Age-related differences in autism: The case of white matter microstructure.

Autism spectrum disorder (ASD) is typified as a brain connectivity disorder in which white matter abnormalities are already present early on in life. However, it is unknown if and to which extent these abnormalities are hard-wired in (older) adults with ASD and how this interacts with age-related white matter changes as observed in typical aging. The aim of this first cross-sectional study in mid- and late-aged adults with ASD was to characterize white matter microstructure and its relationship with age. We utilized diffusion tensor imaging with head motion control in 48 adults with ASD and 48 age-matched controls (30-74 years), who also completed a Flanker task. Intra-individual variability of reaction times (IIVRT) measures based on performance on the Flanker interference task were used to assess IIVRT-white matter microstructure associations. We observed primarily higher mean and radial diffusivity in white matter microstructure in ASD, particularly in long-range fibers, which persisted after taking head motion into account. Importantly, group-by-age interactions revealed higher age-related mean and radial diffusivity in ASD, in projection and association fiber tracts. Subtle dissociations were observed in IIVRT-white matter microstructure relations between groups, with the IIVRT-white matter association pattern in ASD resembling observations in cognitive aging. The observed white matter microstructure differences are lending support to the structural underconnectivity hypothesis in ASD. These reductions seem to have behavioral percussions given the atypical relationship with IIVRT. Taken together, the current results may indicate different age-related patterns of white matter microstructure in adults with ASD. Hum Brain Mapp 38:82-96, 2017. © 2016 Wiley Periodicals, Inc.

Computational meta-analysis of statistical parametric maps in major depression.

OBJECTIVE: Several neuroimaging meta-analyses have summarized structural brain changes in major depression using coordinate-based methods. These methods might be biased toward brain regions where significant differences were found in the original studies. In this study, a novel voxel-based technique is implemented that estimates and meta-analyses between-group differences in grey matter from individual MRI studies, which are then applied to the study of major depression. METHODS: A systematic review and meta-analysis of voxel-based morphometry studies were conducted comparing participants with major depression and healthy controls by using statistical parametric maps. Summary effect sizes were computed correcting for multiple comparisons at the voxel level. Publication bias and heterogeneity were also estimated and the excess of heterogeneity was investigated with metaregression analyses. RESULTS: Patients with major depression were characterized by diffuse bilateral grey matter loss in ventrolateral and ventromedial frontal systems extending into temporal gyri compared to healthy controls. Grey matter reduction was also detected in the right parahippocampal and fusiform gyri, hippocampus, and bilateral thalamus. Other areas included parietal lobes and cerebellum. There was no evidence of statistically significant publication bias or heterogeneity. CONCLUSIONS: The novel computational meta-analytic approach used in this study identified extensive grey matter loss in key brain regions implicated in emotion generation and regulation. Results are not biased toward the findings of the original studies because they include all available imaging data, irrespective of statistically significant regions, resulting in enhanced detection of additional areas of grey matter loss.

The neural coding of feedback learning across child and adolescent development.

The ability to learn from environmental cues is an important contributor to successful performance in a variety of settings, including school. Despite the progress in unraveling the neural correlates of cognitive control in childhood and adolescence, relatively little is known about how these brain regions contribute to learning. In this study, 268 participants aged 8-25 years performed a rule-learning task with performance feedback in a 3T MRI scanner. We examined the development of the frontoparietal network during feedback learning by exploring contributions of age and pubertal development. The pFC showed more activation following negative compared with positive feedback with increasing age. In contrast, our data suggested that the parietal cortex demonstrated a shift from sensitivity to positive feedback in young children to negative feedback in adolescents and adults. These findings were interpreted in terms of separable contributions of the frontoparietal network in childhood to more integrated functions in adulthood. Puberty (testosterone, estradiol, and self-report) did not explain additional variance in neural activation patterns above age, suggesting that development of the frontoparietal network occurs relatively independently from hormonal development. This study presents novel insights into the development of learning, moving beyond a simple frontoparietal immaturity hypothesis.

Delay discounting and frontostriatal fiber tracts: a combined DTI and MTR study on impulsive choices in healthy young adults.

