Background: Pavlovian-to-instrumental transfer (PIT) paradigms assess how environmental cues influence instrumental behaviour. Our previous research linked PIT to alcohol use disorder (AUD) and high-risk drinking using monetary rewards during learning. To better capture alcohol-related cue effects, we developed a PIT paradigm delivering trial-by-trial alcohol and juice rewards alongside monetary rewards, to examine alcohol-specific and general PIT effects in parallel. Methods: Seventy-five participants with AUD and ninety-five controls completed the task during functional magnetic resonance imaging. Alcohol-specific PIT was defined as increased alcohol choices during presentation of alcohol-associated versus juice-associated cues. General PIT was defined as increased response vigor during gain- versus loss-associated cues. Behavioural and neural associations with AUD status and AUDIT scores from baseline through one-year follow-up were examined. Results: Participants with AUD showed stronger alcohol-specific PIT effect than controls. Alcohol-specific PIT was positively associated with baseline AUDIT scores and with AUDIT scores across the one-year follow-up. Alcohol cues elicited stronger anterior insula responses, and region-of-interest analysis showed greater left amygdala responses to alcohol versus juice cues in AUD compared with controls. In contrast, general PIT showed a negative association with AUDIT but no association with AUD status. In the general PIT, no AUD-related neural differences were observed. Conclusions: These findings suggest that alcohol-specific PIT captures a clinically meaningful mechanism of cue-driven alcohol seeking that is distinct from generalized motivational transfer, supporting its potential utility as a mechanistic marker in AUD.

Poor inhibitory control and decision-making are often considered as risks for substance use and other adverse psychiatric outcomes. The Stop-Signal Task (SST) is a widely used protocol, from which inhibitory control is indexed by stop signal reaction time (SSRT). However, heretofore models of SSRT may be too simplistic to capture complex processes underlying task performance. In contrast, the Racing Diffusion Ex-Gaussian ABCD (RDEX-ABCD) model provides a more mechanistic framework, capturing both inhibitory control and task-general decision-making processes during the SST. Here, we applied the RDEX-ABCD model to SST data from the IMAGEN cohort (n > 1000) at ages 19 and 23, and examined model parameters in relation to substance use via Elastic Net regression. Connectome-based predictive modeling was then performed to identify brain networks predicting parameters, and the association between these networks and substance use was examined. We found that parameters indexing inhibitory control had no associations with substance use and were only weakly associated with brain connectivity. In contrast, parameters reflecting general decision-making processes - such as efficiency of evidence accumulation, decision threshold (response caution), probability of go failure - and their associated brain activity were significant predictors of cannabis and cigarette use. These findings suggested that efficiency of evidence accumulation, a neurocognitive mechanism that facilitates adaptive decision making across many contexts, emerged as a robust predictor of substance use vulnerability. Overall, general decision-making mechanisms may act as more reliable indicators of vulnerability to substance use than the conventional inhibitory control measures.

