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Peer reviewed: True, More and more members of the autistic community and the research field are moving away from the idea that there will be a single biological or cognitive explanation for autistic characteristics. However, little is known about the complex dynamic processes that could explain why early difficulties in the language and motor domain often go hand-in-hand. We here study how language and motor skills develop simultaneously in the British Autism Study of Infant Siblings cohort of infants, and compare the way they are linked between children with and without developmental delays. Our results suggest that improvements in one domain go hand-in-hand with improvements in the other in both groups and show no compelling evidence for group differences in how motor skills relate to language and vice versa. We did observe a larger diversity in motor and language skills at 6 months, and because we found the motor and language development to be tightly linked, this suggests that even very small early impairments can result in larger developmental delays in later childhood. Greater variability at baseline, combined with very strong correlations between the slopes, suggests that dynamic processes may amplify small differences between individuals at 6months to result into large individual differences in autism symptomatology at 36 months.

Adverse experiences before the age of eighteen are common and include diverse events ranging from sexual abuse to parental divorce. These stressful experiences have been linked to physical and mental health issues. Previous research has focused mainly on childhood adversity, such as experiences in the family environment. Little consideration has been given to adversities that may be particularly harmful in adolescence. To understand adolescents’ adverse experiences, this project used data from the Avon Longitudinal Study of Parents and Children (ALSPAC, total N = 14,901, N ≈ 1,200 − 10,000 per measure). We modelled interrelations of adversities in childhood (1–11 years) and adolescence (11–23 years) and examined adversity clusters using network analysis. We found two similar clusters in the childhood and adolescence networks: (1) direct abuse and (2) adverse family factors. We identified a third cluster of (3) educational and social adversities for adolescence. For both age groups, emotional abuse in the family environment was closely linked to mental health in early adulthood and most adversities were linked with depression in early adulthood. In adolescence, housing and academic issues and abuse by a romantic partner were particularly central to the network of adversities. Thus, we found commonalities and differences in the relevance of adverse experiences at different developmental stages. These findings highlight the need to develop age-dependent frameworks for adversity research and policymaking.

Well-being and cognition are linked in adulthood, but how the two domains interact during development is currently unclear. Using a complex systems approach, we preregistered and modeled the relationship between well-being and cognition in a prospective cohort of 1,136 children between the ages of 6 to 7 years and 15 years. We found bidirectional interactions between well-being and cognition that unfold dynamically over time. Higher externalizing symptoms in childhood predicted fewer gains in planning over time (standardized estimate [β] = −0.14, p = .019), whereas higher childhood vocabulary predicted smaller increases in loneliness over time (β = −0.34, p ≤ .001). These interactions were characterized by modifiable risk and resilience factors: Relationships to parents, friendship quality, socioeconomic status, and puberty onset were all linked to both cognitive and well-being outcomes. Thus, cognition and well-being are inextricably intertwined during development and may be malleable to social and biological factors.

Contains fulltext : 248893.pdf (Publisher’s version ) (Open Access) Adolescence is a period of rapid change, with cognitive, mental wellbeing, environmental biological factors interacting to shape lifelong outcomes. Large, longitudinal phenotypically rich data sets available for reuse (secondary data) have revolutionized the way we study adolescence, allowing the field to examine these unfolding processes across hundreds or even thousands of individuals. Here, we outline the opportunities and challenges associated with such secondary data sets, provide an overview of particularly valuable resources available to the field, and recommend best practices to improve the rigor and transparency of analyses conducted on large, secondary data sets.

Entering puberty at a relatively young age is often thought to be associated with negative outcomes, such as poorer cardiovascular and psychosocial health. However, the literature on the relationship between early puberty, learning, and academic achievement is inconclusive. Previous work suggests both positive and negative health and cognitive outcomes after early puberty. We here review recent findings on the relationship between early puberty and cognitive outcomes and integrate these findings into larger theoretical frameworks of pubertal development. We argue that differences in observed outcomes may be explained by domain-specific and context-specific effects of early puberty. Early maturation may be linked to positive as well as negative cognitive outcomes, depending on the domain studied, and effects appear to be influenced by the wider social context, with less supportive environments associated with poorer outcomes for early maturers.