Delay discounting, a measure of impulsive choice, has been associated with decreased control of the prefrontal cortex over striatum responses. The anatomical connectivity between both brain regions in delaying gratification remains unknown. Here, we investigate whether the quality of frontostriatal (FS) white matter tracts can predict individual differences in delay-discounting behavior. We use tract-based diffusion tensor imaging and magnetization transfer imaging to measure the microstructural properties of FS fiber tracts in 40 healthy young adults (from 18 to 25 years). We additionally explored whether internal sex hormone levels affect the integrity of FS tracts, based on the hypothesis that sex hormones modulate axonal density within prefrontal dopaminergic circuits. We calculated fractional anisotropy (FA), mean diffusivity (MD), longitudinal diffusivity, radial diffusivity (RD), and magnetization transfer ratio (MTR), a putative measure of myelination, for the FS tract. Results showed that lower integrity within the FS tract (higher MD and RD and lower FA), predicts faster discounting in both sexes. MTR was unrelated to delay-discounting performance. In addition, testosterone levels in males were associated with a lower integrity (higher RD) within the FS tract. Our study provides support for the hypothesis that enhanced structural integrity of white matter fiber bundles between prefrontal and striatal brain areas is associated with better impulse control.

Development of risk taking: contributions from adolescent testosterone and the orbito-frontal cortex.

The role of puberty in the development of risk taking remains poorly understood. Here, in a normative sample of 268 participants between 8 and 25 years old, we applied a psycho-endocrine neuroimaging approach to investigate the contribution of testosterone levels and OFC morphology to individual differences in risk taking. Risk taking was measured with the balloon analogue risk-taking task. We found that, corrected for age, higher endogenous testosterone level was related to increased risk taking in boys (more explosions) and girls (more money earned). In addition, a smaller medial OFC volume in boys and larger OFC surface area in girls related to more risk taking. A mediation analysis indicated that OFC morphology partly mediates the association between testosterone level and risk taking, independent of age. Mediation was found in such a way that a smaller medial OFC in boys potentiates the association between testosterone and risk taking but suppresses the association in girls. This study provides insights into endocrinological and neural underpinnings of normative development of risk taking, by indicating that OFC morphology, at least partly, mediates the association between testosterone and risk-taking behavior.

A three-year longitudinal functional magnetic resonance imaging study of performance monitoring and test-retest reliability from childhood to early adulthood.

Previous cross-sectional functional magnetic resonance imaging studies have shown that performance monitoring functions continue to develop well into adolescence, associated with increased activation in brain regions important for cognitive control (prefrontal cortex, anterior cingulate cortex, and parietal cortex). To date, however, the development of performance monitoring has not yet been studied longitudinally, which leaves open the question whether changes can be detected within individuals over time. In the present study, human boys and girls, between ages 8 and 27 years, performed a child-friendly rule-switch task in the scanner on two occasions ∼3.5 years apart. Change versus stability was examined using two methods: (1) repeated-measures analyses and (2) test-retest reliabilities of blood oxygenation level-dependent responses. Results showed that with increasing age, participants performed better on the task. The changes in neural activation associated with the processing of performance feedback were, however, more reliably correlated with changes in performance than with age. Test-retest reliability was at least fair to good for adults and adolescents, but poor to fair for the youngest age group. Substantially more variability was observed in the pattern and magnitude of children compared with adults, which may be interpreted as proxy for developmental change. Together, the results show that (1) change within individuals is variable, and more so for children than for adolescents and adults, and (2) performance is a better predictor for change in neural activation over time. These findings set the stage for studying developmental change in the perspective of multiple predictors, rather than solely by divisions based on age groups.

Hypothalamus and pituitary volume in schizophrenia: a structural MRI study.

Volumetric differences of the hypothalamus and/or the pituitary gland tend to support involvement of the HPA axis in psychotic disorders. These structures were manually outlined in 154 schizophrenia patients and 156 matched healthy comparison subjects by MRI brain images. Linear regression analyses were performed to investigate differences in volume between groups. Moreover, the effects of illness duration and type of medication were investigated. No significant differences were found between patients and healthy controls in volumes of the hypothalamus and pituitary gland. In addition, there were no differences in volumes between patients with short and long illness duration. There was a trend towards patients receiving typical antipsychotic medication at the time of scanning having larger pituitary volumes than patients receiving atypical medication. These findings indicate that volume decreases in brain structures important for the normal functioning of the HPA axis are not present, either in recent-onset or chronically ill patients.