ABSTRACT Understanding the dynamics of brain–behaviour relationships during adolescence is critical for elucidating the neurodevelopmental basis of mental health. Leveraging two large-scale longitudinal cohorts—the Adolescent Brain Cognitive Development (ABCD) and IMAGEN studies, comprising over 10,000 participants aged 10 to 22 years with six waves of multimodal neuroimaging and behavioural data, we applied multi-view sparse canonical correlation analysis to investigate evolving associations between structural MRI, resting-state functional connectivity, and multi-domain behavioural measures. Our findings reveal four fundamental patterns of developmental reorganisation in brain-psychopathology relationships. First, symptom profiles evolved from predominantly externalising features (aggression, attention problems) at ages 10-12 toward global psychopathology by age 14, then transitioned toward internalising features (e.g., anxiety, depression) by ages 19-22, reflecting fundamental shifts in vulnerability from behavioural dysregulation to affective disturbance. Second, cortical thickness exhibited negative associations with externalising symptom profiles throughout development. During early adolescence (ages 10-14) this was driven by broadly distributed decreases across sensorimotor, temporal, visual, and cingulate regions alongside overall mean cortical thickness. After 14, this diffuse pattern shifted towards late maturing association cortices, notably the dorsolateral prefrontal and lateral temporal cortices. Third, this was accompanied by subcortical effects that exhibited greater age-specificity: whilst cerebellar volume contributions were evident at most timepoints, basal ganglia volume influence was principally evident in early development (ages 10-12), with thalamic structures and global subcortical grey matter volume becoming dominant at age 14, marking a transition in which subcortical structures mediate psychopathology associations. Fourth, functional connectivity showed a more dynamic developmental trajectory. During early adolescence, symptom associations were driven by positive connectivity between cognitive control and sensorimotor networks, whereas late adolescence exhibited predominantly positive connectivity patterns, transitioning from dense sensorimotor-frontoparietal configurations to more specific patterns involving the central executive and default-mode networks. These findings fundamentally challenge static biomarker models, demonstrating that adolescent psychopathology reflects developmentally contingent brain-behaviour relationships rather than static neural markers. Age 14 emerges as a critical inflection point marked by convergent thalamic reconfiguration, global subcortical grey matter dominance, and symptom profile transitions. This work provides an empirical foundation for precision mental health strategies tailored to specific developmental windows, with implications for reducing psychiatric burden in youth.

This study investigated associations between bullying victimization and brain development using longitudinal structural MRI data from the IMAGEN cohort (n = 2,094; 1,009 females) across three time points (~14, ~19, and ~22 years). A data-driven analysis revealed that higher bullying victimization was significantly associated with accelerated volumetric growth in subcortical and limbic regions, including the putamen (β = 0.12, 95% CI: 0.10-0.15), amygdala (β = 0.07, 95% CI: 0.05-0.09), hippocampus (β = 0.06, 95% CI: 0.04-0.08), and anterior cingulate cortex (caudal: β = 0.05, 95% CI: 0.03-0.07; rostral: β = 0.06, 95% CI: 0.04-0.08). In contrast, bullying victimization was also significantly associated with reduced volumetric growth in the cerebellum (β = -0.09, 95% CI: -0.11 to -0.07), entorhinal cortex (β = -0.10, 95% CI: -0.13 to -0.07), and insula (β = -0.08, 95% CI: -0.11 to -0.06). Exploratory analyses indicated that females exhibited more pronounced changes in emotional processing regions, while males showed greater changes in motor and sensory areas. Overall, the findings indicate that bullying victimization is associated with widespread structural differences in brain development from adolescence to early adulthood, with sex-specific trajectories.

Globally, 60% of the population has experienced at least one type of adversity (e.g., emotional abuse, bullying) across infancy, childhood, and adolescence. Such experiences have been linked to an increased risk for mental health disorders. Changes in brain structure following experiences of childhood adversity have been hypothesised to be a mechanistic pathway explaining later mental health issues. However, to understand how changes in brain structure might mediate the effects of adversity, it is essential to identify which underlying neuronal processes may be affected by different types of adverse experiences. A key open question is whether grey or white matter is more vulnerable to adversity, as these two structures reflect distinct neurobiological mechanisms. This study investigated whether differences in trajectories of grey and white matter development during adolescence can be explained by exposure to different types of adversity. We applied the Adverse Adolescent Experiences Framework (Pollmann et al., 2025) categorising adversity into four levels: Intrapersonal (e.g., accidents), Caregiver (e.g., emotional neglect), Peer (e.g., bullying), and Community (e.g., neighbourhood safety). Exposure to each of the four factors was estimated through principal components analyses. We analysed two large longitudinal datasets: the Adolescent Brain Cognitive Development study (~12,000 adolescents measured at ages 10, 12, and 14) and the IMAGEN study (~1,400 adolescents measured at ages 14, 19, and 22). Using latent growth curve models, we captured individual differences in brain development by estimating baseline levels (intercepts) and rates of change (slopes) for total grey matter volume and mean white matter fractional anisotropy. In both cohorts, we found significant interindividual variability in baseline levels and rates of change for both grey matter volume and fractional anisotropy. Caregiver, Peer, and Community adversities were negatively associated only with the intercepts of grey matter volume and white matter fractional anisotropy. Importantly, associations differed between grey and white matter. In ABCD, Peer and Community adversities were more strongly associated with grey matter volume intercepts. In contrast, in IMAGEN, Caregiver, Peer and Community adversities were more strongly linked to white matter fractional anisotropy intercepts. This suggests that adversity has unique associations with grey and white matter, rather than exerting a uniform influence on brain structure. By demonstrating that different environments generate distinct biological associations with brain maturation, this work underscores the need to consider both grey and white matter when assessing the neurodevelopmental pathways to outcomes across the lifespan.