Charting human brain maturation between childhood and adulthood is a fundamental prerequisite for understanding the rapid biological and psychological changes during human development. Two barriers have precluded the quantification of maturational trajectories: demands on data and demands on estimation. Using high-temporal resolution neuroimaging data of up to 12-waves in the HUBU cohort (N = 90, aged 7-21 years) we investigate changes in apparent cortical thickness across childhood and adolescence. Fitting a four-parameter logistic nonlinear random effects mixed model, we quantified the characteristic, s-shaped, trajectory of cortical thinning in adolescence. This approach yields biologically meaningful parameters, including the midpoint of cortical thinning (MCT), which corresponds to the age at which the cortex shows most rapid thinning - in our sample occurring, on average, at 14 years of age. These results show that, given suitable data and models, cortical maturation can be quantified with precision for each individual and brain region.

The thickness and surface area of cortex are genetically distinct aspects of brain structure, and may be affected differently by age. However, their potential to differentially predict age and cognitive abilities has been largely overlooked, likely because they are typically aggregated into the commonly used measure of volume. In a large sample of healthy adults (N=647, aged 18-88), we investigated the brain-age and brain-cognition relationships of thickness, surface area, and volume, plus five additional morphological shape metrics. Cortical thickness was the metric most strongly associated with age cross-sectionally, as well as exhibiting the steepest longitudinal change over time (subsample N=261, aged 25-84). In contrast, surface area was the best single predictor of age-residualized cognitive abilities (fluid intelligence), and changes in surface area were most strongly associated with cognitive change over time. These findings were replicated in an independent dataset (N=1345, aged 18-93). Our results suggest that cortical thickness and surface area make complementary contributions the age-brain-cognition triangle, and highlight the importance of considering these volumetric components separately.

Wellbeing and cognition are linked in adulthood, but how the two domains interact during development is currently unclear. Using a complex systems approach, we preregistered and modelled the relationship between wellbeing and cognition in a prospective cohort of 1136 children, aged 6 - 7 up to 15 years. We found bidirectional interactions between wellbeing and cognition that unfold dynamically over time. Higher externalizing symptoms in childhood predicted fewer gains in planning over time (standardized estimate = - 0.14, p = .019), whereas higher childhood vocabulary predicted smaller increases in loneliness over time (standardized estimate = -0.34, p = < .001). These interactions were characterized by modifiable risk and resilience factors: Relationships to parents, friendship quality, socioeconomic status and puberty onset were all linked to both cognitive and wellbeing outcomes. As such, cognition and wellbeing are inextricably intertwined during development and may be malleable to social and biological factors.

We want to understand how children get so much better at certain cognitive abilities like reading, writing, and problem solving as they get older. To better understand this, we followed hundreds of children across a period of years, to see how abilities like problem solving and vocabulary changed over time. We found that having good vocabulary to start with made children’s problem solving develop more quickly. It also worked the other way around: being better at problem solving meant children were quicker to learn new words. In other words, each cognitive ability may help other abilities develop. This idea is called mutualism. We were very excited by this discovery, because it can help us understand how children get better at things they never practice directly, and how teachers can better help children who find certain school topics more challenging.

Cardiovascular health declines with age, increasing the risk of hypertension and elevated heart rate in middle and old age. Here, we used multivariate techniques to investigate the associations between cardiovascular health (diastolic blood pressure, systolic blood pressure, and heart rate) and white matter macrostructure (lesion volume and number) and microstructure (as measured by diffusion-weighted imaging) in the cross-sectional, population-based Cam-CAN cohort (N = 667, aged 18–88). We found that cardiovascular health and age made approximately similar contributions to white matter health and explained up to 56% of variance therein. Lower diastolic blood pressure, higher systolic blood pressure, and higher heart rate were each strongly, and independently, associated with white matter abnormalities on all indices. Body mass and exercise were associated with white matter health, both directly and indirectly via cardiovascular health. These results highlight the importance of cardiovascular risk factors for white matter health across the adult lifespan and suggest that systolic blood pressure, diastolic blood pressure, and heart rate affect white matter health via separate mechanisms., Highlights • Cardiovascular health is related to white matter lesion burden and diffusivity. • Low diastolic pressure, high systolic pressure, and higher heart rate contribute independently. • Cardiovascular health and age explain up to 56% of variance in white matter health. • The uncinate fasciculus, inferior fronto-occipital fasciculus, and forceps minor show most sensitivity. • Lower BMI and more exercise may have protective effects.