Effects of brain-derived neurotrophic factor Val66Met polymorphism on hippocampal volume change in schizophrenia.

A functional polymorphism of the brain-derived neurotrophic factor (BDNF) gene (Val66Met) has been associated with the risk for schizophrenia and volume differences in the hippocampus. However, little is known about the association between progressive brain volume change in schizophrenia and BDNF genotype. The aim of this study was to investigate the relationship between hippocampal volume change in patients with schizophrenia and healthy control subjects and BDNF genotype. Two structural magnetic resonance imaging brain scans were acquired of 68 patients with schizophrenia and 83 healthy subjects with an interval of approximately 5 yrs. Hippocampal volume change was measured and related to BDNF genotype in patients and healthy controls. BDNF genotype was not associated with hippocampal volume change over time in patients or healthy controls, nor could we replicate earlier findings on smaller hippocampal volume in Met-carriers. However, we did find a genotype-by-diagnosis interaction at baseline demonstrating smaller hippocampal volumes in patients homozygous for the Val-allele relative to healthy Val-homozygotes. In addition, irrespective of genotype, patients showed smaller hippocampal volumes compared with healthy controls at baseline. In summary, our results suggest that the BDNF Val66Met polymorphism is not associated with hippocampal volume change over time. Nevertheless, our findings may support the possibility that BDNF affects brain morphology differently in schizophrenia patients and healthy subjects.

Brain volume abnormalities in major depressive disorder: a meta-analysis of magnetic resonance imaging studies.

OBJECTIVE: So far, there have been no attempts to integrate the growing number of all brain volumetric magnetic resonance imaging studies in depression. In this comprehensive meta-analysis the magnitude and extent of brain volume differences between 2,418 patients with major depressive disorder and 1,974 healthy individuals from 64 studies was determined. METHODS: A systematic research was conducted for volumetric magnetic resonance imaging studies of patients with major depressive disorder in relation to healthy control subjects. Studies had to report sufficient data for computation of effect sizes. For each study, the Cohen's d was calculated. All analyses were performed using the random effects model. Additionally, meta-regression analyses were done to explore the effects of potential sources of heterogeneity. RESULTS: Patients showed large volume reductions in frontal regions, especially in the anterior cingulate and orbitofrontal cortex with smaller reductions in the prefrontal cortex. The hippocampus, the putamen and caudate nucleus showed moderate volume reductions. CONCLUSIONS: This is the first comprehensive meta-analysis in major depressive disorder demonstrating structural brain abnormalities, particularly in those brain areas that are involved in emotion processing and stress-regulation.

Hypothalamus volume in twin pairs discordant for schizophrenia.

Monozygotic and same-sex dizygotic twin pairs discordant for schizophrenia were compared with matched control twin pairs in order to disentangle genetic and environmental contributions to variation in hypothalamus volume. A decrease in hypothalamus volume was found in patients or discordant twin pairs compared to healthy controls which could be attributed to the decrease in total brain volume. Higher within-twin pair similarities in monozygotic compared to dizygotic twin pairs, suggests that hypothalamus volume might be partly genetically controlled.

Gray Matter Characteristics in Mid and Old Aged Adults with ASD.

It is widely acknowledged that the brain anatomy of children and adolescents with autism spectrum disorder (ASD) shows a different developmental pattern then typical age-matched peers. There is however, a paucity of studies examining gray matter in mid and late adulthood in ASD. In this cross-sectional neuroimaging study, we, performed vertex-wise whole-brain and region-of-interest analyses of cortical volume, thickness, surface area, and gyrification index in 51 adults with and 49 without ASD, between 30 and 75 years. There was significant age-related volume loss and cortical thinning, but there were no group differences. The lack of significant anatomical differences between intellectual able individuals with and without ASD, suggests that ASD is not (strongly) related to gray matter morphology in mid and late adulthood.

Longitudinal development of frontoparietal activity during feedback learning: Contributions of age, performance, working memory and cortical thickness.

