Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Diffusion imaging genomics provides novel insight into early mechanisms of cerebral small vessel disease.

Cerebral small vessel disease (cSVD) is a leading cause of stroke and dementia. Genetic risk loci for white matter hyperintensities (WMH), the most common MRI-marker of cSVD in older age, were recently shown to be significantly associated with white matter (WM) microstructure on diffusion tensor imaging (signal-based) in young adults. To provide new insights into these early changes in WM microstructure and their relation with cSVD, we sought to explore the genetic underpinnings of cutting-edge tissue-based diffusion imaging markers across the adult lifespan. We conducted a genome-wide association study of neurite orientation dispersion and density imaging (NODDI) markers in young adults (i-Share study: N = 1 758, (mean[range]) 22.1[18-35] years), with follow-up in young middle-aged (Rhineland Study: N = 714, 35.2[30-40] years) and late middle-aged to older individuals (UK Biobank: N = 33 224, 64.3[45-82] years). We identified 21 loci associated with NODDI markers across brain regions in young adults. The most robust association, replicated in both follow-up cohorts, was with Neurite Density Index (NDI) at chr5q14.3, a known WMH locus in VCAN. Two additional loci were replicated in UK Biobank, at chr17q21.2 with NDI, and chr19q13.12 with Orientation Dispersion Index (ODI). Transcriptome-wide association studies showed associations of STAT3 expression in arterial and adipose tissue (chr17q21.2) with NDI, and of several genes at chr19q13.12 with ODI. Genetic susceptibility to larger WMH volume, but not to vascular risk factors, was significantly associated with decreased NDI in young adults, especially in regions known to harbor WMH in older age. Individually, seven of 25 known WMH risk loci were associated with NDI in young adults. In conclusion, we identified multiple novel genetic risk loci associated with NODDI markers, particularly NDI, in early adulthood. These point to possible early-life mechanisms underlying cSVD and to processes involving remyelination, neurodevelopment and neurodegeneration, with a potential for novel approaches to prevention.

Brain artery diameters and risk of dementia and stroke.

INTRODUCTION: We tested the association of brain artery diameters with dementia and stroke risk in three distinct population-based studies using conventional T2-weighted brain magnetic resonance imaging (MRI) images. METHODS: We included 8420 adults > 40 years old from three longitudinal population-based studies with brain MRI scans. We estimated and meta-analyzed the hazard ratios (HRs) of the brain and carotids and basilar diameters associated with dementia and stroke. RESULT: Overall and carotid artery diameters > 95th percentile increased the risk for dementia by 1.74 (95% confidence interval [CI], 1.13-2.68) and 1.48 (95% CI, 1.12-1.96) fold, respectively. For stroke, meta-analyses yielded HRs of 1.59 (95% CI, 1.04-2.42) for overall arteries and 2.11 (95% CI, 1.45-3.08) for basilar artery diameters > 95th percentile. DISCUSSION: Individuals with dilated brain arteries are at higher risk for dementia and stroke, across distinct populations. Our findings underline the potential value of T2-weighted brain MRI-based brain diameter assessment in estimating the risk of dementia and stroke.

Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation.

The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3-90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia 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 fractional polynomial regression (MFPR) emerged as the preferred algorithm, optimised with non-linear 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 3000 study participants. This model can inform about the biological and behavioural implications of deviations from typical age-related neuroanatomical changes and support future study designs. The model and scripts described here are freely available through CentileBrain.

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization.

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/).

Association of retinal nerve layers thickness and brain imaging in healthy young subjects from the i-Share-Bordeaux study.

