Perinatal period is a critical time for brain development and premature-born children have an elevated likelihood for neurodevelopmental conditions. While strong associations of structural magnetic resonance imaging with preterm birth and post-menstrual age (PMA) have been reported, results with functional MRI (fMRI) have been considerably weaker. Using the task-free neonatal fMRI dataset from the Developing Human Connectome Project (dHCP), we first studied the associations of the aperiodic component of the blood-oxygen-level-dependent (BOLD) signal power spectrum from pre- and postcentral gyri with preterm birth and mapped the associations with PMA, postnatal age, and sex, and found clear differences between preterm and full-term groups, as well as males and females. Second, we used machine learning regression to predict participants’ age from the aperiodic parameters of the BOLD signal from 90 cortical and subcortical regions of interest with relatively high accuracy (test R2’s 0.20–0.41). Statistical and machine learning based analyses reveal associations between aperiodic component of resting-state fMRI BOLD signal and neonatal age and preterm birth status.

The aim of this study was to explore the associations between an aspect of self-regulation (SR), effortful control (EC) and cortical brain structure in 5-year-old children. Efficient EC is a predictor of many attributes and important outcomes in life, such as social-emotional functioning, finance, psychiatric and somatic health. The early brain correlates of EC are not widely studied, and a better understanding of them would aid in understanding how self-regulatory capacities emerge over development. Participants (N = 155) were a part of the FinnBrain Birth Cohort Study in Finland. T1-weighted brain magnetic resonance images were processed using FreeSurfer. The data were statistically analysed with a vertex-wise general linear model. At the age of 5 years, EC was assessed via parental report using The Children's Behaviour Questionnaire. We found positive associations between EC and cortical volume in the left supramarginal region and in the right inferior temporal region. We also found positive associations between EC and surface area on the left hemisphere in the superior parietal region. We extended the previous literature by shedding light on early structural brain correlates of EC in a large sample of typically developing 5-year-olds. The main results differed significantly from previous findings in older children. The results were only present with questionnaire- and not task-based evaluation of EC. Both questionnaire and task-based evaluations are required to consider different aspects of EC and SR. In addition, longitudinal studies are needed to better understand the neural underpinnings of SR throughout development.

BACKGROUND:Maternal depressive symptoms can influence brain development in offspring, prenatally through intrauterine programming, and postnatally through caregiving related mother-child interaction. METHODS:The participants were 5-year-old mother-child dyads from the FinnBrain Birth Cohort Study (N = 68; 28 boys, 40 girls). Maternal depressive symptoms were assessed with the Edinburgh Postnatal Depression Scale (EPDS) at gestational week 24, 3 months, 6 months, and 12 months postnatal. Children's brain imaging data were acquired with task-free functional magnetic resonance imaging (fMRI) at the age of 5 years in 7-min scans while watching the Inscapes movie. The derived brain metrics included whole-brain regional homogeneity (ReHo) and seed-based connectivity maps of the bilateral amygdalae. RESULTS:We found that maternal depressive symptoms were positively associated with ReHo values of the left amygdala. The association was highly localized and strongest with the maternal depressive symptoms at 3 months postnatal. Seed-based connectivity analysis did not reveal associations between distal connectivity of the left amygdala region and maternal depressive symptoms. CONCLUSIONS:These results suggest that maternal depressive symptoms soon after birth may influence offspring's neurodevelopment in the local functional coherence in the left amygdala. They underline the potential relevance of postnatal maternal distress exposure on neurodevelopment that has received much less attention than prenatal exposures. These results offer a possible thus far understudied pathway of intergenerational effects of perinatal depression that should be further explored in future studies.

Maternal immune activation (MIA) during pregnancy is implicated in offspring psychiatric disorders. However, it is unknown to what extent MIA affects neurodevelopment, particularly cerebrocortical anatomy, in the general population, and whether effects differ by sex. The current study used vertex-wise statistics to examine the association between maternal prenatal CRP, an archetypal systemic inflammatory marker, and offspring cortical thickness, surface area, and volume, in 2635 mother-child dyads (5.4-26.5 years) from three population-based cohorts, and one clinical cohort enriched for presence of inflammation markers. Maternal CRP within a normal physiological range (<10 mg/L) exhibited sex-specific quadratic associations with cortical morphological measures in 2 regions in males and 1 region in females at childhood. Elevated (>10 mg/L) CRP was associated with regional cortical morphology in females and in a pooled sample of sexes. Overall, MIA is associated with cortical development in a regional and sex-specific manner in studies spanning childhood to adulthood.

