Developmental Coordination Disorder (DCD) is a prevalent neurodevelopmental disorder characterized by significant motor impairments. Traditionally viewed as a deficit in motor execution, it is now increasingly understood to involve disruptions in cognitive processes underpinning motor control, including internal modeling, motor planning, and predictive control. This cognitive reconceptualization suggests the need for a shift in intervention approaches. This narrative review synthesizes theoretical, neurophysiological, and empirical literature to critically evaluate the role of Motor Imagery (MI)-the mental simulation of action without overt movement-as a cognitive mechanism for intervention in children with DCD. We examine the core cognitive and representational deficits in DCD, outline the neural foundations and theoretical frameworks of MI, and provide a narrative synthesis finding from key intervention studies. Evidence suggests that children with DCD often exhibit impairments in motor imagery ability, reflecting possible disruptions in internal modeling processes. Nonetheless, structured MI-based interventions, particularly when combined with action observation (AOMI), have shown promising, though preliminary, effects in improving motor performance and activities of daily living. MI has been shown to engage neural networks overlapping with those involved in motor execution, and may promote neuroplasticity and support the perception-action cycle by facilitating predictive control and sensorimotor integration. MI may represent not only a therapeutic technique but also a useful window for understanding the cognitive mechanisms underlying DCD. By potentially targeting impaired internal models, MI-based approaches may contribute to functional improvements, although direct causal evidence remains limited. Future research should focus on standardize methodologies, conduct larger-scale trails, and carefully examine emerging technologies to develop personalized and ecologically valid intervention protocols. We propose a forward-looking perspective in which MI may serve as a component of mechanism-driven, technology-augmented, and ecologically valid interventions, potentially contributing to a shift from compensatory training toward more active cognitive-oriented approaches in DCD rehabilitation.
ADHD may lead to depression, but little is known about its underlying mechanisms. We examined whether clinical factors (irritability, anxiety), cognitive-affective processes (emotion recognition, response inhibition, working memory, sustained attention), and negative thought patterns (external locus of control, negative cognitive style), mediate ADHD-depression associations across development and whether these pathways differ by sex. Analyses were performed in the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Twins Early Development Study (TEDS). In both samples, ADHD was assessed using the Strengths and Difficulties Questionnaire (SDQ) hyperactivity/inattention subscale at ages 7, 12/13, and 16/17. Depressive symptoms were assessed using the short Mood and Feelings Questionnaire at ages 12, 18/21, and 26/27. Mediators were assessed at ages 8-11, 16-17, and 21-25 with counterfactual mediation models. Clinical factors were assessed and mediated the ADHD-depression effect in both cohorts across development. In ALSPAC, clinical mediators contributed most in childhood (30%) and young adulthood (25%), whereas in TEDS, they contributed most in adolescence (46%). In ALSPAC, negative thought patterns mostly contributed in adolescence (39%), while cognitive-affective factors did not show consistent evidence of mediating effects across development. All mediators combined explained 30%, 48% and 29% of the total effect of ADHD on depression in childhood, adolescence, and young adulthood, respectively. In sex-stratified models, the relative contribution of mediators varied by sex and developmental stage. In childhood, mediators accounted for a greater proportion of the total effect in males (37%) than in females (25%), while a similar proportion of mediated effects was observed across sexes during adolescence (48% in females and 45% in males). In young adulthood, the indirect effect via all mediators was evident only in females (36%). Mechanisms linking ADHD and depression are developmental stage- and sex-specific. Irritability and anxiety in childhood and young adulthood (particularly for females), and external locus of control and negative cognitive style in adolescence, might represent promising intervention targets for preventing depression in youth with ADHD. Study Preregistration: Clinical and Cognitive Mediators Underlying Subsequent Depression in Individuals With Attention-Deficit/Hyperactivity Disorder: A Developmental Approach; https://www.jaacap.org/article/S0890-8567(25)00171-6/fulltext.
