Gregory L. Wallace

Sexual dimorphism of brain developmental trajectories during childhood and adolescence

Human total brain size is consistently reported to be approximately 8-10% larger in males, although consensus on regionally specific differences is weak. Here, in the largest longitudinal pediatric neuroimaging study reported to date (829 scans from 387 subjects, ages 3 to 27 years), we demonstrate the importance of examining size-by-age trajectories of brain development rather than group averages across broad age ranges when assessing sexual dimorphism. Using magnetic resonance imaging (MRI) we found robust male/female differences in the shapes of trajectories with total cerebral volume peaking at age 10.5 in females and 14.5 in males. White matter increases throughout this 24-year period with males having a steeper rate of increase during adolescence. Both cortical and subcortical gray matter trajectories follow an inverted U shaped path with peak sizes 1 to 2 years earlier in females. These sexually dimorphic trajectories confirm the importance of longitudinal data in studies of brain development and underline the need to consider sex matching in studies of brain development.

Facial Emotion Recognition in Autism Spectrum Disorders: A Review of Behavioral and Neuroimaging Studies

Behavioral studies of facial emotion recognition (FER) in autism spectrum disorders (ASD) have yielded mixed results. Here we address demographic and experiment-related factors that may account for these inconsistent findings. We also discuss the possibility that compensatory mechanisms might enable some individuals with ASD to perform well on certain types of FER tasks in spite of atypical processing of the stimuli, and difficulties with real-life emotion recognition. Evidence for such mechanisms comes in part from eye-tracking, electrophysiological, and brain imaging studies, which often show abnormal eye gaze patterns, delayed event-related-potential components in response to face stimuli, and anomalous activity in emotion-processing circuitry in ASD, in spite of intact behavioral performance during FER tasks. We suggest that future studies of FER in ASD: 1) incorporate longitudinal (or cross-sectional) designs to examine the developmental trajectory of (or age-related changes in) FER in ASD and 2) employ behavioral and brain imaging paradigms that can identify and characterize compensatory mechanisms or atypical processing styles in these individuals.

How Does Your Cortex Grow

Understanding human cortical maturation is a central goal for developmental neuroscience. Significant advances toward this goal have come from two recent strands of in vivo structural magnetic resonance imaging research: (1) longitudinal study designs have revealed that factors such as sex, cognitive ability, and disease are often better related to variations in the tempo of anatomical change than to variations in anatomy at any one time point; (2) largely cross-sectional applications of new surface-based morphometry (SBM) methods have shown how the traditional focus on cortical volume (CV) can obscure information about the two evolutionarily and genetically distinct determinants of CV: cortical thickness (CT) and surface area (SA). Here, by combining these two strategies for the first time and applying SBM in >1250 longitudinally acquired brain scans from 647 healthy individuals aged 3–30 years, we deconstruct cortical development to reveal that distinct trajectories of anatomical change are hidden within, and give rise to, a curvilinear pattern of CV maturation. Developmental changes in CV emerge through the sexually dimorphic and age-dependent interaction of changes in CT and SA. Moreover, SA change itself actually reflects complex interactions between brain size-related changes in exposed cortical convex hull area, and changes in the degree of cortical gyrification, which again vary by age and sex. Knowing of these developmental dissociations, and further specifying their timing and sex-biases, provides potent new research targets for basic and clinical neuroscience.

Understanding Executive Control in Autism Spectrum Disorders in the Lab and in the Real World

In this paper, we review the most recent and often conflicting findings on conventional measures of executive control in autism spectrum disorders. We discuss the obstacles to accurate measurement of executive control, such as: its prolonged developmental trajectory; lack of consensus on its definition and whether it is a unitary construct; the inherent complexity of executive control; and the difficulty measuring executive-control functions in laboratory or clinical settings. We review the potential of an ecological-validity framework to address some of these problems, and describe new tests claiming verisimilitude, or close resemblance to “real life” demands. We also review the concept of veridicality, which allows for the measurement of the ecological validity of any task, and discuss the few studies addressing ecological validity in individuals with autism. Our review suggests that a multi-source approach emphasizing veridicality may provide the most comprehensive assessment of executive control in autism.