Given the anatomical and functional similarities between the retina and the brain, the retina could be a "window" for viewing brain structures. We investigated the association between retinal nerve fiber layers (peripapillary retinal nerve fiber layer, ppRNFL; macular ganglion cell-inner plexiform layer, GC-IPL; and macular ganglion cell complex, GCC), and brain magnetic resonance imaging (MRI) parameters in young health adults. We included 857 students (mean age: 23.3 years, 71.3% women) from the i-Share study. We used multivariate linear models to study the cross-sectional association of each retinal nerve layer thickness assessed by spectral-domain optical coherence tomography (SD-OCT) with structural (volumes and cortical thickness), and microstructural brain markers, assessed on MRI globally and regionally. Microstructural MRI parameters included diffusion tensor imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI). On global brain analysis, thicker ppRNFL, GC-IPL and GCC were all significantly associated with patterns of diffusion metrics consistent with higher WM microstructural integrity. In regional analyses, after multiple testing corrections, our results suggested significant associations of some retinal nerve layers with brain regional gray matter occipital volumes and with diffusion MRI parameters in a region involved in the visual pathway and in regions containing associative tracts. No associations were found with global volumes or with global or regional cortical thicknesses. Results of this study suggest that some retinal nerve layers may reflect brain structures. Further studies are needed to confirm these results in young subjects.

How Traumatic Brain Injury History Relates to Brain Health MRI Markers and Dementia Risk: Findings from the 3C Dijon Cohort.

BACKGROUND: The long-term effects of traumatic brain injury (TBI) with loss of consciousness (LOC) on magnetic resonance imaging (MRI) markers of brain health and on dementia risk are still debated. OBJECTIVE: To investigate the associations of history of TBI with LOC with incident dementia and neuroimaging markers of brain structure and small vessel disease lesions. METHODS: The analytical sample consisted in 4,144 participants aged 65 and older who were dementia-free at baseline from the Three City -Dijon study. History of TBI with LOC was self-reported at baseline. Clinical Dementia was assessed every two to three years, up to 12 years of follow-up. A subsample of 1,675 participants <80 years old underwent a brain MRI at baseline. We investigated the associations between history of TBI with LOC and 1) incident all cause and Alzheimer's disease (AD) dementia using illness-death models, and 2) neuroimaging markers at baseline. RESULTS: At baseline, 8.3% of the participants reported a history of TBI with LOC. In fully-adjusted models, participants with a history of TBI with LOC had no statistically significant differences in dementia risk (HR = 0.90, 95% CI = 0.60-1.36) or AD risk (HR = 1.03, 95% CI = 0.69-1.52), compared to participants without TBI history. History of TBI with LOC was associated with lower white matter volume (ß= -4.58, p = 0.048), but not with other brain volumes, white matter hyperintensities volume, nor covert brain infarct. CONCLUSION: This study did not find evidence of an association between history of TBI with LOC and dementia or AD dementia risks over 12-year follow-up, brain atrophy, or markers of small vessel disease.

Genomic Studies Across the Lifespan Point to Early Mechanisms Determining Subcortical Volumes.

BACKGROUND: Subcortical brain structures play a key role in pathological processes of age-related neurodegenerative disorders. Mounting evidence also suggests that early-life factors may have an impact on the development of common late-life neurological diseases, including genetic factors that can influence both brain maturation and neurodegeneration. METHODS: Using large population-based brain imaging datasets across the lifespan (N ≤ 40,628), we aimed to 1) estimate the heritability of subcortical volumes in young (18-35 years), middle (35-65 years), and older (65+ years) age, and their genetic correlation across age groups; 2) identify whether genetic loci associated with subcortical volumes in older persons also show associations in early adulthood, and explore underlying genes using transcriptome-wide association studies; and 3) explore their association with neurological phenotypes. RESULTS: Heritability of subcortical volumes consistently decreased with increasing age. Genetic risk scores for smaller caudate nucleus, putamen, and hippocampus volume in older adults were associated with smaller volumes in young adults. Individually, 10 loci associated with subcortical volumes in older adults also showed associations in young adults. Within these loci, transcriptome-wide association studies showed that expression of several genes in brain tissues (especially MYLK2 and TUFM) was associated with subcortical volumes in both age groups. One risk variant for smaller caudate nucleus volume (TUFM locus) was associated with lower cognitive performance. Genetically predicted Alzheimer's disease was associated with smaller subcortical volumes in middle and older age. CONCLUSIONS: Our findings provide novel insights into the genetic determinants of subcortical volumes across the lifespan. More studies are needed to decipher the underlying biology and clinical impact.

