Attention enhances category representations across the brain with strengthened residual correlations to ventral temporal cortex

How does attention enhance neural representations of goal-relevant stimuli while suppressing representations of ignored stimuli across regions of the brain? While prior studies have shown that attention enhances visual responses, we lack a cohesive understanding of how selective attention modulates visual representations across the brain. Here, we used functional magnetic resonance imaging (fMRI) while participants performed a selective attention task on superimposed stimuli from multiple categories and used a data-driven approach to test how attention affects both decodability of category information and residual correlations (after regressing out stimulus-driven variance) with category-selective regions of ventral temporal cortex (VTC). Our data reveal three main findings. First, when two objects are simultaneously viewed, the category of the attended object can be decoded more readily than the category of the ignored object, with the greatest attentional enhancements observed in occipital and temporal lobes. Second, after accounting for the response to the stimulus, the correlation in the residual brain activity between a cortical region and a category-selective region of VTC was elevated when that region's preferred category was attended vs. ignored, and more so in the right occipital, parietal, and frontal cortices. Third, we found that the stronger the residual correlations between a given region of cortex and VTC, the better visual category information could be decoded from that region. These findings suggest that heightened residual correlations by selective attention may reflect the sharing of information between sensory regions and higher-order cortical regions to provide attentional enhancement of goal-relevant information.

Are the Items of the Starkstein Apathy Scale Fit for the Purpose of Measuring Apathy Post-stroke?

Importance: Given the importance of apathy for stroke, we felt it was time to scrutinize the psychometric properties of the commonly used Starkstein Apathy Scale (SAS) for this purpose.Objectives: The objectives were to: (i) estimate the extent to which the SAS items fit a hierarchical continuum of the Rasch Model; and (ii) estimate the strength of the relationships between the Rasch analyzed SAS and converging constructs related to stroke outcomes.Methods: Data was from a clinical trial of a community-based intervention targeting participation. A total of 857 SAS questionnaires were completed by 238 people with stroke from up to 5 time points. SAS has 14 items, rated on a 4-point scale with higher values indicating more apathy. Psychometric properties were tested using Rasch partial-credit model, correlation, and regression. Items were rescored so higher scores are interpreted as lower apathy levels.Results: Rasch analysis indicated that the response options were disordered for 8/14 items, pointing to unreliability in the interpretation of the response options; they were consequently reduced from 4 to 3. Only 9/14 items fit the Rasch model and therefore suitable for creating a total score. The new rSAS was deemed unidimensional (residual correlations: < 0.3), reasonably reliable (person separation index: 0.74), with item-locations uniform across time, age, sex, and education. However, 30% of scores were > 2 SD above the standardized mean but only 2/9 items covered this range (construct mistargeting). Apathy (rSAS/SAS) was correlated weakly with anxiety/depression and uncorrelated with physical capacity. Regression showed that the effect of apathy on participation and health perception was similar for rSAS/SAS versions: R2 participation measures ranged from 0.11 to 0.29; R2 for health perception was ∼0.25. When placed on the same scale (0–42), rSAS value was 6.5 units lower than SAS value with minimal floor/ceiling effects. Estimated change over time was identical (0.12 units/month) which was not substantial (1.44 units/year) but greater than expected assuming no change (t: 3.6 and 2.4).Conclusion: The retained items of the rSAS targeted domains of behaviors more than beliefs and results support the rSAS as a robust measure of apathy in people with chronic stroke.

Are the Items of the Starkstein Apathy Scale Fit for the Purpose of Measuring Apathy Post-Stroke?

