Biology subjects

Banaschewski, T.

Publications and source records attributed to Banaschewski, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Early life stress alters lifespan trajectories of amygdala development: a cross-species model of amygdala burnout

Early-life stress is associated with alterations in amygdala volume, but findings vary across studies and species. Rodent models typically report increased amygdala volume, whereas human studies often find reductions or mixed effects. We propose the amygdala burnout hypothesis, which suggests that early-life stress alters amygdala developmental trajectories, producing initial volumetric increases that are followed by reductions later in life. To test this hypothesis, we examined amygdala development across rodent and human cohorts spanning adolescence to older adulthood. In rodents, chronic stress was associated with increased amygdala nuclei volumes during adolescence. Comparable increases were observed in adolescents from the IMAGEN consortium, with evidence of a dose-dependent association between childhood stress and amygdala developmental trajectories. In contrast, analyses of older adults from the UK Biobank revealed reduced bilateral amygdala volume associated with early-life stress. Together, these findings support a developmental model that reconciles previously conflicting observations across species and age groups. Early-life stress is associated with alterations in amygdala volume, but findings vary across studies and species. Rodent models typically report increased amygdala volume, whereas human studies often find reductions or mixed effects. We propose the amygdala burnout hypothesis, which suggests that early-life stress alters amygdala developmental trajectories, producing initial volumetric increases that are followed by reductions later in life. To test this hypothesis, we examined amygdala development across rodent and human cohorts spanning adolescence to older adulthood. In rodents, chronic stress was associated with increased amygdala nuclei volumes during adolescence. Comparable increases were observed in adolescents from the IMAGEN consortium, with evidence of a dose-dependent association between childhood stress and amygdala developmental trajectories. In contrast, analyses of older adults from the UK Biobank revealed reduced bilateral amygdala volume associated with early-life stress. Together, these findings support a developmental model that reconciles previously conflicting observations across species and age groups.

neuroscience↗

bioRxiv2026

Sex-specific associations of childhood adversity with frontostriatal network organization and anhedonia in young adulthood

IntroductionAnhedonia is a transdiagnostic psychiatric symptom linked to increased functional connectivity between the prefrontal cortex and striatum. Here, we examined how dimensions of early adversity contribute to this profile of connectivity. MethodsIn a European community sample of young adults (IMAGEN), we examined cross-sectional (n=613) and longitudinal (n=332) associations of adversity dimensions with resting-state fMRI-derived connectivity. We selected 10 ROIs from anhedonia literature, defined in the functional images as 4mm-radius spheres. We then used network-based regression models to identify clusters of ROI-ROI connections associated with threat and deprivation scores, using interaction terms to examine sex and age-specific associations. We also examined associations between adversity and anhedonia, operationalized using factor analysis of six items from self-report surveys. ResultsAt age 18-22, we identified sex-specific associations between deprivation and connectivity for a cluster of 9 ROI-ROI connections (p-FWE=0.038), primarily involving the nucleus accumbens. Specifically, we observed positive associations between deprivation and connectivity in males, and negative associations in females. In the longitudinal analysis, negative deprivation associations in females attenuated with age for a cluster of 14 connections (p-FWE=0.009). A cluster of 17 connections also had initial positive associations with threat in females that attenuated with age (p-FWE=0.008). No such longitudinal changes were observed in males. Higher deprivation was linked to increased later anhedonia in males but not females (p=0.026). ConclusionCompared to females, young adult males may be more vulnerable to developing anhedonia after experiencing deprivation in childhood. Dimensions of early adversity are linked to distinct pathways of frontostriatal development.

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bioRxiv2026

Protracted Maturation of Proactive and Reactive Systems Predicts Cognitive Stability and Psychopathology : A longitudinal multi-cohort study

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 speed-caution 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.

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bioRxiv2026

Adversity and adolescent brain development: differential associations with grey and white matter across two longitudinal cohorts

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.

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bioRxiv2026

Trajectories of brain organisation transition from predicting externalising to internalising symptoms across adolescence

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.

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bioRxiv2026

Reproducible Human Reward Imaging Phenotypes Exhibit Differential Sensitivity to Dopamine D2 Receptor Antagonism

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 D2/D3 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, D2/D3 partial agonism (aripiprazole) increased anticipatory and reduced outcome-phase responses in GT. In a psychosis cohort, antipsychotic D2 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.

