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White matter T-map of voxels displaying a significant negative correlation between T 1 values and age. Results are masked using a P value image thresholded using α = 0.001 (FDR corrected). Results are shown on the group template created from the T 1 weighted images aligned to the MNI coordinate system.
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The human brain undergoes dramatic structural changes during childhood that co-occur with behavioral development. These age-related changes are documented for the brain's gray matter and white matter. However, their interrelation is largely unknown. In this study, we investigated age-related effects in cortical thickness (CT) and in cortical surfac...
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Context 1
... peaks were found bilaterally in the inferior fronto-occipital fascicle, the inferior and superior longitudinal fascicle as well as in the anterior, superior and posterior corona radiata, and in the corpus callosum. Figure 2 represents the T values of the dis- tribution, thresholded at P < 0.001, FDR corrected. ...
Context 2
... we found that the peak clusters of age-related effects in CT display a partial overlap with peak age-related effects in white matter microstructure and myelin (see in Supplementary Material, Table 2 and Fig. 2), this interaction does not overlap with the results yielded by the SA-qT 1 relationship. Previous studies indicated that myelination and the processes respon- sible for cortical thinning are mostly independent, as changes in myelin water fraction at the adjacent white matter does not seem to be the driving factor in cortical thinning ...
Similar publications
Background: Are cognitive and biological variables useful for predicting future behavioral outcomes? Method: In two independent groups, we measured a set of cognitive (fl uid and crystallized intelligence, working memory, and attention control) and biological (cortical thickness and cortical surface area) variables on two occasions separated by six...
Citations
... This study further disputes the so-called "balloon model" of WM growth, which posits that growing WM causes the cortex to expand by stretching its SA and squashing its CT (Seldon, 2005). Such a model may be valid in earlier childhood (Cafiero et al., 2018), but we found that as children enter adolescence, SA begins to decline along with CT while WM continues to grow. The paired reductions of CT and SA provide strong evidence of true tissue shrinkage, since expanding myelin should not reduce SA. ...
A fundamental puzzle about brain development is why the volume of gray matter (GM) apparently declines as white matter (WM) grows when children enter adolescence. Since pruned synapses are too small to affect GM volume, a prevailing theory posits that an expanded distribution of myelin causes the inner edge of the GM to “whiten” while total brain volume remains steady, shifting the MRI‐measured WM:GM boundary closer to the brain's outer surface. This theory inherently predicts that GM volume loss is concurrent with WM volume growth across regions, within sexes and over time, although these predictions have yet to be explicitly tested. In this study, we test these predictions by mapping regional GM and WM volumetric changes in 2333 participants of the Adolescent Brain Cognitive Development study aged 9–14 years who each received three MRI scans 2 years apart. We show that average GM and WM volume changes follow distinct spatial, temporal, and sex‐specific patterns, indicating that GM volume loss is not balanced by WM volume growth, although cortical GM thinning is weakly correlated with WM growth in some regions. We conclude that myelin is not the main source of measured GM volume loss, and we propose alternative candidates.
... From puberty until the early 20s, there is a significant increase in the volume of white matter (tissue in the central nervous system). The white matter consists mostly of nerve cell axons, which serve as conduits for transmitting information within the nervous system (Blakemore and Choudhury 2006;Cafiero et al. 2019;Gogtay et al. 2004;Paus 2010). These two biological processes, which occur in an accelerated manner during puberty, enable efficient and rapid communication in the nervous system, thus enabling more efficient information processing. ...
Antisocial behaviour arises from a complex interplay of innate and environmental factors, with the brain’s adaptability to shifting environmental demands playing a pivotal role. An important but scantly studied environmental factor – micro-geographic hot spots of crime – covers a broad array of problems that produce frequent triggers for antisocial behaviour. Despite the established influence of neural substrates and various environmental factors on antisocial behaviour, the impact of residing in high-risk, violent crime hot spots in Israel, as well as other global locales, remains understudied. This paper aims to elucidate the intricate interplay between neurobiological mechanisms and crime hot spots in the context of antisocial behaviour. Its objectives are twofold: first, to acquaint researchers with the existing literature on the subject; and second, to catalyse further research and robust discourse in this domain. The article commences by reviewing the behavioural manifestations of antisocial tendencies within the framework of crime hot spots. Subsequently, it delves into the influence of crime hot spots on neurocognitive substrates, particularly emphasizing their impact on developmental trajectories associated with antisocial tendencies and the expression of antisocial behaviours. In closing, the paper offers implications and conclusions pertinent to crime hot spots in Israel.
