Longitudinal trajectories of anterior cingulate glutamate and subclinical psychotic experiences in early adolescence: the impact of bullying victimization.

Previous studies reported decreased glutamate levels in the anterior cingulate cortex (ACC) in non-treatment-resistant schizophrenia and first-episode psychosis. However, ACC glutamatergic changes in subjects at high-risk for psychosis, and the effects of commonly experienced environmental emotional/social stressors on glutamatergic function in adolescents remain unclear. In this study, adolescents recruited from the general population underwent proton magnetic resonance spectroscopy (MRS) of the pregenual ACC using a 3-Tesla scanner. We explored longitudinal data on the association of combined glutamate-glutamine (Glx) levels, measured by MRS, with subclinical psychotic experiences. Moreover, we investigated associations of bullying victimization, a risk factor for subclinical psychotic experiences, and help-seeking intentions, a coping strategy against stressors including bullying victimization, with Glx levels. Finally, path analyses were conducted to explore multivariate associations. For a contrast analysis, gamma-aminobutyric acid plus macromolecule (GABA+) levels were also analyzed. Negative associations were found between Glx levels and subclinical psychotic experiences at both Times 1 (n = 219, mean age 11.5 y) and 2 (n = 211, mean age 13.6 y), as well as for over-time changes (n = 157, mean interval 2.0 y). Moreover, effects of bullying victimization and bullying victimization × help-seeking intention interaction effects on Glx levels were found (n = 156). Specifically, bullying victimization decreased Glx levels, whereas help-seeking intention increased Glx levels only in bullied adolescents. Finally, associations among bullying victimization, help-seeking intention, Glx levels, and subclinical psychotic experiences were revealed. GABA+ analysis revealed no significant results. This is the first adolescent study to reveal longitudinal trajectories of the association between glutamatergic function and subclinical psychotic experiences and to elucidate the effect of commonly experienced environmental emotional/social stressors on glutamatergic function. Our findings may deepen the understanding of how environmental emotional/social stressors induce impaired glutamatergic neurotransmission that could be the underpinning of liability for psychotic experiences in early adolescence.

Distinct roles of monkey OFC-subcortical pathways in adaptive behavior.

To be the most successful, primates must adapt to changing environments and optimize their behavior by making the most beneficial choices. At the core of adaptive behavior is the orbitofrontal cortex (OFC) of the brain, which updates choice value through direct experience or knowledge-based inference. Here, we identify distinct neural circuitry underlying these two separate abilities. We designed two behavioral tasks in which macaque monkeys updated the values of certain items, either by directly experiencing changes in stimulus-reward associations, or by inferring the value of unexperienced items based on the task's rules. Chemogenetic silencing of bilateral OFC combined with mathematical model-fitting analysis revealed that monkey OFC is involved in updating item value based on both experience and inference. In vivo imaging of chemogenetic receptors by positron emission tomography allowed us to map projections from the OFC to the rostromedial caudate nucleus (rmCD) and the medial part of the mediodorsal thalamus (MDm). Chemogenetic silencing of the OFC-rmCD pathway impaired experience-based value updating, while silencing the OFC-MDm pathway impaired inference-based value updating. Our results thus demonstrate a dissociable contribution of distinct OFC projections to different behavioral strategies, and provide new insights into the neural basis of value-based adaptive decision-making in primates.

Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study.

Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites and different developmental stages. Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults and Japanese adults. The neuromarker demonstrated significant generalization for children and adolescents. We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.

Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study.

Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites (U.S., Belgium, and Japan) and different developmental stages (children and adolescents). Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults (area under the curve [AUC] = 0.70) and Japanese adults (AUC = 0.81). The neuromarker demonstrated significant generalization for children (AUC = 0.66) and adolescents (AUC = 0.71; all P<0.05, family-wise-error corrected). We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. These FCs largely centered on social brain regions such as the amygdala, hippocampus, dorsomedial and ventromedial prefrontal cortices, and temporal cortices. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.

Resting-state functional connectivity disruption between the left and right pallidum as a biomarker for subthreshold depression.

Although the identification of late adolescents with subthreshold depression (StD) may provide a basis for developing effective interventions that could lead to a reduction in the prevalence of StD and prevent the development of major depressive disorder, knowledge about the neural basis of StD remains limited. The purpose of this study was to develop a generalizable classifier for StD and to shed light on the underlying neural mechanisms of StD in late adolescents. Resting-state functional magnetic resonance imaging data of 91 individuals (30 StD subjects, 61 healthy controls) were included to build an StD classifier, and eight functional connections were selected by using the combination of two machine learning algorithms. We applied this biomarker to an independent cohort (n = 43) and confirmed that it showed generalization performance (area under the curve = 0.84/0.75 for the training/test datasets). Moreover, the most important functional connection was between the left and right pallidum, which may be related to clinically important dysfunctions in subjects with StD such as anhedonia and hyposensitivity to rewards. Investigation of whether modulation of the identified functional connections can be an effective treatment for StD may be an important topic of future research.

