Prenatal stress and child externalizing behavior: effects of maternal perceived stress and cortisol are moderated by child sex

BACKGROUND

Externalizing behavior problems are related to social maladjustment. Evidence indicates associations between prenatal stress and child behavioral outcomes. It remains unclear how psychological distress vs. biological correlates of stress (cortisol) differentially predict externalizing behavior, and how their effects might differ as a function of child sex.

METHOD

108 pregnant women from the community collected salivary cortisol and reported their perceived stress during each trimester of pregnancy. At child age 9 years (M = 9.01, SD = 0.55), 70 mothers and children reported on child behavior. Structural equation modelling was used to analyze how cortisol levels and perceived stress during pregnancy predicted current child externalizing behavior, considering the moderating effect of child sex.

RESULTS

Perceived stress predicted higher externalizing behavior in boys (β = 0.42, p = 0.009) and lower externalizing behavior in girls (β = - 0.56, p = 0.014). Cortisol predicted lower externalizing behavior in boys (β = - 0.81, p < .001) and was not related to girls' externalizing behavior (β = 0.37, p = 0.200).

DISCUSSION/CONCLUSION

Prenatal stress affected externalizing behavior differently in girls vs. boys. These response patters in turn differed for indicators of psychological vs. biological maternal stress, encouraging an integrated approach. Findings indicate that perceived stress and cortisol may affect child development via different trajectories.

Longitudinal Analysis of Self-Reported Symptoms, Behavioral Measures, and Event-Related Potential Components of a Cued Go/NoGo Task in Adults With Attention-Deficit/Hyperactivity Disorder and Controls

This study characterizes a large sample of adults with attention-deficit/hyperactivity disorder (ADHD) and healthy controls regarding their task performance and neurophysiology; cross-sectionally and longitudinally. Self-reported symptoms, behavioral measures, and event-related potentials from a classical cued Go/NoGo task were used to outline the symptom burden, executive function deficits and neurophysiological features, and the associations between these domains. The study participants (N = 210 ADHD, N = 158 controls, age: 18–62 years) were assessed five (ADHD) or three (controls) times over two years. We describe cross-sectional and longitudinal group differences, and associations between symptom burden, and behavioral and event-related potential (ERP) components variables by latent growth curve models, including random slopes and intercepts. The ADHD group showed increased reaction time variability, increased commission and omission errors, and attenuated cueP3, CNV, N2d, and P3d amplitudes. We observed a decrease in self-reported symptoms in the ADHD group over the two years. The behavioral measures (reaction time variability, number of omission, and commission errors) did not change over time, whereas the cueP3, P3d, and N2d amplitude attenuated in both groups. There was no evidence for a robust association between symptom burden and behavioral or ERP measures. The changes in the ERP components with stable task performance, potentially indicate more efficient neuronal processing over the two years. Whether the lack of association between symptom burden and behavioral or ERP measures might be due to the low reliability of the ADHD assessment criteria, or the inappropriateness of the objective measures cannot be inferred.

Cyclotorsion Measurement on Scanning Laser Ophthalmoscopy Imaging Compared With Fundus Photography in Patients With Fourth Nerve Palsy and Healthy Controls: CySLO-IV Study

BACKGROUND

The purpose of the study is to evaluate the agreement of the foveopapillary angle (FPA) on conventional fundus photography (c-FPA) with the FPA on scanning laser ophthalmoscopy (SLO) imaging (SLO-FPA) in patients with fourth nerve palsy and healthy controls (HCs).

METHODS

The FPA was measured in both eyes of 25 patients and 25 HCs in synedra View (c-FPA) and with the integrated algorithm of the Heidelberg Spectralis OCT (SLO-FPA). The primary endpoint was the agreement of both measurements. Furthermore, we evaluated the influence of the eye tracker, the influence of fixation on objective torsion, and the FPA cutoff between patients and HCs.

RESULTS

The mean SLO-FPA in patients (6/25 acquired palsies) was 11.3 ± 3.6° and 6.4 ± 2.1° in HCs. The mean c-FPA was 11.4 ± 4.0° and 5.8 ± 2.2°, respectively. The Bland-Altman plot of c-FPA vs SLO-FPA in patients and HCs shows no systematic bias (mean of -0.28°). Limits of agreement were -6.58 and 6.02°. Using the eye tracker had no systematic effect. There was no evidence for an immediate shift of torsion with change of fixation (24/25 patients and 23/25 HCs). Discrimination between patients and HCs by the SLO-FPA is very good with an area under the curve = 0.92 (95% confidence interval: 0.84-0.99).

CONCLUSIONS

SLO-FPA measurement allows convenient and consistent assessment of objective cyclotorsion. There was no systematic bias in the difference between SLO-FPA and traditional c-FPA; thus, SLO-FPA is a valuable alternative to the commonly used c-FPA. Using the eye tracker is recommended for proper centering of the ring scan.