Neuropsychiatric disorders such as schizophrenia frequently exhibit marked sex differences in onset, clinical features, and treatment response. However, the molecular and developmental bases of these differences remain poorly defined. Here, we report a sex-dependent effect of developmental, paralog-selective GSK3B inhibition on working memory (WM) in the Df(16)A+/- mouse model of 22q11.2 deletion syndrome (22q11.2DS), a genetic condition conferring high risk for schizophrenia. Pharmacological inhibition of GSK3B with BRD3731 rescued WM deficits and enhanced prefrontal cortex (PFC)-ventral hippocampus (vHPC) theta synchrony in male Df(16)A+/- mice, but had no benefit in female mutants and impaired performance in wild-type (WT) females. Transcriptomic profiling of the postnatal PFC revealed previously unrecognized sex-by-genotype interactions in gene expression associated with the 22q11.2 deletion also implicating GSK3B-associated pathways. Notably, Gsk3b expression itself displayed opposing patterns in Df(16)A+/- mice relative to WT mice, being elevated in males and reduced in females, potentially explaining the observed sex-specific behavioral and circuit responses. Our findings suggest that GSK3B is part of a broader, sexually dimorphic gene network that governs PFC circuit maturation and cognitive function. Specifically, our transcriptomic profiling delineates a postnatal window where the 22q11.2DS model exhibits these sexually dimorphic signatures. Notably, these signatures include many genes previously implicated in schizophrenia, autism, and intellectual disability, likely shaping the disorder's sex-specific pathophysiology. More broadly, this work underscores the importance of incorporating sex as a biological variable in translational research and supports precision psychiatry approaches that align interventions with sex-specific neurobiological profiles.
Emerging evidence suggests the thalamus may be a relevant structure in mild traumatic brain injury (mTBI). However, the structural connectivity profile of the thalamus has not been investigated in mTBI, nor have thalamic contributions to cognitive function been characterized in this population. This study investigated the relative strength of connectivity from thalamic subregions following mTBI and subsequently studied the associations between these metrics and cognitive performance. The final analyzed dataset included 39 mTBI patients and 28 trauma control (TC) patients aged 18-60 years, who were recruited following hospital admission for physical injury. Participants completed a magnetic resonance imaging (MRI) protocol including both structural MRI and multishell diffusion-weighted MRI sequences at 6-12 weeks (mean = 57 days, standard deviation = 11) post-injury. Thalamic segmentations were combined with cortical and subcortical parcellations to define nodes of each participant's structural connectivity network. Connectivity matrices were generated by mapping streamline reconstruction onto the 179 parcels. Nodal edge strength, representing the weighted connections of thalamic subregion edges, was calculated. Participants also completed a range of cognitive tests examining processing speed, attention, memory, and executive functions. The two groups were comparable with respect to thalamic subregion edge strength and performance on cognitive tests. These primary findings suggest that nodal structural connectivity of the thalamus is normal at this time point following injury. Moderation analysis revealed several interactions between group and edge strength predicting cognitive performance, namely, increased edge strength generally predicted better cognitive performance in the TC group, but worse performance in the mTBI group. These preliminary findings require further validation, although they raise the question as to whether sustaining an mTBI results in a change in the relationship between thalamic structure and cognitive function 6-12 weeks after injury.
Functional brain network organisation, measured by functional connectivity (FC), reflects key neurodevelopmental processes for healthy development. Early exposure to adversity, for example undernutrition, affects neurodevelopment, observable via disrupted FC, and leads to poorer outcomes from preschool age onwards. We assessed longitudinally the impact of early growth trajectories on developmental FC in a rural Gambian population from age 5-24 months. To investigate how these early trajectories relate to later childhood outcomes, we assessed cognitive flexibility at 3-5 years. We observed that early physical growth before the fifth month of life drove optimal developmental trajectories of FC that in turn predicted cognitive flexibility at pre-school age. In contrast to previously studied developmental populations, this Gambian sample exhibited long-range interhemispheric FC that decreased with age. Our results highlight the measurable effects that poor growth in early infancy has on brain development and the possible subsequent impact on pre-school age cognitive development, underscoring the need for early life interventions throughout global settings of adversity.
