synaptic pruning and cognitive development. Human studies suggest links between early cognitive performance and later mental health, but inconsistencies remain. It is unclear if specific brain regions mediate this relationship, and the molecular underpinnings are not well understood.

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Mounting evidence suggests hierarchical psychopathology factors underlying psychiatric comorbidity. However, the exact neurobiological characterizations of these multilevel factors remain elusive. In this study, leveraging the brain-behavior predictive framework with a 10-year longitudinal imaging-genetic cohort (IMAGEN, ages 14, 19 and 23, = 1,750), we constructed two neural factors underlying externalizing and internalizing symptoms, which were reproducible across six clinical and population-based datasets (ABCD, STRATIFY/ESTRA, ABIDE II, ADHD-200 and XiNan, from age 10 to age 36, = 3,765).

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The evidence supporting the presence of individual brain structure correlates of the externalizing spectrum (EXT) is sparse and mixed. To date, large-sample studies of brain-EXT relations have mainly found null to very small effects by focusing exclusively on either EXT-related personality traits (e.g.

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Unhealthy eating, a risk factor for eating disorders (EDs) and obesity, often coexists with emotional and behavioral problems; however, the underlying neurobiological mechanisms are poorly understood. Analyzing data from the longitudinal IMAGEN adolescent cohort, we investigated associations between eating behaviors, genetic predispositions for high body mass index (BMI) using polygenic scores (PGSs), and trajectories (ages 14-23 years) of ED-related psychopathology and brain maturation. Clustering analyses at age 23 years ( = 996) identified 3 eating groups: restrictive, emotional/uncontrolled and healthy eaters.

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Background And Aim: Cannabis use disorder (CUD) is strongly influenced by genetic factors; however the mechanisms underpinning this association are not well understood. This study investigated whether a polygenic risk score (PRS) based on a genome-wide association study for CUD in adults predicts cannabis use in adolescents and whether the association can be explained by inter-individual variation in structural properties of brain white matter or risk-taking behaviors.

Design And Setting: Longitudinal and cross-sectional analyses using data from the IMAGEN cohort, a European longitudinal study integrating genetic, neuroimaging and behavioral measures.

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Article Synopsis
  • The study utilized machine learning models to identify reliable diagnostic markers for eating disorders, major depressive disorder, and alcohol use disorder, targeting young adults aged 18-25.
  • The classification models showed high accuracy rates (AUC-ROC ranging from 0.80 to 0.92) even without considering body mass index and highlighted shared predictors like neuroticism and hopelessness.
  • Additionally, the models were moderately successful in predicting future symptoms related to eating disorders, depression, and alcohol use in a longitudinal sample of adolescents, indicating the potential for improved diagnosis and risk assessment in mental health.
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Introduction: A growing literature has shown that exposure to adverse life events during childhood or adolescence is associated with the presence of psychotic-like experiences (PLEs), which is in turn associated with the risk of psychotic outcomes. Ruminative thinking, i.e.

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Article Synopsis
  • This study uses multi-modal MRI to investigate neurobiological differences between anorexia nervosa (AN) and bulimia nervosa (BN), revealing structural and functional brain changes linked to these eating disorders.
  • Key findings include reduced gray matter volume in specific brain regions (like the orbitofrontal cortex) and decreased cortical thickness, particularly in anorexia patients, which are associated with impulsivity and cognitive restraint regarding eating behaviors.
  • The results suggest that these brain changes affect reward processing and contribute to the persistence of eating disorder symptoms, highlighting potential targets for future treatment interventions.
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Article Synopsis
  • * A study utilizing the Adolescent Brain Cognitive Development cohort revealed seven genomic regions where gene-environment interactions affect gray matter volume, tied to metabolic and inflammatory processes, as well as synaptic plasticity.
  • * The analysis highlighted that socioeconomic status, rather than family environment, plays a crucial role in how maternal education influences genetic effects on neurodevelopment, offering insights into the biological and social mechanisms involved.
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Background: Psychotic symptoms in adolescence are associated with social adversity and genetic risk for schizophrenia. This gene-environment interplay may be mediated by personality, which also develops during adolescence. We hypothesized that (i) personality development predicts later Psychosis Proneness Signs (PPS), and (ii) personality traits mediate the association between genetic risk for schizophrenia, social adversities, and psychosis.

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