Given the importance of apathy for stroke, we felt it was time to scrutinize the commonly used Starkstein Apathy Scale (SAS) for psychometric evidence that it is fit for this purpose. The objectives were to: (i) estimate the extent to which the SAS items fit a hierarchical continuum of the Rasch Model; and (ii) estimate the strength of the relationships between the Rasch analysed SAS and converging constructs related to stroke outcomes. Methods Data on 238 people with stroke (mean age=63.1 years (SD=12.1) women=37.4%) from a clinical trial of a community-based intervention targeting participation were available at 5 time points yielding 856 SAS questionnaires. SAS has 14 items, rated on a 4-point scale with higher values indicating more apathy. Psychometric properties were tested using Rasch partial-credit model, correlation, and regression. The construct was modeled as motivation with items rescored as high is better. Results Rasch analysis indicated that the response options were disordered for 8/14 items, pointing to unreliability in the interpretation of the response options; they were consequently reduced from 4 to 3. Only 9/14 items fit the Rasch model and therefore suitable for creating a total score. The new rSAS was deemed unidimensional (residual correlations: < 0.3), reasonably reliable (person separation index: 0.74), with item-locations uniform across time, age, sex, and education. However, 30% of scores were >2 SD above the standardized mean but only 2/9 items covered this range (construct mistargeting). Apathy (rSAS/SAS) was correlated weakly with anxiety/depression and uncorrelated with physical capacity. Regression showed that the effect of apathy on participation and health perception was similar for rSAS/SAS versions: R2 participation measures ranged from 0.11 to 0.29; R2 for health perception was ~0.25. When placed on the same scale (0-42), rSAS value was 6.5 units lower than SAS value with minimal floor/ceiling effects. Estimated change over time was identical (0.12 units/month) which was not substantial (1.44 units/year) but greater than expected assuming no change (t: 3.6 and 2.4). Conclusion The retained items of the rSAS targeted behaviours more than beliefs and results support the rSAS as a robust measure of apathy in people with chronic stroke.

Affective structure, measurement invariance, and reliability across different experience sampling protocols

While measures of affect are often included in studies using experience sampling methodology (ESM), the affective structure at the between- and within-person level has not been thoroughly investigated. Additionally, it is currently unclear to what extent this structure is influenced by variations in sampling protocols. Our first aim was to investigate the structure of affect at the between- and within-person level when measured with 8 or 18 affect items. Second, we investigated the invariance of this structure across different sampling frequencies and questionnaire lengths. Further, the reliability of positive and negative affect (PA and NA, respectively) was calculated. Participants (N = 163) were randomly assigned to receive either a 30 or 60 item questionnaire three, six, or nine times per day over 14 days. Momentary affect was assessed with 8 or 18 items. At both levels, a two-factor structure with correlated PA and NA showed the best fit compared to an orthogonal and a unidimensional model. However, the CFAs and additional EFAs indicated that items shared additional variance that could be accounted for by freeing residual correlations or adding more nuanced affect factors to achieve acceptable fit. A structure accounting for these additional relationships was invariant across different sampling protocols at the within-person level and resulted in high reliability. We observed differences between levels in the strength of the loadings, the correlation between PA and NA, and the number of factors suggested in EFAs. Taken together, these structural differences indicate a more discrete affective structure within than between persons

Comparison between instrumental variable and mediation-based methods for reconstructing causal gene networks in yeast

Causal gene networks model the flow of information within a cell. Reconstructing causal networks from omics data is challenging because correlation does not imply causation. When genomics and transcriptomics data from a segregating population are combined, genomic variants can be used to orient the direction of causality between gene expression traits. Instrumental variable methods use a local expression quantitative trait locus (eQTL) as a randomized instrument for a gene’s expression level, and assign target genes based on distal eQTL associations. Mediation-based methods additionally require that distal eQTL associations are mediated by the source gene. A detailed comparison between these methods has not yet been conducted, due to the lack of a standardized implementation of different methods, the limited sample size of most multi-omics datasets, and the absence of ground-truth networks for most organisms. Here we used Findr, a software package providing uniform implementations of instrumental variable, mediation, and coexpression-based methods, a recent dataset of 1,012 segregants from a cross between two budding yeast strains, and the YEASTRACT database of known transcriptional interactions to compare causal gene network inference methods. We found that causal inference methods result in a significant overlap with the ground-truth, whereas coexpression did not perform better than random. A subsampling analysis revealed that the performance of mediation saturates at large sample sizes, due to a loss of sensitivity when residual correlations become significant. Instrumental variable methods on the other hand contain false positive predictions, due to genomic linkage between eQTL instruments. Instrumental variable and mediation-based methods also have complementary roles for identifying causal genes underlying transcriptional hotspots. Instrumental variable methods correctly predicted STB5 targets for a hotspot centred on the transcription factor STB5, whereas mediation failed due to Stb5p auto-regulating its own expression. Mediation suggests a new candidate gene, DNM1, for a hotspot on Chr XII, whereas instrumental variable methods could not distinguish between multiple genes located within the hotspot. In conclusion, causal inference from genomics and transcriptomics data is a powerful approach for reconstructing causal gene networks, which could be further improved by the development of methods to control for residual correlations in mediation analyses and genomic linkage and pleiotropic effects from transcriptional hotspots in instrumental variable analyses.