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bioRxiv2026

Digital Twin Brain simulation and manipulation of a functional brain network underlying mental illness

Linking synaptic-level perturbations to distributed brain-network dynamics remains a central challenge for understanding and treating mental illness. Although recent whole-brain models can reproduce individual brain activity patterns, they largely function as descriptive simulators rather than mechanistic, intervention-capable systems. Here we present an intervention-capable digital twin of the human brain, integrating individual neuroanatomy and task-evoked dynamics within a neuronal-scale framework. Individualised digital twin brains recapitulate a participant-specific compact cortico-subcortical network phenotype that captures transdiagnostic psychopathology across population and clinical cohorts. In silico modulation of excitatory and inhibitory synaptic conductance produces bidirectional, heterogeneous network responses across individuals. Population-scale simulations stratify individuals and predict longitudinal symptom trajectories from DTB-derived response profiles. Independent pharmacological functional MRI data further validate the predicted baseline-dependent network responses in vivo. Together, these findings establish digital brain models as experimental platforms for mechanistic perturbation, behavioural prediction and stratification, providing a foundation for precision neuroscience and psychiatry.

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bioRxiv2025

Linking White-Matter Development to Clinical Variation in Autism: Longitudinal Normative Modelling of FA in the EU-AIMS LEAP Cohort

BackgroundAutism is characterised by neurobiological and clinical heterogeneity, which often limits the sensitivity of traditional group comparisons. Longitudinal normative modelling offers a way to capture heterogeneity and to describe an individuals brain-behaviour relationships beyond diagnostic categories. MethodsWe analysed diffusion MRI scans from 3 waves of the EU-AIMS Longitudinal European Autism Project (LEAP). Using normative models of white matter fractional anisotropy (FA) trained on a neurotypical reference cohort, we computed individual deviations relative to age-typical norms. Our sample included 544 individuals (Wave 1: 189 autistic 162 non-autistic; Wave 2: 162 autistic136 non-autistic; Wave 3: 145 autistic 84 non-autistic), aged 7-37 years, with mean intervals of [~]1.5 years (W1-W2) and [~]6 years (W2-W3). We first tested for group level differences between autistic and non-autistic participants in FA deviations across 48 white matter tracts and then examined the associations between these deviation scores and sensory, adaptive, cognitive, and behavioural measures across development within the autism group. ResultsGroup-wise comparisons revealed no significant differences in FA deviations between autistic and non-autistic participants. Within the autism group, multivariate analysis (CCA) showed significant (p<0.05) cross-sectional brain-behaviour associations at Wave 1 (r=0.26) and Wave 2 (r=0.32), but not at Wave 3. Longitudinally, we found significant multivariate associations only for the W1-W3 interval (r=0.36). Follow-up univariate correlations supported these findings, with Wave 2 showing widespread moderate (r{approx}0.35) associations while longitudinally, the univariate associations were generally weaker (r{approx}0.2). Across analyses, higher FA was generally associated with higher Vineland Adaptive Behaviour Scales (VABS) and lower Short Sensory Profile (SSP) scores. Associations with the Autism Diagnostic Observation Schedule (ADOS) were mixed, and the Social Responsiveness Scale (SRS) and Repetitive Behaviour Scale (RBS) showed wave-dependent relationships, with specific tract involvement varying across timepoints. ConclusionsWhite-matter organisation in autism does not differ from that of non-autistic on average but rather follows a dimensional architecture within the autism phenotype. We showed that person-specific deviations from shared neurodevelopmental pathways are linked to behavioural variation among autistic individuals, which cannot be captured by group-level approaches alone. Longitudinal normative modelling provides a practical approach to understand and quantify this heterogeneity. EU-AIMS LEAP GroupZuzana Suchomelova, Mee Rim Oh, Chirag Mehra, Mei Lin Law, Sanjana Gandhi, Laura Bravo Balsa, Maria Dauvermann, Isabel Yorke, Beth Oakley, Rosemary J. Holt, Edward Bullock, Yumnah Kahn, Esme Hayes, Leona Strauss, Noel Lam, Anouk Dykstra, Kim Lamers, Marije Mars, Lucas Geelen, Lotte Beckers, Anna Praat, Feline van Aagten, Sjors Reith, Viola Hollestein, Sanne Kluin, Natalie Forde, Jill Naaijen, Anna Kaiser, Sarah Baumeister, Pascal-M. Aggensteiner, Jumana Ahmad, Sara Ambrosino, Bonnie Auyeung, Tobias Banaschewski, Simon Baron-Cohen, Sarah Baumeister, Christian F. Beckmann, Sven Bolte, Thomas Bourgeron, Carsten Bours, Michael Brammer, Daniel Brandeis, Claudia Brogna, Yvette de Bruijn, Jan K. Buitelaar, Bhismadev Chakrabarti, Tony Charman, Ineke Cornelissen, Daisy Crawley, Flavio DellAcqua, Guillaume Dumas, Sarah Durston, Christine Ecker, Jessica Faulkner, Vincent Frouin, Pilar Garces, David Goyard, Lindsay Ham, Hannah Hayward, Joerg Hipp, Rosemary J. Holt, Mark H. Johnson, Emily J. H. Jones, Prantik Kundu, Meng-Chuan Lai, Xavier Liogier Dardhuy, Michael V. Lombardo, Eva Loth, David J. Lythgoe, Rene Mandl, Andre Marquand, Luke Mason, Maarten Mennes, Andreas Meyer-Lindenberg, Carolin Moessnang, Nico Mueller, Declan G. M. Murphy, Laurence ODwyer, Marianne Oldehinkel, Bob Oranje, Gahan Pandina, Antonio M. Persico, Jack Price, Annika Rausch, Barbara Ruggeri, Amber N. V. Ruigrok, Jessica Sabet, Roberto Sacco, Antonia San Jose Caceres, Emily Simonoff, Will Spooren, Julian Tillmann, Roberto Toro, Heike Tost, Jack Waldman, Steve C. R. Williams, Caroline Wooldridge, Iva Ilioska, Ting Mei, Marcel P. Zwiers. Key PointsO_ST_ABSQuestionC_ST_ABSIn the context of heterogeneity in autism, what do individual differences in white-matter development reveal about brain-behaviour relationships over time? FindingsIn this study, we found significant relationships between individual white-matter deviations and clinical traits in autism both cross-sectionally as well as longitudinally. Increased adaptive functioning and decreased sensory processing were associated with higher FA in long-association and commissural pathways, including the cingulum bundle, superior longitudinal fasciculus, and corpus-callosum, with longitudinal effects most evident over a 7.5-year interval. MeaningDevelopmentally informed normative modelling of white matter offers a pathway toward biologically grounded stratification for precision medicine in autism.

