Maternal depressive symptoms influence neurodevelopment in the offspring. Such effects may appear to be gender-dependent. The present study examined contributions of prenatal and postnatal maternal depressive symptoms to the volume and microstructure of the amygdala in 4.5-year-old boys and girls. Prenatal maternal depressive symptoms were measured using the Edinburgh Postnatal Depression Scale (EPDS) at 26 weeks of gestation. Postnatal maternal depression was assessed at 3 months using the EPDS and at 1, 2, 3 and 4.5 years using the Beck's Depression Inventory-II. Structural magnetic resonance imaging and diffusion tensor imaging were performed with 4.5-year-old children to extract the volume and fractional anisotropy (FA) values of the amygdala. Our results showed that greater prenatal maternal depressive symptoms were associated with larger right amygdala volume in girls, but not in boys. Increased postnatal maternal depressive symptoms were associated with higher right amygdala FA in the overall sample and girls, but not in boys. These results support the role of variation in right amygdala structure in transmission of maternal depression to the offspring, particularly to girls. The differential effects of prenatal and postnatal maternal depressive symptoms on the volume and FA of the right amygdala suggest the importance of the timing of exposure to maternal depressive symptoms in brain development of girls. This further underscores the need for intervention targeting both prenatal and postnatal maternal depression to girls in preventing adverse child outcomes.

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.

There is cumulative evidence that young people in an "atrisk 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.

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 T 1 -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 T 1 -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.

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.

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.

BackgroundSalience network (SN) dysconnectivity has been hypothesized to contribute to schizophrenia. Nevertheless, little is known about the functional and structural dysconnectivity of SN in subjects at risk for psychosis. We hypothesized that SN functional and structural connectivity would be disrupted in subjects with At-Risk Mental State (ARMS) and would be associated with symptom severity and disease progression.MethodWe examined 87 ARMS and 37 healthy participants using both resting-state functional magnetic resonance imaging and diffusion tensor imaging. Group differences in SN functional and structural connectivity were examined using a seed-based approach and tract-based spatial statistics. Subject-level functional connectivity measures and diffusion indices of disrupted regions were correlated with CAARMS scores and compared between ARMS with and without transition to psychosis.ResultsARMS subjects exhibited reduced functional connectivity between the left ventral anterior insula and other SN regions. Reduced fractional anisotropy (FA) and axial diffusivity were also found along white-matter tracts in close proximity to regions of disrupted functional connectivity, including frontal-striatal-thalamic circuits and the cingulum. FA measures extracted from these disrupted white-matter regions correlated with individual symptom severity in the ARMS group. Furthermore, functional connectivity between the bilateral insula and FA at the forceps minor were further reduced in subjects who transitioned to psychosis after 2 years.ConclusionsOur findings support the insular dysconnectivity of the proximal SN hypothesis in the early stages of psychosis. Further developed, the combined structural and functional SN assays may inform the prognosis of persons at-risk for psychosis.

No abstract