Neural and psychological correlates of post-traumatic stress symptoms in a community adult sample.

A multitude of factors are associated with the symptoms of post-traumatic stress disorder. However, establishing which predictors are most strongly associated with post-traumatic stress disorder symptoms is complicated because few studies are able to consider multiple factors simultaneously across the biopsychosocial domains that are implicated by existing theoretical models. Further, post-traumatic stress disorder is heterogeneous, and studies using case-control designs may obscure which factors relate uniquely to symptom dimensions. Here we used Bayesian variable selection to identify the most important predictors for overall post-traumatic stress disorder symptoms and individual symptom dimensions in a community sample of 569 adults (18 to 85 yr of age). Candidate predictors were selected from previously established risk factors relevant for post-traumatic stress disorder and included psychological measures, behavioral measures, and resting state functional connectivity among brain regions. In a follow-up analysis, we compared results controlling for current depression symptoms in order to examine specificity. Poor sleep quality and dimensions of temperament and impulsivity were consistently associated with greater post-traumatic stress disorder symptom severity. In addition to self-report measures, brain functional connectivity among regions commonly ascribed to the default mode network, central executive network, and salience network explained the unique variability of post-traumatic stress disorder symptoms. This study demonstrates the unique contributions of psychological measures and neural substrates to post-traumatic stress disorder symptoms.

Resting state functional brain connectivity in child and adolescent psychiatry: where are we now?

Approaching the 30th anniversary of the discovery of resting state functional magnetic resonance imaging (rsfMRI) functional connectivity, we reflect on the impact of this neuroimaging breakthrough on the field of child and adolescent psychiatry. The study of intrinsic functional brain architecture that rsfMRI affords across a wide range of ages and abilities has yielded numerous key insights. For example, we now know that many neurodevelopmental conditions are associated with more widespread circuit alterations across multiple large-scale brain networks than previously suspected. The emergence of population neuroscience and effective data-sharing initiatives have made large rsfMRI datasets publicly available, providing sufficient power to begin to identify brain-based subtypes within heterogeneous clinical conditions. Nevertheless, several methodological and theoretical challenges must still be addressed to fulfill the promises of personalized child and adolescent psychiatry. In particular, incomplete understanding of the physiological mechanisms driving developmental changes in intrinsic functional connectivity remains an obstacle to further progress. Future directions include cross-species and multimodal neuroimaging investigations to illuminate such mechanisms. Data collection and harmonization efforts that span multiple countries and diverse cohorts are urgently needed. Finally, incorporating naturalistic fMRI paradigms such as movie watching should be a priority for future research efforts.

Increasing the representation of minoritized youth for inclusive and reproducible brain-behavior associations.

Population neuroscience datasets allow researchers to estimate reliable effect sizes for brain-behavior associations because of their large sample sizes. However, these datasets undergo strict quality control to mitigate sources of noise, such as head motion. This practice often excludes a disproportionate number of minoritized individuals. We employ motion-ordering and motion-ordering+resampling (bagging) to test if these methods preserve functional MRI (fMRI) data in the Adolescent Brain Cognitive Development Study ( N = 5,733 ). Black and Hispanic youth exhibited excess head motion relative to data collected from White youth, and were discarded disproportionately when using conventional approaches. Both methods retained more than 99% of Black and Hispanic youth. They produced reproducible brain-behavior associations across low-/high-motion racial/ethnic groups based on motion-limited fMRI data. The motion-ordering and bagging methods are two feasible approaches that can enhance sample representation for testing brain-behavior associations and fulfill the promise of consortia datasets to produce generalizable effect sizes across diverse populations.

Brain signal variability and executive functions across the life span.

Neural variability is thought to facilitate survival through flexible adaptation to changing environmental demands. In humans, such capacity for flexible adaptation may manifest as fluid reasoning, inhibition of automatic responses, and mental set-switching-skills falling under the broad domain of executive functions that fluctuate over the life span. Neural variability can be quantified via the BOLD signal in resting-state fMRI. Variability of large-scale brain networks is posited to underpin complex cognitive activities requiring interactions between multiple brain regions. Few studies have examined the extent to which network-level brain signal variability across the life span maps onto high-level processes under the umbrella of executive functions. The present study leveraged a large publicly available neuroimaging dataset to investigate the relationship between signal variability and executive functions across the life span. Associations between brain signal variability and executive functions shifted as a function of age. Limbic-specific variability was consistently associated with greater performance across subcomponents of executive functions. Associations between executive function subcomponents and network-level variability of the default mode and central executive networks, as well as whole-brain variability, varied across the life span. Findings suggest that brain signal variability may help to explain to age-related differences in executive functions across the life span.

Traditionally, regional variability in brain signals has been viewed as a source of noise in human neuroimaging research. Our study demonstrates that brain signal variability may contain meaningful information related to psychological processes. We demonstrate that brain signal variability, particularly whole-brain variability, may serve as a reliable indicator of cognitive functions across the life span. Global variability and network-level variability play differing roles in supporting executive functions. Findings suggest that brain signal variability serves as a meaningful indicator of development and cognitive aging.