Development of a classifier for gambling disorder based on functional connections between brain regions.

AIM: Recently, a machine-learning (ML) technique has been used to create generalizable classifiers for psychiatric disorders based on information of functional connections (FCs) between brain regions at resting state. These classifiers predict diagnostic labels by a weighted linear sum (WLS) of the correlation values of a small number of selected FCs. We aimed to develop a generalizable classifier for gambling disorder (GD) from the information of FCs using the ML technique and examine relationships between WLS and clinical data. METHODS: As a training dataset for ML, data from 71 GD patients and 90 healthy controls (HCs) were obtained from two magnetic resonance imaging sites. We used an ML algorithm consisting of a cascade of an L1-regularized sparse canonical correlation analysis and a sparse logistic regression to create the classifier. The generalizability of the classifier was verified using an external dataset. This external dataset consisted of six GD patients and 14 HCs, and was collected at a different site from the sites of the training dataset. Correlations between WLS and South Oaks Gambling Screen (SOGS) and duration of illness were examined. RESULTS: The classifier distinguished between the GD patients and HCs with high accuracy in leave-one-out cross-validation (area under curve (AUC = 0.89)). This performance was confirmed in the external dataset (AUC = 0.81). There was no correlation between WLS, and SOGS and duration of illness in the GD patients. CONCLUSION: We developed a generalizable classifier for GD based on information of functional connections between brain regions at resting state.

Birth order and prosociality in the early adolescent brain.

Birth order is a crucial environmental factor for child development. For example, later-born children are relatively unlikely to feel secure due to sibling competition or diluted parental resources. The positive effect of being earlier-born on cognitive intelligence is well-established. However, whether birth order is linked to social behavior remains controversial, and the neural correlates of birth order effects in adolescence when social cognition develops remain unknown. Here, we explored the birth order effect on prosociality using a large-scale population-based adolescent cohort. Next, since the amygdala is a key region for sociality and environmental stress, we examined amygdala substrates of the association between birth order and prosociality using a subset neuroimaging cohort. We found enhanced prosociality in later-born adolescents (N = 3160), and observed the mediating role of larger amygdala volume (N = 208) and amygdala-prefrontal functional connectivity with sex-selective effects (N = 183). We found that birth order, a non-genetic environmental factor, affects adolescent social development via different neural substrates. Our findings may indicate the later-born people's adaptive survival strategy in stressful environments.

Chemogenetic activation of nigrostriatal dopamine neurons in freely moving common marmosets.

To interrogate particular neuronal pathways in nonhuman primates under natural and stress-free conditions, we applied designer receptors exclusively activated by designer drugs (DREADDs) technology to common marmosets. We injected adeno-associated virus vectors expressing the excitatory DREADD hM3Dq into the unilateral substantia nigra (SN) in four marmosets. Using multi-tracer positron emission tomography imaging, we detected DREADD expression in vivo, which was confirmed in nigrostriatal dopamine neurons by immunohistochemistry, as well as by assessed activation of the SN following agonist administration. The marmosets rotated in a contralateral direction relative to the activated side 30-90 min after consuming food containing the highly potent DREADD agonist deschloroclozapine (DCZ) but not on the following days without DCZ. These results indicate that non-invasive and reversible DREADD manipulation will extend the utility of marmosets as a primate model for linking neuronal activity and natural behavior in various contexts.

A multi-site, multi-disorder resting-state magnetic resonance image database.

Machine learning classifiers for psychiatric disorders using resting-state functional magnetic resonance imaging (rs-fMRI) have recently attracted attention as a method for directly examining relationships between neural circuits and psychiatric disorders. To develop accurate and generalizable classifiers, we compiled a large-scale, multi-site, multi-disorder neuroimaging database. The database comprises resting-state fMRI and structural images of the brain from 993 patients and 1,421 healthy individuals, as well as demographic information such as age, sex, and clinical rating scales. To harmonize the multi-site data, nine healthy participants ("traveling subjects") visited the sites from which the above datasets were obtained and underwent neuroimaging with 12 scanners. All participants consented to having their data shared and analyzed at multiple medical and research institutions participating in the project, and 706 patients and 1,122 healthy individuals consented to having their data disclosed. Finally, we have published four datasets: 1) the SRPBS Multi-disorder Connectivity Dataset 2), the SRPBS Multi-disorder MRI Dataset (restricted), 3) the SRPBS Multi-disorder MRI Dataset (unrestricted), and 4) the SRPBS Traveling Subject MRI Dataset.