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

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.

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years.

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.

Greater male than female variability in regional brain structure across the lifespan.

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.

Handedness and its genetic influences are associated with structural asymmetries of the cerebral cortex in 31,864 individuals.

Roughly 10% of the human population is left-handed, and this rate is increased in some brain-related disorders. The neuroanatomical correlates of hand preference have remained equivocal. We resampled structural brain image data from 28,802 right-handers and 3,062 left-handers (UK Biobank population dataset) to a symmetrical surface template, and mapped asymmetries for each of 8,681 vertices across the cerebral cortex in each individual. Left-handers compared to right-handers showed average differences of surface area asymmetry within the fusiform cortex, the anterior insula, the anterior middle cingulate cortex, and the precentral cortex. Meta-analyzed functional imaging data implicated these regions in executive functions and language. Polygenic disposition to left-handedness was associated with two of these regional asymmetries, and 18 loci previously linked with left-handedness by genome-wide screening showed associations with one or more of these asymmetries. Implicated genes included six encoding microtubule-related proteins: TUBB, TUBA1B, TUBB3, TUBB4A, MAP2, and NME7-mutations in the latter can cause left to right reversal of the visceral organs. There were also two cortical regions where average thickness asymmetry was altered in left-handedness: on the postcentral gyrus and the inferior occipital cortex, functionally annotated with hand sensorimotor and visual roles. These cortical thickness asymmetries were not heritable. Heritable surface area asymmetries of language-related regions may link the etiologies of hand preference and language, whereas nonheritable asymmetries of sensorimotor cortex may manifest as consequences of hand preference.

Fish Intake and MRI Burden of Cerebrovascular Disease in Older Adults.

BACKGROUND AND OBJECTIVES: Fish intake may prevent cerebrovascular disease (CVD), yet the mechanisms are unclear, especially regarding its impact on subclinical damage. Assuming that fish may have pleiotropic effect on cerebrovascular health, we investigated the association of fish intake with global CVD burden based on brain MRI markers. METHODS: This cross-sectional analysis included participants from the Three-City Dijon population-based cohort (age ≥65 years) without dementia, stroke, or history of hospitalized cardiovascular disease who underwent brain MRI with automated assessment of white matter hyperintensities, visual detection of covert infarcts, and grading of dilated perivascular spaces. Fish intake was assessed through a frequency questionnaire, and the primary outcome measure was defined as the first component of a factor analysis of mixed data applied to MRI markers. The association of fish intake with the CVD burden indicator was studied with linear regressions. RESULTS: In total, 1,623 participants (mean age 72.3 years, 63% women) were included. The first component of factor analysis (32.4% of explained variance) was associated with higher levels of all 3 MRI markers. Higher fish intake was associated with lower CVD burden. In a model adjusted for total intracranial volume, compared to participants consuming fish <1 time per week, those consuming fish 2 to 3 and ≥4 times per week had a ß = -0.19 (95% confidence interval -0.37 to -0.01) and ß = -0.30 (-0.57 to -0.03) lower indicator of CVD burden, respectively (p trend < 0.001). We found evidence of effect modification by age such that the association of fish to CVD was stronger in younger participants (65-69 years) and not significant in participants ≥75 years of age. For comparison, in the younger age group, consuming fish 2 to 3 times a week was roughly equivalent (in the opposite direction) to the effect of hypertension. DISCUSSION: In this large population-based study, higher frequency of fish intake was associated with lower CVD burden, especially among participants <75 years of age, suggesting a beneficial effect on brain vascular health before manifestation of overt brain disease. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in individuals without stroke or dementia, higher fish intake is associated with lower subclinical CVD on MRI.

Novel characterization of the relationship between verbal list-learning outcomes and hippocampal subfields in healthy adults.