Differences in Genetic and Environmental Influences on the Human Cerebral Cortex Associated With Development During Childhood and Adolescence

In this report, we present the first regional quantitative analysis of age‐related differences in the heritability of cortical thickness using anatomic MRI with a large pediatric sample of twins, twin siblings, and singletons (n = 600, mean age 11.1 years, range 5–19). Regions of primary sensory and motor cortex, which develop earlier, both phylogenetically and ontologically, show relatively greater genetic effects earlier in childhood. Later developing regions within the dorsal prefrontal cortex and temporal lobes conversely show increasingly prominent genetic effects with maturation. The observation that regions associated with complex cognitive processes such as language, tool use, and executive function are more heritable in adolescents than children is consistent with previous studies showing that IQ becomes increasingly heritable with maturity(Plomin et al. 1997 : Psychol Sci 8:442–447). These results suggest that both the specific cortical region and the age of the population should be taken into account when using cortical thickness as an intermediate phenotype to link genes, environment, and behavior. Hum Brain Mapp, 2009.

Puberty-related influences on brain development

Puberty is a time of striking changes in cognition and behavior. To indirectly assess the effects of puberty-related influences on the underlying neuroanatomy of these behavioral changes we will review and synthesize neuroimaging data from typically developing children and adolescents and from those with anomalous hormone or sex chromosome profiles. The trajectories (size by age) of brain morphometry differ between boys and girls, with girls generally reaching peak gray matter thickness 1-2 years earlier than boys. Both boys and girls with congenital adrenal hyperplasia (characterized by high levels of intrauterine testosterone), have smaller amygdala volume but the brain morphometry of girls with CAH did not otherwise significantly differ from controls. Subjects with XXY have gray matter reductions in the insula, temporal gyri, amygdala, hippocampus, and cingulate-areas consistent with the language-based learning difficulties common in this group.

Anatomical Brain Magnetic Resonance Imaging of Typically Developing Children and Adolescents.

Many psychiatric disorders, including some with adult onset such as schizophrenia, are increasingly being conceptualized as stemming from anomalies of neurodevelopment. To explore neurodevelopmental hypotheses of illness, it is useful to have well-characterized data regarding typical maturation to serve as a “yardstick” from which to assess possible deviations. Studies of typical development, and the influences on that development, may also unveil the timing and mechanisms of brain maturation guiding the way for novel interventions. In this overview, we will touch on methodological issues relevant to magnetic resonance imaging (MRI) studies of brain anatomy, summarize MRI findings of neuroanatomic changes during childhood and adolescence, and discuss possible influences on brain development trajectories. As indicated in the previous articles of this series, one of the first steps in measuring brain morphometric characteristics in a conventional anatomic MRI is to classify (or “segment”) individual voxels (the smallest elements of different MRI signals—usually approximately 1 mL) as corresponding to CSF, white matter (WM), or gray matter (GM). Once categorized by tissue type, various parcellations can be performed to derive volumes at the level of lobes (e.g., frontal, temporal, parietal, occipital); regions defined by gyral, sulcal, or GM, WM, and CSF boundaries (e.g., caudate nucleus); or individual voxels. Segmentation and parcellation of MRIs was originally exclusively done by trained individuals outlining particular regions of interest (frequently abbreviated as ROIs) by hand. Although having a highly trained individual manually identify brain regions is considered the closest thing to a “gold standard” available, the time and anatomic expertise necessary for training raters and performing this type of analysis can be prohibitive. This has motivated many laboratories to develop computer algorithms capable of automatically classifying regions of MRI images as belonging to different tissue types and anatomic regions. The rapid progress in this area has made it feasible to perform the type of large scale studies necessary to capture many of the changes associated with typical and atypical brain development. Automated methods have also opened the door to innovative ways of looking at brain structure, such as analyzing the shape and thickness of the cortical sheet. However, the fidelity of automated methods depends on the clarity of the borders between structures, which in turn is determined by a combination of the anatomy of a particular structure and the quality of the MRI image. For example, the amygdala and hippocampus are difficult for automated methods to separate properly because they represent adjacent GM structures. In cases such as these, hand measurements may still be the best approach, although even human raters may need considerable experience before they can consistently identify the borders of such structures on conventional MRI. The data for this overview are largely derived from 387 typically developing subjects (829 scans) participating in an ongoing longitudinal study at the Child Psychiatry Branch of the National Institute of Mental Health. Begun in 1989 by Markus Kruesi, M.D., and Judith Rapoport, M.D., the study design is for participants aged 3 to 30 years to come to the National Institutes of Health at approximately 2-year intervals for brain imaging, psychological and behavioral assessment, and collection of DNA. The emphasis on this single source is not to devalue the many excellent contributions of other investigators but to provide an integrated account from the world’s largest collection of child and adolescent brain MRI scans with data acquired using uniform screening/assessment batteries, the same scanner, and the same methods of image analyses. We have supplemented with references to studies by other laboratories, although a complete review of the field is beyond the scope of this article.