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bioRxiv2025

Chronic pain is linked to a resting-state neural archetype that optimizes learning from punishments

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 (n = 892) and three clinical samples with subacute back pain (n = 76), chronic back pain (n = 30), and treatment-resistant depression (n = 24). Using the sample from the general population, we found three neural archetypes that prioritize different cognitive strategies. Clinical pain samples, compared to the sample from the general population, mapped close to an archetype optimized for punishment learning (Archetype P). We replicated these results by recomputing the archetypes starting from the clinical pain samples, additionally revealing an association between Archetype P and pain severity. These findings suggest a neural-cognitive trait underlying susceptibility to chronic pain.

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bioRxiv2025

Brain Diffusion Transformer for Personalized Neuroscience and Psychiatry

Task-fMRI analyses typically focus on localized activation contrasts between stimuli, neglecting the brains dynamic hierarchy. We introduce Brain Diffusion Transformer (Brain-DiT), a deep generative model capturing recurrent processing underlying individualized neurocognitive state transitions via functional networks. Without prior assumptions, Brain-DiT identifies canonical cognitive regions in the brain and reveals replicable subgroups with distinct neural circuits in large cohorts, offering critical clinical insights overlooked by traditional methods: individuals exhibiting negative emotion bias, linked to language-related regions, had a 12-fold higher likelihood of major depression, and those with maladaptive inhibition strategies, associated with overactive medial frontal regions, showed a 9-fold increased risk of alcohol abuse. By bridging cognitive theory and psychiatric applications, Brain-DiT provides a unified analytical paradigm, paving the way for operational personalized medicine in psychiatry.

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bioRxiv2025

Mapping the coupling between tract reachability and cortical geometry of the human brain

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 brains folding patterns and white matter connectivity unexplored. In this study, we aimed to elucidate fundamental links between cortical geometry and white matter tract connectivity. We developed the concept of tract-geometry coupling (TGC) by optimizing the alignment between tract connectivity to the cortex and multiscale cortical geometry. Specifically, spectral analyses of the cortical surface yielded a set of geometrical eigenmodes, which were then used to explain the locations on the cortical surface reached by specific white matter tracts, referred to as tract reachability. In two independent datasets, we confirmed that tract reachability was well characterized by cortical geometry. We further observed that TGC had high test-retest ability and was specific to each individual. Interestingly, low-frequency TGC was found to be heritable and more informative than the high-frequency components in behavior prediction. Finally, we found that TGC could reproduce task-evoked cortical activation patterns. Collectively, our study provides a new approach to mapping coupling between cortical geometry and connectivity, highlighting how these two aspects jointly shape the connected brain.