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Adults with Down syndrome (DS) are at risk for Alzheimer's disease (AD), yet identifying the preclinical phase remains challenging. Intraindividual cognitive variability (IICV) may be a sensitive marker of early AD-related changes but remains understudied in DS. Adults from the Alzheimer's Biomarker Consortium-DS (ABC-DS) study (N = 460, mean age 43.3 years; 45.7% female) were included. Generalized linear models examined whether baseline IICV predicted incident mild cognitive impairment (MCI)/dementia, cognitive decline, and amyloid and tau positron emission tomography outcomes, adjusting for demographics, intellectual disability, apolipoprotein E ε4, site, assessment interval, and mean cognitive performance, with Bonferroni correction. Greater IICV predicted incident MCI/dementia (odds ratio = 4.63 to 5.13, p < 0.05), greater amyloid burden, early tau accumulation, and higher tau across Braak stages, independent of mean cognition. Exploratory analyses suggested sex-specific interactions with tau outcomes. IICV is a sensitive marker of dementia risk and cognitive resilience in DS, with potential utility for secondary prevention and trial enrichment.
Maternal sleep deprivation (MSD) is a common but usually unnoticed issue during pregnancy, and in recent years, it has been increasingly recognised as an important prenatal stressor that may adversely influence maternal physiology, placental function, and fetal neurodevelopment. Sleep disturbances during pregnancy, including reduced sleep duration, fragmented sleep, poor sleep quality, circadian disruption, and rapid eye movement sleep restriction, have been associated with altered hypothalamic-pituitary-adrenal axis activity, systemic inflammation, oxidative stress, and impaired circadian regulation. Emerging evidence from clinical and preclinical studies suggests that these alterations may affect fetal neurogenesis, synaptic development, neuroimmune signaling, and maturation of brain circuits involved in cognition and emotional regulations. Within the framework of the Developmental Origins of Health and Disease, maternal sleep disturbances may contribute to epigenetic modifications, mitochondrial dysfunction, microglial activation, and altered neuroplasticity-related pathways, which are increasingly implicated in long-term neurological vulnerability. Experimental findings further indicate that prenatal sleep disruption may impair offspring cognitive performance, emotional behavior, and stress responsiveness, while potentially influencing biological pathways associated with brain aging-related processes. However, the extent to which MSD directly contributes to pathological brain aging in humans remains incompletely understood. Factors such as timing and duration of exposure, sex-specific responses, and postnatal environmental conditions may further influence offspring outcomes. Therefore, this narrative review critically summarizes current evidence regarding MSD and examines the molecular, cellular, and neurodevelopmental mechanisms through which prenatal sleep disturbances may influence long-term neurological health and vulnerability to brain aging-associated alterations in offspring.This graphical abstract illustrates the mechanistic framework connecting maternal sleep deprivation to the developmental programming of brain aging in offspring. [ MSD: maternal sleep deprivation; DOHaD: Developmental Origins of Health and Disease; 11β HSD2: 11β hydroxysteroid dehydrogenase type 2; ROS: reactive oxygen species; REM: rapid eye movement; HPA axis: hypothalamic pituitary adrenal axis; BDNF: brain derived neurotrophic factor].
Although developmental language delays affect approximately 10% of children in the general population, the neurodevelopmental mechanisms that support normative language acquisition, and atypicalities that may predict later language delay, across the first year of life are poorly understood. Here, resting-state fMRI data from the Baby Connectome Project was used to first evaluate age-related changes in language network functional connectivity and alterations associated with suboptimal language development. Additionally, a data-driven machine learning algorithm was used to partition our sample into three groups who showed Typical, Advanced, or Lagging trajectories of language development. These groups reliably differed on several assessments of language ability during infancy and toddlerhood. Using a priori brain regions involved in adult language processing, a seed-based functional connectivity analysis showed broad age-related increases in functional synchrony and specialization throughout the infant language network. Additionally, the Lagging group showed several distinct patterns of functional connectivity with language regions. Importantly, the magnitude of connectivity differences consistently predicted later language scores at two-year outcome across several different language assessments. These findings add to our understanding of normative neurodevelopmental patterns underlying language acquisition, and identify several potential biomarkers associated with language heterogeneity that could serve as future targets to inform diagnoses and clinical interventions.