Background Patients suffering from alcohol dependence (AD) experience high relapse rates. Prior studies investigating the organization of resting-state functional connectivity networks in AD using graph theory typically focused on alterations of the whole network (macroscale) or on aberrations of single brain regions (microscale). However, little is known about the complex dynamics and interactions among different brain regions and neural systems, i.e. the network organization at mesoscale. Methods To investigate mesoscale network alterations, we applied a data-driven community detection algorithm to identify the modular structure of functional brain networks and assess its association with relapse over a 12-month follow-up period in alcohol-dependent patients (relapsers, REL, n = 59; abstainers, ABS, n = 28) and age-and sex-matched controls (CON, n = 83). Results Our results reveal differences in the modular organization in REL, marked by a fragmentation and reorganization of major functional modules. Across individuals, functional modules of REL exhibited higher modular variability, particularly in brain regions associated with behavioral and emotional regulatory processes. Conversely, prefrontal reward-related brain regions were more central for inter-module communication in REL, emerging as functional brain hubs. Furthermore, higher overall modular variability significantly predicted time to relapse during follow-up. Conclusion Collectively, our results shed light on potential neural substrates of relapse risk in alcohol dependence, which may foster the development of targeted interventions to promote sustained abstinence.

Inhibitory control matures progressively from childhood to early adulthood, yet the neural mechanisms driving this development and their relevance to psychiatric risk remain poorly understood. Guided by the Dual Cognitive Control model, we leveraged longitudinal fMRI from two independent cohorts in the US (ABCD, ages 9-12) and Europe (IMAGEN, ages 14-22) to map the spatiotemporal dynamics of reactive and proactive control using novel single-trial modeling and representational similarity analysis. We found both reactive and proactive stopping networks stabilize after mid-adolescence, tracking the developmental patterns of inhibitory control and behavioral stability. By decoding trial-by-trial fluctuations along a speedcaution continuum, we demonstrate that brain-behavior coupling to a proactive "Safe state" tightens progressively with age. Furthermore, network-level representational coherence of this Safe state emerged as a scanner-invariant, trait-like biomarker that robustly predicted inhibitory control, behavioral stability, and transdiagnostic psychopathology across multiple developmental windows, providing a validated neural phenotype for precision psychiatry.