The accurate processing of neonatal and infant brain MRI data is crucially important for developmental neuroscience, but presents challenges that child and adult data do not. Tissue segmentation and image coregistration accuracy can be improved by optimizing template images and / or related segmentation procedures. Here, we describe the construction of the FinnBrain Neonate (FBN-125) template; a multi-contrast template with T1- and T2-weighted as well as diffusion tensor imaging derived fractional anisotropy and mean diffusivity images. The template is symmetric and aligned to the Talairach-like MNI 152 template and has high spatial resolution (0.5 mm3). In addition, we provide atlas labels, constructed from manual segmentations, for cortical grey matter, white matter, cerebrospinal fluid, brainstem, and cerebellum as well as the bilateral hippocampi, amygdalae, caudate nuclei, putamina, globi pallidi, and thalami. We provide this multi-contrast template along with the labelled atlases for the use of the neuroscience community in the hope that it will prove useful in advancing developmental neuroscience, for example, by helping to achieve reliable means for spatial normalization and measures of neonate brain structure via automated computational methods. Additionally, we provide standard co-registration files that will enable investigators to reliably transform their statistical maps to the adult MNI space, which has the potential to improve the consistency and comparability of neonatal studies or the use of adult MNI space atlases in neonatal neuroimaging. ### Competing Interest Statement The authors have declared no competing interest.

Large multi-site studies that combine magnetic resonance imaging (MRI) data across research sites present exceptional opportunities to advance neuroscience research. However, scanner or site variability and non-standardised image acquisition protocols, data processing and analysis pipelines can adversely affect the reliability and repeatability of MRI derived brain measures. We implemented a standardised MRI protocol based on that used in the Adolescent Brain Cognition Development (ABCD) R circle study in two sites, and across four MRI scanners. Twice repeated measurements of a single healthy volunteer were obtained in two sites and in four 3T MRI scanners (vendors: Siemens, Philips, and GE). Imaging data included anatomical scans (T1 weighted, T2 weighted), diffusion weighted imaging (DWI) and resting state functional MRI (rs-fMRI). Standardised containerized pipelines were utilised to pre -process the data and different image quality metrics and test-retest variability of different brain metrics were evaluated. The implementation of the MRI protocols was possible with minor adjustments in acquisition (e.g. repetition time (TR), higher b-values) and exporting (DICOM formats) of images due to different technical performance of the scanners. This study provides practical insights into the implementation of standardised sequences and data processing for multisite studies, showcase the benefits of containerised preprocessing tools, and highlights the need for careful optimisation of multisite image acquisition.

The development of face processing system is paramount for social interaction and communication skills. Eye-tracking provides a viable means to investigate face processing even in very young children and can be used to derive indices of affective processing biases that are adaptive in supporting preparedness for emotional encoding. The neural correlates of early-emerging attentional biases have not been explored. In the current study, we gathered diffusion tensor imaging (DTI) and eye-tracking data (attention disengagement from neutral, happy, fearful faces, and control pictures towards distractor stimuli) to investigate the association of white matter (WM) microstructural alterations and attentional biases in 117 (55 female) typically developing 5-year-old children. We estimated fractional anisotropy (FA) and used tract-based spatial statistics (TBSS) before conducting voxel-wise analyses testing associations between attentional biases and brain diffusivity. We found that reduced WM integrity (indexed as decrease in FA) in widespread WM regions, including the splenium of corpus callosum, left anterior limb of internal capsule (ALIC), left posterior limb of internal capsule (PLIC), left posterior thalamic radiation and optic tract, predicted higher attentional bias toward fearful expressions in females (adjusted for potential confounders). Further, maternal postnatal anxiety and depressive symptoms were detected to associate positively with attentional bias toward fearful expression, but only in females. Based on these findings and prior results on association between maternal distress and reduced WM integrity in female offspring, it is possible that alterations in WM microstructure may transmit the long-term effects of maternal mental distress during early life to increased vigilance towards negative emotional expressions. These hypotheses and sexual dimorphism in the observed associations require replication and are potential focus areas for future studies.