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bioRxiv2024

Reward processing in children with Affective Dysregulation

IntroductionAffective dysregulation (AD) in children is characterized by irritability, anger, and frequent intense temper outbursts. Considerable evidence implies altered processing of frustration about missed rewards, but few studies investigated the preceding and thus potentially predictive reward anticipation and initial delivery processing in children with AD. MethodsA total of 103 children aged 8 to 12 years (50 with AD and 53 without AD) were examined during a monetary reward anticipation task with event-related potential (ERP) components resolving reward anticipation (cue-CNV [Contingent Negative Variation]) and reward delivery phases (Reward Positivity and Feedback-Related Negativity). All components were analyzed by repeated measures ANOVA. Regression analyses also evaluated the associations between those ERP components and dimensional AD symptoms. ResultsChildren with AD showed attenuated anticipatory reward processing compared to No-ADs. The CNV at fronto-central site (FCz) showed a significant group effect (No-AD>AD, p=0.017). Post-hoc test showed that this group difference was stronger for the cue monetary condition (monetary cue: p=.007, d=0.56, verbal cue: p=.901, d=0.16), and that only the No-AD group showed a significant difference between conditions (p<0.001). No significant effects were obtained for the delivery phase. Regression analysis showed that a reduced anticipatory CNV at FCz significantly explained AD symptoms, and that anger/irritability and anxiety/depressive symptoms predicted a reduced anticipatory CNV at FCz. ConclusionThis neurophysiological characterization of reward anticipation and delivery in children with AD demonstrates altered neural activity in AD during anticipation of reward rather than following the delivery (or omission) of the reward itself. Our results highlight that altered reward anticipation in AD can occur outside frustration-prone tasks or settings, and underline the important role of both anger/irritability and anxiety/depressive symptoms in the pathophysiology of AD for atypical reward anticipation.

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bioRxiv2024

Qualitative EEG abnormalities signal a shift towards inhibition-dominated brain networks. Results from the EU-AIMS LEAP studies

Qualitative EEG abnormalities are common in Autism Spectrum Disorder (ASD) and hypothesized to reflect disrupted excitation/inhibition balance. To test this, we recently introduced a functional measure of network-level E/I ratio (fE/I). Here, we applied fE/I and other EEG measures to alpha oscillations from source-reconstructed data in the EU-AIMS dataset (267 ASD, 209 controls). We analyzed these measures alongside qualitative EEG abnormalities ranging from slowing of activity to epileptiform patterns, aiming to replicate the findings from the SPACE-BAMBI study. EEG abnormalities were rare in adults and could not be statistically assessed. ASD children-adolescents with EEG abnormalities exhibited lower relative alpha power and fE/I compared to those without. However, EEG-abnormality scoring did not stratify the behavioral heterogeneity of ASD using clinical measures. Surprisingly, several controls also exhibited qualitative EEG abnormalities with a strikingly similar anatomical distribution of reduced fE/I, suggesting a shift towards inhibition-dominated network dynamics in sensory processing regions. The robustness of this association between EEG abnormalities and reduced fE/I was further supported by re-analysis of the SPACE-BAMBI study in source space. Stratification by the presence of EEG abnormalities and their effects on network activity may help understand neurodevelopmental physiological heterogeneity and the difficulties in implementing E/I targeting treatments in unselected cohorts.

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bioRxiv2024

Genetic-Dependent Brain Signatures of Resilience: Interactions among Childhood Abuse, Genetic Risks and Brain Function

Resilience to emotional disorders is critical for adolescent mental health, especially following childhood abuse. Yet, brain signatures of resilience remain undetermined due to the differential susceptibility of the brains emotion processing system to environmental stresses. Analyzing brains responses to angry faces in a longitudinally large-scale adolescent cohort (IMAGEN), we identified two functional networks related to the orbitofrontal and occipital regions as candidate brain signatures of resilience. In girls, but not boys, higher activation in the orbitofrontal-related network was associated with fewer emotional symptoms following childhood abuse, but only when the polygenic burden for depression was high. This finding defined a genetic-dependent brain (GDB) signature of resilience. Notably, this GDB signature predicted subsequent emotional disorders in late adolescence, extending into early adulthood and generalizable to another independent prospective cohort (ABCD). Our findings underscore the genetic modulation of resilience-brain connections, laying the foundation for enhancing adolescent mental health through resilience promotion.