Highlights • In childhood and adolescence, cognitive ability is ‘best’ explained as consisting of two factors, gc and gf. • White matter tracts provide independent contributions to cognitive ability. • Associations between white matter and intelligence differed from childhood to adolescence., Despite the reliability of intelligence measures in predicting important life outcomes such as educational achievement and mortality, the exact configuration and neural correlates of cognitive abilities remain poorly understood, especially in childhood and adolescence. Therefore, we sought to elucidate the factorial structure and neural substrates of child and adolescent intelligence using two cross-sectional, developmental samples (CALM: N = 551 (N = 165 imaging), age range: 5–18 years, NKI-Rockland: N = 337 (N = 65 imaging), age range: 6–18 years). In a preregistered analysis, we used structural equation modelling (SEM) to examine the neurocognitive architecture of individual differences in childhood and adolescent cognitive ability. In both samples, we found that cognitive ability in lower and typical-ability cohorts is best understood as two separable constructs, crystallized and fluid intelligence, which became more distinct across development, in line with the age differentiation hypothesis. Further analyses revealed that white matter microstructure, most prominently the superior longitudinal fasciculus, was strongly associated with crystallized (gc) and fluid (gf) abilities. Finally, we used SEM trees to demonstrate evidence for developmental reorganization of gc and gf and their white matter substrates such that the relationships among these factors dropped between 7–8 years before increasing around age 10. Together, our results suggest that shortly before puberty marks a pivotal phase of change in the neurocognitive architecture of intelligence.

Despite the reliability of intelligence measures in predicting important life outcomes such as educational achievement and mortality, the exact configuration and neural correlates of cognitive abilities remain poorly understood, especially in childhood and adolescence. Therefore, we sought to elucidate the factorial structure and neural substrates of child and adolescent intelligence using two cross-sectional, developmental samples (CALM: N = 551 (N = 165 imaging), age range: 5–18 years, NKI-Rockland: N = 337 (N = 65 imaging), age range: 6–18 years). In a preregistered analysis, we used structural equation modelling (SEM) to examine the neurocognitive architecture of individual differences in childhood and adolescent cognitive ability. In both samples, we found that cognitive ability in lower and typical-ability cohorts is best understood as two separable constructs, crystallized and fluid intelligence, which became more distinct across development, in line with the age differentiation hypothesis. Further analyses revealed that white matter microstructure, most prominently the superior longitudinal fasciculus, was strongly associated with crystallized (gc) and fluid (gf) abilities. Finally, we used SEM trees to demonstrate evidence for developmental reorganization of gc and gf and their white matter substrates such that the relationships among these factors dropped between 7–8 years before increasing around age 10. Together, our results suggest that shortly before puberty marks a pivotal phase of change in the neurocognitive architecture of intelligence. Keywords: Neurocognitive reorganization, Crystallized intelligence, Fluid intelligence, White matter, Structural equation modelling