Although prior studies have examined developmental trajectories of adolescent self-harm in terms of frequency and severity, a fundamental gap remains: we lack a dynamic, state-specific understanding of how self-harm ideation and behavior develop during early adolescence. Moreover, few studies have prospectively examined how baseline predictors relate to subsequent self-harm pathways. Using four annual waves of data from a large-scale Chinese adolescent cohort (N = 11,366; 48.6% female; T1: Mage = 10.72 ± 0.29 years), this study used a person-centered approach to delineate distinct self-harm trajectories and interpretable machine learning methods to identify their baseline predictors. Five heterogeneous trajectories were identified: persistently low-risk, persistent ideation, ideation remission, behavior-to-ideation, and ideation-to-behavior. Although depressive symptoms, self-blame, family stress, and gender emerged as the most influential predictors overall, the predictors varied substantially across trajectories, indicating meaningful differences in their developmental drivers. These findings demonstrate the heterogeneous developmental trajectories of self-harm states in early adolescents and reveal trajectory-specific risk predictors, underscoring the importance of prevention efforts that should consider both shared and distinct factors across pathways.
Synchronized spontaneous neural activity is a fundamental feature of developing central nervous systems and is thought to be essential for proper brain development. However, the mechanisms that regulate this synchronization and its long-term impact on brain function remain unclear. Here, we identify a previously unrecognized role of oligodendrocytes in orchestrating synchronized spontaneous activity during a critical developmental window, with lasting consequences for adult behavior. Using oligodendrocyte-specific genetic manipulation in the mouse cerebellum, we demonstrate that oligodendrocyte deficiency during early postnatal development, but not after weaning, disrupts the synchronization of Purkinje cell activity both during development and in adulthood. The early disruption produced persistent deficits in cerebellar-dependent behaviors, including anxiety, sociality, and motor function. Optogenetic re-synchronization in adulthood restored motor and social functions but not anxiety-like behavior, demonstrating that reduced Purkinje cell synchrony specifically drives the motor and social impairments. Our findings establish a causal link between developmental oligodendrocyte-regulated neural synchrony and the emergence of complex brain functions, which depend on the proper developmental trajectory necessary for driving brain function.
Individuals are exposed to chemicals in daily life. Yet, few studies have examined the long-lasting joint effect of prenatal and childhood exposure to endocrine-disrupting chemical (EDC) on cognitive performance. We analyzed data from mother-child pairs from the Generation R birth cohort (The Netherlands, 2002-2006) with urinary levels of ten phthalate metabolites, bisphenol A, and five nonspecific organophosphate pesticides metabolites three times during pregnancy (n = 565) and at 5 years of age (n = 539). Child cognitive performance was assessed using the vocabulary, matrix reasoning, digit span, and coding subtests of the Wechsler Intelligence Scale at 13 years. Using hierarchical Bayesian kernel machine regression, we found that prenatal EDC mixture level at 75th percentile versus the median was associated with 0.33 decrease (95% credible interval: -0.60, -0.06) in verbal comprehension and with 0.26 decrease (-0.51, -0.02) in matrix reasoning scores, with di(2-ethyhexyl) phthalate and dibutyl phthalates as primary contributing chemicals to the mixture effect for matrix reasoning. Higher childhood levels of EDC mixture were associated with higher verbal scores, in contrast to the inverse associations observed for prenatal exposure, although this finding should be interpreted with caution due to potential exposure misclassification, selection bias, and residual confounding. Overall, our findings suggest that prenatal exposure to a mixture of plasticizers and pesticides may have a long-lasting adverse effect on offspring's cognition.
Human social interactions rely on the ability to reflect on one's own and others' internal states and traits-a process known as mentalizing. Impaired or altered mentalizing is a hallmark of multiple psychiatric and neurodevelopmental conditions. Yet, replicable and easily testable brain markers of mentalizing have so far been lacking. Here, we apply an interpretable machine learning approach to multiple datasets (total n = 390) to train and validate fMRI brain signatures that predict i) mentalizing about the self, ii) mentalizing about another person, and iii) both types of mentalizing. Self-mentalizing and other-mentalizing classifiers had positive weights in anterior/medial and posterior/lateral brain areas, respectively, with accuracy rates of 82% and 77% for out-of-sample prediction. The classifier trained across both types of mentalizing showed 98% predictive accuracy and separated (mental) attributional from factual inferences. Classifier patterns revealed better self/other separation in healthy adults compared to individuals with schizophrenia and with increasing age in adolescence. Together, our findings reveal consistent and separable neural patterns subserving trait-based mentalizing about self and others-present at least from the age of adolescence and functionally altered in severe neuropsychiatric disorders. These mentalizing signatures hold promise as candidate neuromarkers of social-cognitive processes in different contexts and clinical conditions.
