Higher emotional synchronization is modulated by relationship quality in romantic relationships and not in close friendships.

Emotions are fundamental to social interaction and deeply intertwined with interpersonal dynamics, especially in romantic relationships. Although the neural basis of interaction processes in romance has been widely explored, the underlying emotions and the connection between relationship quality and neural synchronization remain less understood. Our study employed EEG hyperscanning during a non-interactive video-watching paradigm to compare the emotional coordination between romantic couples and close friends. Couples showed significantly greater behavioral and prefrontal alpha synchronization than friends. Notably, couples with low relationship quality required heightened neural synchronization to maintain robust behavioral synchronization. Further support vector machine analysis underscores the crucial role of prefrontal activity in differentiating couples from friends. In summary, our research addresses gaps concerning how intrinsic emotions linked to relationship quality influence neural and behavioral synchronization by investigating a natural non-interactive context, thereby advancing our understanding of the neural mechanisms underlying emotional coordination in romantic relationships.

Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Treatment outcomes in tinnitus patients are associated with brain functional network: Evidence from connectome gradient and gene expression analysis.

The neuroimaging mechanisms underlying differences in the outcomes of sound therapy for tinnitus patients remain unclear. We hypothesize that abnormal hierarchical architecture is the neuro-biomarker for treatment outcome explanation. We conducted functional connectome gradient analyses on resting-state functional MRI images that acquired before intervention to investigate differences among the patients with effective treatment (ET, n = 27), ineffective treatment (IT, n = 41), and healthy controls (HC, n = 59). General linear models were used to analyze the associations between intergroup differential regions and clinical characteristics. Partial least squares regression was employed to reveal correlations with gene expression. Compared to HC, both ET and IT groups displayed significant differences in the default mode network. Moreover, the ET group exhibited wider gradient range and greater gradient variance. Also, the gradient scores of the differential regions between the ET and HC groups were significantly correlated with Self-rating Anxiety Scale and Self-rating Depression Scale scores, and exhibited positive correlations with the transcriptional profiles of genes related to depression and anxiety. Our results indicated that the abnormalities of ET group, may be more relevant to psychiatric disorders, bringing a higher possible therapeutic potential due to the plasticity of the nervous system. Connectome gradient dysfunction with genetic evidence may serve as an indicator for identifying diverse treatment outcomes of the sound therapy for tinnitus patients before treatment.

Heritability of functional gradients in the human subcortico-cortical connectivity.

The human subcortex plays a pivotal role in cognition and is widely implicated in the pathophysiology of many psychiatric disorders. However, the heritability of functional gradients based on subcortico-cortical functional connectivity remains elusive. Here, leveraging twin functional MRI (fMRI) data from both the Human Connectome Project (n = 1023) and the Adolescent Brain Cognitive Development study (n = 936) datasets, we construct large-scale subcortical functional gradients and delineate an increased principal functional gradient pattern from unimodal sensory/motor networks to transmodal association networks. We observed that this principal functional gradient is heritable, and the strength of heritability exhibits a heterogeneous pattern along a hierarchical unimodal-transmodal axis in subcortex for both young adults and children. Furthermore, employing a machine learning framework, we show that this heterogeneous pattern of the principal functional gradient in subcortex can accurately discern the relationship between monozygotic twin pairs and dizygotic twin pairs with an accuracy of 76.2% (P < 0.001). The heritability of functional gradients is associated with the anatomical myelin proxied by MRI-derived T1-weighted/T2-weighted (T1w/T2w) ratio mapping in subcortex. This study provides new insights into the biological basis of subcortical functional hierarchy by revealing the structural and genetic properties of the subcortical functional gradients.

The neural and genetic underpinnings of different developmental trajectories of Attention-Deficit/Hyperactivity Symptoms in children and adolescents.

