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Understanding how to respond to transgressions is central to cooperation, yet little is known about how individuals understand the consequences of these responses. Accordingly, the current study explored children's (ages 5-9), adolescents' (ages 11-14), and adults' (N = 544, predominantly White, ~50% female, tested in 2021) understandings of three such responses-forgiveness, punishment, and doing nothing. At all ages, participants differentiated between the consequences of these three responses. Forgiveness was associated with more positive and fewer negative outcomes, while the opposite was true for punishment and doing nothing. With age, participants were less likely to expect positive outcomes, and this effect was strongest for punishment and doing nothing. The results of this study allow novel insights into reasoning about three important response strategies., (© 2024 The Author(s). Child Development published by Wiley Periodicals LLC on behalf of Society for Research in Child Development.)

Although the path of Kagan's career led him inexorably toward biology, in the few years between his first benchmark publication on infancy and his later focus on temperament, he turned to other cultures in order to evaluate emerging insights about early development, namely, that major developmental transitions in behavior are maturational products. These forays contributed profoundly to our current understanding of culture and human development and inspired several of his students to focus their own careers on human development in culture, or, turned around, what we might call the developmental context of culture. Drawing largely on Kagan's own writings, this essay attempts to understand what the cross-cultural work meant to him and its lasting influence on his students. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Developmental science aims to explain development across the lifespan. Jerome Kagan observed that the same behavior can occur for different reasons, and differing behaviors can occur for the same reason. To help account for persistence, desistence, and transformation of behavior across development, Kagan introduced various types of continuity and discontinuity of forms and functions of behavior. This framework provides opportunities for identifying explanatory mechanisms in behavior development. However, misconceptions remain in applying the concepts that Kagan introduced. Much of the literature assumes developmental continuity in constructs without examining whether assumptions are supported, leading to faulty developmental inferences. For instance, the use of the same measure across time to assess development assumes that the behavior occurs for the same reason across time (homotypic continuity). In addition, just because one behavior predicts a different behavior at a later time does not necessarily indicate that age-differing behaviors occur for the same reason (heterotypic continuity). This review aims to advance conceptualizations of continuity and discontinuity from a contemporary perspective with aims to improve mechanistic understanding of behavior development across the lifespan. To better align behaviors, functions, and mechanisms, research should (a) examine (dis)continuity of individual behaviors rather than merely syndromes, (b) identify the function(s) of the given behavior(s), and (c) identify the cognitive and biological processes that underlie the behavior-function pairs. Incorporating examples from research on development of humans and nonhuman animals, I discuss challenges from work that has followed Kagan's ideas and ways to advance understanding of continuity and discontinuity across development. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Despite the well-established importance of prenatal experiences for offspring health throughout the lifespan, our understanding of prenatal influences on psychological outcomes faces challenges due to a wide-ranging and somewhat fragmented literature. Here, we introduce the special issue of Developmental Psychology , "Prenatal Influences Across the Life Course: Biobehavioral Mechanisms of Development," which draws together a broad collection of 12 empirical studies and one review article. These studies illustrate the diversity in biobehavioral mechanisms and biopsychosocial processes that help explain the long-term impacts of prenatal experiences on human development. Collectively, these studies help to disentangle sources of influence across different life stages (e.g., prenatal from genetic, preconception, and/or postnatal influences) and fill key gaps in the literature, such as the inclusion of minoritized populations currently underrepresented in research, the role of fathers, and protective mechanisms. The research featured in this special issue underscores both the long reach of prenatal influences on child and adolescent development as well as the challenges in observing specific biological mediators given that prenatal risks are currently operationalized as specific or broad cumulative measures. In an effort to organize this complex literature, we propose a guiding framework for how to conceptualize the continued integration of the prenatal environment into the field of developmental psychology. This framework broadens the prevailing dichotomous view of prenatal mechanisms as cumulative or specific to articulate a dimensional approach focused on adaptation. We anticipate that such an approach may uncover meaningful and observable biobehavioral mechanisms of prenatal influence on offspring development in the future. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Various animal and plant species exhibit allometric relationships among their respective traits, wherein one trait undergoes expansion as a power-law function of another due to constraints acting on growth processes. For instance, the acknowledged consensus posits that tree height scales with the two-thirds power of stem diameter. In the context of human development, it is posited that body weight scales with the second power of height. This prevalent allometric relationship derives its nomenclature from fitting two variables linearly within a logarithmic framework, thus giving rise to the term "power-law relationship." Here, we challenge the conventional assumption that a singular power-law equation adequately encapsulates the allometric relationship between any two traits. We strategically leverage quantile regression analysis to demonstrate that the scaling exponent characterizing this power-law relationship is contingent upon the centile within these traits' distributions. This observation fundamentally underscores the proposition that individuals occupying disparate segments of the distribution may employ distinct growth strategies, as indicated by distinct power-law exponents. We introduce the innovative concept of "multi-scale allometry" to encapsulate this newfound insight. Through a comprehensive reevaluation of (i) the height-weight relationship within a cohort comprising 7, 863, 520 Japanese children aged 5-17 years for which the age, sex, height, and weight were recorded as part of a national study, (ii) the stem-diameter-height and crown-radius-height relationships within an expansive sample of 498, 838 georeferenced and taxonomically standardized records of individual trees spanning diverse geographical locations, and (iii) the brain-size-body-size relationship within an extensive dataset encompassing 1, 552 mammalian species, we resolutely substantiate the viability of multi-scale allometric analysis. This empirical substantiation advocates a paradigm shift from uni-scaling to multi-scaling allometric modeling, thereby affording greater prominence to the inherent growth processes that underlie the morphological diversity evident throughout the living world., (© 2024. The Author(s).)

