Associations between repetitive negative thinking and resting-state network segregation among healthy middle-aged adults

Background: Repetitive Negative Thinking (RNT) includes negative thoughts about the future and past, and is a risk factor for depression and anxiety. Prefrontal and anterior cingulate cortices have been linked to RNT but several regions within large-scale networks are also involved, the efficiency of which depends on their ability to remain segregated. Methods: Associations between RNT and system segregation (SyS) of the Anterior Salience Network (ASN), Default Mode Network (DMN) and Executive Control Network (ECN) were explored in healthy middle-aged adults (N = 341), after undergoing resting-state functional magnetic resonance imaging. Regression analyses were conducted with RNT as outcome variable. Explanatory variables were: SyS, depression, emotional stability, cognitive complaints, age and sex. Results: Analyses indicated that RNT was associated with depression, emotional stability, cognitive complaints, age and segregation of the left ECN (LECN) and ASN. Further, the ventral DMN (vDMN) presented higher connectivity with the ASN and decreased connectivity with the LECN, as a function of RNT. Conclusion: Higher levels of perseverative thinking were related to increased segregation of the LECN and decreased segregation of the ASN. The dissociative connectivity of these networks with the vDMN may partially account for poorer cognitive control and increased self-referential processes characteristic of RNT

COVID-19 after two years: trajectories of different components of mental health in the Spanish population

Abstract Aims Our study aimed to (1) identify trajectories on different mental health components during a two-year follow-up of the COVID-19 pandemic and contextualise them according to pandemic periods; (2) investigate the associations between mental health trajectories and several exposures, and determine whether there were differences among the different mental health outcomes regarding these associations. Methods We included 5535 healthy individuals, aged 40–65 years old, from the Barcelona Brain Health Initiative (BBHI). Growth mixture models (GMM) were fitted to classify individuals into different trajectories for three mental health-related outcomes (psychological distress, personal growth and loneliness). Moreover, we fitted a multinomial regression model for each outcome considering class membership as the independent variable to assess the association with the predictors. Results For the outcomes studied we identified three latent trajectories, differentiating two major trends, a large proportion of participants was classified into ‘resilient’ trajectories, and a smaller proportion into ‘chronic-worsening’ trajectories. For the former, we observed a lower susceptibility to the changes, whereas, for the latter, we noticed greater heterogeneity and susceptibility to different periods of the pandemic. From the multinomial regression models, we found global and cognitive health, and coping strategies as common protective factors among the studied mental health components. Nevertheless, some differences were found regarding the risk factors. Living alone was only significant for those classified into ‘chronic’ trajectories of loneliness, but not for the other outcomes. Similarly, secondary or higher education was only a risk factor for the ‘worsening’ trajectory of personal growth. Finally, smoking and sleeping problems were risk factors which were associated with the ‘chronic’ trajectory of psychological distress. Conclusions Our results support heterogeneity in reactions to the pandemic and the need to study different mental health-related components over a longer follow-up period, as each one evolves differently depending on the pandemic period. In addition, the understanding of modifiable protective and risk factors associated with these trajectories would allow the characterisation of these segments of the population to create targeted interventions

Diagnosis of prodromal and Alzheimer's disease dementia in adults with Down syndrome using neuropsychological tests

We aimed to define prodromal Alzheimer's disease (AD) and AD dementia using normative neuropsychological data in a large population-based cohort of adults with Down syndrome (DS). Cross-sectional study. DS participants were classified into asymptomatic, prodromal AD and AD dementia, based on neurologist's judgment blinded to neuropsychological data (Cambridge Cognitive Examination for Older Adults with Down's syndrome [CAMCOG-DS] and modified Cued Recall Test [mCRT]). We compared the cutoffs derived from the normative data in young adults with DS to those from receiver-operating characteristic curve (ROC) analysis. Diagnostic performance of the CAMCOG-DS and modified Cued Recall Test (mCRT) in subjects with mild and moderate levels of intellectual disability (ID) was high, both for diagnosing prodromal AD and AD dementia (area under the curve [AUC] 0.73-0.83 and 0.90-1, respectively). The cutoffs derived from the normative data were similar to those derived from the ROC analyses. Diagnosing prodromal AD and AD dementia in DS with mild and moderate ID using population norms for neuropsychological tests is possible with high diagnostic accuracy

Accuracy and reproducibility of automated white matter hyperintensities segmentation with lesion segmentation tool: A European multi-site 3T study