BACKGROUND: The trajectory of attention-deficit hyperactivity disorder (ADHD) symptoms in children and adolescents, encompassing descending, stable, and ascending patterns, delineates their ADHD status as remission, persistence or late onset. However, the neural and genetic underpinnings governing the trajectory of ADHD remain inadequately elucidated. METHODS: In this study, we employed neuroimaging techniques, behavioral assessments, and genetic analyses on a cohort of 487 children aged 6-15 from the Children School Functions and Brain Development project at baseline and two follow-up tests for 1 year each (interval 1: 1.14 ± 0.32 years; interval 2: 1.14 ± 0.30 years). We applied a Latent class mixed model (LCMM) to identify the developmental trajectory of ADHD symptoms in children and adolescents, while investigating the neural correlates through gray matter volume (GMV) analysis and exploring the genetic underpinnings using polygenic risk scores (PRS). RESULTS: This study identified three distinct trajectories (ascending-high, stable-low, and descending-medium) of ADHD symptoms from childhood through adolescence. Utilizing the linear mixed-effects (LME) model, we discovered that attention hub regions served as the neural basis for these three developmental trajectories. These regions encompassed the left anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), responsible for inhibitory control; the right inferior parietal lobule (IPL), which facilitated conscious focus on exogenous stimuli; and the bilateral middle frontal gyrus/precentral gyrus (MFG/PCG), accountable for regulating both dorsal and ventral attention networks while playing a crucial role in flexible modulation of endogenous and extrinsic attention. Furthermore, our findings revealed that individuals in the ascending-high group exhibited the highest PRS for ADHD, followed by those in the descending-medium group, with individuals in the stable-low group displaying the lowest PRS. Notably, both ascending-high and descending-medium groups had significantly higher PRS compared to the stable-low group. CONCLUSIONS: The developmental trajectory of ADHD symptoms in the general population throughout childhood and adolescence can be reliably classified into ascending-high, stable-low, and descending-medium groups. The bilateral MFG/PCG, left ACC/mPFC, and right IPL may serve as crucial brain regions involved in attention processing, potentially determining these trajectories. Furthermore, the ascending-high pattern of ADHD symptoms exhibited the highest PRS for ADHD.

Cross-ancestry genome-wide association studies of brain imaging phenotypes.

Genome-wide association studies of brain imaging phenotypes are mainly performed in European populations, but other populations are severely under-represented. Here, we conducted Chinese-alone and cross-ancestry genome-wide association studies of 3,414 brain imaging phenotypes in 7,058 Chinese Han and 33,224 white British participants. We identified 38 new associations in Chinese-alone analyses and 486 additional new associations in cross-ancestry meta-analyses at P < 1.46 × 10-11 for discovery and P < 0.05 for replication. We pooled significant autosomal associations identified by single- or cross-ancestry analyses into 6,443 independent associations, which showed uneven distribution in the genome and the phenotype subgroups. We further divided them into 44 associations with different effect sizes and 3,557 associations with similar effect sizes between ancestries. Loci of these associations were shared with 15 brain-related non-imaging traits including cognition and neuropsychiatric disorders. Our results provide a valuable catalog of genetic associations for brain imaging phenotypes in more diverse populations.

Connections Between the Middle Frontal Gyrus and the Dorsoventral Attention Network Are Associated With the Development of Attentional Symptoms.