While model organisms have had many historians, this article places studies of humans, and particularly our development, in the politics of species choice. Human embryos, investigated directly rather than via animal surrogates, have gone through cycles of attention and neglect. In the past 60 years they moved from the sidelines to center stage. Research was resuscitated in anatomy, launched in reproductive biomedicine, molecular genetics, and stem-cell science, and made attractive in developmental biology. I explain this surge of interest in terms of rivalry with models and reliance on them. The greater involvement of medicine in human reproduction, especially through in vitro fertilization, gave access to fresh sources of material that fed critiques of extrapolation from mice and met demands for clinical relevance or "translation." Yet much of the revival depended on models. Supply infrastructures and digital standards, including biobanks and virtual atlases, emulated community resources for model organisms. Novel culture, imaging, molecular, and postgenomic methods were perfected on less precious samples. Toing and froing from the mouse affirmed the necessity of the exemplary mammal and its insufficiency justified inquiries into humans. Another kind of model-organoids and embryo-like structures derived from stem cells-enabled experiments that encouraged the organization of a new field, human developmental biology. Research on humans has competed with and counted on models., (© 2024. The Author(s).)

Ivancovsky et al.'s Novelty-Seeking Model suggests several mechanisms that might underlie developmental change in creativity and curiosity. We discuss how these implications both do and do not align with extant developmental findings, suggest two further elements that can provide a more complete developmental account, and discuss current methodological barriers to formulating an integrated developmental model of curiosity and creativity.

The Simon, Stroop, and Eriksen flanker tasks are commonly used to assess cognitive control across the lifespan. However, it remains unclear whether these three tasks in fact measure the same cognitive abilities and in the same proportion. We take a developmental approach to this question: if the Simon, Stroop, and flanker tasks all roughly measure the same capacity, they should show similar patterns of age-related change. We present data from two massive online cross-sectional studies: Study 1 included 9,585 native English speakers between 10 and 80 years of age who completed the Simon and Stroop tasks, and Study 2 included 13,448 English speakers between 10 and 79 years of age who completed the flanker task. Of the three tasks, only the flanker task revealed an inverted U-shaped developmental trajectory, with performance improving until approximately 23 years of age and declining starting around 40 years of age. Performance on the Simon and Stroop tasks peaked around 34 and 26 years of age, respectively, and did not decline significantly in later life, though it is possible that age-related declines would be observed with more difficult versions of the tasks. Although the Simon and Stroop tasks are commonly interpreted to target similar underlying processes, we observed near zero correlations between the congruency effects observed in each task in terms of both accuracy and response time. We discuss these results in light of recent debates regarding the suitability of these tasks for assessing developmental and individual differences in cognitive control. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Historically, the immune system was believed to develop along a linear axis of maturity from fetal life to adulthood. Now, it is clear that distinct layers of immune cells are generated from unique waves of hematopoietic progenitors during different windows of development. This model, known as the layered immune model, has provided a useful framework for understanding why distinct lineages of B cells and γδ T cells arise in succession and display unique functions in adulthood. However, the layered immune model has not been applied to CD8 + T cells, which are still often viewed as a uniform population of cells belonging to the same lineage, with functional differences between cells arising from environmental factors encountered during infection. Recent studies have challenged this idea, demonstrating that not all CD8 + T cells are created equally and that the functions of individual CD8 + T cells in adults are linked to when they were created in the host. In this review, we discuss the accumulating evidence suggesting there are distinct ontogenetic subpopulations of CD8 + T cells and propose that the layered immune model be extended to the CD8 + T cell compartment., (© 2023 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Convolutional neural networks (CNN) can accurately predict chronological age in healthy individuals from structural MRI brain scans. Potentially, these models could be applied during routine clinical examinations to detect deviations from healthy ageing, including early-stage neurodegeneration. This could have important implications for patient care, drug development, and optimising MRI data collection. However, existing brain-age models are typically optimised for scans which are not part of routine examinations (e.g., volumetric T1-weighted scans), generalise poorly (e.g., to data from different scanner vendors and hospitals etc.), or rely on computationally expensive pre-processing steps which limit real-time clinical utility. Here, we sought to develop a brain-age framework suitable for use during routine clinical head MRI examinations. Using a deep learning-based neuroradiology report classifier, we generated a dataset of 23,302 'radiologically normal for age' head MRI examinations from two large UK hospitals for model training and testing (age range = 18-95 years), and demonstrate fast (< 5 s), accurate (mean absolute error [MAE] < 4 years) age prediction from clinical-grade, minimally processed axial T2-weighted and axial diffusion-weighted scans, with generalisability between hospitals and scanner vendors (Δ MAE < 1 year). The clinical relevance of these brain-age predictions was tested using 228 patients whose MRIs were reported independently by neuroradiologists as showing atrophy 'excessive for age'. These patients had systematically higher brain-predicted age than chronological age (mean predicted age difference = +5.89 years, 'radiologically normal for age' mean predicted age difference = +0.05 years, p < 0.0001). Our brain-age framework demonstrates feasibility for use as a screening tool during routine hospital examinations to automatically detect older-appearing brains in real-time, with relevance for clinical decision-making and optimising patient pathways., Competing Interests: Declaration of Competing Interest Co-author Sebastien Ourselin is the co-founder of Brainminer; however, he did not control or analyse the data. The other authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Medial frontal theta-band oscillations are a robust marker of action-outcome monitoring. In a large developmental sample (n = 432, 9-16 years), we examined whether phase and non-phase locked medial frontal theta power were related to inhibitory control among children and adolescents. Our results showed that the well-established increase in medial frontal theta power during inhibitory control was captured largely by non-phase locked dynamics, which partially mediated the positive effect of age on task performance. A person-centered approach also revealed latent classes of individuals based on their multivariate theta power dynamics (phase locked/non-phase locked, GO/NOGO). The class of individuals showing low phase locked and high non-phase locked medial frontal theta were significantly older, had better inhibitory control, scored higher on measures of general cognitive function, and were more efficient in their behavioural responses. The functional significance of phase and non-phase locked theta dynamics, and their potential changes, could have important implications for action-outcome monitoring and cognitive function in both typical and atypical development, as well as related psychopathology ., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021. Published by Elsevier Inc.)

