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Here we report on detailed three-dimensional quantitative maps of brain surface and gray matter density asymmetry patterns during normal adolescent development and show how these anatomical features of the brain are disrupted as a result of prenatal exposure to large quantities of alcohol. We studied two independent samples of normally developing children, adolescents, and young adults, totaling 83 subjects from two different research groups, and compared them to 21 individuals with heavy prenatal alcohol exposure. Surface-based image analysis techniques allowed us to match cortical anatomy across subjects and between hemispheres based on manually delineated sulcal landmarks. Quantitative maps of brain surface asymmetry reveal prominent peri-Sylvian hemispheric differences in which the superior temporal and inferior parietal cortices are shifted backward in the left relative to the right hemisphere in both normal and alcohol-exposed subjects. Cortical surface gray matter asymmetry, mapped here in adolescent populations, is most prominent in the posterior inferior temporal lobes (right greater than left), and this effect does not differ between groups of normally developing children, adolescents, or young adults. Alcohol-exposed individuals show a significant reduction in this asymmetry, whether studied with surface-based or more traditional volumetric region of interest analyses. This region of cortex, near the junction of Brodmann's areas 21, 22, and 37, primarily subserves language functions that are known to be impaired on average in the alcohol-exposed subjects. Our findings elucidate regional patterns of brain surface and gray matter asymmetry during normal development and may contribute to a more comprehensive understanding of the neural substrates of cognitive dysfunction after heavy prenatal alcohol exposure.

Introduction: Repetitive, subconcussive events may adversely affect the brain and cognition during sensitive periods of development. Prevention of neurocognitive consequences of concussion in high school football is therefore an important public health priority. We aimed to identify the player positions and demographic, behavioral, cognitive, and impact characteristics that predict the frequency and acceleration of head impacts in high school football players. Methods: In this prospective study, three cohorts of adolescent male athletes (N = 53, 28.3% Hispanic) were recruited over three successive seasons in a high school American football program. Demographic and cognitive functioning were assessed at baseline prior to participating in football. Helmet sensors recorded impact frequency and acceleration. Each head impact was captured on film from five different angles. Research staff verified and characterized on-field impacts. Player-level Poisson regressions and year-level and impact-level linear mixed-effect models were used to determine demographic, behavioral, cognitive, and impact characteristics as predictors of impact frequency and acceleration. Results: 4,678 valid impacts were recorded. Impact frequency positively associated with baseline symptoms of hyperactivity-impulsivity [β(SE) = 1.05 impacts per year per unit of symptom severity (1.00), p = 0.01] and inattentiveness [β(SE) = 1.003 impacts per year per T-score unit (1.001), p = 0.01]. Compared to quarterbacks, the highest acceleration impacts were sustained by kickers/punters [β(SE) = 21.5 g's higher (7.1), p = 0.002], kick/punt returners [β(SE) = 9.3 g's higher (4.4), p = 0.03], and defensive backs [β(SE) = 4.9 g's higher (2.5), p = 0.05]. Impacts were more frequent in the second [β(SE) = 33.4 impacts (14.2), p = 0.02)] and third [β(SE) = 50.9 impacts (20.1), p = 0.01] year of play. Acceleration was highest in top-of-the-head impacts [β(SE) = 4.4 g's higher (0.8), p<0.001]. Conclusion: Including screening questions for Attention-Deficit/Hyperactivity Disorder in pre-participation evaluations can help identify a subset of prospective football players who may be at risk for increased head impacts. Position-specific strategies to modify kickoffs and correct tackling and blocking may also reduce impact burden. [ABSTRACT FROM AUTHOR]

The purpose of this qualitative study was to capture the perspectives of individuals representing an urban, predominantly Latinx community who are underresourced by mental health services about the use of telehealth to deliver mental health treatment. The COVID-19 pandemic required hospital- and community-based mental health programs to pivot to telehealth with alarming speed and very little opportunity to assess the feasibility, acceptability, and disparate impact on unique populations of patients. This study aimed to assess perceived strengths and limitations of telehealth mental health service delivery via qualitative focus group methods. Three focus groups were conducted with 13 youth (aged 8–17) who were being treated at an urban, academic children's hospital serving a predominantly Latinx community mental health population; two focus groups were conducted with 19 parents of said children; and one focus group was conducted with four mental health providers providing services to this population. A coding schema was designed to capture themes relevant to the following: (1) privacy and confidentiality; (2) perceived limitations of telehealth; (3) comfort with telehealth; (4) therapeutic relationship; (5) perceived strengths of telehealth; (6) perceived safety of telehealth; and (7) advice for providers engaging in telehealth. Findings were illustrative of both perceived strengths and limitations across these domains that can inform optimized telehealth mental health services moving forward. [ABSTRACT FROM AUTHOR]

