What can Cortical Development in Attention-Deficit/Hyperactivity Disorder Teach us About the Early Developmental Mechanisms Involved?

Studies of Attention-Deficit/Hyperactivity Disorder (ADHD) have shown developmental changes in the cortical mantle. Different dimensions of cortical morphology, such as surface area and thickness, relate to different neurodevelopmental mechanisms. As such, studying multiple dimensions may inform us about the developmental origins of ADHD. Furthermore, results from existing longitudinal samples await replication. Therefore, we conducted a longitudinal study of multiple cortical dimensions in a sizable, independent ADHD sample. We analyzed 297 anatomical MRI scans from two matched groups of 94 subjects with ADHD and 94 controls, aged 6-28 years. We estimated the developmental trajectories of cortical volume, surface, thickness and gyrification for 68 regions using mixed-effects regression analysis. Subjects with ADHD had smaller overall cortical volume, predominantly driven by decreases in frontal lobe volume that were associated with reduced surface area and gyrification. Nearly all decreases were stable across development. Only a few decreases survived stringent Bonferroni correction for multiple comparisons, with the smallest detectable Cohen's d |0.43|. There were no between-group differences in cortical thickness, or in subcortical volumes. Our results suggest that ADHD is associated with developmentally persistent reductions in frontal cortical volume, surface area, and gyrification. This may implicate early neurodevelopmental mechanisms regulating cortical expansion and convolution in ADHD.

The development of brain network architecture.

Brain connectivity shows protracted development throughout childhood and adolescence, and, as such, the topology of brain networks changes during this period. The complexity of these changes with development is reflected by regional differences in maturation. This study explored age-related changes in network topology and regional developmental patterns during childhood and adolescence. We acquired two sets of Diffusion Weighted Imaging-scans and anatomical T1-weighted scans. The first dataset included 85 typically developing individuals (53 males; 32 females), aged between 7 and 23 years and was acquired on a Philips Achieva 1.5 Tesla scanner. A second dataset (N = 38) was acquired on a different (but identical) 1.5 T scanner and was used for independent replication of our results. We reconstructed whole brain networks using tractography. We operationalized fiber tract development as changes in mean diffusivity and radial diffusivity with age. Most fibers showed maturational changes in mean and radial diffusivity values throughout childhood and adolescence, likely reflecting increasing white matter integrity. The largest age-related changes were observed in association fibers within and between the frontal and parietal lobes. Furthermore, there was a simultaneous age-related decrease in average path length (P < 0.0001), increase in node strength (P < 0.0001) as well as network clustering (P = 0.001), which may reflect fine-tuning of topological organization. These results suggest a sequential maturational model where connections between unimodal regions strengthen in childhood, followed by connections from these unimodal regions to association regions, while adolescence is characterized by the strengthening of connections between association regions within the frontal and parietal cortex. Hum Brain Mapp 37:717-729, 2016. © 2015 Wiley Periodicals, Inc.

DRD3 gene and striatum in autism spectrum disorder.

A single-nucleotide polymorphism (SNP) of the DRD3 gene (rs167771) was recently associated with autism spectrum disorders (ASD). Different polymorphisms of rs167771 corresponded to varying degrees of stereotyped behaviour. As DRD3 receptors are relatively overexpressed in the striatum, we investigated whether striatal volume was related to these polymorphisms in autism. We assessed volumes of caudate nucleus and putamen in 86 participants with ASD (mean age 15.3 years). MANCOVA showed an association between alleles of the rs167771 SNP and the volume of striatal structures. Furthermore, greater caudate nucleus volume correlated with stereotyped behaviour. These findings support a relationship between DRD3 gene SNPs, striatum and stereotyped behaviour in ASD.

Typical development of basal ganglia, hippocampus, amygdala and cerebellum from age 7 to 24.