SummaryAccurate identification of brain function is necessary to understand neurocognitive ageing, and thereby promote health and well-being. Many studies of neurocognitive aging have investigated brain function with the blood-oxygen level-dependent (BOLD) signal measured by functional magnetic resonance imaging. However, the BOLD signal is a composite of neural and vascular signals, which are differentially affected by aging. It is therefore essential to distinguish the age effects on vascularversusneural function. The BOLD signal variability at rest (known as resting state fluctuation amplitude, RSFA), is a safe, scalable and robust means to calibrate vascular responsivity, as an alternative to breath-holding and hypercapnia. However, the use of RSFA for normalization of BOLD imaging assumes that age differences in RSFA reflecting only vascular factors, rather than age-related differences in neural function (activity) or neuronal loss (atrophy). Previous studies indicate that two vascular factors, cardiovascular health and cerebrovascular function, are insufficient when used alone to fully explain age-related differences in RSFA. It remains possible that their joint consideration is required to fully capture age differences in RSFA. We tested the hypothesis that RSFA no longer varies with age after adjusting for a combination of cardiovascular and cerebrovascular measures. We also tested the hypothesis that RSFA variation with age is not associated with atrophy. We used data from the population-based, lifespan Cam-CAN cohort. After controlling for cardiovascular and cerebrovascular estimates alone, the residual variance in RSFA across individuals was significantly associated with age. However, when controlling for both cardiovascular and cerebrovascular estimates, the variance in RSFA was no longer associated with age. Grey matter volumes did not explain age-differences in RSFA, after controlling for cardiovascular health. The results were consistent between voxel-level analysis and independent component analysis. Our findings indicate that cardiovascular and cerebrovascular signals are together sufficient predictors of age differences in RSFA. We suggest that RSFA can be used to separate vascular from neuronal factors, to characterise neurocognitive aging. We discuss the implications and make recommendations for the use of RSFA in the research of aging.

Adolescence has been proposed to be a sensitive period of social development, during which the social environment has a heightened effect on brain and behaviour. As such, negative social experiences, such as social exclusion, may have particularly detrimental effects on psychological well-being. However, little is known about how social exclusion affects cognitive performance during this time of life. Here, we compared the effects of exclusion between adolescence and adulthood. We recruited 98 females in three age groups: young adolescents (N = 36, aged 10.1–14.0), mid-adolescents (N = 35, aged 14.3–17.9) and adults (N = 27, aged 18.3–38.1). All age groups showed reductions in mood after exclusion, compared to inclusion, in a virtual ball-tossing game. Young adolescents also showed reduced verbal working memory accuracy following exclusion. There was no effect of exclusion on visuo-spatial working memory in any age group. These results suggest young adolescent girls’ verbal working memory accuracy was affected by a short, virtual social exclusion experience. This highlights the importance of the social environment in adolescence and underlines the need to consider age differences in response to exclusion in the design and timing of social exclusion interventions in schools. Keywords: Cyberball, Sensitive period, Adolescence, n-back, Visuo-spatial working memory, Mood

Existing non-verbal ability tests are typically protected by copyright, preventingthem from being freely adapted or computerized. Working towards an openscience framework, we provide 80 novel, open-access abstract reasoning items,an online implementation, and item-level data from 659 participants agedbetween 11 and 33 years: the Matrix Reasoning Item Bank (“MaRs-IB”). EachMaRs-IB item consists of an incomplete matrix containing abstract shapes.Participants complete matrices by identifying relationships between the shapes.Our data demonstrate age differences in non-verbal reasoning accuracy, whichincreased during adolescence and stabilized in early adulthood. There was aslight linear increase in response times with age, resulting in a peak in efficiency(i.e., a measure combining speed and accuracy) in late adolescence. Overall, thedata suggests that the MaRs-IB is sensitive to developmental differences inreasoning accuracy. Further psychometric validation is recommended.

Much evidence suggests that the angular gyrus (AnG) is involved in episodic memory, but its precise role is yet to be determined. We examined two possible accounts, within the same experimental paradigm: the CoBRA account (Shimamura, 2011), which suggests that the AnG acts as a convergence zone that binds multimodal episodic features; and the Subjectivity account (Yazar et al., 2012), which implicates AnG involvement in subjective mnemonic experience (such as vividness or confidence). fMRI was employed during both encoding and retrieval of paired-associates. During study, female and male human participants memorised picture-pairs of common objects (in the unimodal task) or of an object-picture and an environmental sound (in the crossmodal task). At test, they performed a cued-recall task, and further indicated the vividness of their memory. During retrieval, BOLD activation in the AnG was greatest for vividly remembered associates, consistent with the Subjectivity account. During encoding, the same effect of vividness was found, but this was further modulated by task: Greater activations were associated with subsequent recall in the crossmodal than the unimodal task. Thus, encoding data suggests an additional role to the AnG in cross-modal integration, consistent with its role at retrieval proposed by CoBRA. These results resolve some of the puzzles in the literature and indicate that the AnG can play different roles during encoding and retrieval, determined by the cognitive demands posed by different mnemonic tasks.Significance StatementWe offer new insights into the multiplicity of processes that are associated with angular gyrus (AnG) activation during encoding and retrieval of newly formed memories. We used fMRI while human participants learned and subsequently recalled pairs of objects presented to the same sensory modality or to different modalities. We were able to show that the AnG is involved when vivid memories are created and retrieved, as well as when encoded information is integrated across different sensory modalities. These findings provide novel evidence for the contribution of the AnG to our subjective experience of remembering, alongside its role in integrative processes that promote subsequent memory.