Basic Values Survey (BVS) - A 20-nation validation study

The present paper tests the structure and invariance of the Functional Theory of Human Values across 20 countries (N = 21,362). This theory proposes that values have the functions of guiding behaviour and expressing needs. The interplay between these two functions produces six subfunctions that in turn produce distinct content. These subfunctions are operationalised in the Basic Values Survey with three items each, forming an 18-item measure. Although this measure has been used for more than two decades, studies examining its psychometric properties in multiple-group data are scarce. Using multidimensional scaling (MDS), it was found that values were organised in a bidimensional space according to the hypothesised degree of congruence between subfunctions. Also, Confirmatory Factor Analysis (CFA) with a Bayes estimator and approximate zero cross-loadings and residual correlations supported the six-factor structure. A strict CFA with Robust-ML estimator did not support the model. Metric invariance was supported for all the items, except religiosity, using the alignment method and approximate Bayesian invariance.

A Dyadic Growth Modeling Approach for Examining Associations Between Weight Gain and Lung Function Decline

The relationship between body weight and lung function is complex. Using a dyadic multilevel linear modeling approach, treating body mass index (BMI; weight (kg)/height (m)2) and lung function as paired, within-person outcomes, we tested the hypothesis that persons with more rapid increase in BMI exhibit more rapid decline in lung function, as measured by forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), and their ratio (FEV1:FVC). Models included random intercepts and slopes and adjusted for sociodemographic and smoking-related factors. A sample of 9,115 adults with paired measurements of BMI and lung function taken at ≥3 visits were selected from a pooled set of 5 US population-based cohort studies (1983–2018; mean age at baseline = 46 years; median follow-up, 19 years). At age 46 years, average annual rates of change in BMI, FEV1, FVC, and FEV1:FVC ratio were 0.22 kg/m2/year, −25.50 mL/year, −21.99 mL/year, and −0.24%/year, respectively. Persons with steeper BMI increases had faster declines in FEV1 (r = −0.16) and FVC (r = −0.26) and slower declines in FEV1:FVC ratio (r = 0.11) (all P values &lt; 0.0001). Results were similar in subgroup analyses. Residual correlations were negative (P &lt; 0.0001), suggesting additional interdependence between BMI and lung function. Results show that greater rates of weight gain are associated with greater rates of lung function loss.

The transpeptidase PBP2 governs initial localization and activity of the major cell-wall synthesis machinery in E. coli

Bacterial shape is physically determined by the peptidoglycan cell wall. The cell-wall-synthesis machinery responsible for rod shape in Escherichia coli is the processive 'Rod complex'. Previously, cytoplasmic MreB filaments were thought to govern formation and localization of Rod complexes based on local cell-envelope curvature. Using single-particle tracking of the transpeptidase and Rod-complex component PBP2, we found that PBP2 binds to a substrate different from MreB. Depletion and localization experiments of other putative Rod-complex components provide evidence that none of those provide the sole rate-limiting substrate for PBP2 binding. Consistently, we found only weak correlations between MreB and envelope curvature in the cylindrical part of cells. Residual correlations do not require curvature-based Rod-complex initiation but can be attributed to persistent rotational motion. We therefore speculate that the local cell-wall architecture provides the cue for Rod-complex initiation, either through direct binding by PBP2 or through an unknown intermediate.

Transpeptidase PBP2 governs initial localization and activity of major cell-wall synthesis machinery in Escherichia coli

Bacterial shape is physically determined by the peptidoglycan cell wall. The cell-wall-synthesis machinery responsible for rod shape in Escherichia coli is the processive ‘Rod complex’. Previously, cytoplasmic MreB filaments were thought to govern formation and localization of Rod complexes based on local cell-envelope curvature. However, using single-particle tracking of the transpeptidase PBP2, we found strong evidence that PBP2 initiates new Rod complexes by binding to a substrate different from MreB or any known Rod-complex component. This substrate is likely the cell wall. Consistently, we found only weak correlations between MreB and envelope curvature in the cylindrical part of cells. Residual correlations do not require any curvature-based Rod-complex initiation but can be attributed to persistent rotational motion. Therefore, local cell-wall architecture likely provides the cue for PBP2 binding and subsequent Rod-complex initiation. We also found that PBP2 has a limiting role for Rod-complex activity, thus supporting its central role.