The findings demonstrate that the most consistent gray matter abnormalities in individuals exposed to childhood maltreatment are in relatively late-developing ventrolateral prefrontal-limbic-temporal regions that are known to mediate late-developing functions of affect and cognitive control, which are typically compromised in this population.

Studies of the psychological well-being of elderly living alone have yielded inconsistent results. Few investigators have distinguished living alone from loneliness in the same study. Thus, the present study examined the independent and interactive effects of living alone and loneliness on depressive symptoms (GDS score) and quality of life (SF-12 MCS score) in a prospective 2-year follow-up cohort study of 2808 community-dwelling older adults (aged ≥55 years) in Singapore, controlling for baseline covariates. In cross-sectional analysis, loneliness was a more robust predictor of GDS score than living arrangements; living alone, when controlled for loneliness, was not associated with GDS score. GDS score associated with living alone was worse for those who felt lonely than for those who did not feel lonely. Similar patterns of association were found in longitudinal analyses and for SF-12 MCS score, although not all were significant. Thus, though living alone predicted lower psychological well-being, its predictive ability was reduced when loneliness was taken into account and loneliness, a stronger predictor, worsened the psychological effects of living alone.

Functional inhibitory neural networks mature progressively with age. However, nothing is known about the impact of gender on their development. This study employed functional magnetic resonance imaging (fMRI) to investigate the effects of age, sex, and sex by age interactions on the brain activation of 63 healthy males and females, between 13 and 38 years, performing a Stop task. Increasing age was associated with progressively increased activation in typical response inhibition areas of right inferior and dorsolateral prefrontal and temporo-parietal regions. Females showed significantly enhanced activation in left inferior and superior frontal and striatal regions relative to males, while males showed increased activation relative to females in right inferior and superior parietal areas. Importantly, left frontal and striatal areas that showed increased activation in females, also showed significantly increased functional maturation in females relative to males, while the right inferior parietal activation that was increased in males showed significantly increased functional maturation relative to females. The findings demonstrate for the first time that sex-dimorphic activation patterns of enhanced left fronto-striatal activation in females and enhanced right parietal activation in males during motor inhibition appear to be the result of underlying gender differences in the functional maturation of these brain regions.

The findings suggest that severe childhood abuse is associated with abnormally increased activation in classical dorsomedial frontal error-processing regions; furthermore, the increased activation in the supplementary motor area was abuse specific. However, childhood abuse was not associated with inhibitory dysfunction. Increased sensitivity of error-detection networks in participants in the childhood abuse group may be due to the constant need to monitor their own actions in order to avoid painful mistakes, which are often associated with harsh punishment in abusive settings.

ObjectiveAttention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder, but diagnosed by subjective clinical and rating measures. The study’s aim was to apply Gaussian process classification (GPC) to grey matter (GM) volumetric data, to assess whether individual ADHD adolescents can be accurately differentiated from healthy controls based on objective, brain structure measures and whether this is disorder-specific relative to autism spectrum disorder (ASD).MethodTwenty-nine adolescent ADHD boys and 29 age-matched healthy and 19 boys with ASD were scanned. GPC was applied to make disorder-specific predictions of ADHD diagnostic status based on individual brain structure patterns. In addition, voxel-based morphometry (VBM) analysis tested for traditional univariate group level differences in GM.ResultsThe pattern of GM correctly classified 75.9% of patients and 82.8% of controls, achieving an overall classification accuracy of 79.3%. Furthermore, classification was disorder-specific relative to ASD. The discriminating GM patterns showed higher classification weights for ADHD in earlier developing ventrolateral/premotor fronto-temporo-limbic and stronger classification weights for healthy controls in later developing dorsolateral fronto-striato-parieto-cerebellar networks. Several regions were also decreased in GM in ADHD relative to healthy controls in the univariate VBM analysis, suggesting they are GM deficit areas.ConclusionsThe study provides evidence that pattern recognition analysis can provide significant individual diagnostic classification of ADHD patients and healthy controls based on distributed GM patterns with 79.3% accuracy and that this is disorder-specific relative to ASD. Findings are a promising first step towards finding an objective differential diagnostic tool based on brain imaging measures to aid with the subjective clinical diagnosis of ADHD.