Background: Fluid intelligence declines with advancing age, starting in early adulthood. Within-subject declines in fluid intelligence are highly correlated with contemporaneous declines in the ability to live and function independently. To support healthy aging, the mechanisms underlying these declines need to be better understood. Methods: In this pre-registered analysis, we applied latent growth curve modelling to investigate the neural determinants of longitudinal changes in fluid intelligence across three time points in 185,317 individuals (N=9,719 two waves, N=870 three waves) from the UK Biobank (age range: 39-73 years). Results: We found a weak but significant effect of cross-sectional age on the mean fluid intelligence score, such that older individuals scored slightly lower. However, the mean longitudinal slope was positive, rather than negative, suggesting improvement across testing occasions. Despite the considerable sample size, the slope variance was non-significant, suggesting no reliable individual differences in change over time. This null-result is likely due to the nature of the cognitive test used. In a subset of individuals, we found that white matter microstructure (N=8839, as indexed by fractional anisotropy) and grey-matter volume (N=9931) in pre-defined regions-of-interest accounted for complementary and unique variance in mean fluid intelligence scores. The strongest effects were such that higher grey matter volume in the frontal pole and greater white matter microstructure in the posterior thalamic radiations were associated with higher fluid intelligence scores. Conclusions: In a large preregistered analysis, we demonstrate a weak but significant negative association between age and fluid intelligence. However, we did not observe plausible longitudinal patterns, instead observing a weak increase across testing occasions, and no significant individual differences in rates of change, likely due to the suboptimal task design. Finally, we find support for our preregistered expectation that white- and grey matter make separate contributions to individual differences in fluid intelligence beyond age.

Cardiovascular health declines with age, increasing the risk of hypertension and elevated heart rate in middle- and old age. Here, we used multivariate techniques to investigate the associations between cardiovascular health (diastolic blood pressure, systolic blood pressure and heart rate) and white matter macrostructure (lesion volume and number), and microstructure (as measured by Diffusion Weighted Imaging) in the cross-sectional, population-based Cam-CAN cohort (N = 667, aged 18 to 88). We found that cardiovascular health and age made approximately similar contributions to white matter health and explained up to 56% of variance. Lower diastolic blood pressure, higher systolic blood pressure and higher heart rate were each strongly, and independently, associated with white matter abnormalities on all indices. Body mass and exercise were associated with white matter health, both directly and indirectly via cardiovascular health. These results highlight the importance of cardiovascular risk factors for white matter health across the adult lifespan and suggest that systolic blood pressure, diastolic blood pressure and heart rate affect white matter via separate mechanisms.

Most research on sensitive periods has focussed on early sensory, motor, and language development, but it has recently been suggested that adolescence might represent a second ‘window of opportunity’ in brain development. Here, we explore three candidate areas of development that are proposed to undergo sensitive periods in adolescence: memory, the effects of social stress, and drug use. We describe rodent studies, neuroimaging, and large-scale behavioural studies in humans that have yielded data that are consistent with heightened neuroplasticity in adolescence. Critically however, concrete evidence for sensitive periods in adolescence is mostly lacking. To provide conclusive evidence, experimental studies are needed that directly manipulate environmental input and compare effects in child, adolescent, and adult groups.