BACKGROUND:Adolescence is a sensitive period when suicidal ideation can peak. Although traumatic life events are a well established risk factor for suicidal ideation, the role of cumulative ordinary life events across multiple dimensions, such as family, autonomy, and sexuality, remains underexplored. Crucially, no evidence is available on how multidimensional trajectories of cumulative exposure to such events relate to suicidal ideation throughout adolescence. We aimed to examine how cumulative and domain-specific trajectories of ordinary life events during adolescence relate to suicidal ideation. METHODS:In this multinational, prospective cohort study, we used longitudinal data from the IMAGEN cohort, gathered from eight centres in Germany, France, Ireland, and the UK between January, 2008, and January, 2010, to model trajectories of exposure to life events during adolescence, and to quantify the association between trajectory group and suicidal ideation. Participants were assessed at ages 14, 16, 19, and 23 years, and key inclusion criteria included having the capacity to provide informed assent or consent, and having parental completion of perinatal and developmental history. Exposure to 39 life events across seven dimensions (family, accidents, distress, autonomy, deviance, sexuality, and relocation) were assessed using the Life Events Questionnaire (LEQ), administered at each of the study timepoints. Childhood maltreatment was also assessed, using the Childhood Trauma Questionnaire, administered once at age 19 years. The primary outcome was the number of participants with suicidal ideation across trajectories, assessed via a dedicated item in the LEQ at the first three timepoints. We also compared self-harm and suicidal ideation responses from the Developmental and Well-Being Assessment at the first three timepoints. Latent trajectory analysis was used to identify classes of cumulative life event exposure across repeated assessments: high, mid-high, mid-low, and low. The association between trajectory group and suicidal ideation was quantified using logistic mixed model regressions, adjusting for childhood maltreatment and demographic covariates. No individuals with lived experience of suicidality or mental health conditions were involved in the design, conduct, or reporting of this research. FINDINGS:At baseline, 2161 adolescents, enrolled between January, 2008, and January, 2010, were included in the cohort (1106 [51·2%] female and 1055 [48·8%] male). Sample sizes at subsequent waves were 1581 at first follow-up (which took place between January, 2011, and January, 2012), 1474 at second follow-up (between January, 2013, and January, 2015), and 1331 at third follow-up (between January, 2016, and January, 2019). At each timepoint, the high trajectory group (1125 [52·1%] of 2161 participants) had the highest proportion of participants with suicidal ideation (90 [8·0%] of 1125 at pre-baseline, 127 [11·3%] of 1125 at age 14 years, 102 [13·4%] of 759 at age 16 years, and 78 [11·0%] of 709 at age 19 years). After controlling for demographics and childhood maltreatment, the high trajectory group had the highest predicted probability of suicidal ideation at each timepoint. Life events in the family dimension predicted adolescent suicidal ideation (marginal R2GLMM=0·078) more than those in all remaining dimensions combined (marginal R2GLMM=0·073). INTERPRETATION:We found that higher cumulative exposure to ordinary life events across multiple dimensions is associated with higher suicidal ideation in adolescence, with life events occurring within the family environment carrying the highest risk. These results point to the importance of evaluating different types of everyday life event exposure, not just childhood trauma or maltreatment, when assessing suicidal risk in adolescents. FUNDING:Abroad Advanced Study Fellowship, Chang Gung Medical Foundation, Taiwan; National Science and Technology Council, Taiwan; Medical Research Council, UK.

Human cognitive processing involves dynamic interactions across brain regions, evolving over time. Traditional neuroimaging analysis often overlooks this temporal aspect, limiting insights into how functional network connectivity (FNC) supports ongoing cognition and behaviour. Using sliding window analysis, we captured FNC changes during tasks, reflecting network reconfiguration in cognitive processes. We further determined behavioural relevance of time-varying FNC by relating network measurements with task performances and psychopathology. We found that several whole-brain FNC patterns, or states, persist across resting and task-based fMRI, with state occurrences fluctuating with the most prominent task stimuli. Regional FNC distinguishes specific task conditions, and time-varying FNC explains more variance in psychopathology symptoms compared to static connectivity. These findings highlight that cognitive tasks reshape regional and whole-brain connectivity. By considering the different FNC states, time-varying connectivity provides a more comprehensive representation of brain interactions and thus may represent a better neural proxy for cognition and behaviour.

