Electroconvulsive therapy mediates neuroplasticity of white matter microstructure in major depression.

Whether plasticity of white matter (WM) microstructure relates to therapeutic response in major depressive disorder (MDD) remains uncertain. We examined diffusion tensor imaging (DTI) correlates of WM structural connectivity in patients receiving electroconvulsive therapy (ECT), a rapidly acting treatment for severe MDD. Tract-Based Spatial Statistics (TBSS) applied to DTI data (61 directions, 2.5 mm(3) voxel size) targeted voxel-level changes in fractional anisotropy (FA), and radial (RD), axial (AD) and mean diffusivity (MD) in major WM pathways in MDD patients (n=20, mean age: 41.15 years, 10.32 s.d.) scanned before ECT, after their second ECT and at transition to maintenance therapy. Comparisons made at baseline with demographically similar controls (n=28, mean age: 39.42 years, 12.20 s.d.) established effects of diagnosis. Controls were imaged twice to estimate scanning-related variance. Patients showed significant increases of FA in dorsal fronto-limbic circuits encompassing the anterior cingulum, forceps minor and left superior longitudinal fasciculus between baseline and transition to maintenance therapy (P<0.05, corrected). Decreases in RD and MD were observed in overlapping regions and the anterior thalamic radiation (P<0.05, corrected). Changes in DTI metrics associated with therapeutic response in tracts showing significant ECT effects differed between patients and controls. All measures remained stable across time in controls. Altered WM microstructure in pathways connecting frontal and limbic areas occur in MDD, are modulated by ECT and relate to therapeutic response. Increased FA together with decreased MD and RD, which trend towards normative values with treatment, suggest increased fiber integrity in dorsal fronto-limbic pathways involved in mood regulation

Early structural brain development in infants exposed to HIV and antiretroviral therapy in utero in a South African birth cohort

INTRODUCTION: There is a growing population of children who are HIV-exposed and uninfected (HEU) with the successful expansion of antiretroviral therapy (ART) use in pregnancy. Children who are HEU are at risk of delayed neurodevelopment; however, there is limited research on early brain growth and maturation. We aimed to investigate the effects of in utero exposure to HIV/ART on brain structure of infants who are HEU compared to HIV-unexposed (HU). METHODS: Magnetic resonance imaging using a T2-weighted sequence was undertaken in a subgroup of infants aged 2–6 weeks enrolled in the Drakenstein Child Health Study birth cohort, South Africa, between 2012 and 2015. Mother–child pairs received antenatal and postnatal HIV testing and ART per local guidelines. We compared subcortical and total grey matter volumes between HEU and HU groups using multivariable linear regression adjusting for infant age, sex, intracranial volume and socio-economic variables. We further assessed associations between brain volumes with maternal CD4 cell count and ART exposure. RESULTS: One hundred forty-six infants (40 HEU; 106 HU) with high-resolution images were included in this analysis (mean age 3 weeks; 50.7% male). All infants who were HEU were exposed to ART (88% maternal triple ART). Infants who were HEU had smaller caudate volumes bilaterally (5.4% reduction, p 0.2). Total grey matter volume was also reduced in infants who were HEU (2.1% reduction, p < 0.05). Exploratory analyses showed that low maternal CD4 cell count (<350 cells/mm3) was associated with decreased infant grey matter volumes. There was no relationship between timing of ART exposure and grey matter volumes. CONCLUSIONS: Lower caudate and total grey matter volumes were found in infants who were HEU compared to HU in the first weeks of life, and maternal immunosuppression was associated with reduced volumes. These findings suggest that antenatal HIV exposure may impact early structural brain development and improved antenatal HIV management may have the potential to optimize neurodevelopmental outcomes of children who are HEU

Broad white matter impairment in multiple system atrophy.

Multiple system atrophy (MSA) is a rare neurodegenerative disorder characterized by the widespread aberrant accumulation of α-synuclein (α-syn). MSA differs from other synucleinopathies such as Parkinson's disease (PD) in that α-syn accumulates primarily in oligodendrocytes, the only source of white matter myelination in the brain. Previous MSA imaging studies have uncovered focal differences in white matter. Here, we sought to build on this work by taking a global perspective on whole brain white matter. In order to do this, in vivo structural imaging and diffusion magnetic resonance imaging were acquired on 26 MSA patients, 26 healthy controls, and 23 PD patients. A refined whole brain approach encompassing the major fiber tracts and the superficial white matter located at the boundary of the cortical mantle was applied. The primary observation was that MSA but not PD patients had whole brain deep and superficial white matter diffusivity abnormalities (p < .001). In addition, in MSA patients, these abnormalities were associated with motor (Unified MSA Rating Scale, Part II) and cognitive functions (Mini-Mental State Examination). The pervasive whole brain abnormalities we observe suggest that there is widespread white matter damage in MSA patients which mirrors the widespread aggregation of α-syn in oligodendrocytes. Importantly, whole brain white matter abnormalities were associated with clinical symptoms, suggesting that white matter impairment may be more central to MSA than previously thought