Racial Discrimination and Risk for Internalizing and Externalizing Symptoms Among Black Youths.

Importance: Racial discrimination is a psychosocial stressor associated with youths' risk for psychiatric symptoms. Scarce data exist on the moderating role of amygdalar activation patterns among Black youths in the US. Objective: To investigate the association between racial discrimination and risk for psychopathology moderated by neuroaffective processing. Design, Setting, and Participants: This cohort study used longitudinal self-report and functional magnetic resonance imaging (fMRI) data from Black youth participants in the US from the Adolescent Brain Cognitive Development (ABCD) study. Data were analyzed from January 2023 to May 2024. Exposures: At time 1 of the current study (12 months after baseline), youths self-reported on their experiences of interpersonal racial discrimination and their feelings of marginalization. Amygdalar response was measured during an emotionally valenced task that included blocks of faces expressing either neutral or negative emotion. Main Outcomes and Measures: At 24 and 36 months after baseline, youths reported their internalizing (anxiety and depressive symptoms) and externalizing symptoms (aggression and rule-breaking symptoms). Results: A total of 1596 youths were a mean (SD) age of 10.92 (0.63) years, and 803 were female (50.3%). Families in the study had a mean annual income range of $25 000 to $34 999. Two factors were derived from factor analysis: interpersonal racial discrimination and feelings of marginalization (FoM). Using structural equation modeling in a linear regression, standardized ß coefficients were obtained. Neural response to faces expressing negative emotion within the right amygdala significantly moderated the association between FoM and changes in internalizing symptoms (ß = -0.20; 95% CI, -0.32 to -0.07; P < .001). The response to negative facial emotion within the right amygdala significantly moderated the association between FoM and changes in externalizing symptoms (ß = 0.24; 95% CI, 0.04 to 0.43; P = .02). Left amygdala response to negative emotion significantly moderated the association between FoM and changes in externalizing symptoms (ß = -0.16; 95% CI, -0.32 to -0.01; P = .04). Conclusions and Relevance: In this cohort study of Black adolescents in the US, findings suggest that amygdala function in response to emotional stimuli can both protect and intensify the affective outcomes of feeling marginalized on risk for psychopathology, informing preventive interventions aimed at reducing the adverse effects of racism on internalizing and externalizing symptoms among Black youths.

Widespread Autonomic Physiological Coupling Across the Brain-Body Axis.

The brain is closely attuned to visceral signals from the body's internal environment, as evidenced by the numerous associations between neural, hemodynamic, and peripheral physiological signals. We show that these brain-body co-fluctuations can be captured by a single spatiotemporal pattern. Across several independent samples, as well as single-echo and multi-echo fMRI data acquisition sequences, we identify widespread co-fluctuations in the low-frequency range (0.01 - 0.1 Hz) between resting-state global fMRI signals, neural activity, and a host of autonomic signals spanning cardiovascular, pulmonary, exocrine and smooth muscle systems. The same brain-body co-fluctuations observed at rest are elicited by arousal induced by cued deep breathing and intermittent sensory stimuli, as well as spontaneous phasic EEG events during sleep. Further, we show that the spatial structure of global fMRI signals is maintained under experimental suppression of end-tidal carbon dioxide (PETCO2) variations, suggesting that respiratory-driven fluctuations in arterial CO2 accompanying arousal cannot explain the origin of these signals in the brain. These findings establish the global fMRI signal as a significant component of the arousal response governed by the autonomic nervous system.

A network correspondence toolbox for quantitative evaluation of novel neuroimaging results.

Decades of neuroscience research has shown that macroscale brain dynamics can be reliably decomposed into a subset of large-scale functional networks, but the specific spatial topographies of these networks and the names used to describe them can vary across studies. Such discordance has hampered interpretation and convergence of research findings across the field. To address this problem, we have developed the Network Correspondence Toolbox (NCT) to permit researchers to examine and report spatial correspondence between their novel neuroimaging results and sixteen widely used functional brain atlases, consistent with recommended reporting standards developed by the Organization for Human Brain Mapping. The atlases included in the toolbox show some topographical convergence for specific networks, such as those labeled as default or visual. Network naming varies across atlases, particularly for networks spanning frontoparietal association cortices. For this reason, quantitative comparison with multiple atlases is recommended to benchmark novel neuroimaging findings. We provide several exemplar demonstrations using the Human Connectome Project task fMRI results and UK Biobank independent component analysis maps to illustrate how researchers can use the NCT to report their own findings through quantitative evaluation against multiple published atlases. The NCT provides a convenient means for computing Dice coefficients with spin test permutations to determine the magnitude and statistical significance of correspondence among user-defined maps and existing atlas labels. The NCT also includes functionality to incorporate additional atlases in the future. The adoption of the NCT will make it easier for network neuroscience researchers to report their findings in a standardized manner, thus aiding reproducibility and facilitating comparisons between studies to produce interdisciplinary insights.