We investigated the role of age and gender in cognitive estimation abilities. Participants completed two online tasks, where different categories of estimation were assessed (speed estimation by time and distance, and auditory estimation). Data from a total of 18886 participants (9911 females) with ages between 18 and 65 years old were gathered. Results showed variations in the estimation capacity as a function of age, with a slow but progressive decline. Estimates of duration and sound seemed to be more affected by age than estimates of speed and movement. Overall, male participants showed a better performance on both auditory and visual estimation tasks compared to females., Competing Interests: The authors declare no conflict of interest. None of the authors are employees of CogniFit Inc., (© 2022 The Author(s). Published by IMR Press.)

Converging evidence from biopsychosocial research in humans and animals demonstrates that chronic sensory stimulation (via excessive screen exposure) affects brain development increasing the risk of cognitive, emotional, and behavioural disorders in adolescents and young adults. Emerging evidence suggests that some of these effects are similar to those seen in adults with symptoms of mild cognitive impairment (MCI) in the early stages of dementia, including impaired concentration, orientation, acquisition of recent memories (anterograde amnesia), recall of past memories (retrograde amnesia), social functioning, and self-care. Excessive screen time is known to alter gray matter and white volumes in the brain, increase the risk of mental disorders, and impair acquisition of memories and learning which are known risk factors for dementia. Chronic sensory overstimulation (i.e., excessive screen time) during brain development increases the risk of accelerated neurodegeneration in adulthood (i.e., amnesia, early onset dementia). This relationship is affected by several mediating/moderating factors (e.g., IQ decline, learning impairments and mental illness). We hypothesize that excessive screen exposure during critical periods of development in Generation Z will lead to mild cognitive impairments in early to middle adulthood resulting in substantially increased rates of early onset dementia in later adulthood. We predict that from 2060 to 2100, the rates of Alzheimer's disease and related dementias (ADRD) will increase significantly, far above the Centres for Disease Control (CDC) projected estimates of a two-fold increase, to upwards of a four-to-six-fold increase. The CDC estimates are based entirely on factors related to the age, sex, race and ethnicity of individuals born before 1950 who did not have access to mobile digital technology during critical periods of brain development. Compared to previous generations, the average 17-19-year-old spends approximately 6 hours a day on mobile digital devices (MDD) (smartphones, tablets, and laptop computers) whereas individuals born before 1950 at the same age spent zero. Our estimates include the documented effects of excessive screen time on individuals born after 1980, Millennials and Generation Z, who will be the majority of individuals ≥65 years old. An estimated 4-to-6-fold increase in rates of ADRD post-2060 will result in widespread societal and economic distress and the complete collapse of already overburdened healthcare systems in developed countries. Preventative measures must be set in place immediately including investments and interventions in public education, social policy, laws, and healthcare., Competing Interests: The authors declare no conflict of interest., (© 2022 The Author(s). Published by IMR Press.)

Objectives: Age-related differences in cognition are typically assessed by comparing groups of older to younger participants, but little is known about the continuous trajectory of cognitive changes across age, or when a shift to older adulthood occurs. We examined the pattern of mean age differences and variability on episodic memory and executive function measures over the adult life span, in a more fine-grained way than past group or life-span comparisons., Method: We used a sample of over 40,000 people aged 18-90 who completed psychometrically validated online tests measuring episodic memory and executive functions (the Cogniciti Brain Health Assessment)., Results: Cognitive performance declined gradually over adulthood, and rapidly later in life on spatial working memory, processing speed, facilitation (but not interference), associative recognition, and set shifting. Both polynomial and segmented regression fit the data well, indicating a nonlinear pattern. Segmented regression revealed a shift from gradual to rapid decline that occurred in the early 60s. Variability between people (interindividual variability or diversity) and variability within a person across tasks (intraindividual variability or dispersion) also increased gradually until the 60s, and rapidly after. Confirmatory factor analysis revealed a single general factor (of variance shared between tasks) offered a good fit for performance across tasks., Discussion: Life-span cognitive performance shows a nonlinear pattern, with gradual decline over early and mid-adulthood, followed by a transition in the 60s to notably accelerated, but more variable, decline. Some people show less decline than others, and some cognitive abilities show less within-person decline than others., (© The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America.)

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Children's learning capabilities change while growing up. One framework that describes the cognitive and neural development of children's growing learning abilities is the two-component model. It distinguishes processes that integrate separate features into a coherent memory representation (associative component) and executive abilities, such as elaboration, evaluation, and monitoring, that support memory processing (strategic component). In an fMRI study using an object-location association paradigm, we investigated how the two components influence memory performance across development. We tested children (10-12 years, n = 31), late adolescents (18 years, n = 29), and adults (25+ years, n = 30). For studying the associative component, we also probed how the utilisation of prior knowledge (schemas) facilitates memory across age groups. Children had overall lower retrieval performance, while adolescents and adults did not differ from each other. All groups benefitted from schemas, but this effect did not differ between groups. Performance differences between groups were associated with deactivation of the dorsal medial prefrontal cortex (dmPFC), which in turn was linked to executive functioning. These patterns were stronger in adolescents and adults and seemed absent in children. Thus, the children's executive system, the strategic component, is not as mature and thus cannot facilitate memory performance in the same way as in adolescents/adults. In contrast, we did not find age-related differences in the associative component; with activity in the angular gyrus predicting memory performance systematically across groups. Overall, our results suggest that differences of executive rather than associative abilities explain memory differences between children, adolescents, and adults., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Exploring typical and atypical brain developmental trajectories is very important for understanding the normal pace of brain development and the mechanisms by which mental disorders deviate from normal development. A precise and sex-specific brain age prediction model is desirable for investigating the systematic deviation and individual heterogeneity of disorders associated with atypical brain development, such as autism spectrum disorders. In this study, we used partial least squares regression and the stacking algorithm to establish a sex-specific brain age prediction model based on T1-weighted structural magnetic resonance imaging and resting-state functional magnetic resonance imaging. The model showed good generalization and high robustness on four independent datasets with different ethnic information and age ranges. A predictor weights analysis showed the differences and similarities in changes in structure and function during brain development. At the group level, the brain age gap estimation for autistic patients was significantly smaller than that for healthy controls in both the ABIDE dataset and the healthy brain network dataset, which suggested that autistic patients as a whole exhibited the characteristics of delayed development. However, within the ABIDE dataset, the premature development group had significantly higher Autism Diagnostic Observation Schedule (ADOS) scores than those of the delayed development group, implying that individuals with premature development had greater severity. Using these findings, we built an accurate typical brain development trajectory and developed a method of atypical trajectory analysis that considers sex differences and individual heterogeneity. This strategy may provide valuable clues for understanding the relationship between brain development and mental disorders., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

