Sex-Dependent Associations among Maternal Depressive Symptoms, Child Reward Network, and Behaviors in Early Childhood.

Maternal depression is associated with disrupted neurodevelopment in offspring. This study examined relationships among postnatal maternal depressive symptoms, the functional reward network and behavioral problems in 4.5-year-old boys (57) and girls (65). We employed canonical correlation analysis to evaluate whether the resting-state functional connectivity within a reward network, identified through an activation likelihood estimation (ALE) meta-analysis of fMRI studies, was associated with postnatal maternal depressive symptoms and child behaviors. The functional reward network consisted of three subnetworks, that is, the mesolimbic, mesocortical, and amygdala-hippocampus reward subnetworks. Postnatal maternal depressive symptoms were associated with the functional connectivity of the mesocortical subnetwork with the mesolimbic and amygdala-hippocampus complex subnetworks in girls and with the functional connectivity within the mesocortical subnetwork in boys. The functional connectivity of the amygdala-hippocampus subnetwork with the mesocortical and mesolimbic subnetworks was associated with both internalizing and externalizing problems in girls, while in boys, the functional connectivity of the mesocortical subnetwork with the amygdala-hippocampus complex and the mesolimbic subnetworks was associated with the internalizing and externalizing problems, respectively. Our findings suggest that the functional reward network might be a promising neural phenotype for effects of maternal depression and potential intervention to nurture child behavioral development.

Neural Transcription Correlates of Multimodal Cortical Phenotypes during Development.

During development, cellular events such as cell proliferation, migration, and synaptogenesis determine the structural organization of the brain. These processes are driven in part by spatiotemporally regulated gene expression. We investigated how the genetic signatures of specific neural cell types shape cortical organization of the human brain throughout infancy and childhood. Using a transcriptional atlas and in vivo magnetic resonance imaging (MRI) data, we demonstrated time-dependent associations between the expression levels of neuronal and glial genes and cortical macro- and microstructure. Neonatal cortical phenotypes were associated with prenatal glial but not neuronal gene expression. These associations reflect cell migration and proliferation during fetal development. Childhood cortical phenotypes were associated with neuronal and astrocyte gene expression related to synaptic signaling processes, reflecting the refinement of cortical connections. These findings indicate that sequential developmental stages contribute to distinct MRI measures at different time points. This helps to bridge the gap between the genetic mechanisms driving cellular changes and widely used neuroimaging techniques.

Functional and structural networks of lateral and medial orbitofrontal cortex as potential neural pathways for depression in childhood.

BACKGROUND: Converging evidence suggests that the lateral and medial orbitofrontal cortices (lOFC and mOFC) may contribute distinct neural mechanisms in depression. This study investigated the relations of their functional and structural organizations with postnatal maternal depressive symptoms in young children. METHODS: Resting-state functional magnetic resonance imaging and structural magnetic resonance imaging were acquired in children at age 4 (n = 199) and 6 years (n = 234). Child's withdrawal behavior problems were assessed using Child's Behavior Checklist. RESULTS: In 4-year-old girls, postnatal maternal depressive symptoms were positively associated with the lOFC functional connectivity with the visual network but negatively with the cognitive control network. The lOFC functional connectivity with the visual network and cerebellum, which was influenced by postnatal maternal depressive symptoms, was also associated with child's withdrawal behavior problems in 6-year-old girls. Moreover, postnatal maternal depressive symptoms were also negatively associated with the mOFC functional connectivity with the cognitive control and motor networks in 4-year-old girls. Furthermore, postnatal maternal depressive symptoms influenced the structural connectivity of left mOFC with the right middle frontal cortex and left inferior temporal cortex in 4-year-old girls. Unlike girls, boys showed that postnatal maternal depressive symptoms selectively impacted the mOFC functional connectivity with the memory system at age 6 years. CONCLUSION: Our study provided novel evidence on the distinct neural mechanisms of the lOFC and mOFC structural and functional organizations for intergenerational transmission of maternal depression to the offspring. Boys and girls may potentially employ different neural mechanisms to adapt to maternal environment at different timings of early life.