Intergenerational transmission of the patterns of functional and structural brain networks.

There is clear evidence of intergenerational transmission of life values, cognitive traits, psychiatric disorders, and even aspects of daily decision making. To investigate biological substrates of this phenomenon, the brain has received increasing attention as a measurable biomarker and potential target for intervention. However, no previous study has quantitatively and comprehensively investigated the effects of intergenerational transmission on functional and structural brain networks. Here, by employing an unusually large cohort dataset (N = 84 parent-child dyads; 45 sons, 39 daughters, 81 mothers, and 3 fathers), we show that patterns of functional and structural brain networks are preserved over a generation. We also demonstrate that several demographic factors and behavioral/physiological phenotypes have a relationship with brain similarity. Collectively, our results provide a comprehensive picture of neurobiological substrates of intergenerational transmission and demonstrate the usability of our dataset for investigating the neurobiological substrates of intergenerational transmission.

Common Brain Networks Between Major Depressive-Disorder Diagnosis and Symptoms of Depression That Are Validated for Independent Cohorts.

Large-scale neuroimaging data acquired and shared by multiple institutions are essential to advance neuroscientific understanding of pathophysiological mechanisms in psychiatric disorders, such as major depressive disorder (MDD). About 75% of studies that have applied machine learning technique to neuroimaging have been based on diagnoses by clinicians. However, an increasing number of studies have highlighted the difficulty in finding a clear association between existing clinical diagnostic categories and neurobiological abnormalities. Here, using resting-state functional magnetic resonance imaging, we determined and validated resting-state functional connectivity related to depression symptoms that were thought to be directly related to neurobiological abnormalities. We then compared the resting-state functional connectivity related to depression symptoms with that related to depression diagnosis that we recently identified. In particular, for the discovery dataset with 477 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a brain network prediction model of depression symptoms (Beck Depression Inventory-II [BDI] score). The prediction model significantly predicted BDI score for an independent validation dataset with 439 participants from 4 different imaging sites. Finally, we found 3 common functional connections between those related to depression symptoms and those related to MDD diagnosis. These findings contribute to a deeper understanding of the neural circuitry of depressive symptoms in MDD, a hetero-symptomatic population, revealing the neural basis of MDD.

The extrastriate body area is involved in reciprocal imitation of hand gestures, vocalizations, and facial expressions: A univariate and multivariate fMRI study.

The extrastriate body area (EBA) in the lateral occipito-temporal cortex has an important role in reciprocal interaction, as it detects congruence between self and other's hand actions. However, it is unclear whether the EBA can detect congruence regardless of the type of action. In the present study, we examined the neural substrate underlying congruence detection of three types of actions: hand gestures, vocalizations, and facial expressions. A univariate analysis revealed a congruency effect, especially for imitating action, for all three types of actions in the EBA. A multi-voxel pattern analysis classifier in the EBA was able to distinguish between initiating interaction from responding to interaction in all experiments. Correspondingly, the congruency effect in the EBA revealed by univariate analysis was stronger for responding to than for initiating interaction. These findings suggest that the EBA might contribute to detect congruence regardless of the body part used (i.e. face or hand) and the type of action (i.e. gestural or vocal). Moreover, initiating and responding to interaction might be processed differently within the EBA. This study highlights the role of the EBA in comparing between self and other's actions beyond hand actions.Running head: Function of EBA in reciprocal imitation.

Generalizable brain network markers of major depressive disorder across multiple imaging sites.

Many studies have highlighted the difficulty inherent to the clinical application of fundamental neuroscience knowledge based on machine learning techniques. It is difficult to generalize machine learning brain markers to the data acquired from independent imaging sites, mainly due to large site differences in functional magnetic resonance imaging. We address the difficulty of finding a generalizable marker of major depressive disorder (MDD) that would distinguish patients from healthy controls based on resting-state functional connectivity patterns. For the discovery dataset with 713 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a machine learning MDD classifier. The classifier achieved an approximately 70% generalization accuracy for an independent validation dataset with 521 participants from 5 different imaging sites. The successful generalization to a perfectly independent dataset acquired from multiple imaging sites is novel and ensures scientific reproducibility and clinical applicability.