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology

We predicted residual fluid intelligence scores from T1-weighted MRI data available as part of the ABCD NP Challenge 2019, using morphological similarity of grey-matter regions across the cortex. Individual structural covariance networks (SCN) were abstracted into graph-theory metrics averaged over nodes across the brain and in data-driven communities/modules. Metrics included degree, path length, clustering coefficient, centrality, rich club coefficient, and small-worldness. These features derived from the training set were used to build various regression models for predicting residual fluid intelligence scores, with performance evaluated both using cross-validation within the training set and using the held-out validation set. Our predictions on the test set were generated with a support vector regression model trained on the training set. We found minimal improvement over predicting a zero residual fluid intelligence score across the sample population, implying that structural covariance networks calculated from T1-weighted MR imaging data provide little information about residual fluid intelligence.Comment: 8 pages plus references, 3 figures, 2 tables. Submission to the ABCD Neurocognitive Prediction Challenge at MICCAI 201

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression

We applied several regression and deep learning methods to predict fluid intelligence scores from T1-weighted MRI scans as part of the ABCD Neurocognitive Prediction Challenge (ABCD-NP-Challenge) 2019. We used voxel intensities and probabilistic tissue-type labels derived from these as features to train the models. The best predictive performance (lowest mean-squared error) came from Kernel Ridge Regression (KRR; $\lambda=10$), which produced a mean-squared error of 69.7204 on the validation set and 92.1298 on the test set. This placed our group in the fifth position on the validation leader board and first place on the final (test) leader board.Comment: Winning entry in the ABCD Neurocognitive Prediction Challenge at MICCAI 2019. 7 pages plus references, 3 figures, 1 tabl

Brain size and brain/intracranial volume ratio in major mental illness

<p>Abstract</p> <p>Background</p> <p>This paper summarizes the findings of a long term study addressing the question of how several brain volume measure are related to three major mental illnesses in a Colorado subject group. It reports results obtained from a large N, collected and analyzed by the same laboratory over a multiyear period, with visually guided MRI segmentation being the primary initial analytic tool.</p> <p>Methods</p> <p>Intracerebral volume (ICV), total brain volume (TBV), ventricular volume (VV), ventricular/brain ratio (VBR), and TBV/ICV ratios were calculated from a total of 224 subject MRIs collected over a period of 13 years. Subject groups included controls (C, N = 89), and patients with schizophrenia (SZ, N = 58), bipolar disorder (BD, N = 51), and schizoaffective disorder (SAD, N = 26).</p> <p>Results</p> <p>ICV, TBV, and VV measures compared favorably with values obtained by other research groups, but in this study did not differ significantly between groups. TBV/ICV ratios were significantly decreased, and VBR increased, in the SZ and BD groups compared to the C group. The SAD group did not differ from C on any measure.</p> <p>Conclusions</p> <p>In this study TBV/ICV and VBR ratios separated SZ and BD patients from controls. Of interest however, SAD patients did not differ from controls on these measures. The findings suggest that the gross measure of TBV may not reliably differ in the major mental illnesses to a degree useful in diagnosis, likely due to the intrinsic variability of the measures in question; the differences in VBR appear more robust across studies. Differences in some of these findings compared to earlier reports from several laboratories finding significant differences between groups in VV and TBV may relate to phenomenological drift, differences in analytic techniques, and possibly the "file drawer problem".</p

Basal ganglia correlates of fatigue in young adults

Although the prevalence of chronic fatigue is approximately 20% in healthy individuals, there are no studies of brain structure that elucidate the neural correlates of fatigue outside of clinical subjects. We hypothesized that fatigue without evidence of disease might be related to changes in the basal ganglia and prefrontal cortex and be implicated in fatigue with disease. We aimed to identify the white matter structures of fatigue in young subjects without disease using magnetic resonance imaging (MRI). Healthy young adults (n = 883; 489 males and 394 females) were recruited. As expected, the degrees of fatigue and motivation were associated with larger mean diffusivity (MD) in the right putamen, pallidus and caudate. Furthermore, the degree of physical activity was associated with a larger MD only in the right putamen. Accordingly, motivation was the best candidate for widespread basal ganglia, whereas physical activity might be the best candidate for the putamen. A plausible mechanism of fatigue may involve abnormal function of the motor system, as well as areas of the dopaminergic system in the basal ganglia that are associated with motivation and reward

Differential Brain Development with Low and High IQ in Attention-Deficit/Hyperactivity Disorder