Brain morphometry in recent decades has increased our understanding of the neural bases of psychiatric disorders by localizing anatomical disturbances to specific nuclei and subnuclei of the brain. At least some of these disturbances precede the overt expression of clinical symptoms and possibly are endophenotypes that could be used to diagnose an individual accurately as having a specific psychiatric disorder. More accurate diagnoses could significantly reduce the emotional and financial burden of disease by aiding clinicians in implementing appropriate treatments earlier and in tailoring treatment to the individual needs. Several methods, especially those based on machine learning, have been proposed that use anatomical brain measures and gold-standard diagnoses of participants to learn decision rules that classify a person automatically as having one disorder rather than another. We review the general principles and procedures for machine learning, particularly as applied to diagnostic classification, and then review the procedures that have thus far attempted to diagnose psychiatric illnesses automatically using anatomical measures of the brain. We discuss the strengths and limitations of extant procedures and note that the sensitivity and specificity of these procedures in their most successful implementations have approximated 90%. Although these methods have not yet been applied within clinical settings, they provide strong evidence that individual patients can be diagnosed accurately using the spatial pattern of disturbances across the brain.

Aim: The aim of this article is to review neuroimaging studies of autism spectrum disorders (ASD) that examine declarative, socio-emotional, and procedural learning and memory systems. Method: We conducted a search of PubMed from 1996 to 2010 using the terms "autism,""learning,""memory," and "neuroimaging." We limited our review to studies correlating learning and memory function with neuroimaging features of the brain. Results: The early literature supports the following preliminary hypotheses: (1) abnormalities of hippocampal subregions may contribute to autistic deficits in episodic and relational memory; (2) disturbances to an amygdala-based network (which may include the fusiform gyrus, superior temporal cortex, and mirror neuron system) may contribute to autistic deficits in socio-emotional learning and memory; and (3) abnormalities of the striatum may contribute to developmental dyspraxia in individuals with ASD. Interpretation: Characterizing the disturbances to learning and memory systems in ASD can inform our understanding of the neural bases of autistic behaviors and the phenotypic heterogeneity of ASD.

Objective: Exposure to heavy maternal cigarette smoking in pregnancy and severe maternal psychosocial stress during pregnancy appear to be important risk factors for the development of ADHD. This study aimed to determine whether these perinatal risk factors were associated with neuropsychological deficits commonly seen in ADHD. Method: We examined the effect of these two risk factors on measures of attentional control, motor inhibition, visual-motor integration, and fine motor coordination in a group of 81 children with ADHD, aged from 8 to 18 years. The neuropsychological battery included the Connors' Continuous Performance Test (CPT), the Stroop Color-Word Interference Test, the Beery Visual-Motor Integration Test, and the Purdue Pegboard Test. Results: Heavy maternal smoking during pregnancy was associated with slower reaction times (p less than 0.002), and reaction time variability (p less than 0.007) on the CPT. Conclusions: This study suggests a persistent negative effect of heavy prenatal maternal smoking on attentional control in children with ADHD. Future studies should examine the neurobiological basis and determine the degree to which inherited genetic susceptibility factors contribute to this finding. (Contains 4 tables.)

Background: Half of pediatric-onset OCD cases remit by adulthood. Studies have demonstrated that initial response to pharmacotherapy, age of onset, prominent hoarding symptoms, and the presence of comorbid tic disorders are associated with long-term outcome. Our goal was to examine the association between childhood performance on neuropsychological testing and persistence of OCD into adulthood. Methods: Twenty-four children with OCD were followed for an average of 7.5 years into early adulthood. Neuropsychological performance in childhood (less than 16 years) was measured. The battery included the Wechsler Intelligence Scale for Children (WISC-III), the Purdue pegboard test, the Rey-Osterreith Complex Figure Task (RCFT) and the Beery-Buktenica test of Visual Motor Integration (VMI). We hypothesized that deficits in fine-motor skills, visuospatial skills, and nonverbal memory as well as overall intelligence would be associated with adulthood outcome. We used a Cox proportional hazard model of survival analysis in which time to remission of OCD symptoms was the main outcome variable. Results: Poor childhood performance on the Purdue pegboard task and the block design subscale of WISC-III was associated with persistence of OCD symptoms into adulthood. IQ, VMI, and nonverbal memory performance did not predict significantly the persistence of OCD. Conclusions: These results suggest that visuospatial and fine-motor skill deficits are predictive of poor long-term outcome in pediatric-onset OCD. Future longitudinal studies are needed to chart the course of these deficits relative to the course of symptoms in OCD and to determine whether the association of these neuropsychiatric deficits with long-term outcome is specific to pediatric-onset OCD or generalizes to other psychiatric disorders.

Neuroimaging findings which identify normal brain development trajectories are presented. Results show that early brain development begins with the neural tube formation and ends with myelintation. How disturbances in brain development patterns are related to childhood psychiatric disorders is examined.

The article helps to understand the interpretation of an image by presenting as to what constitutes an image. A common feature in all images is the basic physical structure that can be described with a common set of terms.