... Previous aging and brain reserve studies often focused on a single cortical morphometry 26,73 . However, more recent research has shown that different morphometric features may exhibit varying sensitivity to factors such as development, aging 74,75 , disease 76,77 , and life experiences [78][79][80] . For instance, Claussenius-Kalman and colleagues 81 reported that the effects of L2AoA on brain structure differed depending on the gray matter metric used. ...
Lifelong bilingualism may result in neural reserve against decline not only in the general cognitive domain, but also in social cognitive functioning. In this study, we show the brain structural correlates that are associated with second language age of acquisition (L2AoA) and theory of mind (the ability to reason about mental states) in normal aging. Participants were bilingual adults (46 young, 50 older) who completed a theory-of-mind task battery, a language background questionnaire, and an anatomical MRI scan to obtain cortical morphometric features (i.e., gray matter volume, thickness, and surface area). Findings indicated a theory-of-mind decline in older adults compared to young adults, controlling for education and general cognition. Importantly, earlier L2AoA and better theory-of-mind performance were associated with larger volume, higher thickness, and larger surface area in the bilateral temporal, medial temporal, superior parietal, and prefrontal brain regions. These regions are likely to be involved in mental representations, language, and cognitive control. The morphometric association with L2AoA in young and older adults were comparable, but its association with theory of mind was stronger in older adults than young adults. The results demonstrate that early bilingual acquisition may provide protective benefits to intact theory-of-mind abilities against normal age-related declines.
... Magnetic resonance imaging (MRI) has been widely used to gain insights into both the structural and functional development of the brain during this critical period. Anatomical MR images have revealed substantial increases in brain volume (Gao et al., 2017;Peterson et al., 2021), expansion of regional surface area (Huang et al., 2022;Cafiero et al., 2019), and developmental trajectories of cortical thickness Nie et al., 2014). Diffusion tensor imaging (DTI), a technique that provides insights into white matter microstructures, has revealed the rapid process of myelination and the establishment of white matter connectome (Bagonis et al., 2022;Cafiero et al., 2019;Tymofiyeva et al., 2013;Yap et al., 2011). ...
... Anatomical MR images have revealed substantial increases in brain volume (Gao et al., 2017;Peterson et al., 2021), expansion of regional surface area (Huang et al., 2022;Cafiero et al., 2019), and developmental trajectories of cortical thickness Nie et al., 2014). Diffusion tensor imaging (DTI), a technique that provides insights into white matter microstructures, has revealed the rapid process of myelination and the establishment of white matter connectome (Bagonis et al., 2022;Cafiero et al., 2019;Tymofiyeva et al., 2013;Yap et al., 2011). Resting-state functional MRI (rsfMRI) has been utilized to establish brain functional networks, uncovering temporal progression of various cognitive domains (Gao et al., 2017;Gilmore et al., 2018;Zhang et al., 2019). ...
Human brain undergoes rapid growth during the first few years of life. While previous research has employed graph theory to study early brain development, it has mostly focused on the topological attributes of the whole brain. However, examining regional graph-theory features may provide unique insights into the development of cognitive abilities. Utilizing a large and longitudinal rsfMRI dataset from the UNC/UMN Baby Connectome Project, we investigated the developmental trajectories of regional efficiency and evaluated the relationships between these changes and cognitive abilities using Mullen Scales of Early Learning during the first twenty-eight months of life. Our results revealed a complex and spatiotemporally heterogeneous development pattern of regional global and local efficiency during this age period. Furthermore, we found that the trajectories of the regional global efficiency at the left temporal occipital fusiform and bilateral occipital fusiform gyri were positively associated with cognitive abilities, including visual reception, expressive language, receptive language, and early learning composite scores (P < 0.05, FDR corrected). However, these associations were weakened with age. These findings offered new insights into the regional developmental features of brain topologies and their associations with cognition and provided evidence of ongoing optimization of brain networks at both whole-brain and regional levels.