Behavioral Heterogeneity in Relation with Brain Functional Networks in Young Children.

This study aimed to identify distinct behavioral profiles in a population-based sample of 654 4-year-old children and characterize their relationships with brain functional networks using resting-state functional magnetic resonance imaging data. Young children showed 7 behavioral profiles, including a super healthy behavioral profile with the lowest scores across all Child Behavior CheckList (CBCL) subscales (G1) and other 6 behavioral profiles, respectively with pronounced withdrawal (G2), somatic complaints (G3), anxiety and withdrawal (G4), somatic complaints and withdrawal (G5), the mixture of emotion, withdrawal, and aggression (G6), and attention (G7) problems. Compared with children in G1, children with withdrawal shared abnormal functional connectivities among the sensorimotor networks. Children in emotionally relevant problems shared the common pattern among the attentional and frontal networks. Nevertheless, children in sole withdrawal problems showed a unique pattern of connectivity alterations among the sensorimotor, cerebellar, and salience networks. Children with somatic complaints showed abnormal functional connectivities between the attentional and subcortical networks, and between the language and posterior default mode networks. This study provides novel evidence on the existence of behavioral heterogeneity in early childhood and its associations with specific functional networks that are clinically relevant phenotypes for mental illness and are apparent from early childhood.

Large-Scale Network Topology Reveals Heterogeneity in Individuals With at Risk Mental State for Psychosis: Findings From the Longitudinal Youth-at-Risk Study.

Emerging evidence demonstrates heterogeneity in clinical outcomes of prodromal psychosis that only a small percentage of at-risk individuals eventually progress to full-blown psychosis. To examine the neurobiological underpinnings of this heterogeneity from a network perspective, we tested whether the early patterns of large-scale brain network topology were associated with risk of developing clinical psychosis. Task-free functional MRI data were acquired from subjects with At Risk Mental State (ARMS) for psychosis and healthy controls (HC). All individuals had no history of drug abuse and were not on antipsychotics. We performed functional connectomics analysis to identify patterns of system-level functional brain dysconnectivity associated with ARMS individuals with different outcomes. In comparison to HC and ARMS who did not transition to psychosis at follow-up (ARMS-NT), ARMS individuals who did (ARMS-T) showed marked brain functional dysconnectivity, characterized by loss of network segregation and disruption of network communities, especially the salience, default, dorsal attention, sensorimotor and limbic networks (P < 0.05 FWE-corrected, Cohen's d > 1.00), and was associated with baseline symptom severity. In contrast, we did not observe connectivity differences between ARMS-NT and HC individuals. Taken together, these results suggest a possible large-scale functional brain network topology phenotype related to risk of psychosis transition in ARMS individuals.

Improving mass-univariate analysis of neuroimaging data by modelling important unknown covariates: Application to Epigenome-Wide Association Studies.

Statistical inference on neuroimaging data is often conducted using a mass-univariate model, equivalent to fitting a linear model at every voxel with a known set of covariates. Due to the large number of linear models, it is challenging to check if the selection of covariates is appropriate and to modify this selection adequately. The use of standard diagnostics, such as residual plotting, is clearly not practical for neuroimaging data. However, the selection of covariates is crucial for linear regression to ensure valid statistical inference. In particular, the mean model of regression needs to be reasonably well specified. Unfortunately, this issue is often overlooked in the field of neuroimaging. This study aims to adopt the existing Confounder Adjusted Testing and Estimation (CATE) approach and to extend it for use with neuroimaging data. We propose a modification of CATE that can yield valid statistical inferences using Principal Component Analysis (PCA) estimators instead of Maximum Likelihood (ML) estimators. We then propose a non-parametric hypothesis testing procedure that can improve upon parametric testing. Monte Carlo simulations show that the modification of CATE allows for more accurate modelling of neuroimaging data and can in turn yield a better control of False Positive Rate (FPR) and Family-Wise Error Rate (FWER). We demonstrate its application to an Epigenome-Wide Association Study (EWAS) on neonatal brain imaging and umbilical cord DNA methylation data obtained as part of a longitudinal cohort study. Software for this CATE study is freely available at http://www.bioeng.nus.edu.sg/cfa/Imaging_Genetics2.html.