A great deal of research has tried to understand the nature of children's memory representations across time-especially in regard to how young learners navigate the conflicting pressures of remembering specific details of their experiences versus learning about more general aspects of their worlds. Here, we conducted a preregistered, exploratory analysis of developmental fMRI data to ask how learning speed impacts memory formation, and probe the idea that developmental differences in the balance of specific and general memory might be partially explained by the rate at which children (N = 35, ages 9-10) and adults (N = 35) learn. Using a statistical learning task and a novel application of decoding with MVPA, we quantified whether each learner's brain detected the presence of structured information early or late in learning. Adults who showed early neural sensitivity to structure formed only general memories while those who detected structure later formed both specific and general memories. In children, however, we observed a trade-off: children who showed early neural sensitivity to structure formed only specific memories while those who detected structure later formed only general memories. These data have important implications for theories of learning and memory development in many contexts.
Ovarian theca cells constitute essential components of the follicular microenvironment and play central roles in follicular development, steroidogenesis, and endocrine regulation. Despite their significance, the developmental origins, differentiation processes, and functional dynamics of theca cells remain incompletely defined, particularly in humans. This review provides an updated synthesis of current knowledge on the ontogeny, molecular signaling pathways, and intercellular interactions of theca cells. It also presents recent findings on the role of theca stem or progenitor cells and their relevance to reproductive disorders, including polycystic ovary syndrome (PCOS), hyperthecosis, and ovarian insufficiency. A comprehensive literature search was conducted using PubMed, Scopus, and Web of Science through May 2025. Search terms included "theca cells," "theca progenitors," "follicular development," "ovarian differentiation," "steroidogenesis," and "reproductive disorders." Original research articles and reviews providing mechanistic insights were included. Current evidence indicates that several signaling pathways, including IGF, SCF, FGF, members of the TGF-β superfamily, GDF9, BMPs, and Hedgehog proteins, are involved in the recruitment, proliferation, and differentiation of theca cells. Bidirectional communication among oocytes, granulosa cells, and theca cells remains essential for folliculogenesis. Increasing evidence links theca cell dysfunction to the pathophysiology of PCOS, primary ovarian insufficiency, and reproductive aging. The identification of theca stem cells (TSCs) and their proposed roles in ovarian regeneration represents an important conceptual advance. A deeper understanding of theca cell biology may guide the development of targeted strategies for infertility and ovarian dysfunction. In contrast, the integration of TSC biology offers new directions for reproductive medicine and reproductive health.
Adolescence is characterized by heightened sensitivity to social relationships, emotional experiences, and evaluative contexts, making schools a central developmental environment for motivation, learning, and brain maturation. Although educational research has long emphasized the importance of belonging, teacher-student relationships, and socio-emotional learning, and neuroscience has identified adolescence as a sensitive period for social-affective brain systems, these lines of research remain only loosely connected. As a result, socio-emotional school experiences are rarely examined in relation to their underlying neural mechanisms. This article synthesizes findings from the socio-emotional learning factors (SELF) study and introduces an integrative neuroeducational model of the social brain in the classroom. SELF represents an interdisciplinary research approach that combines educational science, psychology, and developmental and social neuroscience to investigate how adolescents' socio-emotional experiences at school-such as belonging, social exclusion, teacher-student relationships, and socio-motivational orientations-are associated with psychological processes and neural systems supporting self-referential processing, socio-emotional salience, feedback learning, and cognitive control. Building on evidence from both behavioral and neuroimaging research, including longitudinal and cross-sectional studies, the proposed model conceptualizes learning in adolescence as a socially embedded process that is psychologically mediated and reflected in neural processes during a period of heightened developmental sensitivity and plasticity. Rather than assuming linear brain-behavior relationships, the model emphasizes reciprocal interactions between classroom social ecology, motivational and affective processes, and neural mechanisms. By integrating multiple levels of analysis, the SELF neuroeducational model advances a non-reductionist perspective on educational neuroscience. It provides a framework for theory-driven research and highlights socio-emotional classroom conditions-particularly belonging and relational quality-as foundational for adolescents' motivation, learning, and socio-emotional development.
