Disinhibition is one of the most distressing and difficult to treat neuropsychiatric symptoms of dementia. It involves socially inappropriate behaviours, such as hypersexual comments, inappropriate approaching of strangers and excessive jocularity. Disinhibition occurs in multiple dementia syndromes, including behavioural variant frontotemporal dementia, and dementia of the Alzheimers type. Morphometric similarity networks are a relatively new method for examining brain structure and can be used to calculate measures of network integrity on large scale brain networks and subnetworks such as the salience network and cognitive control network. In a cross-sectional study, we calculated morphometric similarity networks to determine whether disinhibition in behavioural variant frontotemporal dementia (n = 75) and dementia of the Alzheimers type (n = 111) was associated with reduced integrity of these networks independent of diagnosis. We found that presence of disinhibition, measured by the Neuropsychiatric Inventory Questionnaire, was associated with reduced global efficiency of the cognitive control network in both dementia of the Alzheimers type and behavioural variant frontotemporal dementia. Future research should replicate this transdiagnostic finding in other dementia diagnoses and imaging modalities, and investigate the potential for intervention at the level of the cognitive control network to target disinhibition.

Dementia of Alzheimer's type (DAT) is associated with devastating and irreversible cognitive decline. Predicting which patients with mild cognitive impairment (MCI) will progress to DAT is an ongoing challenge in the field. We developed a deep learning model to predict conversion from MCI to DAT. Structural magnetic resonance imaging scans were used as input to a 3-dimensional convolutional neural network. The 3-dimensional convolutional neural network was trained using transfer learning; in the source task, normal control and DAT scans were used to pretrain the model. This pretrained model was then retrained on the target task of classifying which MCI patients converted to DAT. Our model resulted in 82.4% classification accuracy at the target task, outperforming current models in the field. Next, we visualized brain regions that significantly contribute to the prediction of MCI conversion using an occlusion map approach. Contributory regions included the pons, amygdala, and hippocampus. Finally, we showed that the model's prediction value is significantly correlated with rates of change in clinical assessment scores, indicating that the model is able to predict an individual patient's future cognitive decline. This information, in conjunction with the identified anatomical features, will aid in building a personalized therapeutic strategy for individuals with MCI.

Midlife blood pressure is associated with structural brain changes, cognitive decline, and dementia in late life. However, the relationship between early adulthood blood pressure exposure, brain structure and function, and cognitive performance in midlife is not known. A better understanding of these relationships in the preclinical stage may advance our mechanistic understanding of vascular contributions to late-life cognitive decline and dementia and may provide early therapeutic targets. To identify resting-state functional connectivity of executive control networks (ECNs), a group independent components analysis was performed of functional MRI scans of 600 individuals from the Coronary Artery Risk Development in Young Adults longitudinal cohort study, with cumulative systolic blood pressure (cSBP) measured at nine visits over the preceding 30 y. Dual regression analysis investigated performance-related connectivity of ECNs in 578 individuals (mean age 55.5 ± 3.6 y, 323 female, 243 Black) with data from the Stroop color-word task of executive function. Greater connectivity of a left ECN to the bilateral anterior gyrus rectus, right posterior orbitofrontal cortex, and nucleus accumbens was associated with better executive control performance on the Stroop. Mediation analyses showed that while the relationship between cSBP and Stroop performance was mediated by white matter hyperintensities (WMH), resting-state connectivity of the ECN mediated the relationship between WMH and executive function. Increased connectivity of the left ECN to regions involved in reward processing appears to compensate for the deleterious effects of WMH on executive function in individuals across the burden of cumulative systolic blood pressure exposure in midlife.

Occurring in at least 1 in 3,000 live births, chromosome 22q11.2 deletion syndrome (22q11DS) produces a complex phenotype that includes a constellation of medical complications such as congenital cardiac defects, immune deficiency, velopharyngeal dysfunction, and characteristic facial dysmorphic features. There is also an increased incidence of psychiatric diagnosis, especially intellectual disability and ADHD in childhood, lifelong anxiety, and a strikingly high rate of schizophrenia spectrum disorders, which occur in around 30% of adults with 22q11DS. Using innovative computational connectomics, we studied how 22q11DS affects high-level network signatures of hierarchical modularity and its intrinsic geometry in 55 children with confirmed 22q11DS and 27 Typically Developing (TD) children. Results identified 3 subgroups within our 22q11DS sample using a K-means clustering approach based on several midline structural measures-of-interests. Each subgroup exhibited distinct patterns of connectome abnormalities. Subtype 1, containing individuals with generally healthy-looking brains, exhibited no significant differences in either modularity or intrinsic geometry when compared with TD. By contrast, the more anomalous 22q11DS Subtypes 2 and 3 brains revealed significant modular differences in the right hemisphere, while Subtype 3 (the most anomalous anatomy) further exhibited significantly abnormal connectome intrinsic geometry in the form of left-right temporal disintegration. Taken together, our findings supported an overall picture of (a) anterior-posteriorly differential interlobar frontotemporal/frontoparietal dysconnectivity in Subtypes 2 and 3 and (b) differential intralobar dysconnectivity in Subtype 3. Our ongoing studies are focusing on whether these subtypes and their connnectome signatures might be valid biomarkers for predicting the degree of psychosis-proneness risk found in 22q11DS. Hum Brain Mapp 39:232-248, 2018. © 2017 Wiley Periodicals, Inc.

Youth with perinatally-acquired HIV (PHIV) experience specific and global cognitive deficits at increased rates compared to typically-developing HIV-uninfected youth. In youth with PHIV, HIV infects the brain early in development. Neuroimaging studies have demonstrated altered grey matter morphometry in youth with PHIV compared to typically-developing youth. This study examined cortical thickness, surface area, and gyrification of grey matter in youth (age 11-20 years old) with PHIV (n = 40) from the Pediatric HIV/AIDS Cohort Study (PHACS) compared to typically-developing presumed HIV uninfected and unexposed youth (n = 80) from the Pediatric Imaging, Neurocognition and Genetics Study (PING) using structural magnetic resonance imaging. This study also examined the relationship between grey matter morphometry and age. Youth with PHIV had reduced cortical thickness, surface area, and gyrification compared to typically-developing youth. In addition, an inverse relationship between age and grey matter volume was found in typically-developing youth, but was not observed in youth with PHIV. Longitudinal studies are necessary to understand the neurodevelopmental trajectory of youth with PHIV.