Geflüchtete Menschen haben ein höheres Risiko für Substanzkonsum. Risikofaktoren umfassen traumatische Erfahrungen und Belastungen durch Migration. Unser Verständnis von Substanzkonsum als soziokulturell geprägter Erfahrung ist noch immer begrenzt. Diese Studie zielt darauf ab, die kulturelle Dimension von Substanzkonsum in der Wahrnehmung arabischsprachiger Geflüchteter in Berlin zu explorieren. In einem qualitativen Ansatz wurden zwischen 2020 und 2021 Tiefen- und teilstrukturierte Interviews mit 13 arabischsprachigen Geflüchteten in suchttherapeutischer Behandlung geführt. Die Stichprobe wurde in zwei suchttherapeutischen Einrichtungen in Berlin rekrutiert und repräsentiert verschiedene soziodemografische Charakteristika und Konsumprofile. Die Teilnehmenden waren zwischen 21 und 52 Jahre alt und stammten aus acht verschiedenen arabischen Ländern. Die Interviews wurden aufgezeichnet, transkribiert und im Rahmen einer thematischen Analyse mit MAXQDA ausgewertet. Drei Hauptthemen wurden herausgearbeitet: (1) die Beachtung individueller Motive für Substanzkonsum vor dem Hintergrund von Coping-Mechanismen, Vertreibung und Marginalisierung; (2) die Beeinflussung des Konsumverhaltens durch soziokulturelle Normen; (3) die Rolle unterschiedlicher Terminologien und Begrifflichkeiten für einen effektiven Austausch zu dem Thema. Die Studie untersucht Unterschiede in kulturellen, individuellen und sozialen Dimensionen in Bezug auf Substanzkonsum unter arabischsprachigen Geflüchteten. Wir verweisen auf die Notwendigkeit, linguistische und kulturelle Dynamiken in Forschung und Praxis anzuerkennen. Weitere Forschung sollte Motive für Substanzkonsum sowie Möglichkeiten der Prävention und Behandlung bei Geflüchteten.

Background Adolescence is a critical period for the emergence of obesity and disordered eating behaviours, yet the biological mechanisms underlying persistent differences in body mass index (BMI) development remain poorly understood. We investigated whether longitudinal BMI profiles are associated with behavioural, neurodevelopmental, and epigenetic variation during adolescence. Methods Participants from the IMAGEN cohort (N = 1,296) were followed from ages 14 to 23 years. Latent profile analysis identified longitudinal BMI profiles. Disordered eating behaviours were repeatedly assessed across adolescence. Structural MRI acquired at ages 14 and 23 characterised longitudinal changes in grey matter volume (GMV), cortical thickness (CT), and sulcal depth (SD). Genome-wide DNA methylation was measured in whole blood at age 14. Epigenome-wide association studies (EWAS), functional enrichment analyses, and a DNA methylation-based BMI risk score (bmiMRS) were conducted. Results Two distinct BMI profiles were identified: a persistently overweight group and a persistently normal-weight group. Adolescents with persistent overweight showed progressively increasing BMI, greater eating-, weight-, and shape-related concerns, and more frequent dieting and binge-eating behaviours. They also exhibited atypical cortical maturation, characterised by attenuated cortical thinning, accelerated reductions in sulcal depth, and reduced grey matter volume loss within frontal and temporal association cortices. EWAS identified 29 BMI-associated CpGs (Bonferroni-corrected P < 1.3×10-7), enriched for genes involved in adipogenesis, immune and inflammatory signalling, type 2 diabetes, and brain-related biological processes. The bmiMRS predicted BMI, cumulative BMI across adolescence, and membership of the persistently overweight group, and remained significantly associated with BMI in an independent cohort. Longitudinal analyses further suggested reciprocal associations between BMI and brain maturation, with higher BMI in early adolescence predicting subsequent regional GMV changes, whereas lower baseline cortical thickness predicted greater BMI increases independently of baseline BMI. Conclusions Persistent adolescent overweight is associated with distinct behavioural, neurodevelopmental, and peripheral epigenetic signatures. Integrating longitudinal neuroimaging and DNA methylation identifies molecular biomarkers and brain developmental features associated with sustained BMI elevation, providing a framework for earlier risk stratification and informing biologically grounded approaches to obesity prevention.