Angelman syndrome is a neurodevelopmental disorder caused by loss of maternal UBE3A expression. With promising therapies now in clinical trials, there is a pressing need for reliable and translatable biomarkers. Elevated delta power in electroencephalography (EEG) recordings is a hallmark of Angelman syndrome and a promising biomarker, but traditional measures of delta power conflate true delta oscillations with broadband spectral shifts, limiting interpretability and utility. We sought to investigate whether separating out periodic and aperiodic contributions to delta power would yield more interpretable biomarkers. We applied spectral parameterization to EEG recordings from children with Angelman syndrome (n = 95) and typically developing children (n = 185), and to cortical local field potential recordings from Ube3a mutant mice (n = 39) and littermate controls (n = 47) across postnatal development. We related periodic and aperiodic features to Bayley developmental scores in children, and to performance on a motor-based behavioral battery in mice. Here we show that elevated delta power reflects a combination of increased periodic delta oscillations as well as elevated aperiodic slope and offset in both humans and mice. Periodic delta power predicts cognitive ability in children, while aperiodic features predict motor deficits in mice. These features also follow divergent developmental trajectories in both species, suggesting distinct underlying mechanisms. Aperiodic spectral features represent a translatable biomarker for Angelman syndrome. Periodic and aperiodic components of the delta phenotype show separable behavioral and developmental signatures, and their complementary use offers improved precision for biomarker-based evaluation in preclinical and clinical research. Angelman syndrome is a rare genetic disorder affecting movement, speech, cognition, and sleep. As new therapies enter clinical trials, reliable measures of brain function are needed to determine whether treatments are effective. Children with Angelman syndrome show elevated slow brain waves in EEG recordings, but this commonly used measure actually reflects two distinct signals: rhythmic slow oscillations and a broader shift in background brain activity. We separated these two signals in EEG recordings from children with Angelman syndrome and in a mouse model of the disorder. Each component was linked to different behavioral features and followed different developmental trajectories. Together, these findings provide more precise tools for tracking Angelman syndrome and evaluating emerging treatments in both patients and preclinical models.
SLC6A8 encodes the creatine transporter (CRT), which mediates creatine transport across the plasma membrane in the brain, including the blood-brain barrier and neurons. Creatine transporter deficiency (CTD), caused by pathogenic variants in SLC6A8, leads to cerebral creatine depletion and cognitive impairment. Here, we investigated the developmental molecular mechanisms underlying CTD using the pathogenic c.1681G>C (G561R) variant of Slc6a8, which corresponds to a variant identified in SLC6A8 in a patient with CTD. In vitro analyses using HEK293 cells expressing mutant mouse CRT carrying the G561R variant demonstrated impaired N-glycan maturation and plasma membrane localization of the transporter, resulting in markedly reduced creatine uptake, consistent with previous reports on the corresponding human CRT variant. To investigate the in vivo effects of this pathogenic variant, we generated CRT-G561R knock-in mice by introducing the c.1681G>C point mutation into the mouse Slc6a8 gene using the CRISPR/Cas9 system. These male mice exhibited severe reductions in brain creatine levels, postnatal growth retardation, and impaired spatial memory, despite preserved gross brain morphology. Quantitative proteomic analyses of the hippocampus and cerebral cortex during postnatal development revealed region-dependent protein alterations in CTD. The hippocampus showed pronounced early postnatal remodeling involving proteins related to actin cytoskeleton organization and vesicle-mediated membrane trafficking, whereas the cerebral cortex exhibited a more gradual response involving creatine biosynthesis-related enzymes and later-emerging mitochondrial pathways, including the mitochondrial translation machinery. These findings demonstrate stage- and region-dependent proteomic remodeling during postnatal brain development in CTD.Significance Statement Creatine transporter deficiency (CTD) causes cerebral creatine depletion and intellectual disability; however, the developmental mechanisms linking creatine loss to brain dysfunction remain unclear. We performed developmental proteomic profiling of the hippocampus and cerebral cortex using a mouse model carrying a pathogenic Slc6a8 variant identified in patients with CTD. Creatine transporter dysfunction induces distinct region- and stage-dependent molecular responses during postnatal brain maturation. The hippocampus shows early alterations in cytoskeleton-dependent membrane trafficking pathways, consistent with impaired synaptic and circuit maturation, whereas the cerebral cortex exhibits progressive metabolic and mitochondrial adaptations. These findings suggest that impaired creatine-dependent energy buffering disrupts distinct developmental programs across brain regions, potentially contributing to cognitive dysfunction by hindering early hippocampal circuit maturation.