Perinatal maternal depressive symptoms alter amygdala functional connectivity in girls.

Perinatal maternal depressive symptoms influence brain development of offspring. Such effects are particularly notable in the amygdala, a key structure involved in emotional processes. This study investigated whether the functional organization of the amygdala varies as a function of pre- and postnatal maternal depressive symptoms. The amygdala functional network was assessed using resting-state functional magnetic resonance imaging (rs-fMRI) in 128 children at age of 4.4 to 4.8 years. Maternal depressive symptoms were obtained at 26 weeks of gestation, 3 months, 1, 2, 3, and 4.5 years after delivery. Linear regression was used to examine associations between maternal depressive symptoms and the amygdala functional network. Prenatal maternal depressive symptoms were significantly associated with the functional connectivity between the amygdala and the cortico-striatal circuitry, especially the orbitofrontal cortex (OFC), insula, subgenual anterior cingulate (ACC), temporal pole, and striatum. Interestingly, greater pre- than post-natal depressive symptoms were associated with lower functional connectivity of the left amygdala with the bilateral subgenual ACC and left caudate and with lower functional connectivity of the right amygdala with the left OFC, insula, and temporal pole. These findings were only observed in girls but not in boys. Early exposure to maternal depressive symptoms influenced the functional organization of the cortico-striato-amygdala circuitry, which is intrinsic to emotional perception and regulation in girls. This suggests its roles in the transgenerational transmission of vulnerability for socio-emotional problems and depression. Moreover, this study underscored the importance of gender-dependent developmental pathways in defining the neural circuitry that underlies the risk for depression.

Developmental synchrony of thalamocortical circuits in the neonatal brain.

The thalamus is a deep gray matter structure and consists of axonal fibers projecting to the entire cortex, which provide the anatomical support for its sensorimotor and higher-level cognitive functions. There is limited in vivo evidence on the normal thalamocortical development, especially in early life. In this study, we aimed to investigate the developmental patterns of the cerebral cortex, the thalamic substructures, and their connectivity with the cortex in the first few weeks of the postnatal brain. We hypothesized that there is developmental synchrony of the thalamus, its cortical projections, and corresponding target cortical structures. We employed diffusion tensor imaging (DTI) and divided the thalamus into five substructures respectively connecting to the frontal, precentral, postcentral, temporal, and parietal and occipital cortex. T2-weighted magnetic resonance imaging (MRI) was used to measure cortical thickness. We found age-related increases in cortical thickness of bilateral frontal cortex and left temporal cortex in the early postnatal brain. We also found that the development of the thalamic substructures was synchronized with that of their respective thalamocortical connectivity in the first few weeks of the postnatal life. In particular, the right thalamo-frontal substructure had the fastest growth in the early postnatal brain. Our study suggests that the distinct growth patterns of the thalamic substructures are in synchrony with those of the cortex in early life, which may be critical for the development of the cortical and subcortical functional specialization.

Cortical graph neural network for AD and MCI diagnosis and transfer learning across populations.

Combining machine learning with neuroimaging data has a great potential for early diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, it remains unclear how well the classifiers built on one population can predict MCI/AD diagnosis of other populations. This study aimed to employ a spectral graph convolutional neural network (graph-CNN), that incorporated cortical thickness and geometry, to identify MCI and AD based on 3089 T1-weighted MRI data of the ADNI-2 cohort, and to evaluate its feasibility to predict AD in the ADNI-1 cohort (n = 3602) and an Asian cohort (n = 347). For the ADNI-2 cohort, the graph-CNN showed classification accuracy of controls (CN) vs. AD at 85.8% and early MCI (EMCI) vs. AD at 79.2%, followed by CN vs. late MCI (LMCI) (69.3%), LMCI vs. AD (65.2%), EMCI vs. LMCI (60.9%), and CN vs. EMCI (51.8%). We demonstrated the robustness of the graph-CNN among the existing deep learning approaches, such as Euclidean-domain-based multilayer network and 1D CNN on cortical thickness, and 2D and 3D CNNs on T1-weighted MR images of the ADNI-2 cohort. The graph-CNN also achieved the prediction on the conversion of EMCI to AD at 75% and that of LMCI to AD at 92%. The find-tuned graph-CNN further provided a promising CN vs. AD classification accuracy of 89.4% on the ADNI-1 cohort and >90% on the Asian cohort. Our study demonstrated the feasibility to transfer AD/MCI classifiers learned from one population to the other. Notably, incorporating cortical geometry in CNN has the potential to improve classification performance.

