Heightened fear and inefficient safety learning are key features of fear and anxiety disorders. Evidence-based interventions for anxiety disorders, such as cognitive behavioral therapy, primarily rely on mechanisms of fear extinction. However, up to 50% of clinically anxious individuals do not respond to current evidence-based treatment, suggesting a critical need for new interventions based on alternative neurobiological pathways. Using parallel human and rodent conditioned inhibition paradigms alongside brain imaging methodologies, we investigated neural activity patterns in the ventral hippocampus in response to stimuli predictive of threat or safety and compound cues to test inhibition via safety in the presence of threat. Distinct hippocampal responses to threat, safety, and compound cues suggest that the ventral hippocampus is involved in conditioned inhibition in both mice and humans. Moreover, unique response patterns within target-differentiated subpopulations of ventral hippocampal neurons identify a circuit by which fear may be inhibited via safety. Specifically, ventral hippocampal neurons projecting to the prelimbic cortex, but not to the infralimbic cortex or basolateral amygdala, were more active to safety and compound cues than threat cues, and activity correlated with freezing behavior in rodents. A corresponding distinction was observed in humans: hippocampal–dorsal anterior cingulate cortex functional connectivity—but not hippocampal–anterior ventromedial prefrontal cortex or hippocampal–basolateral amygdala connectivity—differentiated between threat, safety, and compound conditions. These findings highlight the potential to enhance treatment for anxiety disorders by targeting an alternative neural mechanism through safety signal learning.

Children make up over half of the world's migrants and refugees and face a multitude of traumatic experiences prior to, during, and following migration. Here, we focus on migrant children emigrating from Mexico and Central America to the United States and review trauma related to migration, as well as its implications for the mental health of migrant and refugee children. We then draw upon the early adversity literature to highlight potential behavioral and neurobiological sequalae of migration‐related trauma exposure, focusing on attachment, emotion regulation, and fear learning and extinction as transdiagnostic mechanisms underlying the development of internalizing and externalizing symptomatology following early‐life adversity. This review underscores the need for interdisciplinary efforts to both mitigate the effects of trauma faced by migrant and refugee youth emigrating from Mexico and Central America and, of primary importance, to prevent child exposure to trauma in the context of migration. Thus, we conclude by outlining policy recommendations aimed at improving the mental health of migrant and refugee youth.

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets.

Cross-species evidence suggests that the ability to exert control over a stressor is a key dimension of stress exposure that may sensitize frontostriatal-amygdala circuitry to promote more adaptive responses to subsequent stressors. The present study examined neural correlates of stressor controllability in young adults. Participants (N = 56; Mage = 23.74, range = 18–30 years) completed either the controllable or uncontrollable stress condition of the first of two novel stressor controllability tasks during functional magnetic resonance imaging (fMRI) acquisition. Participants in the uncontrollable stress condition were yoked to age- and sex-matched participants in the controllable stress condition. All participants were subsequently exposed to uncontrollable stress in the second task, which is the focus of fMRI analyses reported here. A whole-brain searchlight classification analysis revealed that patterns of activity in the right dorsal anterior insula (dAI) during subsequent exposure to uncontrollable stress could be used to classify participants' initial exposure to either controllable or uncontrollable stress with a peak of 73% accuracy. Previous experience of exerting control over a stressor may change the computations performed within the right dAI during subsequent stress exposure, shedding further light on the neural underpinnings of stressor controllability.

Anxiety disorders are the most prevalent psychiatric condition among youth, with symptoms commonly emerging prior to or during adolescence. Delineating neurodevelopmental trajectories associated with anxiety disorders is important for understanding the pathophysiology of pediatric anxiety and for early risk identification. While a growing literature has yielded valuable insights into the nature of brain structure and function in pediatric anxiety, progress has been limited by inconsistent findings and challenges common to neuroimaging research. In this review, we first discuss these challenges and the promise of ‘big data’ to map neurodevelopmental trajectories in pediatric anxiety. Next, we review evidence of age-related differences in neural structure and function among anxious youth, with a focus on anxiety-relevant processes such as threat and safety learning. We then highlight large-scale cross-sectional and longitudinal studies that assess anxiety and are well positioned to inform our understanding of neurodevelopment in pediatric anxiety. Finally, we detail relevant challenges of ‘big data’ and propose future directions through which large publicly available datasets can advance knowledge of deviations from normative brain development in anxiety. Leveraging ‘big data’ will be essential for continued progress in understanding the neurobiology of pediatric anxiety, with implications for identifying markers of risk and novel treatment targets.