The relationship between hippocampal subfield volumetry and verbal list-learning test outcomes have mostly been studied in clinical and elderly populations, and remain controversial. For the first time, we characterized a relationship between verbal list-learning test outcomes and hippocampal subfield volumetry on two large separate datasets of 447 and 1,442 healthy young and middle-aged adults, and explored the processes that could explain this relationship. We observed a replicable positive linear correlation between verbal list-learning test free recall scores and CA1 volume, specific to verbal list learning as demonstrated by the hippocampal subfield volumetry independence from verbal intelligence. Learning meaningless items was also positively correlated with CA1 volume, pointing to the role of the test design rather than word meaning. Accordingly, we found that association-based mnemonics mediated the relationship between verbal list-learning test outcomes and CA1 volume. This mediation suggests that integrating items into associative representations during verbal list-learning tests explains CA1 volume variations: this new explanation is consistent with the associative functions of the human CA1.

Age-Related Variations in Regional White Matter Volumetry and Microstructure During the Post-adolescence Period: A Cross-Sectional Study of a Cohort of 1,713 University Students.

Human brain white matter undergoes a protracted maturation that continues well into adulthood. Recent advances in diffusion-weighted imaging (DWI) methods allow detailed characterizations of the microstructural architecture of white matter, and they are increasingly utilized to study white matter changes during development and aging. However, relatively little is known about the late maturational changes in the microstructural architecture of white matter during post-adolescence. Here we report on regional changes in white matter volume and microstructure in young adults undergoing university-level education. As part of the MRi-Share multi-modal brain MRI database, multi-shell, high angular resolution DWI data were acquired in a unique sample of 1,713 university students aged 18-26. We assessed the age and sex dependence of diffusion metrics derived from diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) in the white matter regions as defined in the John Hopkins University (JHU) white matter labels atlas. We demonstrate that while regional white matter volume is relatively stable over the age range of our sample, the white matter microstructural properties show clear age-related variations. Globally, it is characterized by a robust increase in neurite density index (NDI), and to a lesser extent, orientation dispersion index (ODI). These changes are accompanied by a decrease in diffusivity. In contrast, there is minimal age-related variation in fractional anisotropy. There are regional variations in these microstructural changes: some tracts, most notably cingulum bundles, show a strong age-related increase in NDI coupled with decreases in radial and mean diffusivity, while others, mainly cortico-spinal projection tracts, primarily show an ODI increase and axial diffusivity decrease. These age-related variations are not different between males and females, but males show higher NDI and ODI and lower diffusivity than females across many tracts. These findings emphasize the complexity of changes in white matter structure occurring in this critical period of late maturation in early adulthood.

The MRi-Share database: brain imaging in a cross-sectional cohort of 1870 university students.

We report on MRi-Share, a multi-modal brain MRI database acquired in a unique sample of 1870 young healthy adults, aged 18-35 years, while undergoing university-level education. MRi-Share contains structural (T1 and FLAIR), diffusion (multispectral), susceptibility-weighted (SWI), and resting-state functional imaging modalities. Here, we described the contents of these different neuroimaging datasets and the processing pipelines used to derive brain phenotypes, as well as how quality control was assessed. In addition, we present preliminary results on associations of some of these brain image-derived phenotypes at the whole brain level with both age and sex, in the subsample of 1722 individuals aged less than 26 years. We demonstrate that the post-adolescence period is characterized by changes in both structural and microstructural brain phenotypes. Grey matter cortical thickness, surface area and volume were found to decrease with age, while white matter volume shows increase. Diffusivity, either radial or axial, was found to robustly decrease with age whereas fractional anisotropy only slightly increased. As for the neurite orientation dispersion and densities, both were found to increase with age. The isotropic volume fraction also showed a slight increase with age. These preliminary findings emphasize the complexity of changes in brain structure and function occurring in this critical period at the interface of late maturation and early ageing.

Large-Scale Phenomic and Genomic Analysis of Brain Asymmetrical Skew.