Maternal care in infancy and the course of limbic development.

Maternal care may predict limbic development, though relations may vary by age and type of assessment. Here, we examined maternal behavior during early infancy (i.e., six months postpartum) in relation to offspring hippocampal and amygdala volume and microstructure development between 4.5 (n = 99) and 6 (n = 111) years. In interaction with offspring sex, maternal sensitivity predicted left amygdala volume at 6.0 years (ß=-0.214, p = 0.032, df = 89) and independently predicted predominately left lateralized aspects of amygdala and hippocampal microstructure at both time points (hippocampus: left FA at 4.5 years [ß=-0.241, p = 0.043, df = 68], and, in interaction with sex, left [(ß = 0.349, p = 0.022, df = 86) and right FA at 6 years (ß = 0.357, p = 0.016, df = 86] and left MD growth [ß = -0.517, p = 0.021, df = 37]; amygdala: left MD at 4.5 years [ß = -0.319, p = 0.007, df = 69] and, in interaction with offspring sex, left MD growth [ß = -0.546, p = 0.019, df = 37]). Results suggest exposure to non-extreme, early insensitive care impacts neuroanatomy important to learning and stress regulation, perhaps by accelerating development. This underscores the need to promote sensitive caregiving during early infancy within community samples.

Long-term Influences of Prenatal Maternal Depressive Symptoms on the Amygdala-Prefrontal Circuitry of the Offspring From Birth to Early Childhood.

BACKGROUND: Prenatal maternal depression may have long-term impacts on amygdala-cortical development. This study explored associations of prenatal maternal depressive symptoms on the amygdala-cortical structural covariance of the offspring from birth to early childhood, derived from a longitudinal birth cohort. METHODS: Structural magnetic resonance imaging was performed to obtain the amygdala volume and cortical thickness at each time point. Prenatal maternal depressive symptoms were measured using the Edinburgh Postnatal Depression Scale at 26 weeks of pregnancy. Regression analysis was used to examine the effects of the Edinburgh Postnatal Depression Scale on a structural coupling between the amygdala volume and cortical thickness at birth (n = 167) and 4.5 years of age (n = 199). RESULTS: Girls whose mothers had high prenatal maternal depressive symptoms showed a positive coupling between the amygdala volume and insula thickness at birth (ß = .617, p = .001) but showed a negative coupling between the amygdala volume and inferior frontal thickness at 4.5 years of age (ß = -.369, p = .008). No findings were revealed in boys at any time point. CONCLUSIONS: The development of the amygdala-prefrontal circuitry is vulnerable to environmental factors related to depression. Such a vulnerability might be sex dependent.

Maternal sensitivity predicts anterior hippocampal functional networks in early childhood.

Maternal care influences child hippocampal development. The hippocampus is functionally organized along an anterior-posterior axis. Little is known with regards to the extent maternal care shapes offspring anterior and posterior hippocampal (aHPC, pHPC) functional networks. This study examined maternal behavior, especially maternal sensitivity, at 6 months postpartum in relation to aHPC and pHPC functional networks of children at age 4 and 6 years. Maternal sensitivity was assessed at 6 months via the "Maternal Behavior Q Sort (MBQS) mini for video". Subsequently, 61 and 76 children underwent resting-state functional magnetic resonance imaging (rs-fMRI), respectively, at 4 and 6 years of age. We found that maternal sensitivity assessed at 6 months postpartum was associated with the right aHPC functional networks in children at both 4 and 6 years of age. At age 4 years, maternal sensitivity was associated positively with the right aHPC's functional connectivity with the sensorimotor network and negatively with the aHPC's functional connectivity with the top-down cognitive control network. At 6 years of age, maternal sensitivity was linked positively with the right aHPC's functional connectivity with the visual-processing network. Our findings suggested that maternal sensitivity in infancy has a long-term impact on the anterior hippocampal functional network in preschool children, implicating a potential role of maternal care in shaping child brain development in early life.

