Reaction Time Variability in Children Is Specifically Associated With Attention Problems and Regional White Matter Microstructure

Background Increased intraindividual variability (IIV) in reaction times (RTs) has been suggested as a key cognitive and behavioral marker of attention problems, but findings for other dimensions of psychopathology are less consistent. Moreover, while studies have linked IIV to brain white matter microstructure, large studies testing the robustness of these associations are needed. Methods We used data from the Adolescent Brain Cognitive Development (ABCD) Study baseline assessment to test the associations between IIV and psychopathology (n = 8622, age = 8.9–11.1 years) and IIV and white matter microstructure (n = 7958, age = 8.9–11.1 years). IIV was investigated using an ex-Gaussian distribution analysis of RTs in correct response go trials in the stop signal task. Psychopathology was measured by the Child Behavior Checklist and a bifactor structural equation model was performed to extract a general p factor and specific factors reflecting internalizing, externalizing, and attention problems. To investigate white matter microstructure, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity were examined in 23 atlas-based tracts. Results Increased IIV in both short and long RTs was positively associated with the specific attention problems factor (Cohen’s d = 0.13 and d = 0.15, respectively). Increased IIV in long RTs was also positively associated with radial diffusivity in the left and right corticospinal tract (both tracts, d = 0.12). Conclusions Using a large sample and a data-driven dimensional approach to psychopathology, the results provide novel evidence for a small but specific association between IIV and attention problems in children and support previous findings on the relevance of white matter microstructure for IIV.publishedVersio

The Interplay of Sleep, Cognitive Control and Brain Connectivity from a Graph Theoretical Perspective

Sleep deprivation (SD) has severe negative effects on health and is a widespread problem in society. However, how it affects cognition, and in particular, cognitive control and the brain, is less well understood. This study sought to elucidate the interplay of sleep duration, cognitive control and brain connectivity. In order to investigate this, 17 participants underwent diffusion weighted imaging (DWI), performed a stop-signal task (SST) and wore actigraphs for two weeks. The DWIs were analysed with atlas-based deterministic tractography, and the obtained connectivity matrices were then analysed with a graph theoretical approach to assess brain connectivity. While it was predicted that short sleep duration would be positively correlated with attention, performance monitoring and global efficiency, no such correlations were identified. However, higher global efficiency was found to be associated with longer reaction times on go trials. Results further indicated a positive relationship between stop signal reaction times (SSRTs) and local efficiencies of right inferior frontal gyrus pars opercularis and right supplementary motor area/pre-supplementary motor area. Lastly, as predicted, post-error slowing and post-stop slowing were both found to positively correlate with local efficiency of left anterior cingulate cortex. The somewhat unexpected results can be explained by the small, homogenous sample, although the latter results and the identified small-worldness implies that the analysis itself was successfully applied. Thus, this study provides useful insight into how a graph theoretical approach can be applied in order to assess sleep, cognitive control and brain connectivity in a healthy sample and encourages further research with a comparable approach

On the (un)reliability of common behavioral and electrophysiological measures from the stop signal task: Measures of inhibition lack stability over time.

Response inhibition, the intentional stopping of planned or initiated actions, is often considered a key facet of control, impulsivity, and self-regulation. The stop signal task is argued to be the purest inhibition task we have, and it is thus central to much work investigating the role of inhibition in areas like development and psychopathology. Most of this work quantifies stopping behavior by calculating the stop signal reaction time as a measure of individual stopping latency. Individual difference studies aiming to investigate why and how stopping latencies differ between people often do this under the assumption that the stop signal reaction time indexes a stable, dispositional trait. However, empirical support for this assumption is lacking, as common measures of inhibition and control tend to show low test-retest reliability and thus appear unstable over time. The reasons for this could be methodological, where low stability is driven by measurement noise, or substantive, where low stability is driven by a larger influence of state-like and situational factors. To investigate this, we characterized the split-half and test-retest reliability of a range of common behavioral and electrophysiological measures derived from the stop signal task. Across three independent studies, different measurement modalities, and a systematic review of the literature, we found a pattern of low temporal stability for inhibition measures and higher stability for measures of manifest behavior and non-inhibitory processing. This pattern could not be explained by measurement noise and low internal consistency. Consequently, response inhibition appears to have mostly state-like and situational determinants, and there is little support for the validity of conceptualizing common inhibition measures as reflecting stable traits

On the (un)reliability of common behavioral and electrophysiological measures from the stop signal task: Measures of inhibition lack stability over time. Data and analysis scripts.

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Puberty differentially predicts brain maturation in males and females during early adolescence: A longitudinal ABCD Study

Abstract Background Research has demonstrated associations between pubertal development and brain maturation. However, existing studies have been limited by small samples, cross-sectional designs, and inconclusive findings regarding coupling directionality and sex differences. Methods We examined the longitudinal temporal coupling of puberty status assessed using the Pubertal Development Scale (PDS) and magnetic resonance imaging (MRI)-based brain grey and white matter structure. Our sample consisted of 8,896 children and adolescents at baseline (mean age = 9.9) and 6,099 at follow-up (mean age = 11.9) from the Adolescent Brain and Cognitive Development (ABCD) Study. Results Applying multigroup Bivariate Latent Change Score (BLCS) models, we found that baseline pubertal status predicted the rate of change in cortical thickness among females only, while it predicted rate of change in cortical surface area for both males and females, with a significantly stronger association for females. For cortical surface area, we also found a correlation between baseline pubertal status and area and co-occurring changes over time, with both associations present in males only. Diffusion tensor imaging (DTI) analysis revealed correlated change between pubertal status and fractional anisotropy (FA) for both males and females, but no significant associations for mean diffusivity (MD). Conclusions Our results suggest that pubertal status in early adolescence predicts cortical maturation, and that the strength of the associations differ between sex. Further research is needed to understand how the associations between puberty and brain maturation are related to environmental and lifestyle factors, and the impact on mental health