Publisher Correction: Primary functional brain connections associated with melancholic major depressive disorder and modulation by antidepressants.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Association between duration of breastfeeding based on maternal reports and dorsal and ventral striatum and medial orbital gyrus volumes in early adolescence.

Maternal breastfeeding has an impact on motor and emotional development in children of the next generation. Elucidating how breastfeeding during infancy affects brain regional structural development in early adolescence will be helpful for promoting healthy development. However, previous studies that have shown relationships between breastfeeding during infancy and cortical brain regions in adolescence are usually based on maternal retrospective recall of breastfeeding, and the accuracy of the data is unclear. In this study, we investigated the association between breastfeeding duration and brain regional volume in a population-neuroimaging study of early adolescents in Japan (N â€‹= â€‹207; 10.5-13.4 years) using voxel-based morphometry, which enabled us to analyze the whole brain. We evaluated breastfeeding duration as indexed by maternal and child health handbook records during infancy. The results showed a significant positive correlation between the duration of breastfeeding and gray matter volume in the dorsal and ventral striatum and the medial orbital gyrus. Post hoc exploratory analyses revealed that the duration of breastfeeding was significantly correlated with emotional behavior. Additionally, the volume in the medial orbital gyrus mediated an association between breastfeeding duration and emotional behavior. This is the first study to evaluate the effect of breastfeeding during infancy on regional brain volumes in early adolescence based on maternal and child health handbook records. Our findings shed light upon the importance of maternal breastfeeding for brain development related to emotional and motivational processing in early adolescence.

Functional connectomes linking child-parent relationships with psychological problems in adolescence.

The child-parent relationship is a significant factor in an adolescent's well-being and functional outcomes. Epidemiological evidence indicates that relationships with the father and mother are differentially associated with specific psychobehavioral problems that manifest differentially between boys and girls. Neuroimaging is expected to bridge the gap in understanding such a complicated mapping between the child-parent relationships and adolescents' problems. However, possible differences in the effects of child-father and child-mother relationships on sexual dimorphism in children's brains and psychobehavioral problems have not been examined yet. This study used a dataset of 10- to 13-year-old children (N â€‹= â€‹93) to reveal the triad of associations among child-parent relationship, brain, and psychobehavioral problems by separately estimating the respective effects of child-father and child-mother relationships on boys and girls. We first fitted general linear models to identify the effects of paternal and maternal relationships in largely different sets of children's resting-state functional connectivity, which we term paternal and maternal functional brain connectomes (FBCs). We then performed connectome-based predictive modeling (CPM) to predict children's externalizing and internalizing problems from these parental FBCs. The models significantly predicted a range of girls' internalizing problems, whereas the prediction of boys' aggression was also significant using a more liberal uncorrected threshold. A series of control analyses confirmed that CPMs using FBCs associated with peer relationship or family socioeconomic status failed to make significant predictions of psychobehavioral problems. Lastly, a causal discovery method identified causal paths from daughter-mother relationship to maternal FBC, and then to daughter's internalizing problems. These observations indicate sex-dependent mechanisms linking child-parent relationship, brain, and psychobehavioral problems in the development of early adolescence.

Neurometabolic underpinning of the intergenerational transmission of prosociality.

Parent-child personality transmission can occur via biological gene-driven processes as well as through environmental factors such as shared environment and parenting style. We recently revealed a negative association between prosociality, a highly valued personality attribute in human society, and anterior cingulate cortex (ACC) γ-aminobutyric acid (GABA) levels in children at the age of 10 years. We thus hypothesized that prosociality would be intergenerationally transmitted, and that transmission would be underwritten by neurometabolic heritability. Here, we collected prosociality data from children aged 10 years and their parents in a large-scale population-based birth cohort study. We also measured ACC GABA+ and glutamate plus glutamine (Glx) levels in a follow-up assessment with a subsample of the participants (aged 11 years) using magnetic resonance spectroscopy. We analyzed the associations among children's and parents' prosociality and GABA+/Glx ratios. We also examined the effect of socioeconomic status (SES) and verbalized parental affection (VPA) on these associations. We found a significant positive parent-child association for prosociality (N â€‹= â€‹3026; children's mean age 10.2 years) and GABA+/Glx ratio (N â€‹= â€‹99; children's mean age 11.4 years). There was a significant negative association between GABA+/Glx ratio and prosociality in both children (N â€‹= â€‹208) and parents (N â€‹= â€‹128). Our model accounting for the effects of neurometabolic heritability on prosociality transmission fitted well. Moreover, in this model, a significant positive effect of VPA but not SES on children's prosociality was observed independently of the effect of neurometabolic transmission, while SES but not VPA was significantly associated with parental prosociality. Our results provide novel insights into the neurometabolic substrates of parent-child transmission of social behavior.