The human cerebral hemispheres show a left-right asymmetrical torque pattern, which has been claimed to be absent in chimpanzees. The functional significance and developmental mechanisms are unknown. Here, we carried out the largest-ever analysis of global brain shape asymmetry in magnetic resonance imaging data. Three population datasets were used, UK Biobank (N = 39 678), Human Connectome Project (N = 1113), and BIL&GIN (N = 453). At the population level, there was an anterior and dorsal skew of the right hemisphere, relative to the left. Both skews were associated independently with handedness, and various regional gray and white matter metrics oppositely in the two hemispheres, as well as other variables related to cognitive functions, sociodemographic factors, and physical and mental health. The two skews showed single nucleotide polymorphisms-based heritabilities of 4-13%, but also substantial polygenicity in causal mixture model analysis, and no individually significant loci were found in genome-wide association studies for either skew. There was evidence for a significant genetic correlation between horizontal brain skew and autism, which requires future replication. These results provide the first large-scale description of population-average brain skews and their inter-individual variations, their replicable associations with handedness, and insights into biological and other factors which associate with human brain asymmetry.

The genetic architecture of structural left-right asymmetry of the human brain.

Left-right hemispheric asymmetry is an important aspect of healthy brain organization for many functions including language, and it can be altered in cognitive and psychiatric disorders. No mechanism has yet been identified for establishing the human brain's left-right axis. We performed multivariate genome-wide association scanning of cortical regional surface area and thickness asymmetries, and subcortical volume asymmetries, using data from 32,256 participants from the UK Biobank. There were 21 significant loci associated with different aspects of brain asymmetry, with functional enrichment involving microtubule-related genes and embryonic brain expression. These findings are consistent with a known role of the cytoskeleton in left-right axis determination in other organs of invertebrates and frogs. Genetic variants associated with brain asymmetry overlapped with those associated with autism, educational attainment and schizophrenia. Comparably large datasets will likely be required in future studies, to replicate and further clarify the associations of microtubule-related genes with variation in brain asymmetry, behavioural and psychiatric traits.

Typical and atypical language brain organization based on intrinsic connectivity and multitask functional asymmetries.

Based on the joint investigation in 287 healthy volunteers (150 left-Handers (LH)) of language task-induced asymmetries and intrinsic connectivity strength of the sentence-processing supramodal network, we show that individuals with atypical rightward language lateralization (N = 30, 25 LH) do not rely on an organization that simply mirrors that of typical leftward lateralized individuals. Actually, the resting-state organization in the atypicals showed that their sentence processing was underpinned by left and right networks both wired for language processing and highly interacting by strong interhemispheric intrinsic connectivity and larger corpus callosum volume. Such a loose hemispheric specialization for language permits the hosting of language in either the left and/or right hemisphere as assessed by a very high incidence of dissociations across various language task-induced asymmetries in this group.

Development of handedness, anatomical and functional brain lateralization.

The present chapter offers a report on the recent literature on the neural bases of hemispheric specialization (HS), anatomical and functional developmental timecourse of HS, and on the available knowledge of their relationships with the development of handedness. Strong anatomical asymmetries can be seen located along the end of the sylvian fissure and the superior temporal sulcus (STS) as soon as the 23rd gestational week. They correspond to a leftward sulcal depth asymmetry of the Sylvian fissure coupled with a rightward asymmetry of STS. These neonatal asymmetries targeting speech processing areas do not further change with development. Different from these anatomical asymmetries, the functional asymmetries of language areas develop during childhood. Such a development is characterized at birth by a predominant interhemispheric intrinsic connectivity between homotopic areas that will evolve toward left hemisphere intrahemispheric intrinsic connectivity between anterior and posterior language poles. The development of such a typical architecture of language networks in the left hemisphere dominant for language in more than 90% of humans translates into a continuous increase in the leftward asymmetries of activation during language production throughout childhood. With regard to the rightward cerebral lateralization for visuospatial functions, neuroimaging studies tend to indicate an increase in rightward lateralization of frontal-parietal network with age during visuospatial memory and visuospatial search tasks. In addition, the spatial-attentional behavioral asymmetries emerge early (in preschool children) and, then, can be modulated by factors linked to motor asymmetry and handedness. Finally, the study of manual lateralization in relation to language development has shown the importance of considering several characteristics of manual activities. In particular, the dissociation between manipulative activities and communicative gestures in young children may open further perspectives for future research on HS.