BACKGROUND: The right middle frontal gyrus (MFG) has been proposed as a convergence site for the dorsal attention network (DAN) and ventral attention network (VAN), regulating both networks and enabling flexible modulation of attention. However, it is unclear whether the connections between the right MFG and these networks can predict changes in attention-deficit/hyperactivity disorder (ADHD) symptoms. METHODS: This study used data from the Children School Functions and Brain Development project (N = 713, 56.2% boys). Resting-state functional magnetic resonance imaging was employed to analyze the connections of the right MFG with the DAN/VAN; connectome-based predictive modeling was applied for longitudinal prediction, and ADHD polygenic risk scores were used for genetic analysis. RESULTS: ADHD symptoms were associated with the connections between the right MFG and DAN subregion, including the frontal eye field, as well as the VAN subregions, namely the inferior parietal lobule and inferior frontal gyrus. Furthermore, these connections of the right MFG with the frontal eye field, the inferior parietal lobule, and the inferior frontal gyrus could significantly predict changes in ADHD symptoms over 1 year and mediate the prediction of ADHD symptom changes by polygenic risk scores for ADHD. Finally, the validation samples confirmed that the functional connectivity between the right MFG and the frontal eye field/inferior parietal lobule in patients with ADHD was significantly weaker than that in typically developing control participants, and this difference disappeared after medication. CONCLUSIONS: The connection of the right MFG with the DAN and VAN can serve as a predictive indicator for changes in ADHD symptoms over the following year, while also mediating the prediction of ADHD symptom changes by a polygenic risk score for ADHD. These findings hold promise as potential biomarkers for early identification of children who are at risk of developing ADHD.

Neural specialization with generalizable representations underlies children's cognitive development of attention.

From childhood to adulthood, the human brain develops highly specialized yet interacting neural modules that give rise to nuanced attention and other cognitive functions. Each module can specialize over development to support specific functions, yet also coexist in multiple neurobiological modes to support distinct processes. Advances in cognitive neuroscience have conceptualized human attention as a set of cognitive processes anchored in highly specialized yet interacting neural systems. The underlying mechanisms of how these systems interplay to support children's cognitive development of multiple attention processes remain unknown. Leveraging developmental functional magnetic resonance imaging with attention network test paradigm, we demonstrate differential neurocognitive development of three core attentional processes from childhood to adulthood, with alerting reaching adult-like level earlier, followed by orienting and executive attention with more protracted development throughout middle and late childhood. Relative to adults, young children exhibit immature specialization with less pronounced dissociation of neural systems specific to each attentional process. Children manifest adult-like distributed representations in the ventral attention and cingulo-opercular networks, but less stable and weaker generalizable representations across multiple processes in the dorsal attention network. Our findings provide insights into the functional specialization and generalization of neural representations scaffolding cognitive development of core attentional processes from childhood to adulthood. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Association of emotional and behavioral problems with the development of the substantia nigra, subthalamic nucleus, and red nucleus volumes and asymmetries from childhood to adolescence: A longitudinal cohort study.

The substantia nigra (SN), subthalamic nucleus (STN), and red nucleus (RN) have been widely studied as important biomarkers of degenerative diseases. However, how they develop in childhood and adolescence and are affected by emotional behavior has not been studied thus far. This population-based longitudinal cohort study used data from a representative sample followed two to five times. Emotional and behavioral problems were assessed with the Strengths and Difficulties Questionnaire (SDQ). Linear mixed models were used to map developmental trajectories and behavioral regulation. Using an innovative automated image segmentation technique, we quantified the volumes and asymmetries of the SN, STN and RN with 1226 MRI scans of a large longitudinal sample of 667 subjects aged 6-15 years and mapped their developmental trajectories. The results showed that the absolute and relative volumes of the bilateral SN and right STN showed linear increases, while the absolute volume of the right RN and relative volume of the bilateral RN decreased linearly, these effects were not affected by gender. Hyperactivity/inattention weakened the increase in SN volume and reduced the absolute volume of the STN, conduct problems impeded the RN volume from decreasing, and emotional symptoms changed the direction of SN lateralization. This longitudinal cohort study mapped the developmental trajectories of SN, STN, and RN volumes and asymmetries from childhood to adolescence, and found the association of emotional symptoms, conduct problems, and hyperactivity/inattention with these trajectories, providing guidance for preventing and intervening in cognitive and emotional behavioral problems.

Structural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence.

Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Here, we show cortical thinning patterns primarily located in the lateral frontal and parietal heteromodal nodes during childhood and adolescence, which are structurally constrained by white matter network architecture and are particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible in another independent dataset. These findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.