... Surface area may also be influenced by factors that are inherent to the sMRI signal; for instance, as surface area is measured along the white matter surface, a blurring of the graywhite matter boundary may influence reliable surface area estimates (Storsve et al., 2014). Recently, emerging evidence also suggests that surface area measures may be related to the myelination of cortico-cortical axons (Cafiero et al., 2019). For instance, white matter growth may induce a tangential stretching of the brain, leading to an increase in surface area (Seldon, 2005). ...
Autism has been associated with differences in the developmental trajectories of multiple neuroanatomical features, including cortical thickness, surface area, cortical volume, measures of gyrification, and the gray-white matter tissue contrast. These neuroimaging features have been proposed as intermediate phenotypes on the gradient from genomic variation to behavioral symptoms. Hence, examining what these proxy markers represent, i.e., disentangling their associated molecular and genomic underpinnings, could provide crucial insights into the etiology and pathophysiology of autism. In line with this, an increasing number of studies are exploring the association between neuroanatomical, cellular/molecular, and (epi)genetic variation in autism, both indirectly and directly in vivo and across age. In this review, we aim to summarize the existing literature in autism (and neurotypicals) to chart a putative pathway from (i) imaging-derived neuroanatomical cortical phenotypes to (ii) underlying (neuropathological) biological processes, and (iii) associated genomic variation.
... In view of that, we developed sex-specific models for each brain morphometric measure thus extending prior normative studies that considered males and females together (Bayer et al., 2022;Rutherford et al., 2022a). Additionally, we provide normative models for regional cortical surface area measures; changes in the cortical surface area have important functional implications for cognition during development (Cafiero et al., 2019;Wierenga et al., 2014;Vijayakumar et al., 2016) and aging (Lemaitre et al., 2012) but have been overlooked in prior normative studies (Bethlehem et al., 2022;Rutherford et al., 2022a). We note that the current normative model is compiled cross-sectionally, from people of different ages who experienced different exposures to factors that can influence brain health. ...
We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3–90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain ( https://centilebrain.org/ ).
... Even though adolescence is an especially important period in terms of the neurobiological pathway leading to psychosis 17 , few studies so far have focused on adolescents at CHR-P, or have considered structural imaging findings in the context of neurodevelopmental change 18,19 . Adolescence provides the opportunity to study possible deviations in the developmental trajectories of CSA associated with psychosis in relation to normotypical maturation 20,21 . Only one study to date has evaluated longitudinal change in CSA in an adolescent sample at CHR-P, but this study focused on resilience and did not provide data for actual transition to psychosis 18 . ...
... In our study we chose to examine regional CSA over other measures of cortical structure J o u r n a l P r e -p r o o f 14 because it has been shown to be more specific than gray matter volume and possibly less influenced by external factors than cortical thickness 9,11 . Although further research is needed to increase understanding of the etiopathological mechanisms underlying changes in CSA leading to psychosis, deviance in processes which characterize neurodevelopment, such as intracortical myelination, synaptic pruning and/or dendritic arborization 20,21,43 , have been suggested to play a potential role. ...
Objective:
Identifying biomarkers of transition to psychosis in individuals at clinical high-risk for psychosis (CHR-P) is essential to understand the mechanisms underlying the disease. Although cross-sectional abnormalities in cortical surface area (CSA) have been demonstrated in individuals at CHR-P who transition to psychosis (CHR-P-T) compared to those who do not (CHR-P-NT), how CSA longitudinally develops remains unclear, especially in younger individuals. We set out to compare CSA in adolescents at CHR-P and healthy controls (HC) over two points in time.
Method:
A longitudinal multicenter study was performed in adolescents at CHR-P in comparison to HC and according to transition to psychosis. MRI scans were acquired at baseline, at 18-month follow-up or at the time of transition. Images were pre-processed and hemisphere and regional CSA were computed using FreeSurfer. Between group analyses were performed with linear mixed effects models.