Background Childhood maltreatment exposure (CME) and related trauma could be considered some of psychiatry’s greatest public health challenges. CME and early adversity have been associated with increased amygdala volume in exposed individuals. Emerging evidence implies that CME could also affect prenatal development of the offspring. Methods As part of the FinnBrain Birth Cohort Study, we measured bilateral amygdala volumes from MR images in 76 healthy infants at 2–5 weeks of gestation corrected age and obtained the Trauma and Distress Scale (TADS) questionnaire from both parents. The associations between neonatal amygdala volumes and TADS scores were examined in stepwise regression models. Results We found that maternal CME associated positively with infant left amygdala volume (p = .045) while the positive association for the paternal trauma score was only marginally significant (p = .099). Similar associations were not observed for the right amygdala. In the exploratory analyses, we used age ranges (0–6, 7–12, and 13–18 years) as estimate of the timing of the CME and included all three time points from both parents using left amygdala volume into the stepwise regression models. We found that maternal TADS scores from 13–18 years of age associated positively with infant left amygdala volumes (p = .008). Correspondingly, paternal TADS scores from 0–6 years of age associated positively with the infant left amygdala volumes (p = .014). Conclusions Our link the infant offspring amygdala volume with parental CME with some agreement with prior findings, and they also imply links paternal CME to infant amygdala volumes. Amygdala is one of the key brain structures associated with both early life exposures and later psychiatric health, which makes it crucially important to elucidate both the underlying mechanisms and the later relevance of these associations in future studies.

Non-verbal cognitive ability predicts multiple important life outcomes, for example, school and job performance. It has been associated with parieto-frontal cortical anatomy in prior studies in adult and adolescent populations, while young children have received relatively little attention. We explored the associations between cortical anatomy and non-verbal cognitive ability in 165 5-year-old participants (mean scan age 5.40 years, SD 0.13; 90 males) from the FinnBrain Birth Cohort study. T1-weighted brain magnetic resonance images were processed using FreeSurfer. Non-verbal cognitive ability was measured using the Performance Intelligence Quotient (PIQ) estimated from the Block Design and Matrix Reasoning subtests from the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III). In vertex-wise general linear models, PIQ scores associated positively with volumes in the left caudal middle frontal and right pericalcarine regions, as well as surface area in left the caudal middle frontal, left inferior temporal, and right lingual regions. There were no associations between PIQ and cortical thickness. To the best of our knowledge, this is the first study to examine structural correlates of non-verbal cognitive ability in a large sample of typically developing 5-year-olds. The findings are generally in line with prior findings from older age groups, with the important addition of the positive association between volume / surface area in the right medial occipital region and non-verbal cognitive ability. This finding adds to the literature by discovering a new brain region that should be considered in future studies exploring the role of cortical structure for cognitive development in young children.

ABSTRACT The rapid white matter (WM) maturation of first years of life is followed by slower yet long-lasting development, accompanied by learning of more elaborate skills. By the age of five years, behavioural and cognitive differences between females and males, and functions associated with brain lateralization such as language skills are appearing. Diffusion tensor imaging (DTI) can be used to quantify fractional anisotropy (FA) within the WM and increasing values correspond to advancing brain development. To investigate the normal features of WM development during early childhood, we gathered a DTI data set of 166 healthy infants (mean 3.8 wk, range 2-5wk; 89 males; born on gestational week 36 or later) and 144 healthy children (mean 5.4 years, range 5.1-5.8 years; 76 males). The sex differences, lateralization patterns and age-dependent changes were examined using tractbased spatial statistics (TBSS). In 5-year-olds, females showed higher FA in wide-spread regions in the posterior and the temporal WM and more so in the right hemisphere, while sex differences were not detected in infants. Gestational age showed stronger association with FA values compared to age after birth in infants. Additionally, child age at scan associated positively with FA around the age of 5 years in the body of corpus callosum, the connections of which are important especially for sensory and motor functions. Lastly, asymmetry of WM microstructure was detected already in infants, yet significant changes in lateralization pattern seems to occur during early childhood, and in 5-year-olds the pattern already resembles adult-like WM asymmetry. Highlights White matter tract integrity shows widespread sex differences at the age of 5 years. White matter structure is highly lateralized during early childhood, and changes in asymmetry occur between the birth and 5 years of age. The white matter lateralization pattern of 5-year-olds, unlike of infants, resembles asymmetry observed in adults.