Brain vascular damage accumulate in aging and often manifest as white matter hyperintensities (WMHs) on MRI. Despite increased interest in automated methods to segment WMHs, a gold standard has not been achieved and their longitudinal reproducibility has been poorly investigated. The aim of present work is to evaluate accuracy and reproducibility of two freely available segmentation algorithms. A harmonized MRI protocol was implemented in 3T-scanners across 13 European sites, each scanning five volunteers twice (test-retest) using 2D-FLAIR. Automated segmentation was performed using Lesion segmentation tool algorithms (LST): the Lesion growth algorithm (LGA) in SPM8 and 12 and the Lesion prediction algorithm (LPA). To assess reproducibility, we applied the LST longitudinal pipeline to the LGA and LPA outputs for both the test and retest scans. We evaluated volumetric and spatial accuracy comparing LGA and LPA with manual tracing, and for reproducibility the test versus retest. Median volume difference between automated WMH and manual segmentations (mL) was −0.22[IQR = 0.50] for LGA-SPM8, −0.12[0.57] for LGA-SPM12, −0.09[0.53] for LPA, while the spatial accuracy (Dice Coefficient) was 0.29[0.31], 0.33[0.26] and 0.41[0.23], respectively. The reproducibility analysis showed a median reproducibility error of 20%[IQR = 41] for LGA-SPM8, 14% [31] for LGA-SPM12 and 10% [27] with the LPA cross-sectional pipeline. Applying the LST longitudinal pipeline, the reproducibility errors were considerably reduced (LGA: 0%[IQR = 0], p < 0.001; LPA: 0% [3], p < 0.001) compared to those derived using the cross-sectional algorithms. The DC using the longitudinal pipeline was excellent (median = 1) for LGA [IQR = 0] and LPA [0.02]. LST algorithms showed moderate accuracy and good reproducibility. Therefore, it can be used as a reliable cross-sectional and longitudinal tool in multi-site studies

Down-Regulation of Negative Emotional Processing by Transcranial Direct Current Stimulation: Effects of Personality Characteristics

Evidence from neuroimaging and electrophysiological studies indicates that the left dorsolateral prefrontal cortex (DLPFC) is a core region in emotional processing, particularly during down-regulation of negative emotional conditions. However, emotional regulation is a process subject to major inter-individual differences, some of which may be explained by personality traits. In the present study we used transcranial direct current stimulation (tDCS) over the left DLPFC to investigate whether transiently increasing the activity of this region resulted in changes in the ratings of positive, neutral and negative emotional pictures. Results revealed that anodal, but not cathodal, tDCS reduced the perceived degree of emotional valence for negative stimuli, possibly due to an enhancement of cognitive control of emotional expression. We also aimed to determine whether personality traits (extraversion and neuroticism) might condition the impact of tDCS. We found that individuals with higher scores on the introversion personality dimension were more permeable than extraverts to the modulatory effects of the stimulation. The present study underlines the role of the left DLPFC in emotional regulation, and stresses the importance of considering individual personality characteristics as a relevant variable, although replication is needed given the limited sample size of our study

Self-reported sleep relates to hippocampal atrophy across the adult lifespan: Results from the Lifebrain consortium

Contains fulltext : 218709.pdf (publisher's version ) (Open Access)Poor sleep is associated with multiple age-related neurodegenerative and neuropsychiatric conditions. The hippocampus plays a special role in sleep and sleep-dependent cognition, and accelerated hippocampal atrophy is typically seen with higher age. Hence, it is critical to establish how the relationship between sleep and hippocampal volume loss unfolds across the adult lifespan.Self-reported sleep measures and MRI-derived hippocampal volumes were obtained from 3105 cognitively normal participants (18-90 years) from major European brain studies in the Lifebrain consortium. Hippocampal volume change was estimated from 5116 MRIs from 1299 participants for whom longitudinal MRIs were available, followed up to 11 years with a mean interval of 3.3 years. Cross-sectional analyses were repeated in a sample of 21390 participants from the UK Biobank.No cross-sectional sleep - hippocampal volume relationships were found. However, worse sleep quality, efficiency, problems, and daytime tiredness were related to greater hippocampal volume loss over time, with high scorers showing 0.22% greater annual loss than low scorers. The relationship between sleep and hippocampal atrophy did not vary across age. Simulations showed that the observed longitudinal effects were too small to be detected as age-interactions in the cross-sectional analyses.Worse self-reported sleep is associated with higher rates of hippocampal volume decline across the adult lifespan. This suggests that sleep is relevant to understand individual differences in hippocampal atrophy, but limited effect sizes call for cautious interpretation.15 p