Results:
A total of 313 scans (107 CHR-P and 102 HC) were included in the analysis. At 18 months, rate of transition to psychosis in CHR-P was 23.4%. Adolescents at CHR-P-T presented greater age-related decrease in CSA in the left parietal and occipital lobes compared to HC; and in the bilateral parietal lobe and right frontal lobe relative to CHR-P-NT. These results were not influenced by antipsychotic treatment, cannabis use or intelligence quotient.
Conclusion:
Adolescents at CHR-P that developed a psychotic disorder presented different developmental trajectories of CSA relative to those who did not. A relatively greater decrease in CSA in the parietal and frontal lobes may index clinical transition to psychosis in adolescents at CHR-P.
... Cortical surface area has been shown to expand dramatically across the entire cortex between infancy and adulthood with a peak in late childhood (Li et al. 2014;Lyall et al. 2015). On a regional level, this increase in cortical surface area is positively related to cognitive development in childhood (Walhovd et al. 2016;Cafiero et al. 2019;Grosse Wiesmann et al. 2020). The developmental trajectory of cortical thickness, in contrast, is less clear, as its peak depends on complementary microphysiological processes and is subject to considerable local and interindividual variation (Shaw et al. 2006;Cafiero et al. 2019;Natu et al. 2019;Grosse Wiesmann et al. 2020). ...
... On a regional level, this increase in cortical surface area is positively related to cognitive development in childhood (Walhovd et al. 2016;Cafiero et al. 2019;Grosse Wiesmann et al. 2020). The developmental trajectory of cortical thickness, in contrast, is less clear, as its peak depends on complementary microphysiological processes and is subject to considerable local and interindividual variation (Shaw et al. 2006;Cafiero et al. 2019;Natu et al. 2019;Grosse Wiesmann et al. 2020). A range of studies suggest that cortical thickness peaks around late childhood and thins thereafter, with association cortices showing a later peak than sensory and motor cortices (Sowell 2004;Shaw et al. 2008). ...
... A range of studies suggest that cortical thickness peaks around late childhood and thins thereafter, with association cortices showing a later peak than sensory and motor cortices (Sowell 2004;Shaw et al. 2008). Accordingly, depending on the age, cognitive domain, and brain region, cortical thickness has been found to be either positively or negatively related to cognitive function (Shaw et al. 2006;Cafiero et al. 2019;Grosse Wiesmann et al. 2020). ...
Within the first years of life, children learn major aspects of their native language. However, the ability to process complex sentence structures, a core faculty in human language called syntax, emerges only slowly. A milestone in syntax acquisition is reached around the age of 4 years, when children learn a variety of syntactic concepts. Here, we ask which maturational changes in the child’s brain underlie the emergence of syntactically complex sentence processing around this critical age. We relate markers of cortical brain maturation to 3- and 4-year-olds’ sentence processing in contrast to other language abilities. Our results show that distinct cortical brain areas support sentence processing in the two age groups. Sentence production abilities at 3 years were associated with increased surface area in the most posterior part of the left superior temporal sulcus, whereas 4-year-olds showed an association with cortical thickness in the left posterior part of Broca’s area, i.e. BA44. The present findings suggest that sentence processing abilities rely on the maturation of distinct cortical regions in 3- compared to 4-year-olds. The observed shift to more mature regions involved in processing syntactically complex sentences may underlie behavioral milestones in syntax acquisition at around 4 years.
... Although the neural bases of first and second language acquisition are discussed to be partly overlapping (Perani & Abutalebi, 2005), there may be substantial differences, in that second language acquisition relies on more variable and widespread neural networks (Cargnelutti et al., 2019;Dehaene et al., 1997) compared to the relatively well defined first language network (Friederici, 2011(Friederici, , 2017. For native language acquisition, we found developmental changes in the gray and white matter of the language network (Cafiero et al., 2019;Ekerdt et al., 2020;Huber et al., 2018). In adults, the language capabilities are largely established, which is paralleled by a fully matured language network (Skeide et al., 2016). ...