Overlapping but Asymmetrical Relationships Between Schizophrenia and Autism Revealed by Brain Connectivity.

Although the relationship between schizophrenia spectrum disorder (SSD) and autism spectrum disorder (ASD) has long been debated, it has not yet been fully elucidated. The authors quantified and visualized the relationship between ASD and SSD using dual classifiers that discriminate patients from healthy controls (HCs) based on resting-state functional connectivity magnetic resonance imaging. To develop a reliable SSD classifier, sophisticated machine-learning algorithms that automatically selected SSD-specific functional connections were applied to Japanese datasets from Kyoto University Hospital (N = 170) including patients with chronic-stage SSD. The generalizability of the SSD classifier was tested by 2 independent validation cohorts, and 1 cohort including first-episode schizophrenia. The specificity of the SSD classifier was tested by 2 Japanese cohorts of ASD and major depressive disorder. The weighted linear summation of the classifier's functional connections constituted the biological dimensions representing neural classification certainty for the disorders. Our previously developed ASD classifier was used as ASD dimension. Distributions of individuals with SSD, ASD, and HCs s were examined on the SSD and ASD biological dimensions. We found that the SSD and ASD populations exhibited overlapping but asymmetrical patterns in the 2 biological dimensions. That is, the SSD population showed increased classification certainty for the ASD dimension but not vice versa. Furthermore, the 2 dimensions were correlated within the ASD population but not the SSD population. In conclusion, using the 2 biological dimensions based on resting-state functional connectivity enabled us to discover the quantified relationships between SSD and ASD.

Primary functional brain connections associated with melancholic major depressive disorder and modulation by antidepressants.

The limited efficacy of available antidepressant therapies may be due to how they affect the underlying brain network. The purpose of this study was to develop a melancholic MDD biomarker to identify critically important functional connections (FCs), and explore their association to treatments. Resting state fMRI data of 130 individuals (65 melancholic major depressive disorder (MDD) patients, 65 healthy controls) were included to build a melancholic MDD classifier, and 10 FCs were selected by our sparse machine learning algorithm. This biomarker generalized to a drug-free independent cohort of melancholic MDD, and did not generalize to other MDD subtypes or other psychiatric disorders. Moreover, we found that antidepressants had a heterogeneous effect on the identified FCs of 25 melancholic MDDs. In particular, it did impact the FC between left dorsolateral prefrontal cortex (DLPFC)/inferior frontal gyrus (IFG) and posterior cingulate cortex (PCC)/precuneus, ranked as the second 'most important' FC based on the biomarker weights, whilst other eight FCs were normalized. Given that left DLPFC has been proposed as an explicit target of depression treatments, this suggest that the limited efficacy of antidepressants might be compensated by combining therapies with targeted treatment as an optimized approach in the future.

Smaller anterior subgenual cingulate volume mediates the effect of girls' early sexual maturation on negative psychobehavioral outcome.

Early-maturing girls are relatively likely to experience compromised psychobehavioral outcomes. Some studies have explored the association between puberty and brain morphology in adolescents, while the results were non-specific for females or the method was a region-of-interest analysis. To our knowledge, no large-scale study has comprehensively explored the effects of pubertal timing on whole-brain volumetric development or the neuroanatomical substrates of the association in girls between pubertal timing and psychobehavioral outcomes. We collected structural magnetic resonance imaging (MRI) data of a subsample (N â€‹= â€‹203, mean age 11.6 years) from a large-scale population-based birth cohort. Tanner stage, a scale of physical maturation in adolescents, was rated almost simultaneously with MRI scan. The Strengths and Difficulties Questionnaire total difficulties (SDQ-TD) scores were rated by primary parents some duration after MRI scan (mean age 12.1 years). In each sex group, we examined brain regions associated with Tanner stage using whole-brain analysis controlling for chronological age, followed by an exploration of brain regions also associated with the SDQ-TD scores. We also performed mediation analyses. In girls, Tanner stage was significantly negatively correlated with gray matter volumes (GMVs) in the anterior/middle cingulate cortex (ACC/MCC), of which the subgenual ACC (sgACC) showed a negative correlation between GMVs and SDQ-TD scores. Smaller GMVs in the sgACC mediated the association between higher Tanner stages and higher SDQ-TD scores. We found no significant results in boys. Our results from a minimally biased, large-scale sample provide new insights into neuroanatomical correlates of the effect of pubertal timing on developmental psychological difficulties emerging in adolescence.