Feedback learning is a crucial skill for cognitive flexibility that continues to develop into adolescence, and is linked to neural activity within a frontoparietal network. Although it is well conceptualized that activity in the frontoparietal network changes during development, there is surprisingly little consensus about the direction of change. Using a longitudinal design (N=208, 8-27 years, two measurements in two years), we investigated developmental trajectories in frontoparietal activity during feedback learning. Our first aim was to test for linear and nonlinear developmental trajectories in dorsolateral prefrontal cortex (DLPFC), superior parietal cortex (SPC), supplementary motor area (SMA) and anterior cingulate cortex (ACC). Second, we tested which factors (task performance, working memory, cortical thickness) explained additional variance in time-related changes in activity besides age. Developmental patterns for activity in DLPFC and SPC were best characterized by a quadratic age function leveling off/peaking in late adolescence. There was a linear increase in SMA and a linear decrease with age in ACC activity. In addition to age, task performance explained variance in DLPFC and SPC activity, whereas cortical thickness explained variance in SMA activity. Together, these findings provide a novel perspective of linear and nonlinear developmental changes in the frontoparietal network during feedback learning.

Are Autistic Traits in the General Population Related to Global and Regional Brain Differences?

There is accumulating evidence that autistic-related traits in the general population lie on a continuum, with autism spectrum disorders representing the extreme end of this distribution. Here, we tested the hypothesis of a possible relationship between autistic traits and brain morphometry in the general population. Participants completed the short autism-spectrum quotient-questionnaire (AQ); T1-anatomical and DWI-scans were acquired. Associations between autistic traits and gray matter, and white matter microstructural-integrity were performed on the exploration-group (N = 204; 105 males, M-age = 22.85), and validated in the validation-group (N = 304; 155 males, M-age = 22.82). No significant associations were found between AQ-scores and brain morphometry in the exploration-group, or after pooling the data. This questions the assumption that autistic traits and their morphological associations do lie on a continuum in the general population.

The influence of sex steroids on structural brain maturation in adolescence.

Puberty reflects a period of hormonal changes, physical maturation and structural brain reorganization. However, little attention has been paid to what extent sex steroids and pituitary hormones are associated with the refinement of brain maturation across adolescent development. Here we used high-resolution structural MRI scans from 215 typically developing individuals between ages 8-25, to examine the association between cortical thickness, surface area and (sub)cortical brain volumes with luteinizing hormone, testosterone and estradiol, and pubertal stage based on self-reports. Our results indicate sex-specific differences in testosterone related influences on gray matter volumes of the anterior cingulate cortex after controlling for age effects. No significant associations between subcortical structures and sex hormones were found. Pubertal stage was not a stronger predictor than chronological age for brain anatomical differences. Our findings indicate that sex steroids are associated with cerebral gray matter morphology in a sex specific manner. These hormonal and morphological differences may explain in part differences in brain development between boys and girls.

The relation between gray matter morphology and divergent thinking in adolescents and young adults.

Adolescence and early adulthood are developmental time periods during which creative cognition is highly important for adapting to environmental changes. Divergent thinking, which refers to generating novel and useful solutions to open-ended problems, has often been used as a measure of creative cognition. The first goal of this structural neuroimaging study was to elucidate the relationship between gray matter morphology and performance in the verbal (AUT; alternative uses task) and visuo-spatial (CAT; creative ability test) domain of divergent thinking in adolescents and young adults. The second goal was to test if gray matter morphology is related to brain activity during AUT performance. Neural and behavioral data were combined from a cross-sectional study including 25 adolescents aged 15-17 and 20 young adults aged 25-30. Brain-behavior relationships were assessed without a priori location assumptions and within areas that were activated during an AUT-scanner task. Gray matter volume and cortical thickness were not significantly associated with verbal divergent thinking. However, visuo-spatial divergent thinking (CAT originality and fluency) was positively associated with cortical thickness of the right middle temporal gyrus and left brain areas including the superior frontal gyrus and various occipital, parietal, and temporal areas, independently of age. AUT brain activity was not associated with cortical thickness. The results support an important role of a widespread brain network involved in flexible visuo-spatial divergent thinking, providing evidence for a relation between cortical thickness and visuo-spatial divergent thinking in adolescents and young adults. However, studies including visuo-spatial divergent thinking tasks in the scanner are warranted.

Strategies influence neural activity for feedback learning across child and adolescent development.