Individual differences in the ability to process language have long been discussed. Much of the neural basis of these, however, is yet unknown. Here we investigated the relationship between long-range white matter connectivity of the brain, as revealed by diffusion tractography, and the ability to process syntactically complex sentences in the participants' native language as well as the improvement thereof by multiday training. We identified specific network motifs by singular value decomposition that indeed related white matter structural connectivity to individual language processing performance. First, for two such motifs, one in the left and one in the right hemisphere, their individual prevalence significantly predicted the individual language performance, suggesting an anatomical predisposition for the individual ability to process syntactically complex sentences. Both motifs comprise a number of cortical regions, but seem to be dominated by areas known for the involvement in working memory rather than the classical language network itself. Second, we identified another left hemispheric network motif, whose change of prevalence over the training period significantly correlated with the individual change in performance, thus reflecting training induced white matter plasticity. This motif comprises diverse cortical areas including regions known for their involvement in language processing, working memory and motor functions. The present findings suggest that individual differences in language processing and learning can be explained, in part, by individual differences in the brain's white matter structure. Brain structure may be a crucial factor to be considered when discussing variations in human cognitive performance, more generally.
... Normative changes in surface area and gyrification have also been documented at later stages of the lifespan and may index underlying cellular processes including synaptogenesis, dendritic branching and myelination (Cafiero et al., 2019;White et al., 2010). However, surface area and gyrification are generally shown to be less influenced by changeable factors such as socioeconomic status or medication as is cortical thickness Piccolo et al., 2016). ...
... Surface area is proposed to be influenced by the number of ontogenetic cortical columns situated perpendicular to the surface of the brain (Mountcastle, 1997). While the organisation of these columns is influenced by neurogenesis, cell proliferation, and neuronal migration from the ventricular zone during early foetal development, ongoing cellular processes including synaptogenesis, intra-cortical myelination and dendritic arborization are thought to continue to shape cortical surface area expansion beyond this early time window (Cafiero et al., 2019;Rakic, 1988). Although cortical surface area and gyrification are positively related, the former has been found to reach maturity during late childhood/early adolescence, while the development of gyrification is greatest in the third trimester of pregnancy and peaks prior to toddlerhood (Bethlehem et al., 2022;Cafiero et al., 2019;Raznahan et al., 2011;Wierenga et al., 2014). ...
... While the organisation of these columns is influenced by neurogenesis, cell proliferation, and neuronal migration from the ventricular zone during early foetal development, ongoing cellular processes including synaptogenesis, intra-cortical myelination and dendritic arborization are thought to continue to shape cortical surface area expansion beyond this early time window (Cafiero et al., 2019;Rakic, 1988). Although cortical surface area and gyrification are positively related, the former has been found to reach maturity during late childhood/early adolescence, while the development of gyrification is greatest in the third trimester of pregnancy and peaks prior to toddlerhood (Bethlehem et al., 2022;Cafiero et al., 2019;Raznahan et al., 2011;Wierenga et al., 2014). Hence, when considered relative to each other, measures of gyrification and surface area appear to index very early and slightly later peaking neurodevelopmental processes, respectively. ...
Background
Despite reports of altered brain morphology in established bipolar disorder (BD), there is limited understanding of when these morphological abnormalities emerge. Assessment of patients during the early course of illness can help to address this gap, but few studies have examined surface-based brain morphology in patients at this illness stage.
Methods
We completed a secondary analysis of baseline data from a randomised control trial of BD individuals stabilised after their first episode of mania (FEM). The magnetic resonance imaging scans of n = 35 FEM patients and n = 29 age-matched healthy controls were analysed. Group differences in cortical thickness, surface area and gyrification were assessed at each vertex of the cortical surface using general linear models. Significant results were identified at p < 0.05 using cluster-wise correction.
Results
The FEM group did not differ from healthy controls with regards to cortical thickness or gyrification. However, there were two clusters of increased surface area in the left hemisphere of FEM patients, with peak coordinates falling within the lateral occipital cortex and pars triangularis.
Conclusions
Cortical thickness and gyrification appear to be intact in the aftermath of a first manic episode, whilst cortical surface area in the inferior/middle prefrontal and occipitoparietal cortex is increased compared to age-matched controls. It is possible that increased surface area in the FEM group is the outcome of abnormalities in a premorbidly occurring process. In contrast, the findings raise the hypothesis that cortical thickness reductions seen in past studies of individuals with more established BD may be more attributable to post-onset factors.