Age-related decline in the brain: a longitudinal study on inter-individual variability of cortical thickness, area, volume, and cognition

Magnetic Resonance Imaging (MRI) studies have shown that cortical volume declines with age. Although volume is a multiplicative measure consisting of thickness and area, few studies have focused on both its components. Information on decline variability and associations between person-specific changes of different brain metrics, brain regions, and cognition is sparse. In addition, the estimates have often been biased by the measurement error, because three repeated measures are minimally required to separate the measurement error from person-specific changes. With a sample size of N = 231, five repeated measures, and an observational time span of seven years, this study explores the associations between changes of different brain metrics, brain regions, and cognitive abilities in aging. Person-specific changes were obtained by latent growth curve models using Bayesian estimation. Our data indicate that both thickness and area are important contributors to volumetric changes. In most brain regions, area clearly declined on average over the years, while thickness showed only little decline. However, there was also substantial variation around the average slope in thickness and area. The correlation pattern of changes in thickness between brain regions was strong and largely homogenous. The pattern for changes in area was similar but weaker, indicating that factors affecting area may be more region-specific. Changes in thickness and volume were substantially correlated with changes in cognition. In some brain regions, changes in area were also related to changes in cognition. Overall, studying the associations between the trajectories of brain regions in different brain metrics provides insights into the regional heterogeneity of structural changes. SIGNIFICANCE STATEMENT: Many studies have described volumetric brain changes in aging. Few studies have focused on both its individual components: area and thickness. Longitudinal studies with three or more time points are highly needed, because they provide more precise average change estimates and, more importantly, allow us to quantify the associations between changes in the different brain metrics, brain regions, and other variables (e.g. cognitive abilities). Studying these associations is important because they can provide information regarding possible underlying factors of these changes. Our study, with a large sample size, five repeated measures, and an observational time span of seven years, provides new insights about the associations between person-specific changes in thickness, area, volume, and cognitive abilities.

Decline Variability of Cortical and Subcortical Regions in Aging: A Longitudinal Study

Describing the trajectories of age-related change for different brain structures has been of interest in many recent studies. However, our knowledge regarding these trajectories and their associations is still limited due to small sample sizes and low numbers of repeated measures. For the present study, we used a large longitudinal dataset (four measurements over 4 years) comprising anatomical data from a sample of healthy older adults (N = 231 at baseline). This dataset enables us to gain new insights about volumetric cortical and subcortical changes and their associations in the context of healthy aging. Brain structure volumes were derived from T1-weighted MRI scans using FreeSurfer segmentation tools. Brain structure trajectories were fitted using mixed models and latent growth curve models to gain information about the mean extent and variability of decline trajectories for different brain structures as well as the associations between individual trajectories. On the group level, our analyses indicate similar linear changes for frontal and parietal brain regions, while medial temporal regions showed an accelerated decline with advancing age. Regarding subcortical regions, some structures showed strong declines (e.g., hippocampus), others showed little decline (e.g., pallidum). Our data provide little evidence for sex differences regarding the aforementioned trajectories. Between-person variability of the person-specific slopes (random slopes) was largest in subcortical and medial temporal brain structures. When looking at the associations between the random slopes from each brain structure, we found that the decline is largely homogenous across the majority of cortical brain structures. In subcortical and medial temporal brain structures, however, more heterogeneity of the decline was observed, meaning that the extent of the decline in one structure is less predictive of the decline in another structure. Taken together, our study contributes to enhancing our understanding of structural brain aging by demonstrating (1) that average volumetric change differs across the brain and (2) that there are regional differences with respect to between-person variability in the slopes. Moreover, our data suggest (3) that random slopes are highly correlated across large parts of the cerebral cortex but (4) that some brain regions (i.e., medial temporal regions) deviate from this homogeneity.

Heterogeneity of EEG resting-state brain networks in absolute pitch

The neural basis of absolute pitch (AP), the ability to effortlessly identify a musical tone without an external reference, is poorly understood. One of the key questions is whether perceptual or cognitive processes underlie the phenomenon, as both sensory and higher-order brain regions have been associated with AP. To integrate the perceptual and cognitive views on AP, here, we investigated joint contributions of sensory and higher-order brain regions to AP resting-state networks. We performed a comprehensive functional network analysis of source-level EEG in a large sample of AP musicians (n = 54) and non-AP musicians (n = 51), adopting two analysis approaches: First, we applied an ROI-based analysis to examine the connectivity between the auditory cortex and the dorsolateral prefrontal cortex (DLPFC) using several established functional connectivity measures. This analysis is a replication of a previous study which reported increased connectivity between these two regions in AP musicians. Second, we performed a whole-brain network-based analysis on the same functional connectivity measures to gain a more complete picture of the brain regions involved in a possibly large-scale network supporting AP ability. In our sample, the ROI-based analysis did not provide evidence for an AP-specific connectivity increase between the auditory cortex and the DLPFC. The whole-brain analysis revealed three networks with increased connectivity in AP musicians comprising nodes in frontal, temporal, subcortical, and occipital areas. Commonalities of the networks were found in both sensory and higher-order brain regions of the perisylvian area. Further research will be needed to confirm these exploratory results.

Neural patterns reveal single-trial information on absolute pitch and relative pitch perception

Pitch is a fundamental attribute of sounds and yet is not perceived equally by all humans. Absolute pitch (AP) musicians perceive, recognize, and name pitches in absolute terms, whereas relative pitch (RP) musicians, representing the large majority of musicians, perceive pitches in relation to other pitches. In this study, we used electroencephalography (EEG) to investigate the neural representations underlying tone listening and tone labeling in a large sample of musicians (n = 105). Participants performed a pitch processing task with a listening and a labeling condition during EEG acquisition. Using a brain-decoding framework, we tested a prediction derived from both theoretical and empirical accounts of AP, namely that the representational similarity of listening and labeling is higher in AP musicians than in RP musicians. Consistent with the prediction, time-resolved single-trial EEG decoding revealed a higher representational similarity in AP musicians during late stages of pitch perception. Time-frequency-resolved EEG decoding further showed that the higher representational similarity was present in oscillations in the theta and beta frequency bands. Supplemental univariate analyses were less sensitive in detecting subtle group differences in the frequency domain. Taken together, the results suggest differences between AP and RP musicians in late pitch processing stages associated with cognition, rather than in early processing stages associated with perception.