A generalized QUCESOP method with evaluating CEST peak overlap.

The overlapping peaks of the target chemical exchange saturation transfer (CEST) solutes and other unknown CEST solutes affect the quantification results and accuracy of the chemical exchange parameters-the fractional concentration, f b , exchange rate, k b , and transverse relaxation rate, R 2 b -for the target solutes. However, to date, no method has been established for assessing the overlapping peaks. This study aimed to develop a method for quantifying the f b , k b , and R 2 b values of a specific CEST solute, as well as assessing the overlap between the CEST peaks of the specific solute(s) and other unknown solutes. A simplified R 1 ρ model was proposed, assuming linear approximation of the other solutes' contributions to R 1 ρ . A CEST data acquisition scheme was applied with various saturation offsets and saturation powers. In addition to fitting the f b , k b , and R 2 b values of the specific solute, the overlapping condition was evaluated based on the root mean square error (RMSE) between the trajectories of the acquired and synthesized data. Single-solute and multi-solute phantoms with various phosphocreatine (PCr) concentrations and pH values were used to calculate the f b and k b of PCr and the corresponding RMSE. The feasibility of RMSE for evaluating the overlapping condition, and the accurate fitting of f b and k b in weak overlapping conditions, were verified. Furthermore, the method was employed to quantify the nuclear Overhauser effect signal in rat brains and the PCr signal in rat skeletal muscles, providing results that were consistent with those reported in previous studies. In summary, the proposed approach can be applied to evaluate the overlapping condition of CEST peaks and quantify the f b , k b , and R 2 b values of specific solutes, if the weak overlapping condition is satisfied.

Development of the triadic neural systems involved in risky decision-making during childhood.

Risk-taking often occurs in childhood as a compex outcome influenced by individual, family, and social factors. The ability to govern risky decision-making in a balanced manner is a hallmark of the integrity of cognitive and affective development from childhood to adulthood. The Triadic Neural Systems Model posits that the nuanced coordination of motivational approach, avoidance and prefrontal control systems is crucial to regulate adaptive risk-taking and related behaviors. Although widely studied in adolescence and adulthood, how these systems develop in childhood remains elusive. Here, we show heterogenous age-related differences in the triadic neural systems involved in risky decision-making in 218 school-age children relative to 80 young adults. Children were generally less reward-seeking and less risk-taking than adults, and exhibited gradual increases in risk-taking behaviors from 6 to 12 years-old, which are associated with age-related differences in brain activation patterns underlying reward and risk processing. In comparison to adults, children exhibited weaker activation in control-related prefrontal systems, but stronger activation in reward-related striatal systems. Network analyses revealed that children showed greater reward-related functional connectivity within and between the triadic systems. Our findings support an immature and unbalanced developmental view of the core neurocognitive systems involved in risky decision-making and related behaviors in middle to late childhood.

Non-rigid-registration-based positioning and labelling of triaxial OPMs on a flexible cap for wearable magnetoencephalography.

BACKGROUND: Recent advances in highly sensitive miniaturized optically pumped magnetometers (OPMs) have enabled the development of wearable magnetoencephalography (MEG) offering great flexibility in experimental setting. The OPM array for wearable MEG is typically attached to a flexible cap and exhibits a variable spatial layout across different subjects, which imposes challenges concerning the efficient positioning and labelling of OPMs. NEW METHOD: A pair of reflective markers are affixed to each triaxial OPM sensor above its cable to determine its location and sensitive axes. A non-rigid registration of optically digitized marker locations with a pre-labelled template of marker locations is performed to map newly digitized markers to OPMs. RESULTS: The positioning and labelling of 66 OPM sensors could be completed within 35 s. Across ten experiments, all OPMs were accurately labelled, and the mean test-retest errors were 0.48 mm for sensor locations and 0.20 degree for sensitive axes. By combining six OPMs' positions with their respective recordings, magnetic dipoles inside a phantom were located with a mean error of 5.5 mm, and the best fitted dipole for MEG with auditory stimuli presented was located on a subject's primary auditory cortex. COMPARISON WITH EXISTING METHODS: The proposed method reduces the reliance on error-prone and laborious manual operations inherent in existing methods, therefore significantly improving the efficiency of OPM positioning and labelling on a flexible cap. CONCLUSION: We developed a method for the precise and rapid positioning and labelling triaxial OPMs on a flexible cap, thereby facilitating the practical implementation of wearable OPM-MEG.