There is an increasing appreciation for the role of metabolism in cell signaling and cell decision making. Precise metabolic control is essential in development, as evident by the disorders caused by mutations in metabolic enzymes. The metabolic profile of cells is often cell-type specific, changing as cells differentiate or during tumorigenesis. Recent evidence has shown that changes in metabolism are not merely a consequence of changes in cell state but that metabolites can serve to promote and/or inhibit these changes. Metabolites can link metabolic pathways with cell signaling pathways via several mechanisms, for example, by serving as substrates for protein post-translational modifications, by affecting enzyme activity via allosteric mechanisms, or by altering epigenetic markers. Unraveling the complex interactions governing metabolism, gene expression, and protein activity that ultimately govern a cell's fate will require new tools and interactions across disciplines. On March 24 and 25, 2021, experts in cell metabolism, developmental biology, and human disease met virtually for the Keystone eSymposium, "Metabolic Decisions in Development and Disease." The discussions explored how metabolites impact cellular and developmental decisions in a diverse range of model systems used to investigate normal development, developmental disorders, dietary effects, and cancer-mediated changes in metabolism., (© 2021 New York Academy of Sciences.)

The ability to effectively and automatically regulate one's response to emotional information is a basic, fundamental skill for social functioning. The neural mechanisms underlying emotion regulation processing have been assessed, however few investigations have leveraged neurophysiological techniques, particularly magnetoencephalography (MEG) to determine the development of this critical ability. The current MEG study is the first to examine developmental changes in the neural mechanisms supporting automatic emotion regulation. We used an emotional go/no-go task with happy and angry faces in a single-site cohort of 97 healthy participants, 4-40 years of age. We found age-related changes as a function of emotion and condition in brain regions key to emotion regulation, including the right inferior frontal gyrus, orbitofrontal cortices and primarily right-lateralized temporal areas. Interaction effects, including an age by emotion and condition, were also found in the left angular gyrus, an area critical in emotion regulation and attention. Findings demonstrate protracted and nonlinear development, due to the adolescent group, of emotion regulation processing from child to adulthood, and highlight that age-related differences in emotion regulation are modulated by emotional face type., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Brain predicted age difference, or BrainPAD, compares chronological age to an age estimate derived by applying machine learning (ML) to MRI brain data. BrainPAD studies in youth have been relatively limited, often using only a single MRI modality or a single ML algorithm. Here, we use multimodal MRI with a stacked ensemble ML approach that iteratively applies several ML algorithms (AutoML). Eligible participants in the Healthy Brain Network (N = 489) were split into training and test sets. Morphometry estimates, white matter connectomes, or both were entered into AutoML to develop BrainPAD models. The best model was then applied to a held-out evaluation dataset, and associations with psychometrics were estimated. Models using morphometry and connectomes together had a mean absolute error of 1.18 years, outperforming models using a single MRI modality. Lower BrainPAD values were associated with more symptoms on the CBCL (p corr  = .012) and lower functioning on the Children's Global Assessment Scale (p corr  = .012). Higher BrainPAD values were associated with better performance on the Flanker task (p corr  = .008). Brain age prediction was more accurate using ComBat-harmonized brain data (MAE = 0.26). Associations with psychometric measures remained consistent after ComBat harmonization, though only the association with CGAS reached statistical significance in the reduced sample. Our findings suggest that BrainPAD scores derived from unharmonized multimodal MRI data using an ensemble ML approach may offer a clinically relevant indicator of psychiatric and cognitive functioning in youth., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

