Effective visualization is central to the exploration and comprehension of brain imaging data. While MRI data are acquired in three-dimensional space, the methods for visualizing such data have rarely taken advantage of three-dimensional stereoscopic technologies. We present here results of stereoscopic visualization of clinical data, as well as an atlas of whole-brain functional connectivity. In comparison with traditional 3D rendering techniques, we demonstrate the utility of stereoscopic visualizations to provide an intuitive description of the exact location and the relative sizes of various brain landmarks, structures and lesions. In the case of resting state fMRI, stereoscopic 3D visualization facilitated comprehension of the anatomical position of complex large-scale functional connectivity patterns. Overall, stereoscopic visualization improves the intuitive visual comprehension of image contents, and brings increased dimensionality to visualization of traditional MRI data, as well as patterns of functional connectivity.
The United States is facing a mental health workforce shortage, exacerbated by the COVID-19 pandemic. Low- and middle-income countries (LMICs) have historically grappled with even greater shortages. Therefore, LMICs have thought creatively about expanding the mental health workforce and the settings in which to deliver evidence-based and equitable mental health care. The authors introduce some mental health interventions in LMICs, describe evidence of the efficacy of these interventions gleaned from this context, and discuss the applicability of these interventions to the United States. The authors also reflect on the benefits and challenges of implementing these interventions in the U.S. mental health care system to alleviate its current workforce shortage.
ABSTRACT Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5-21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics, and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n = 664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).
In the US, unaccompanied migrant children and adolescents (hereinafter referred to as children) are predominantly from Central America's Northern Triangle. While unaccompanied migrant children are at high risk for psychiatric sequelae due to complex traumatic exposures, longitudinal investigations of psychiatric distress after resettlement are lacking.To identify factors associated with emotional distress and longitudinal changes in emotional distress among unaccompanied migrant children in the US.For this retrospective cohort study, the 15-item Refugee Health Screener (RHS-15) was administered between January 1, 2015, and December 31, 2019, to unaccompanied migrant children as part of their medical care to detect emotional distress. Follow-up RHS-15 results were included if they were completed before February 29, 2020. Median follow-up interval was 203 days (IQR, 113-375 days). The study was conducted in a federally qualified health center that provides medical, mental health, and legal services. Unaccompanied migrant children who completed the initial RHS-15 were eligible for analysis. Data were analyzed from April 18, 2022, to April 23, 2023.Traumatic events before migration, during migration, during detention, and after resettlement in the US.Emotional distress, including symptoms of posttraumatic stress disorder, anxiety, and depressive symptoms, as indicated by the RHS-15 (ie, score ≥12 on items 1-14 or ≥5 on item 15).In total, 176 unaccompanied migrant children completed an initial RHS-15. They were primarily from Central America's Northern Triangle (153 [86.9%]), were mostly male (126 [71.6%]), and had a mean (SD) age of 16.9 (2.1) years. Of the 176 unaccompanied migrant children, 101 (57.4%) had screen results above the positive cutoff. Girls were more likely to have positive screen results than boys (odds ratio, 2.48 [95% CI, 1.15-5.34]; P = .02). Follow-up scores were available for 68 unaccompanied migrant children (38.6%). On the follow-up RHS-15, most scored above the positive cutoff (44 [64.7%]). Three-quarters of unaccompanied migrant children who scored above the positive cutoff initially continued to have positive scores at follow-up (30 of 40), and half of those with negative screen scores initially had positive scores at follow-up (14 of 28). Female vs male unaccompanied migrant children (unstandardized β = 5.14 [95% CI, 0.23-10.06]; P = .04) and initial total score (unstandardized β = 0.41 [95% CI, 0.18-0.64]; P = .001) were independently associated with increased follow-up RHS-15 total score.The findings suggest that unaccompanied migrant children are at high risk for emotional distress, including symptoms of depression, anxiety, and posttraumatic stress. The persistence of emotional distress suggests that unaccompanied migrant children would benefit from ongoing psychosocial and material support after resettlement.
Abstract Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5–21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release ( n =664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).
Although typically measured during the resting state, a growing literature is illustrating the ability to map intrinsic connectivity with functional MRI during task and naturalistic viewing conditions. These paradigms are drawing excitement due to their greater tolerability in clinical and developing populations and because they enable a wider range of analyses (e.g., inter-subject correlations). To be clinically useful, the test-retest reliability of connectivity measured during these paradigms needs to be established. This resource provides data for evaluating test-retest reliability for full-brain connectivity patterns detected during each of four scan conditions that differ with respect to level of engagement (rest, abstract animations, movie clips, flanker task). Data are provided for 13 participants, each scanned in 12 sessions with 10 minutes for each scan of the four conditions. Diffusion kurtosis imaging data was also obtained at each session. Technical validation and demonstrative reliability analyses were carried out at the connection-level using the Intraclass Correlation Coefficient and at network-level representations of the data using the Image Intraclass Correlation Coefficient. Variation in intrinsic functional connectivity across sessions was generally found to be greater than that attributable to scan condition. Between-condition reliability was generally high, particularly for the frontoparietal and default networks. Between-session reliabilities obtained separately for the different scan conditions were comparable, though notably lower than between-condition reliabilities. This resource provides a test-bed for quantifying the reliability of connectivity indices across subjects, conditions and time. The resource can be used to compare and optimize different frameworks for measuring connectivity and data collection parameters such as scan length. Additionally, investigators can explore the unique perspectives of the brain's functional architecture offered by each of the scan conditions.
Motor inhibition is among the most commonly studied executive functions in Attention-Deficit/Hyperactivity Disorder (ADHD). Imaging studies using probes of motor inhibition such as the Stop Signal Task (SST) consistently demonstrate ADHD-related dysfunction within a right-hemisphere fronto-striatal network that includes inferior frontal gyrus and pre-supplementary motor area (pre-SMA). Beyond findings of focal hypo- or hyper-function, emerging models of ADHD psychopathology highlight disease-related changes in functional interactions between network components. Resting state fMRI (R-fMRI) approaches have emerged as powerful tools for mapping such interactions (i.e., resting state functional connectivity, RSFC), and for relating behavioral and diagnostic variables to network properties. We used R-fMRI data collected from 17 typically developing controls (TDC) and 17 age-matched children with ADHD (aged 8-13 years) to identify neural correlates of SST performance measured outside the scanner. We examined two related inhibition indices: stop signal reaction time (SSRT), indexing inhibitory speed, and stop signal delay (SSD), indexing inhibitory success. Using 11 fronto-striatal seed regions-of-interest, we queried the brain for relationships between RSFC and each performance index, as well as for interactions with diagnostic status. Both SSRT and SSD exhibited connectivity-behavior relationships independent of diagnosis. At the same time, we found differential connectivity-behavior relationships in children with ADHD relative to TDC. Our results demonstrate the utility of RSFC approaches for assessing brain/behavior relationships, and for identifying pathology-related differences in the contributions of neural circuits to cognition and behavior.