Existing non-verbal ability tests are typically protected by copyright, preventing them from being freely adapted or computerized. Working towards an open science framework, we provide 80 novel, open-access abstract reasoning items, an online implementation and item-level data from 659 participants aged between 11 and 33 years: the matrix reasoning item bank (MaRs-IB). Each MaRs-IB item consists of an incomplete matrix containing abstract shapes. Participants complete the matrices by identifying relationships between the shapes. Our data demonstrate age differences in non-verbal reasoning accuracy, which increased during adolescence and stabilized in early adulthood. There was a slight linear increase in response times with age, resulting in a peak in efficiency (i.e. a measure combining speed and accuracy) in late adolescence. Overall, the data suggest that the MaRs-IB is sensitive to developmental differences in reasoning accuracy. Further psychometric validation is recommended.

A.R. was supported by ERC Advanced Grant 230604 SOMACCA to W. Tecumseh Fitch. SMP was supported by funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement n. [311870]. Cumulative tool-based culture underwrote our species' evolutionary success, and tool-based nut-cracking is one of the strongest candidates for cultural transmission in our closest relatives, chimpanzees. However the social learning processes that may explain both the similarities and differences between the species remain unclear. A previous study of nut-cracking by initially naive chimpanzees suggested that a learning chimpanzee holding no hammer nevertheless replicated hammering actions it witnessed. This observation has potentially important implications for the nature of the social learning processes and underlying motor coding involved. In the present study, model and observer actions were quantified frame-by-frame and analysed with stringent statistical methods, demonstrating synchrony between the observer's and model's movements, cross-correlation of these movements above chance level and a unidirectional transmission process from model to observer. These results provide the first quantitative evidence for motor mimicking underlain by motor coding in apes, with implications for mirror neuron function. Publisher PDF

Accurate identification of brain function is necessary to understand neurocognitive aging, and thereby promote health and well‐being. Many studies of neurocognitive aging have investigated brain function with the blood‐oxygen level‐dependent (BOLD) signal measured by functional magnetic resonance imaging. However, the BOLD signal is a composite of neural and vascular signals, which are differentially affected by aging. It is, therefore, essential to distinguish the age effects on vascular versus neural function. The BOLD signal variability at rest (known as resting state fluctuation amplitude, RSFA), is a safe, scalable, and robust means to calibrate vascular responsivity, as an alternative to breath‐holding and hypercapnia. However, the use of RSFA for normalization of BOLD imaging assumes that age differences in RSFA reflecting only vascular factors, rather than age‐related differences in neural function (activity) or neuronal loss (atrophy). Previous studies indicate that two vascular factors, cardiovascular health (CVH) and cerebrovascular function, are insufficient when used alone to fully explain age‐related differences in RSFA. It remains possible that their joint consideration is required to fully capture age differences in RSFA. We tested the hypothesis that RSFA no longer varies with age after adjusting for a combination of cardiovascular and cerebrovascular measures. We also tested the hypothesis that RSFA variation with age is not associated with atrophy. We used data from the population‐based, lifespan Cam‐CAN cohort. After controlling for cardiovascular and cerebrovascular estimates alone, the residual variance in RSFA across individuals was significantly associated with age. However, when controlling for both cardiovascular and cerebrovascular estimates, the variance in RSFA was no longer associated with age. Grey matter volumes did not explain age differences in RSFA, after controlling for CVH. The results were consistent between voxel‐level analysis and independent component analysis. Our findings indicate that cardiovascular and cerebrovascular signals are together sufficient predictors of age differences in RSFA. We suggest that RSFA can be used to separate vascular from neuronal factors, to characterize neurocognitive aging. We discuss the implications and make recommendations for the use of RSFA in the research of aging., Impact Statement The use of resting state fluctuation amplitudes (RSFA) for normalization of BOLD imaging assumes that age differences in RSFA reflect only vascular factors, rather than age‐related differences in neural function or neuronal loss. In this multimodal and multivariate study of 250 population‐based adults (18–88 years of age), we found that cardiovascular and cerebrovascular signals together sufficiently captured the age differences in RSFA. Our findings establish RSFA as an important marker that can be used to separate vascular signals from neuronal signals in BOLD‐fMRI, allowing the development of better models of ageing and age‐related disorders.