Abstract Changes in personality during adolescence may shape future alcohol use, especially in times of societal crisis. The COVID-19 pandemic disrupted social norms and stress regulation, making it a natural experiment to examine how early-life personality trajectories predict later substance use. Using longitudinal data from the European IMAGEN cohort (N = 968), we investigated whether intra-individual personality changes during adolescence predicted alcohol use at three timepoints: pre-pandemic, immediately after COVID-19 onset (T1), and several months into the pandemic (T2). Generalized Additive Mixed Models (GAMMs) were used to model non-linear relationships between adolescent personality change (e.g., in anxiety sensitivity and openness) and alcohol use frequency across time. Participants were drawn from the IMAGEN cohort (N = 968; 54.4% female), assessed longitudinally from early adolescence (BL: M = 13.93, SD = 0.41) through middle (FU1: M = 16.04, SD = 0.60) and late adolescence (FU2: M = 18.41, SD = 0.65) to early adulthood (FU3: M = 22.00, SD = 0.66), with additional follow-ups during the COVID-19 pandemic (COVID-T1: M = 25.00, SD = 0.81; COVID-T2: M = 25.56, SD = 0.75). Assessments were conducted at approximately 2-year intervals during adolescence and at shorter intervals (several months) during the COVID-19 period. Analyses controlled for sex and country-level lockdown stringency. Intra-individual fluctuations in anxiety sensitivity significantly predicted increased alcohol use several months into the pandemic (T2; EDF = 1.86, p < 0.05), but not immediately after lockdown (T1). Pre-pandemic alcohol use was instead associated with changes in openness (EDF = 1.00, p < 0.05). Exploratory analyses suggested gender differences in anxiety-related drinking risk. Our findings suggest that personality dynamics in adolescence shape alcohol use responses during societal crises. Different traits appear to matter depending on the temporal and emotional context of the stressor. These findings have implications for personalized prevention efforts targeting stress-related substance use in youth.

BACKGROUND:Although the initiation of alcohol consumption is common during adolescence, some individuals engage in binge drinking behavior that could lead to harmful consequences such as developing alcohol use disorder later in life. Evidence suggests a relationship between depressive symptoms and harmful alcohol consumption that seems to vary depending on sex. Furthermore, it has been suggested that amygdala activation in response to negative emotional stimuli influences drinking due to depressive mood states. Therefore, we expected a sex-dependent effect of neuronal activation and depressive symptoms on risky drinking. METHODS:Here, we tested our hypothesis using a large dataset of 19-year-old participants (n = 958) in the IMAGEN study. Amygdala activation during an emotional faces task was extracted and entered into sex-moderated mediation models that also included scores from the Alcohol Use Disorders Identification Test and the Adolescent Depression Rating Scale. RESULTS:Moderated mediation models indicated that amygdala activation was associated with hazardous drinking through enhanced depressive symptoms in males, while amygdala reactivity in females was associated with decreased risky drinking. CONCLUSIONS:Taken together, our findings reveal sex differences in negative emotional processing in at-risk adolescents. These associations have the potential to inform the development of sex-specific strategies as well as the detection of early neuronal risk factors to effectively curtail alcohol risk behavior.

Alcohol use disorder (AUD) is considered a chronic disorder with a highly variable course. Understanding this variability is crucial for identifying factors associated with persistence versus spontaneous remission. We analysed data from N = 462 individuals with AUD in an observational longitudinal cohort study to identify factors associated with spontaneous remission. All participants met Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria for AUD at study entry and were reassessed after 1 year, in which they were classified as being in spontaneous remission (n = 107), falling below the ≥ 2-criteria threshold for AUD (n = 87) or continuing to meet AUD criteria (n = 296). Groups were compared on socio-demographic, clinical and substance use variables at baseline and after 1 year. Additionally, we used machine learning models to identify baseline characteristics predicting a persistent course of AUD. Between-group comparisons revealed that individuals who experienced spontaneous remission reported significantly lower AUD severity (F(2,459) = 25.17, p < 0.001), lower levels of alcohol intake (F(2,459) = 8.31, p = 0.013) and fewer drinking days (F(2,459) = 11.91, p < 0.001) at baseline and after 1 year. Machine learning analysis demonstrated moderate classification performance (AUC = 0.679), with the Alcohol Use Disorders Identification Test (AUDIT) sum score being the most informative predictor for group classification. Our findings indicate significant differences between spontaneously remitted and non-remitted individuals on key alcohol-related variables, supporting the clinical validity of remission as defined by the National Institute on Alcohol Abuse and Alcoholism (NIAAA). In addition, baseline characteristics may help identify individuals at risk of persistent AUD, enabling earlier identification of those who may benefit from specialized treatment. TRIAL REGISTRATION: DRKS number: DRKS00020580.