The insular cortex and anterior cingulate cortex together comprise the salience or midcingulo-insular network, involved in detecting salient events and initiating control signals to mediate brain network dynamics. The extent to which functional coupling between the salience network and the rest of the brain undergoes changes due to development and aging is at present largely unexplored. Here, we examine dynamic functional connectivity (dFC) of the salience network in a large life span sample (n = 601; 6-85 years old). A sliding-window analysis and k-means clustering revealed five states of dFC formed with the salience network, characterized by either widespread asynchrony or different patterns of synchrony between the salience network and other brain regions. We determined the frequency, dwell time, total transitions, and specific state-to-state transitions for each state and subject, regressing the metrics with subjects' age to identify life span trends. A dynamic state characterized by low connectivity between the salience network and the rest of the brain had a strong positive quadratic relationship between age and both frequency and dwell time. Additional frequency, dwell time, total transitions, and state-to-state transition trends were observed with other salience network states. Our results highlight the metastable dynamics of the salience network and its role in the maturation of brain regions critical for cognition., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Objectives: The theory of selective survival suggests that possibly around 70-75 years of age, Blacks may display substantive changes in their pattern of cognitive decline. This study examined the age-graded pattern of cognitive decline within older Blacks by describing a trend that characterizes differences in the change of cognitive decline from ages 51.5 to 95.5, and hypothesized that this age-graded pattern is nonlinear., Method: Utilizing 2 waves of longitudinal data from the Baltimore Study of Black Aging, this study used multilevel modeling to test whether the interaction between age and the 3-year study period (time between waves) had a positive effect on changes in inductive reasoning, declarative memory, working memory, and perceptual speed., Results: A significant positive interaction between age and wave was found for inductive reasoning, demonstrating an age-grade pattern of change/decline in cognitive pattern for Blacks aged 51.5-95.4. Simple slope probing via the Johnson-Neyman Technique suggested that Black adults ~64 years and younger experienced significant decline in inductive reasoning across study time, whereas for those older than 63.71, the decline was nonsignificant. No significant age-wave interactions were found for declarative memory, working memory, or perceptual speed., Discussion: Findings suggest a selective survival effect for inductive reasoning ability among Blacks. With decline evident so early, common cognitive intervention programs targeting adults 65+ may come too late for Blacks, signifying the importance and urgency for early health interventions and public policy designed to promote cognitive reserve., (© The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a behavioral phenotype characterized by impaired development of social-communicative skills and excessive repetitive and stereotyped behaviors. Despite high phenotypic heterogeneity in ASD, a meaningful subpopulation of children with ASD (∼90%) show significant general motor impairment. More focused studies on the nature of motor impairment in ASD reveal that children with ASD are particularly impaired on tasks such as ball catching and motor imitation that require efficient visual-motor integration (VMI). Motor computational approaches also provide evidence for VMI impairment showing that children with ASD form internal sensorimotor representations that bias proprioceptive over visual feedback. Impaired integration of visual information to form internal representations of others' and the external world may explain observed impairments on VMI tasks and motor imitation of others. Motor imitation is crucial for acquiring both social and motor skills, and impaired imitation skill may contribute to the observed core behavioral phenotype of ASD. The current review examines evidence supporting VMI impairment as a core feature of ASD that may contribute to both impaired motor imitation and social-communicative skill development. We propose that understanding the neurobiological mechanisms underlying VMI impairment in ASD may be key to discovery of therapeutics to address disability in children and adults with ASD., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The ability to enhance motivated performance through incentives is crucial to guide and ultimately optimise the outcome of goal-directed behaviour. It remains largely unclear how motivated behaviour and performance develops particularly across adolescence. Here, we used computational fMRI to assess how response speed and its underlying neural circuitry are modulated by reward and loss in a monetary incentive delay paradigm. We demonstrate that maturational fine-tuning of functional coupling within the cortico-striatal incentive circuitry from adolescence to adulthood facilitates the ability to enhance performance selectively for higher subjective values. Additionally, during feedback, we found developmental sex differences of striatal representations of reward prediction errors in an exploratory analysis. Our findings suggest that a reduced capacity to utilise subjective value for motivated behaviour in adolescence is rooted in immature information processing in the incentive system. This indicates that the neurocircuitry for coordination of incentivised, motivated cognitive control acts as a bottleneck for behavioural adjustments in adolescence., Competing Interests: Declaration of Competing Interest The authors declare no competing interests. Outside professional activities and interests of SB and SW are declared under the link of the University of Zurich https://www.uzh.ch/prof/apps/interessenbindungen/client/site/lang?lang=English., (Copyright © 2021. Published by Elsevier Inc.)

Resting-state neural activity plays an important role for cognitive control processes. Regarding response inhibition processes, an important facet of cognitive control, especially theta-band activity has been the focus of research. Theoretical considerations suggest that the interrelation of resting and task-related theta activity is subject to maturational effects. To investigate whether the relationship between resting theta activity and task-related theta activity during a response inhibition task changes even in young age, we tested N = 166 healthy participants between 8 and 30 years of age. We found significant correlations between resting and inhibitory control-related theta activity as well as behavioral inhibition performance. Importantly, these correlations were moderated by age. The moderation analysis revealed that higher resting theta activity was associated with stronger inhibition-related theta activity in individuals above the age of ~10.7 years. The EEG beamforming analysis showed that this activity is associated with superior frontal region function (BA6). The correlation between resting and superior frontal response inhibition-related theta activity became stronger with increasing age. A similar pattern was found for response inhibition performance, albeit only evident from the age of ~19.5 years. The results suggest that with increasing age, resting theta activity becomes increasingly important for processing the alarm/surprise signals in superior frontal brain regions during inhibitory control. Possible causes for these developmental changes are discussed., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with unknown brain etiology. Our knowledge to date about structural brain development across the lifespan in ASD comes mainly from cross-sectional studies, thereby limiting our understanding of true age effects within individuals with the disorder that can only be gained through longitudinal research. The present study describes FreeSurfer-derived volumetric findings from a longitudinal dataset consisting of 607 T1-weighted magnetic resonance imaging (MRI) scans collected from 105 male individuals with ASD (349 MRIs) and 125 typically developing male controls (258 MRIs). Participants were six to forty-five years of age at their first scan, and were scanned up to 5 times over a period of 16 years (average inter-scan interval of 3.7 years). Atypical age-related volumetric trajectories in ASD included enlarged gray matter volume in early childhood that approached levels of the control group by late childhood, an age-related increase in ventricle volume resulting in enlarged ventricles by early adulthood and reduced corpus callosum age-related volumetric increase resulting in smaller corpus callosum volume in adulthood. Larger corpus callosum volume was related to a lower (better) ADOS score at the most recent study visit for the participants with ASD. These longitudinal findings expand our knowledge of volumetric brain-based abnormalities in males with ASD, and highlight the need to continue to examine brain structure across the lifespan and well into adulthood., (Copyright © 2021. Published by Elsevier Inc.)

In the last few years, a significant amount of work has aimed to characterize maturational trajectories of cortical development. The role of pericortical microstructure putatively characterized as the gray-white matter contrast (GWC) at the pericortical gray-white matter boundary and its relationship to more traditional morphological measures of cortical morphometry has emerged as a means to examine finer grained neuroanatomical underpinnings of cortical changes. In this work, we characterize the GWC developmental trajectories in a representative sample (n = 394) of children and adolescents (~4 to ~22 years of age), with repeated scans (1-3 scans per subject, total scans n = 819). We tested whether linear, quadratic, or cubic trajectories of contrast development best described changes in GWC. A best-fit model was identified vertex-wise across the whole cortex via the Akaike Information Criterion (AIC). GWC across nearly the whole brain was found to significantly change with age. Cubic trajectories were likeliest for 63% of vertices, quadratic trajectories were likeliest for 20% of vertices, and linear trajectories were likeliest for 16% of vertices. A main effect of sex was observed in some regions, where males had a higher GWC than females. However, no sex by age interactions were found on GWC. In summary, our results suggest a progressive decrease in GWC at the pericortical boundary throughout childhood and adolescence. This work contributes to efforts seeking to characterize typical, healthy brain development and, by extension, can help elucidate aberrant developmental trajectories., Competing Interests: Declaration of Competing Interest None., (Copyright © 2021. Published by Elsevier Inc.)