Fractionation of social brain circuits in autism spectrum disorders

Autism spectrum disorders are developmental disorders characterized by impairments in social and communication abilities and repetitive behaviours. Converging neuroscientific evidence has suggested that the neuropathology of autism spectrum disorders is widely distributed, involving impaired connectivity throughout the brain. Here, we evaluate the hypothesis that decreased connectivity in high-functioning adolescents with an autism spectrum disorder relative to typically developing adolescents is concentrated within domain-specific circuits that are specialized for social processing. Using a novel whole-brain connectivity approach in functional magnetic resonance imaging, we found that not only are decreases in connectivity most pronounced between regions of the social brain but also they are selective to connections between limbic-related brain regions involved in affective aspects of social processing from other parts of the social brain that support language and sensorimotor processes. This selective pattern was independently obtained for correlations with measures of social symptom severity, implying a fractionation of the social brain in autism spectrum disorders at the level of whole circuits.

Attention deficit/hyperactivity disorder symptoms moderate cognition and behavior in children with autism spectrum disorders†‡

Recent estimates suggest that 31% of children with autism spectrum disorders (ASD) meet diagnostic criteria for attention deficit/hyperactivity disorder (ADHD), and another 24% of children with ASD exhibit subthreshold clinical ADHD symptoms. Presence of ADHD symptoms in the context of ASD could have a variety of effects on cognition, autistic traits, and adaptive/maladaptive behaviors including: exacerbating core ASD impairments; adding unique impairments specific to ADHD; producing new problems unreported in ASD or ADHD; having no clear impact; or producing some combination of these scenarios. Children with ASD and co‐morbid ADHD symptoms (ASD+ADHD; n=21), children with ASD without ADHD (ASD; n=28), and a typically developing control group (n=21) were included in the study; all groups were matched on age, gender‐ratio, IQ, and socioeconomic status. Data were collected on verbal and spatial working memory, response inhibition, global executive control (EC), autistic traits, adaptive functioning, and maladaptive behavior problems. In this sample, the presence of ADHD symptoms in ASD exacerbated impairments in EC and adaptive behavior and resulted in higher autistic trait, and externalizing behavior ratings. ADHD symptoms were also associated with greater impairments on a lab measure of verbal working memory. These findings suggest that children with ASD+ADHD symptoms present with exacerbated impairments in some but not all domains of functioning relative to children with ASD, most notably in adaptive behavior and working memory. Therefore, ADHD may moderate the expression of components of the ASD cognitive and behavioral phenotype, but ASD+ADHD may not represent an etiologically distinct phenotype from ASD alone.

Age-related temporal and parietal cortical thinning in autism spectrum disorders

Studies of head size and brain volume in autism spectrum disorders have suggested that early cortical overgrowth may be followed by prematurely arrested growth. However, the few investigations quantifying cortical thickness have yielded inconsistent results, probably due to variable ages and/or small sample sizes. We assessed differences in cortical thickness between high-functioning adolescent and young adult males with autism spectrum disorders (n = 41) and matched typically developing males (n = 40). We hypothesized thinner cortex, particularly in frontal, parietal and temporal regions, for individuals with autism spectrum disorders in comparison with typically developing controls. Furthermore, we expected to find an age × diagnosis interaction: with increasing age, more pronounced cortical thinning would be observed in autism spectrum disorders than typically developing participants. T(1)-weighted magnetization prepared rapid gradient echo 3 T magnetic resonance imaging scans were acquired from high-functioning males with autism spectrum disorders and from typically developing males matched group-wise on age (range 12-24 years), intelligence quotient (≥ 85) and handedness. Both gyral-level and vertex-based analyses revealed significantly thinner cortex in the autism spectrum disorders group that was located predominantly in left temporal and parietal regions (i.e. the superior temporal sulcus, inferior temporal, postcentral/superior parietal and supramarginal gyri). These findings remained largely unchanged after controlling for intelligence quotient and after accounting for psychotropic medication usage and comorbid psychopathology. Furthermore, a significant age × diagnosis interaction was found in the left fusiform/inferior temporal cortex: participants with autism spectrum disorders had thinner cortex in this region with increasing age to a greater degree than did typically developing participants. Follow-up within group comparisons revealed significant age-related thinning in the autism spectrum disorders group but not in the typically developing group. Both thinner temporal and parietal cortices during adolescence and young adulthood and discrepantly accelerated age-related cortical thinning in autism spectrum disorders suggest that a second period of abnormal cortical growth (i.e. greater thinning) may be characteristic of these disorders.