Developmental imaging studies show that cortical grey matter decreases in volume during childhood and adolescence. However, considerably less research has addressed the development of subcortical regions (caudate, putamen, pallidum, accumbens, thalamus, amygdala, hippocampus and the cerebellar cortex), in particular not in longitudinal designs. We used the automatic labeling procedure in FreeSurfer to estimate the developmental trajectories of the volume of these subcortical structures in 147 participants (age 7.0-24.3years old, 94 males; 53 females) of whom 53 participants were scanned twice or more. A total of 223 magnetic resonance imaging (MRI) scans (acquired at 1.5-T) were analyzed. Substantial diversity in the developmental trajectories was observed between the different subcortical gray matter structures: the volume of caudate, putamen and nucleus accumbens decreased with age, whereas the volume of hippocampus, amygdala, pallidum and cerebellum showed an inverted U-shaped developmental trajectory. The thalamus showed an initial small increase in volume followed by a slight decrease. All structures had a larger volume in males than females over the whole age range, except for the cerebellum that had a sexually dimorphic developmental trajectory. Thus, subcortical structures appear to not yet be fully developed in childhood, similar to the cerebral cortex, and continue to show maturational changes into adolescence. In addition, there is substantial heterogeneity between the developmental trajectories of these structures.

Development of cortical thickness and surface area in autism spectrum disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder often associated with changes in cortical volume. The constituents of cortical volume - cortical thickness and surface area - have separable developmental trajectories and are related to different neurobiological processes. However, little is known about the developmental trajectories of cortical thickness and surface area in ASD. In this magnetic resonance imaging (MRI) study, we used an accelerated longitudinal design to investigate the cortical development in 90 individuals with ASD and 90 typically developing controls, aged 9 to 20 years. We quantified cortical measures using the FreeSurfer software package, and then used linear mixed model analyses to estimate the developmental trajectories for each cortical measure. Our primary finding was that the development of surface area follows a linear trajectory in ASD that differs from typically developing controls. In typical development, we found a decline in cortical surface area between the ages of 9 and 20 that was absent in ASD. We found this pattern in all regions where developmental trajectories for surface area differed between groups. When we applied a more stringent correction that takes the interdependency of measures into account, this effect on cortical surface area retained significance for left banks of superior temporal sulcus, postcentral area, and right supramarginal area. These areas have previously been implicated in ASD and are involved in the interpretation and processing of audiovisual social stimuli and distinction between self and others. Although some differences in cortical volume and thickness were found, none survived the more stringent correction for multiple testing. This study underscores the importance of distinguishing between cortical surface area and thickness in investigating cortical development, and suggests the development of cortical surface area is of importance to ASD.

Deficits in cognitive control, timing and reward sensitivity appear to be dissociable in ADHD.

Recent neurobiological models of ADHD suggest that deficits in different neurobiological pathways may independently lead to symptoms of this disorder. At least three independent pathways may be involved: a dorsal frontostriatal pathway involved in cognitive control, a ventral frontostriatal pathway involved in reward processing and a frontocerebellar pathway related to temporal processing. Importantly, we and others have suggested that disruptions in these three pathways should lead to separable deficits at the cognitive level. Furthermore, if these truly represent separate biological pathways to ADHD, these cognitive deficits should segregate between individuals with ADHD. The present study tests these hypotheses in a sample of children, adolescents and young adults with ADHD and controls. 149 Subjects participated in a short computerized battery assessing cognitive control, timing and reward sensitivity. We used Principal Component Analysis to find independent components underlying the variance in the data. The segregation of deficits between individuals was tested using Loglinear Analysis. We found four components, three of which were predicted by the model: Cognitive control, reward sensitivity and timing. Furthermore, 80% of subjects with ADHD that had a deficit were deficient on only one component. Loglinear Analysis statistically confirmed the independent segregation of deficits between individuals. We therefore conclude that cognitive control, timing and reward sensitivity were separable at a cognitive level and that deficits on these components segregated between individuals with ADHD. These results support a neurobiological framework of separate biological pathways to ADHD with separable cognitive deficits.

Imaging gene and environmental effects on cerebellum in Attention-Deficit/Hyperactivity Disorder and typical development.