Fear and safety learning are necessary adaptive behaviors that develop over the course of maturation. While there is a large body of literature regarding the neurobiology of fear and safety learning in adults, less is known regarding safety learning during development. Given developmental changes in the brain, there are corresponding changes in safety learning that are quantifiable; these may serve to predict risk and point to treatment targets for fear and anxiety-related disorders in children and adolescents. For healthy, typically developing youth, the main developmental variation observed is reduced discrimination between threat and safety cues in children compared to adolescents and adults, while lower expression of extinction learning is exhibited in adolescents compared to adults. Such distinctions may be related to faster maturation of the amygdala relative to the prefrontal cortex, as well as incompletely developed functional circuits between the two. Fear and anxiety-related disorders, childhood maltreatment, and behavioral problems are all associated with alterations in safety learning for youth, and this dysfunction may proceed into adulthood with corresponding abnormalities in brain structure and function-including amygdala hypertrophy and hyperreactivity. As impaired inhibition of fear to safety may reflect abnormalities in the developing brain and subsequent psychopathology, impaired safety learning may be considered as both a predictor of risk and a treatment target. Longitudinal neuroimaging studies over the course of development, and studies that query change with interventions are needed in order to improve outcomes for individuals and reduce long-term impact of developmental psychopathology., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Neurochemical profile and brain connectivity are both critical aspects of brain function. However, our knowledge of their interplay across development is currently poor. We combined single-voxel magnetic resonance spectroscopy and resting functional magnetic resonance imaging in a cross-sectional sample spanning from childhood to adulthood which was reassessed in ~1.5 years (N = 293). We revealed the developmental trajectories of 20 neurochemicals in two key developmental brain regions (the intraparietal sulcus, IPS, and the middle frontal gyrus, MFG). We found that certain neurochemicals exhibited similar developmental trajectories across the two regions, while other trajectories were region-specific. Crucially, we mapped the connectivity of the brain regions IPS and MFG to the rest of the brain across development as a function of regional glutamate and GABA concentration. We demonstrated that glutamate concentration within the IPS is modulated by age in explaining IPS connectivity with frontal, temporal and parietal regions. In mature participants, higher glutamate within the IPS was related to more negative connectivity while the opposite pattern was found for younger participants. Our findings offer specific developmental insights on the interplay between the brain's resting activity and the glutamatergic system both of which are crucial for regulating normal functioning and are dysregulated in several clinical conditions., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Although most dramatic structural changes occur in the perinatal period, a growing body of evidences demonstrates that adolescence and early adulthood are also important for substantial neurodevelopment. We were thus motivated to explore brain development during puberty by evaluating functional connectivity network (FCN) differences between childhood and young adulthood using multi-paradigm task-based functional magnetic resonance imaging (fMRI) measurements. Different from conventional multigraph based FCN construction methods where the graph network was built independently for each modality/paradigm, we proposed a multigraph learning model in this work. It promises a better fitting to FCN construction by jointly estimating brain network from multi-paradigm fMRI time series, which may share common graph structures. To investigate the hub regions of the brain, we further conducted graph Fourier transform (GFT) to divide the fMRI BOLD time series of a node within the brain network into a range of frequencies. Then we identified the hub regions characterizing brain maturity through eigen-analysis of the low frequency components, which were believed to represent the organized structures shared by a large population. The proposed method was evaluated using both synthetic and real data, which demonstrated its effectiveness in extracting informative brain connectivity patterns. We detected 14 hub regions from the child group and 12 hub regions from the young adult group. We show the significance of these findings with a discussion of their functions and activation patterns as a function of age. In summary, our proposed method can extract brain connectivity network more accurately by considering the latent common structures between different fMRI paradigms, which are significant for both understanding brain development and recognizing population groups of different ages., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

The g-ratio, defined as the inner-to-outer diameter of a myelinated axon, is associated with the speed of nerve impulse conduction, and represents an index of axonal myelination and integrity. It has been shown to be a sensitive and specific biomarker of neurodevelopment and neurodegeneration. However, there have been very few magnetic resonance imaging studies of the g-ratio in the context of normative aging; characterizing regional and time-dependent cerebral changes in g-ratio in cognitively normal subjects will be a crucial step in differentiating normal from abnormal microstructural alterations. In the current study, we investigated age-related differences in aggregate g-ratio, that is, g-ratio averaged over all fibers within regions of interest, in several white matter regions in a cohort of 52 cognitively unimpaired participants ranging in age from 21 to 84 years. We found a quadratic, U-shaped, relationship between aggregate g-ratio and age in most cerebral regions investigated, suggesting myelin maturation until middle age followed by a decrease at older ages. As expected, we observed that these age-related differences vary across different brain regions, with the frontal lobes and parietal lobes exhibiting slightly earlier ages of minimum aggregate g-ratio as compared to more posterior structures such as the occipital lobes and temporal lobes; this agrees with the retrogenesis paradigm. Our results provide evidence for a nonlinear association between age and aggregate g-ratio in a sample of adults from a highly controlled population. Finally, sex differences in aggregate g-ratio were observed in several cerebral regions, with women exhibiting overall lower values as compared to men; this likely reflects the greater myelin content in women's brain, in agreement with recent investigations., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Previous literature about the structural characterization of the human cerebellum is related to the context of a specific pathology or focused in a restricted age range. In fact, studies about the cerebellum maturation across the lifespan are scarce and most of them considered the cerebellum as a whole without investigating each lobule. This lack of study can be explained by the lack of both accurate segmentation methods and data availability. Fortunately, during the last years, several cerebellum segmentation methods have been developed and many databases comprising subjects of different ages have been made publically available. This fact opens an opportunity window to obtain a more extensive analysis of the cerebellum maturation and aging. In this study, we have used a recent state-of-the-art cerebellum segmentation method called CERES and a large data set (N = 2,831 images) from healthy controls covering the entire lifespan to provide a model for 12 cerebellum structures (i.e., lobules I-II, III, IV, VI, Crus I, Crus II, VIIB, VIIIA, VIIIB, IX, and X). We found that lobules have generally an evolution that follows a trajectory composed by a fast growth and a slow degeneration having sometimes a plateau for absolute volumes, and a decreasing tendency (faster in early ages) for normalized volumes. Special consideration is dedicated to Crus II, where slow degeneration appears to stabilize in elder ages for absolute volumes, and to lobule X, which does not present any fast growth during childhood in absolute volumes and shows a slow growth for normalized volumes., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Performing a goal-directed movement consists of a chain of complex preparatory mechanisms. Such planning especially requires integration (or binding) of various action features, a process that has been conceptualized in the "theory of event coding." Theoretical considerations and empirical research suggest that these processes are subject to developmental effects from adolescence to adulthood. The aim of the present study was to investigate age-related modulations in action feature binding processes and to shed light on underlying neurophysiological development from preadolescence to early adulthood. We examined a group of healthy participants ( n = 61) between 10 and 30 yr of age, who performed a task that requires a series of bimanual response selections in an embedded paradigm. For an in-depth analysis of the underlying neural correlates, we applied EEG signal decomposition together with source localization analyses. Behavioral results across the whole group did not show binding effects in reaction times but in intraindividual response variability. From age 10 to 30 yr, there was a decrease in reaction times and reaction time variability but no age-related effect in action file binding. The latter were corroborated by Bayesian data analyses. On the brain level, the developmental effects on response selection were associated with activation modulations in the superior parietal cortex (BA7). The results show that mechanisms of action execution and speed, but not those of action feature binding, are subject to age-related changes between the age of 10 and 30 yr. NEW & NOTEWORTHY Different aspects of an action need to be integrated to allow smooth unfolding of behavior. We examine developmental effects in these processes and show that mechanisms of action execution and speed, but not those of action feature binding, are subject to age-related changes between the age of 10 and 30 yr.