Early-life sensory environments can shape lifelong brain function, yet the neuroimmune and neuroplastic mechanisms through which musical stimulation influences cognitive development remain poorly understood. Here, we examined how graded musical brain intervention (MBI) during embryonic and early postnatal periods affects adult cognition and its underlying immune and neural substrates. Pregnant C57BL/6J mice were exposed to a standardized music paradigm starting on embryonic day 13, with groups differing in how long exposure continued into the early postnatal period to test how the developmental extent of auditory stimulation influences adult outcomes. MBI produced robust, exposure-dependent improvements in spatial learning, recognition memory, working memory, and long-term fear memory. Under auditory-control conditions, white noise did not recapitulate the learning and memory benefits observed after MBI, whereas E13-initiated exposure produced stronger effects than D15-onset exposure. Maternal pup retrieval, maternal heart rate, and maternal-offspring HPA-axis indices also varied across exposure conditions. Transcriptomic profiling of the hippocampus (Hip) and nucleus accumbens (NAC) revealed coordinated shifts in endocrine, G protein-coupled receptor (GPCR), serotonin, and autonomic regulatory pathways, indicating broad transcriptional reprogramming. Golgi-Cox analyses demonstrated enhanced dendritic complexity and spine density in a region- and exposure-dependent manner, accompanied by increased expression of DCX and MAP2, suggesting strengthened synaptic remodeling and neuronal maturation. MBI also attenuated astrocytic and microglial reactivity, together with reduced pro-inflammatory cytokine expression, indicating modulation of the neuroimmune state. Together, these findings suggest that early-life structured music exposure is associated with coordinated developmental modulation of neuroimmune activity, synaptic architecture, and gene regulatory networks. These convergent findings provide experimental support for further investigation of music-based interventions in neurodevelopmental and cognitive disorders.
Individual variation in neurodevelopment plays a central role in shaping cognitive abilities and behavioural profiles, influencing both typical functioning and risk for neurodevelopmental conditions. While much research has focused on characterising trajectories of brain structure during development, this typically entails assessing brain regions individually, overlooking the multivariate nature of neuroimaging data. In this study, we trained an autoencoder to map latent representations of children's brain development using T1-weighted MRI scans from a paediatric cohort (n = 564, 55% male, mean age 4.90 years, range [0.11,15.38]). The latent representation from this model effectively captured demographic variables (age and sex), while preserving both global and local structural features. The model accurately reconstructed the data (mean reconstruction error = 0.04 ± 0.01) and captured demographic features with sex classification accuracy of 84% ± 4% and mean absolute error of 0.79 ± 0.06 years for age prediction, highlighting its sensitivity to developmental changes. We further validated the approach using correlation analysis showing that deviations from the latent norms were significantly associated with multiple cognitive and behavioural measures, suggesting that structural variations may reflect individual differences in neurodevelopment. Finally, we generated reference brain images that represent typical development and used them to visualise structural differences in individuals who deviate from this normative pattern. Our findings demonstrate that conditioned autoencoders, combined with multivariate normative modelling, offer a framework for characterising neurodevelopmental trajectories. This approach can identify meaningful deviations and has potential future applications across the lifespan.