Fronto-parietal numerical networks in relation with early numeracy in young children.

Early numeracy provides the foundation of acquiring mathematical skills that is essential for future academic success. This study examined numerical functional networks in relation to counting and number relational skills in preschoolers at 4 and 6 years of age. The counting and number relational skills were assessed using school readiness test (SRT). Resting-state fMRI (rs-fMRI) was acquired in 123 4-year-olds and 146 6-year-olds. Among them, 61 were scanned twice over the course of 2 years. Meta-analysis on existing task-based numeracy fMRI studies identified the left parietal-dominant network for both counting and number relational skills and the right parietal-dominant network only for number relational skills in adults. We showed that the fronto-parietal numerical networks, observed in adults, already exist in 4-year and 6-year-olds. The counting skills were associated with the bilateral fronto-parietal network in 4-year-olds and with the right parietal-dominant network in 6-year-olds. Moreover, the number relational skills were related to the bilateral fronto-parietal and right parietal-dominant networks in 4-year-olds and had a trend of the significant relationship with the right parietal-dominant network in 6-year-olds. Our findings suggested that neural fine-tuning of the fronto-parietal numerical networks may subserve the maturation of numeracy in early childhood.

Correction: Progressive decline in hippocampal CA1 volume in individuals at ultra-high-risk for psychosis who do not remit: findings from the longitudinal youth at risk study.

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

Neonatal amygdalae and hippocampi are influenced by genotype and prenatal environment, and reflected in the neonatal DNA methylome.

The amygdala and hippocampus undergo rapid development in early life. The relative contribution of genetic and environmental factors to the establishment of their developmental trajectories has yet to be examined. We performed imaging on neonates and examined how the observed variation in volume and microstructure of the amygdala and hippocampus varied by genotype, and compared with prenatal maternal mental health and socioeconomic status. Gene × Environment models outcompeted models containing genotype or environment only to best explain the majority of measures but some, especially of the amygdaloid microstructure, were best explained by genotype only. Models including DNA methylation measured in the neonate umbilical cords outcompeted the Gene and Gene × Environment models for the majority of amygdaloid measures and minority of hippocampal measures. This study identified brain region-specific gene networks associated with individual differences in fetal brain development. In particular, genetic and epigenetic variation within CUX1 was highlighted.

Progressive Decline in Hippocampal CA1 Volume in Individuals at Ultra-High-Risk for Psychosis Who Do Not Remit: Findings from the Longitudinal Youth at Risk Study.

Most individuals identified as ultra-high-risk (UHR) for psychosis do not develop frank psychosis. They continue to exhibit subthreshold symptoms, or go on to fully remit. Prior work has shown that the volume of CA1, a subfield of the hippocampus, is selectively reduced in the early stages of schizophrenia. Here we aimed to determine whether patterns of volume change of CA1 are different in UHR individuals who do or do not achieve symptomatic remission. Structural MRI scans were acquired at baseline and at 1-2 follow-up time points (at 12-month intervals) from 147 UHR and healthy control subjects. An automated method (based on an ex vivo atlas of ultra-high-resolution hippocampal tissue) was used to delineate the hippocampal subfields. Over time, a greater decline in bilateral CA1 subfield volumes was found in the subgroup of UHR subjects whose subthreshold symptoms persisted (n=40) and also those who developed clinical psychosis (n=12), compared with UHR subjects who remitted (n=41) and healthy controls (n=54). No baseline differences in volumes of the overall hippocampus or its subfields were found among the groups. Moreover, the rate of volume decline of CA1, but not of other hippocampal subfields, in the non-remitters was associated with increasing symptom severity over time. Thus, these findings indicate that there is deterioration of CA1 volume in persistently symptomatic UHR individuals in proportion to symptomatic progression.