This study investigates the effects of XKR4, a recently identified candidate gene for Attention-Deficit/Hyperactivity Disorder (ADHD), birth weight, and their interaction on brain volume in ADHD. XKR4 is expressed in cerebellum and low birth weight has been associated both with changes in cerebellum and with ADHD, probably due to its relation with prenatal adversity. Anatomical MRI scans were acquired in 58 children with ADHD and 64 typically developing controls and processed to obtain volumes of cerebrum, cerebellum and gray and white matter in each structure. DNA was collected from saliva. Analyses including data on birth weight were conducted in a subset of 37 children with ADHD and 51 controls where these data were retrospectively collected using questionnaires. There was an interaction between genotype and birth weight for cerebellum gray matter volume (p = .020). The combination of homozygosity for the G-allele (the allele previously found to be overtransmitted in ADHD) and higher birth weight was associated with smaller volume. Furthermore, birth weight was positively associated with cerebellar white matter volume in controls, but not ADHD (interaction: p = .021). The interaction of genotype with birth weight affecting cerebellum gray matter is consistent with models that emphasize increased influence of genetic risk-factors in an otherwise favorable prenatal environment. The absence of an association between birth weight and cerebellum white matter volume in ADHD suggests that other genetic or environmental effects may be at play, unrelated to XKR4. These results underscore the importance of considering environmental effects in imaging genetics studies.

Differential brain development with low and high IQ in attention-deficit/hyperactivity disorder.

Attention-Deficit/Hyperactivity Disorder (ADHD) and intelligence (IQ) are both heritable phenotypes. Overlapping genetic effects have been suggested to influence both, with neuroimaging work suggesting similar overlap in terms of morphometric properties of the brain. Together, this evidence suggests that the brain changes characteristic of ADHD may vary as a function of IQ. This study investigated this hypothesis in a sample of 108 children with ADHD and 106 typically developing controls, who participated in a cross-sectional anatomical MRI study. A subgroup of 64 children also participated in a diffusion tensor imaging scan. Brain volumes, local cortical thickness and average cerebral white matter microstructure were analyzed in relation to diagnostic group and IQ. Dimensional analyses investigated possible group differences in the relationship between anatomical measures and IQ. Second, the groups were split into above and below median IQ subgroups to investigate possible differences in the trajectories of cortical development. Dimensionally, cerebral gray matter volume and cerebral white matter microstructure were positively associated with IQ for controls, but not for ADHD. In the analyses of the below and above median IQ subgroups, we found no differences from controls in cerebral gray matter volume in ADHD with below-median IQ, but a delay of cortical development in a number of regions, including prefrontal areas. Conversely, in ADHD with above-median IQ, there were significant reductions from controls in cerebral gray matter volume, but no local differences in the trajectories of cortical development.In conclusion, the basic relationship between IQ and neuroanatomy appears to be altered in ADHD. Our results suggest that there may be multiple brain phenotypes associated with ADHD, where ADHD combined with above median IQ is characterized by small, more global reductions in brain volume that are stable over development, whereas ADHD with below median IQ is associated more with a delay of cortical development.

Basic impairments in regulating the speed-accuracy tradeoff predict symptoms of attention-deficit/hyperactivity disorder.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is characterized by poor optimization of behavior in the face of changing demands. Theoretical accounts of ADHD have often focused on higher-order cognitive processes and typically assume that basic processes are unaffected. It is an open question whether this is indeed the case. METHOD: We explored basic cognitive processing in 25 subjects with ADHD and 30 typically developing children and adolescents with a perceptual decision-making paradigm. We investigated whether individuals with ADHD were able to balance the speed and accuracy of decisions. RESULTS: We found impairments in the optimization of the speed-accuracy tradeoff. Furthermore, these impairments were directly related to the hyperactive and impulsive symptoms that characterize the ADHD-phenotype. CONCLUSIONS: These data suggest that impairments in basic cognitive processing are central to the disorder. This calls into question conceptualizations of ADHD as a "higher-order" deficit, as such simple decision processes are at the core of almost every paradigm used in ADHD research.