Learning from feedback is an important aspect of executive functioning that shows profound improvements during childhood and adolescence. This is accompanied by neural changes in the feedback-learning network, which includes pre-supplementary motor area (pre- SMA)/anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), superior parietal cortex (SPC), and the basal ganglia. However, there can be considerable differences within age ranges in performance that are ascribed to differences in strategy use. This is problematic for traditional approaches of analyzing developmental data, in which age groups are assumed to be homogenous in strategy use. In this study, we used latent variable models to investigate if underlying strategy groups could be detected for a feedback-learning task and whether there were differences in neural activation patterns between strategies. In a sample of 268 participants between ages 8 to 25 years, we observed four underlying strategy groups, which were cut across age groups and varied in the optimality of executive functioning. These strategy groups also differed in neural activity during learning; especially the most optimal performing group showed more activity in DLPFC, SPC and pre-SMA/ACC compared to the other groups. However, age differences remained an important contributor to neural activation, even when correcting for strategy. These findings contribute to the debate of age versus performance predictors of neural development, and highlight the importance of studying individual differences in strategy use when studying development.

Cognitive strategy use as an index of developmental differences in neural responses to feedback.

Developmental differences in dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), and superior parietal cortex (SPC) activation are associated with differences in how children, adolescents, and adults learn from performance feedback in rule-learning tasks (Crone, Zanolie, Leijenhorst, Westenberg, & Rombouts, 2008). Both maturational differences and performance differences can potentially explain variance in functional brain activation. To disentangle those effects, we established strategy differences in the performance of participants on the task of Crone et al. (2008) by the application of latent mixture models (McLachlan & Peel, 2000). We found 4 categorically different strategies, which were divided across age groups. Both adults and adolescents were distributed among all strategy groups except for the worst performing one, whereas children were distributed among all strategy groups except for the best performing one. Strategy use was a mediator and largely explained the relation between age and variance in activation patterns in the DLPFC and the SPC but not in the ACC. These findings are interpreted vis-à-vis age versus performance predictors of brain development.

Sex differences and structural brain maturation from childhood to early adulthood.

Recent advances in structural brain imaging have demonstrated that brain development continues through childhood and adolescence. In the present cross-sectional study, structural MRI data from 442 typically developing individuals (range 8-30) were analyzed to examine and replicate the relationship between age, sex, brain volumes, cortical thickness and surface area. Our findings show differential patterns for subcortical and cortical areas. Analysis of subcortical volumes showed that putamen volume decreased with age and thalamus volume increased with age. Independent of age, males demonstrated larger amygdala and thalamus volumes compared to females. Cerebral white matter increased linearly with age, at a faster pace for females than males. Gray matter showed nonlinear decreases with age. Sex-by-age interactions were primarily found in lobar surface area measurements, with males demonstrating a larger cortical surface up to age 15, while cortical surface in females remained relatively stable with increasing age. The current findings replicate some, but not all prior reports on structural brain development, which calls for more studies with large samples, replications, and specific tests for brain structural changes. In addition, the results point toward an important role for sex differences in brain development, specifically during the heterogeneous developmental phase of puberty.

The neural coding of creative idea generation across adolescence and early adulthood.

Creativity is considered key to human prosperity, yet the neurocognitive principles underlying creative performance, and their development, are still poorly understood. To fill this void, we examined the neural correlates of divergent thinking in adults (25-30 years) and adolescents (15-17 years). Participants generated alternative uses (AU) or ordinary characteristics (OC) for common objects while brain activity was assessed using fMRI. Adults outperformed adolescents on the number of solutions for AU and OC trials. Contrasting neural activity for AU with OC trials revealed increased recruitment of left angular gyrus, left supramarginal gyrus, and bilateral middle temporal gyrus in both adults and adolescents. When only trials with multiple AU were included in the analysis, participants showed additional left inferior frontal gyrus (IFG)/middle frontal gyrus (MFG) activation for AU compared to OC trials. Correspondingly, individual difference analyses showed a positive correlation between activations for AU relative to OC trials in left IFG/MFG and divergent thinking performance and activations were more pronounced in adults than in adolescents. Taken together, the results of this study demonstrated that creative idea generation involves recruitment of mainly left lateralized parietal and temporal brain regions. Generating multiple creative ideas, a hallmark of divergent thinking, shows additional lateral PFC activation that is not yet optimized in adolescence.