Attention-Deficit/Hyperactivity Disorder (ADHD) and intelligence (IQ) are both heritable phenotypes. Overlapping genetic effects have been suggested to influence both, with neuroimaging work suggesting similar overlap in terms of morphometric properties of the brain. Together, this evidence suggests that the brain changes characteristic of ADHD may vary as a function of IQ. This study investigated this hypothesis in a sample of 108 children with ADHD and 106 typically developing controls, who participated in a cross-sectional anatomical MRI study. A subgroup of 64 children also participated in a diffusion tensor imaging scan. Brain volumes, local cortical thickness and average cerebral white matter microstructure were analyzed in relation to diagnostic group and IQ. Dimensional analyses investigated possible group differences in the relationship between anatomical measures and IQ. Second, the groups were split into above and below median IQ subgroups to investigate possible differences in the trajectories of cortical development. Dimensionally, cerebral gray matter volume and cerebral white matter microstructure were positively associated with IQ for controls, but not for ADHD. In the analyses of the below and above median IQ subgroups, we found no differences from controls in cerebral gray matter volume in ADHD with below-median IQ, but a delay of cortical development in a number of regions, including prefrontal areas. Conversely, in ADHD with above-median IQ, there were significant reductions from controls in cerebral gray matter volume, but no local differences in the trajectories of cortical development

Adiposity is Associated with Regional Cortical Thinning

BACKGROUND: Although obesity is associated with structural changes in brain grey matter, findings have been inconsistent and the precise nature of these changes is unclear. Inconsistencies may partly be due to the use of different volumetric morphometry methods, and the inclusion of participants with comorbidities that exert independent effects on brain structure. The latter concern is particularly critical when sample sizes are modest. The purpose of the current study was to examine the relationship between cortical grey matter and body mass index (BMI), in healthy participants, excluding confounding comorbidities and using a large sample size. SUBJECTS: A total of 202 self-reported healthy volunteers were studied using surface-based morphometry, which permits the measurement of cortical thickness, surface area and cortical folding, independent of each other. RESULTS: Although increasing BMI was not associated with global cortical changes, a more precise, region-based analysis revealed significant thinning of the cortex in two areas: left lateral occipital cortex (LOC) and right ventromedial prefrontal cortex (vmPFC). An analogous region-based analysis failed to find an association between BMI and regional surface area or folding. Participants' age was also found to be negatively associated with cortical thickness of several brain regions; however, there was no overlap between the age- and BMI-related effects on cortical thinning. CONCLUSIONS: Our data suggest that the key effect of increasing BMI on cortical grey matter is a focal thinning in the left LOC and right vmPFC. Consistent implications of the latter region in reward valuation, and goal control of decision and action suggest a possible shift in these processes with increasing BMI.We thank all the participants and the staff of the Wolfson Brain Imaging Centre. This work was supported by the Bernard Wolfe Health Neuroscience Fund (NM, HZ, ISF, PCF), the Wellcome Trust (RGAG/144 to N.M, RGAG/188 to ISF, RNAG/259 to PCF) and the Medical Research Council (G0701497 to KDE).This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ijo.2016.42

Cerebral Blood Flow during Rest Associates with General Intelligence and Creativity

Recently, much scientific attention has been focused on resting brain activity and its investigation through such methods as the analysis of functional connectivity during rest (the temporal correlation of brain activities in different regions). However, investigation of the magnitude of brain activity during rest has focused on the relative decrease of brain activity during a task, rather than on the absolute resting brain activity. It is thus necessary to investigate the association between cognitive factors and measures of absolute resting brain activity, such as cerebral blood flow (CBF), during rest (rest-CBF). In this study, we examined this association using multiple regression analyses. Rest-CBF was the dependent variable and the independent variables included two essential components of cognitive functions, psychometric general intelligence and creativity. CBF was measured using arterial spin labeling and there were three analyses for rest-CBF; namely mean gray matter rest-CBF, mean white matter rest-CBF, and regional rest-CBF. The results showed that mean gray and white matter rest-CBF were significantly and positively correlated with individual psychometric intelligence. Furthermore, mean white matter rest-CBF was significantly and positively correlated with creativity. After correcting the effect of mean gray matter rest-CBF the significant and positive correlation between regional rest-CBF in the perisylvian anatomical cluster that includes the left superior temporal gyrus and insula and individual psychometric intelligence was found. Also, regional rest-CBF in the precuneus was significantly and negatively correlated with individual creativity. Significance of these results of regional rest-CBF did not change when the effect of regional gray matter density was corrected. The findings showed mean and regional rest-CBF in healthy young subjects to be correlated with cognitive functions. The findings also suggest that, even in young cognitively intact subjects, resting brain activity (possibly underlain by default cognitive activity or metabolic demand from developed brain structures) is associated with cognitive functions