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bioRxiv2024

Bullying and Early Brain Development: A Longitudinal Structural Magnetic Resonance Imaging Study from Adolescence to Early Adulthood

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 ({beta} = 0.12, 95% CI: 0.10-0.15), amygdala ({beta} = 0.07, 95% CI: 0.05-0.09), hippocampus ({beta} = 0.06, 95% CI: 0.04- 0.08), and anterior cingulate cortex (caudal: {beta} = 0.05, 95% CI: 0.03-0.07; rostral: {beta} = 0.06, 95% CI: 0.04-0.08). In contrast, bullying victimization was also significantly associated with reduced volumetric growth in the cerebellum ({beta} = -0.09, 95% CI: -0.11 to -0.07), entorhinal cortex ({beta} = -0.10, 95% CI: -0.13 to -0.07), and insula ({beta} = -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.

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bioRxiv2024

Variation in moment-to-moment brain state engagement changes across development and contributes to individual differences in executive function

Neural variability, or variation in brain signals, facilitates dynamic brain responses to ongoing demands. This flexibility is important during development from childhood to young adulthood, a period characterized by rapid changes in experience. However, little is known about how variability in the engagement of recurring brain states changes during development. Such investigations would require the continuous assessment of multiple brain states concurrently. Here, we leverage a new computational framework to study state engagement variability (SEV) during development. A consistent pattern of SEV changing with age was identified across cross-sectional and longitudinal datasets (N>3000). SEV developmental trajectories stabilize around mid-adolescence, with timing varying by sex and brain state. SEV successfully predicts executive function (EF) in youths from an independent dataset. Worse EF is further linked to alterations in SEV development. These converging findings suggest SEV changes over development, allowing individuals to flexibly recruit various brain states to meet evolving needs.

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bioRxiv2024

Generating Synthetic Task-based Brain Fingerprints for Population Neuroscience Using Deep Learning

Task-based functional magnetic resonance imaging (tb-fMRI) reveals individual differences in the neural basis of cognitive functions by linking specific tasks to neural responses. However, scaling tb-fMRI to population-level studies is challenging due to its cognitive demands, variations in task design across studies, and the limited scope of tasks in large datasets. To address this, we propose DeepTaskGen, a deep-learning approach that generates non-acquired task-based contrast maps from resting-state fMRI (rs-fMRI) data. Our approach enables generating synthetic task images for non-acquired tasks within the study protocol. We validate this approach using the Human Connectome Project lifespan data, then generate 47 contrast maps from 7 different cognitive tasks for over 20,000 individuals from UK Biobank. DeepTaskGen outperforms several benchmarks in generating synthetic task-contrast maps, exhibiting superior reconstruction performance while retaining inter-individual variation essential for biomarker development. Notably, we further showed that synthetic task contrast maps achieved similar or greater performance compared to actual task contrast maps and resting-state connectomes for predicting a wide range of demographic, cognitive, and clinical variables. This approach will facilitate the study of individual differences and the generation of task-related biomarkers by enabling the generation of arbitrary functional cognitive tasks from readily available rs-fMRI data.

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bioRxiv2024

Adolescent maturation of cortical excitation-inhibition balance based on individualized biophysical network modeling

The balance of excitation and inhibition is a key functional property of cortical microcircuits which changes through the lifespan. Adolescence is considered a crucial period for the maturation of excitation-inhibition balance. This has been primarily observed in animal studies, yet human in vivo evidence on adolescent maturation of the excitation-inhibition balance at the individual level is limited. Here, we developed an individualized in vivo marker of regional excitation-inhibition balance in human adolescents, estimated using large-scale simulations of biophysical network models fitted to resting-state functional magnetic resonance imaging data from two independent cross-sectional (N = 752) and longitudinal (N = 149) cohorts. We found a widespread relative increase of inhibition in association cortices paralleled by a relative age-related increase of excitation, or lack of change, in sensorimotor areas across both datasets. This developmental pattern co-aligned with multiscale markers of sensorimotor-association differentiation. The spatial pattern of excitation-inhibition development in adolescence was robust to inter-individual variability of structural connectomes and modeling configurations. Notably, we found that alternative simulation-based markers of excitation-inhibition balance show a variable sensitivity to maturational change. Taken together, our study highlights an increase of inhibition during adolescence in association areas using cross sectional and longitudinal data, and provides a robust computational framework to estimate microcircuit maturation in vivo at the individual level.

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