Brain charts have emerged as a highly useful approach for understanding brain development and aging on the basis of brain imaging and have shown substantial utility in describing typical and atypical brain development with respect to a given reference model. However, all existing models are fundamentally cross-sectional and cannot capture change over time at the individual level. We address this using velocity centiles, which directly map change over time and can be overlaid onto cross-sectionally derived population centiles. We demonstrate this by modelling rates of change for 24,062 scans from 10,795 healthy individuals with up to 8 longitudinal measurements across the lifespan. We provide a method to detect individual deviations from a stable trajectory, generalising the notion of 'thrive lines', which are used in pediatric medicine to declare 'failure to thrive'. Using this approach, we predict transition from mild cognitive impairment to dementia more accurately than by using either time point alone, replicated across two datasets. Last, by taking into account multiple time points, we improve the sensitivity of velocity models for predicting the future trajectory of brain change. This highlights the value of predicting change over time and makes a fundamental step towards precision medicine.

Clinical heterogeneity in the symptom trajectories of attention deficit hyperactivity disorder (ADHD) is well documented, but their neurodevelopmental mechanisms remain unclear. We used a longitudinal cohort of adolescents (ABCD; n = 7,436) to show that persistent, remitting and emergent ADHD symptom trajectories correlated with persistent, improving and worsening behavioral changes, respectively. Each trajectory had distinct brain signatures: faster cortical thinning (persistence), slower thinning (emergence) and faster subcortical expansion (remission). Slower cortical thinning in the right posterior cingulate was associated with inattention symptom increase, whereas faster hippocampal expansion was associated with inattention symptom decrease. These signatures enhance ADHD symptom prediction at age 13 and generalize to young adults (age 23) in the IMAGEN cohort. The hippocampal signature for remitting symptoms was replicated in IMAGEN and two clinical cohorts (ADHD-200 and ADHD-1000). Given that baseline ADHD medication use was not significantly associated with the remitting trajectory, our findings suggest that current treatments may not facilitate sustained remission, highlighting the potential for new interventions.

Abstract Human reward processing varies along cue-centric and outcome-centric axes, but a reproducible mechanistic account of individual variation in incentive salience attribution has been lacking. Using fMRI across five cohorts (N-total=1,251; N1=890; N2=245; N3=34; N4=48; N5=34), we identified two robust imaging phenotypes mirroring sign- and goal-tracking (ST-like, GT-like). ST-like individuals showed dominant ventral striatal responses to reward-anticipation cues and sustained incentive salience attribution; GT-like individuals showed heightened responses to reward outcomes. This distinction was replicable across sites and independent samples. Single-dose and repeated-dose D 2 /D 3 antagonism (risperidone, haloperidol, amisulpride) selectively reduced anticipatory ventral striatal activity in ST, with single-dose antagonism additionally producing a parallel drop in self-reported energy. Instead, D 2 /D 3 partial agonism (aripiprazole) increased anticipatory and reduced outcome-phase responses in GT. In a psychosis cohort, antipsychotic D 2 affinity was associated with blunted anticipatory signals and higher negative symptom burden, offering a neuroimaging-driven basis for stratifying patients and predicting response to dopaminergic agents.