Functional connectome through the human life span.

The functional connectome of the human brain represents the fundamental network architecture of functional interdependence in brain activity, but its normative growth trajectory across the life course remains unknown. Here, we aggregate the largest, quality-controlled multimodal neuroimaging dataset from 119 global sites, including 33,809 task-free fMRI and structural MRI scans from 32,328 individuals ranging in age from 32 postmenstrual weeks to 80 years. Lifespan growth charts of the connectome are quantified at the whole cortex, system, and regional levels using generalized additive models for location, scale, and shape. We report critical inflection points in the non-linear growth trajectories of the whole-brain functional connectome, particularly peaking in the fourth decade of life. Having established the first fine-grained, lifespan-spanning suite of system-level brain atlases, we generate person-specific parcellation maps and further show distinct maturation timelines for functional segregation within different subsystems. We identify a spatiotemporal gradient axis that governs the life-course growth of regional connectivity, transitioning from primary sensory cortices to higher-order association regions. Using the connectome-based normative model, we demonstrate substantial individual heterogeneities at the network level in patients with autism spectrum disorder and patients with major depressive disorder. Our findings shed light on the life-course evolution of the functional connectome and serve as a normative reference for quantifying individual variation in patients with neurological and psychiatric disorders.

Reduced volume of the left cerebellar lobule VIIb and its increased connectivity within the cerebellum predict more general psychopathology one year later via worse cognitive flexibility in children.

Predicting the risk for general psychopathology (the p factor) requires the examination of multiple factors ranging from brain to cognitive skills. While an increasing number of findings have reported the roles of the cerebral cortex and executive functions, it is much less clear whether and how the cerebellum and cognitive flexibility (a core component of executive function) may be associated with the risk for general psychopathology. Based on the data from more than 400 children aged 6-12 in the Children School Functions and Brain Development (CBD) Project, this study examined whether the left cerebellar lobule VIIb and its connectivity within the cerebellum may prospectively predict the risk for general psychopathology one year later and whether cognitive flexibility may mediate such predictions in school-age children. The reduced gray matter volume in the left cerebellar lobule VIIb and the increased connectivity of this region to the left cerebellar lobule VI prospectively predicted the risk for general psychopathology and was partially mediated by worse cognitive flexibility. Deficits in cognitive flexibility may play an important role in linking cerebellar structure and function to the risk for general psychopathology.

An artificial intelligence-based pipeline for automated detection and localisation of epileptic sources from magnetoencephalography.

Objective.Magnetoencephalography (MEG) is a powerful non-invasive diagnostic modality for presurgical epilepsy evaluation. However, the clinical utility of MEG mapping for localising epileptic foci is limited by its low efficiency, high labour requirements, and considerable interoperator variability. To address these obstacles, we proposed a novel artificial intelligence-based automated magnetic source imaging (AMSI) pipeline for automated detection and localisation of epileptic sources from MEG data.Approach.To expedite the analysis of clinical MEG data from patients with epilepsy and reduce human bias, we developed an autolabelling method, a deep-learning model based on convolutional neural networks and a hierarchical clustering method based on a perceptual hash algorithm, to enable the coregistration of MEG and magnetic resonance imaging, the detection and clustering of epileptic activity, and the localisation of epileptic sources in a highly automated manner. We tested the capability of the AMSI pipeline by assessing MEG data from 48 epilepsy patients.Main results.The AMSI pipeline was able to rapidly detect interictal epileptiform discharges with 93.31% ± 3.87% precision based on a 35-patient dataset (with sevenfold patientwise cross-validation) and robustly rendered accurate localisation of epileptic activity with a lobar concordance of 87.18% against interictal and ictal stereo-electroencephalography findings in a 13-patient dataset. We also showed that the AMSI pipeline accomplishes the necessary processes and delivers objective results within a much shorter time frame (∼12 min) than traditional manual processes (∼4 h).Significance.The AMSI pipeline promises to facilitate increased utilisation of MEG data in the clinical analysis of patients with epilepsy.