A number of studies have indicated alterations of brain morphology in individuals with autism spectrum disorder (ASD); however, how ASD influences the topological organization of the brain cortex at different developmental stages is not yet well characterized. In this study, we used structural images of 492 high-functioning participants in the Autism Brain Imaging Data Exchange database acquired from 17 international imaging centers, including 75 autistic children (age 7-11 years), 91 adolescents with ASD (age 12-17 years), and 80 young adults with ASD (age 18-29 years), and 246 typically developing controls (TDCs) that were age, gender, handedness, and full-scale IQ matched. Cortical thickness (CT) and surface area (SA) were extracted and the covariance between cortical regions across participants were treated as a network to examine developmental patterns of the cortical topological organization at different stages. A center-paired resampling strategy was developed to control the center bias during the permutation test. Compared with the TDCs, network of SA (but not CT) of individuals with ASD showed reduced small-worldness in childhood, and the network hubs were reorganized in the adulthood such that hubs inclined to connect with nonhub nodes and demonstrated more dispersed spatial distribution. Furthermore, the SA network of the ASD cohort exhibited increased segregation of the inferior parietal lobule and prefrontal cortex, and insular-opercular cortex in all three age groups, resulting in the emergence of two unique modules in the autistic brain. Our findings suggested that individuals with ASD may undergo remarkable remodeling of the cortical topology from childhood to adulthood, which may be associated with the altered social and cognitive functions in ASD., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

It is well established that temporal lobe epilepsy-the most common and well-studied form of epilepsy-can impair communication by disrupting social-emotional and language functions. In pediatric epilepsy, where seizures co-occur with the development of critical brain networks, age of onset matters: The earlier in life seizures begin, the worse the disruption in network establishment, resulting in academic hardship and social isolation. Yet, little is known about the processes by which epileptic activity disrupts developing human brain networks. Here we take a synthetic perspective-reviewing a range of research spanning studies on molecular and oscillatory processes to those on the development of large-scale functional networks-in support of a novel model of how such networks can be disrupted by epilepsy. We seek to bridge the gap between research on molecular processes, on the development of human brain circuitry, and on clinical outcomes to propose a model of how epileptic activity disrupts brain development., (Copyright © 2020 Elsevier B.V. All rights reserved.)

This review aims to establish the cognitive processing of patients with attention-deficit hyperactive disorder (ADHD) across age. Functional magnetic resonance imaging (fMRI) studies on children and adult populations were conducted, thus delineating deficits that could have been maintained and ameliorated across age. This allowed for the examination of the correlation between patterns of brain activation and the corresponding development of functional heterogeneity in ADHD. A systematic literature search of fMRI studies on ADHD was conducted using the PubMed and Scopus electronic databases based on PRISMA guidelines. References and citations were verified in Scopus database. The present study has identified 14 studies on children, 16 studies on adults, and one study on both populations of ADHD consisting of 1371 participants. Functional heterogeneity is present in ADHD across age, which can manifest either as different brain activation patterns, intra-subject variability, or both. This is shown in the increased role of the frontal regions and the specialized network in adults with ADHD from inefficient non-specific activation in childhood. Functional heterogeneity may manifest when delayed maturation is insufficient to normalize frontal lobe functions., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Since the beginning of life on earth, microorganisms have played a significant role in evolution. Throughout the history of Homo sapiens and its precursor humanoid forms, microorganisms have been present at birth and proliferated until death. It is at these extremes of life that the microbiome, especially that within the gastrointestinal tract, is most dynamic and perhaps has its greatest influence on host health. Here, we focus on the role of the gut microbiome as a regulator of brain and behaviour through key points in the human lifespan. We first describe trajectories of the microbiome in early life and ageing, before providing evidence for the existence of sensitive periods in the microbiome-gut-brain axis at these extremes of the lifespan. Finally, we briefly examine potential mechanisms for interactions between the microbiome and the brain during development and ageing., (© 2021 S. Karger AG, Basel.)