Pre- and Post-Natal Maternal Depressive Symptoms in Relation with Infant Frontal Function, Connectivity, and Behaviors.

This study investigated the relationships between pre- and early post-natal maternal depression and their changes with frontal electroencephalogram (EEG) activity and functional connectivity in 6- and 18-month olds, as well as externalizing and internalizing behaviors in 24-month olds (n = 258). Neither prenatal nor postnatal maternal depressive symptoms independently predicted neither the frontal EEG activity nor functional connectivity in 6- and 18-month infants. However, increasing maternal depressive symptoms from the prenatal to postnatal period predicted greater right frontal activity and relative right frontal asymmetry amongst 6-month infants but these finding were not observed amongst 18-month infants after adjusted for post-conceptual age on the EEG visit day. Subsequently increasing maternal depressive symptoms from the prenatal to postnatal period predicted lower right frontal connectivity within 18-month infants but not among 6-month infants after controlling for post-conceptual age on the EEG visit day. These findings were observed in the full sample and the female sample but not in the male sample. Moreover, both prenatal and early postnatal maternal depressive symptoms independently predicted children's externalizing and internalizing behaviors at 24 months of age. This suggests that the altered frontal functional connectivity in infants born to mothers whose depressive symptomatology increases in the early postnatal period compared to that during pregnancy may reflect a neural basis for the familial transmission of phenotypes associated with mood disorders, particularly in girls.

Lack of Evidence for Regional Brain Volume or Cortical Thickness Abnormalities in Youths at Clinical High Risk for Psychosis: Findings From the Longitudinal Youth at Risk Study.

There is cumulative evidence that young people in an "at-risk mental state" (ARMS) for psychosis show structural brain abnormalities in frontolimbic areas, comparable to, but less extensive than those reported in established schizophrenia. However, most available data come from ARMS samples from Australia, Europe, and North America while large studies from other populations are missing. We conducted a structural brain magnetic resonance imaging study from a relatively large sample of 69 ARMS individuals and 32 matched healthy controls (HC) recruited from Singapore as part of the Longitudinal Youth At-Risk Study (LYRIKS). We used 2 complementary approaches: a voxel-based morphometry and a surface-based morphometry analysis to extract regional gray and white matter volumes (GMV and WMV) and cortical thickness (CT). At the whole-brain level, we did not find any statistically significant difference between ARMS and HC groups concerning total GMV and WMV or regional GMV, WMV, and CT. The additional comparison of 2 regions of interest, hippocampal, and ventricular volumes, did not return any significant difference either. Several characteristics of the LYRIKS sample like Asian origins or the absence of current illicit drug use could explain, alone or in conjunction, the negative findings and suggest that there may be no dramatic volumetric or CT abnormalities in ARMS.

Preserved working memory and altered brain activation in persons at risk for psychosis.

OBJECTIVE: Patients with schizophrenia exhibit impairments in working memory that often appear in attenuated form in persons at high risk for the illness. The authors hypothesized that deviations in task-related brain activation and deactivation would occur in persons with an at-risk mental state performing a working memory task that entailed the maintenance and manipulation of letters. METHOD: Participants at ultra high risk for developing psychosis (N=60), identified using the Comprehensive Assessment of At-Risk Mental States, and healthy comparison subjects (N=38) 14 to 29 years of age underwent functional MRI while performing a verbal working memory task. Group differences in brain activation were identified using analysis of covariance. RESULTS: The two groups did not show significant differences in speed or accuracy of performance, even after accounting for differences in education. Irrespective of task condition, at-risk participants exhibited significantly less activation than healthy comparison subjects in the left anterior insula. During letter manipulation, at-risk persons exhibited greater task-related deactivation within the default-mode network than comparison subjects. Region-of-interest analysis in the at-risk group revealed significantly greater right dorsolateral prefrontal cortex activation during manipulation of letters. CONCLUSIONS: Despite comparable behavioral performance, at-risk participants performing a verbal working memory task exhibited altered brain activation compared with healthy subjects. These findings demonstrate an altered pattern of brain activation in at-risk persons that contains elements of reduced function as well as compensation.