Theta Signal Transfer from Parietal to Prefrontal Cortex Ignites Conscious Awareness of Implicit Knowledge during Sequence Learning.

Unconscious acquisition of sequence structure from experienced events can lead to explicit awareness of the pattern through extended practice. Although the implicit-to-explicit transition has been extensively studied in humans using the serial reaction time (SRT) task, the subtle neural activity supporting this transition remains unclear. Here, we investigated whether frequency-specific neural signal transfer contributes to this transition. A total of 208 participants (107 females) learned a sequence pattern through a multisession SRT task, allowing us to observe the transitions. Session-by-session measures of participants' awareness for sequence knowledge were conducted during the SRT task to identify the session when the transition occurred. By analyzing time course RT data using switchpoint modeling, we identified an increase in learning benefit specifically at the transition session. Electroencephalogram (EEG)/magnetoencephalogram (MEG) recordings revealed increased theta power in parietal (precuneus) regions one session before the transition (pretransition) and a prefrontal (superior frontal gyrus; SFG) one at the transition session. Phase transfer entropy (PTE) analysis confirmed that directional theta transfer from precuneus → SFG occurred at the pretransition session and its strength positively predicted learning improvement at the subsequent transition session. Furthermore, repetitive transcranial magnetic stimulation (TMS) modulated precuneus theta power and altered transfer strength from precuneus to SFG, resulting in changes in both transition rate and learning benefit at that specific point of transition. Our brain-stimulation evidence supports a role for parietal → prefrontal theta signal transfer in igniting conscious awareness of implicitly acquired knowledge.SIGNIFICANCE STATEMENT There exists a pervasive phenomenon wherein individuals unconsciously acquire sequence patterns from their environment, gradually becoming aware of the underlying regularities through repeated practice. While previous studies have established the robustness of this implicit-to-explicit transition in humans, the refined neural mechanisms facilitating conscious access to implicit knowledge remain poorly understood. Here, we demonstrate that prefrontal activity, known to be crucial for conscious awareness, is triggered by neural signal transfer originating from the posterior brain region, specifically the precuneus. By employing brain stimulation techniques, we establish a causal link between neural signal transfer and the occurrence of awareness. Our findings unveil a mechanism by which implicit knowledge becomes consciously accessible in human cognition.

Emotional and behavioral problems change the development of cerebellar gray matter volume, thickness, and surface area from childhood to adolescence: A longitudinal cohort study.