The human gut microbiome is a collection of bacteria, protozoa, fungi, and viruses that coexist in our bodies and are essential in protective, metabolic, and physiologic functions of human health. Gut dysbiosis has traditionally been linked to increased risk of infection, but imbalances within the intestinal microbial community structure that correlate with untoward inflammatory responses are increasingly recognized as being involved in disease processes that affect many organ systems in the body. Furthermore, it is becoming more apparent that the connection between gut dysbiosis and age-related diseases may lie in how the gut microbiome communicates with both the intestinal mucosa and the systemic immune system, given that these networks have a common interconnection to frailty. We therefore discuss recent advances in our understanding of the important role the microbiome plays in aging and how this knowledge opens the door for potential novel therapeutics aimed at shaping a less dysbiotic microbiome to prevent or treat age-related diseases., (Copyright © 2021 AGA Institute. Published by Elsevier Inc. All rights reserved.)

Objectives: Life experiences are thought to prompt changes in personality. However, existing studies find few replicable mean-level changes in personality following life events. The focus on mean-level change may obscure other types of personality change that are not routinely studied in the context of life events. These are variability in response, structural, and ipsative change., Methods: The current proposal examines whether major life events (e.g., divorce and job loss) affect these 3 understudied types of personality trait change using 3 waves of Big Five trait data in a large-scale, representative longitudinal study (German Socioeconomic Panel Study, N = 16,368). Structural equation models compare those who had an event to their prior self and a control group who did not experience the event., Results: Life events were found to have mostly null or small effects on variability in response, structural, and ipsative change. Across 2 types of tests for variability in response, few replications occurred. The only consistent effect across 3 types of change was for mental health events, which served to increase variance in all Big Five traits and increase consistency in ipsative profiles., Discussion: Life events tend not to affect these novel metrics of personality trait change. The one exception of mental health events is consistent with previous literature on mean-level change. Overall, life events do not appear to by major catalysts of personality change, regardless of how change is defined., (© The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Importance: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood., Objective: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia., Design, Setting, and Participants: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244., Main Outcomes and Measures: Interregional profiles of group difference in cortical thickness between cases and controls., Results: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders., Conclusions and Relevance: In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

Traditionally sex hormones have been associated with reproductive and developmental processes only. Since the 1950s we know that hormones can have organizational effects on the developing brain and initiate hormonal transition periods such as puberty. However, recent evidence shows that sex hormones additionally structure the brain during important hormonal transition periods across a woman's life including short-term fluctuations during the menstrual cycle. However, a comprehensive review focusing on structural changes during all hormonal transition phases of women is still missing. Therefore, in this review structural changes across hormonal transition periods (i.e., puberty, menstrual cycle, oral contraceptive intake, pregnancy and menopause) were investigated in a structured way and correlations with sex hormones evaluated. Results show an overall reduction in grey matter and region-specific decreases in prefrontal, parietal and middle temporal areas during puberty. Across the menstrual cycle grey matter plasticity in the hippocampus, the amygdala as well as temporal and parietal regions were most consistently reported. Studies reporting on pre- and post-pregnancy measurements revealed volume reductions in midline structures as well as prefrontal and temporal cortices. During perimenopause, the decline in sex hormones was paralleled with a reduction in hippocampal and parietal cortex volume. Brain volume changes were significantly correlated with estradiol, testosterone and progesterone levels in some studies, but directionality remains inconclusive between studies. These results indicate that sex hormones play an important role in shaping women's brain structure during different transition periods and are not restricted to specific developmental periods., (© 2020 S. Karger AG, Basel.)

Objectives: Personality traits have been related to concurrent memory performance. Most studies, however, have focused on personality as a predictor of memory; comparatively less is known about whether memory is related to personality development across adulthood. Using 4 samples, the present study tests whether memory level and change are related to personality change in adulthood., Method: Participants were drawn from 2 waves of the Wisconsin Longitudinal Study Graduates (WLSG; N = 3,232, mean age = 64.28, SD = 0.65) and Wisconsin Longitudinal Study Siblings (WLSS; N = 1,570, mean age = 63.52, SD = 6.69) samples, the Midlife in the United States (MIDUS; N = 1,901, mean age = 55.43, SD = 10.98), and the Health and Retirement Study (HRS; N = 6,038, mean age = 65.47, SD = 8.28). Immediate and delayed recall and the 5 major personality traits were assessed at baseline and follow-up., Results: There was heterogeneity in the associations across samples. A meta-analysis of latent change in the four samples indicated that lower baseline memory performance was related to an increase in neuroticism (B = -0.002; 95% CI = -0.004, -0.0008) and a decrease in agreeableness (B = 0.004; 95% CI = 0.002, 0.007) and conscientiousness (B = 0.005; 95% CI = 0.0008, 0.010). In addition, declines in memory were related to steeper declines in extraversion (B = 0.06; 95% CI = 0.003, 0.11), openness (B = 0.04; 95% CI = 0.007, 0.069), and conscientiousness (B = 0.05; 95% CI = 0.019, 0.09)., Discussion: The present study indicates that poor memory and declines in memory over time are related to maladaptive personality change. These associations, however, were small and inconsistent across samples., (© The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Studies of socioeconomic disparities have largely focused on correlating brain measures with either composite measure of socioeconomic status (SES), or its components-family income or parental education, giving little attention to the component of parental occupation. Emerging evidence suggests that parental occupation may be an important and neglected indicator of childhood and adolescent SES compared to absolute measures of material resources or academic attainment because, while related, it may more precisely capture position in social hierarchy and related health outcomes. On the other hand, although cortical thickness and surface area are brain measures with distinct genetic and developmental origins, large-scale neuroimaging studies investigating regional differences in interaction of the composite measure of SES or its components with cortical thickness and surface area are missing. We set out to fill this gap, focusing specifically on the role of parental occupation on cortical thickness and surface area by analyzing magnetic resonance imaging scans from 704 healthy individuals (age = 3-21 years). We observed spatially distributed patterns of (parental occupation × age 2 ) interaction with cortical thickness (localized at the left caudal middle frontal, the left inferior parietal and the right superior parietal) and surface area (localized at the left orbitofrontal cortex), indicating independent sources of variability. Further, with decreased cortical thickness, children from families with lower parental occupation exhibited lower self-esteem. Our findings demonstrate distinct influence of parental occupation on cortical thickness and surface area in children and adolescents, potentially reflecting different neurobiological mechanisms by which parental occupation may impact brain development., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)