AIMS: Increasing evidence indicates that major neurodevelopmental disorders have potential links to abnormal cerebellar development. However, the developmental trajectories of cerebellar subregions from childhood to adolescence are lacking, and it is not clear how emotional and behavioral problems affect them. We aim to map the developmental trajectories of gray matter volume (GMV), cortical thickness (CT), and surface area (SA) in cerebellar subregions from childhood to adolescence and examine how emotional and behavioral problems change the cerebellar development trajectory in a longitudinal cohort study. METHOD: This population-based longitudinal cohort study used data on a representative sample of 695 children. Emotional and behavioral problems were assessed at baseline and at three annual follow-ups with the Strengths and Difficulties Questionnaire (SDQ). RESULTS: Using an innovative automated image segmentation technique, we quantified the GMV, CT, and SA of the whole cerebellum and 24 subdivisions (lobules I-VI, VIIB, VIIIA&B, and IX-X plus crus I-II) with 1319 MRI scans from a large longitudinal sample of 695 subjects aged 6-15 years and mapped their developmental trajectories. We also examined sex differences and found that boys showed more linear growth, while girls showed more nonlinear growth. Boys and girls showed nonlinear growth in the cerebellar subregions; however, girls reached the peak earlier than boys. Further analysis found that emotional and behavioral problems modulated cerebellar development. Specifically, emotional symptoms impede the expansion of the SA of the cerebellar cortex, and no gender differences; conduct problems lead to inadequate cerebellar GMV development only in girls, but not boys; hyperactivity/inattention delays the development of cerebellar GMV and SA, with left cerebellar GMV, right VIIIA GMV and SA in boys and left V GMV and SA in girls; peer problems disrupt CT growth and SA expansion, resulting in delayed GMV development, with bilateral IV, right X CT in boys and right Crus I GMV, left V SA in girls; and prosocial behavior problems impede the expansion of the SA and lead to excessive CT growth, with bilateral IV, V, right VI CT, left cerebellum SA in boys and right Crus I GMV in girls. CONCLUSIONS: This study maps the developmental trajectories of GMV, CT, and SA in cerebellar subregions from childhood to adolescence. In addition, we provide the first evidence for how emotional and behavioral problems affect the dynamic development of GMV, CT, and SA in the cerebellum, which provides an important basis and guidance for the prevention and intervention of cognitive and emotional behavioral problems in the future.

Neural Signatures of Hierarchical Linguistic Structures in Second Language Listening Comprehension.

Native speakers excel at parsing continuous speech into smaller elements and entraining their neural activities to the linguistic hierarchy at different levels (e.g., syllables, phrases, and sentences) to achieve speech comprehension. However, how a nonnative brain tracks hierarchical linguistic structures in second language (L2) speech comprehension and whether it relates to top-down attention and language proficiency remains elusive. Here, we applied a frequency-tagging paradigm in human adults and investigated the neural tracking responses to hierarchically organized linguistic structures (i.e., the syllabic rate of 4 Hz, the phrasal rate of 2 Hz, and the sentential rate of 1 Hz) in both first language (L1) and L2 listeners when they attended to a speech stream or ignored it. We revealed disrupted neural responses to higher-order linguistic structures (i.e., phrases and sentences) for L2 listeners in which the phrasal-level tracking was functionally related to an L2 subject's language proficiency. We also observed less efficient top-down modulation of attention in L2 speech comprehension than in L1 speech comprehension. Our results indicate that the reduced δ-band neuronal oscillations that subserve the internal construction of higher-order linguistic structures may compromise listening comprehension in a nonnative language.

Cross-ancestry genome-wide association meta-analyses of hippocampal and subfield volumes.

The hippocampus is critical for memory and cognition and neuropsychiatric disorders, and its subfields differ in architecture and function. Genome-wide association studies on hippocampal and subfield volumes are mainly conducted in European populations; however, other ancestral populations are under-represented. Here we conduct cross-ancestry genome-wide association meta-analyses in 65,791 individuals for hippocampal volume and 38,977 for subfield volumes, including 7,009 individuals of East Asian ancestry. We identify 339 variant-trait associations at P < 1.13 × 10-9 for 44 hippocampal traits, including 23 new associations. Common genetic variants have similar effects on hippocampal traits across ancestries, although ancestry-specific associations exist. Cross-ancestry analysis improves the fine-mapping precision and the prediction performance of polygenic scores in under-represented populations. These genetic variants are enriched for Wnt signaling and neuron differentiation and affect cognition, emotion and neuropsychiatric disorders. These findings may provide insight into the genetic architectures of hippocampal and subfield volumes.