BACKGROUND:Prenatal and postnatal maternal psychological distress predicts various detrimental consequences on social, behavioral, and cognitive development of offspring, especially in girls. Maturation of white matter (WM) continues from prenatal development into adulthood and is thus susceptible to exposures both before and after birth. METHODS:WM microstructural features of 130 children (mean age, 5.36 years; range, 5.04-5.79 years; 63 girls) and their association with maternal prenatal and postnatal depressive and anxiety symptoms were investigated with diffusion tensor imaging, tract-based spatial statistics, and regression analyses. Maternal questionnaires were collected during first, second, and third trimesters and at 3, 6, and 12 months postpartum with the Edinburgh Postnatal Depression Scale (EPDS) for depressive symptoms and Symptom Checklist-90 for general anxiety. Covariates included child's sex; child's age; maternal prepregnancy body mass index; maternal age; socioeconomic status; and exposures to smoking, selective serotonin reuptake inhibitors, and synthetic glucocorticoids during pregnancy. RESULTS:Prenatal second-trimester EPDS scores were positively associated with fractional anisotropy in boys (p < .05, 5000 permutations) after controlling for EPDS scores 3 months postpartum. In contrast, postpartum EPDS scores at 3 months correlated negatively with fractional anisotropy (p < .01, 5000 permutations) in widespread areas only in girls after controlling for prenatal second-trimester EPDS scores. Perinatal anxiety was not associated with WM structure. CONCLUSIONS:These results suggest that prenatal and postnatal maternal psychological distress is associated with brain WM tract developmental alterations in a sex- and timing-dependent manner. Future studies including behavioral data are required to consolidate associative outcomes for these alterations.

The human brain develops dynamically during early childhood, when the child is sensitive to both genetic programming and extrinsic exposures. Recent studies have found links between prenatal and early life environmental factors, family demographics and the cortical brain morphology in newborns measured by surface area, volume and thickness. Here in this magnetic resonance imaging study, we evaluated whether a similar set of variables associates with cortical surface area and volumes measured in a sample of 170 healthy 5-year-olds from the FinnBrain Birth Cohort Study. We found that child sex, maternal pre-pregnancy body mass index, 5 min Apgar score, neonatal intensive care unit admission and maternal smoking during pregnancy associated with surface areas. Furthermore, child sex, maternal age and maternal level of education associated with brain volumes. Expectedly, many variables deemed important for neonatal brain anatomy (such as birth weight and gestational age at birth) in earlier studies did not associate with brain metrics in our study group of 5-year-olds, which implies that their effects on brain anatomy are age-specific. Future research may benefit from including pre- and perinatal covariates in the analyses when such data are available. Finally, we provide evidence for right lateralization for surface area and volumes, except for the temporal lobes which were left lateralized. These subtle differences between hemispheres are variable across individuals and may be interesting brain metrics in future studies.

Diffusion tensor imaging (DTI) has provided great insights into the microstructural features of the developing brain. However, DTI images are prone to several artifacts and the reliability of DTI scalars is of paramount importance for interpreting and generalizing the findings of DTI studies, especially in the younger population. In this study, we investigated the intrascan test-retest repeatability of four DTI scalars: fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) in 5-year-old children (N = 67) with two different data preprocessing approaches: a volume censoring pipeline and an outlier replacement pipeline. We applied a region of interest (ROI) and a voxelwise analysis after careful quality control, tensor fitting and tract-based spatial statistics. The data had three subsets and each subset included 31, 32, or 33 directions thus a total of 96 unique uniformly distributed diffusion encoding directions per subject. The repeatability of DTI scalars was evaluated with intraclass correlation coefficient (ICC(3,1)) and the variability between test and retest subsets. The results of both pipelines yielded good to excellent (ICC(3,1) > 0.75) reliability for most of the ROIs and an overall low variability (<10%). In the voxelwise analysis, FA and RD had higher ICC(3,1) values compared to AD and MD and the variability remained low (<12%) across all scalars. Our results suggest high intrascan repeatability in pediatric DTI and lend confidence to the use of the data in future cross-sectional and longitudinal studies.

Pediatric neuroimaging is a quickly developing field that still faces important methodological challenges. Pediatric images usually have more motion artifact than adult images. The artifact can cause visible errors in brain segmentation, and one way to address it is to manually edit the segmented images. Variability in editing and quality control protocols may complicate comparisons between studies. In this article, we describe in detail the semiautomated segmentation and quality control protocol of structural brain images that was used in FinnBrain Birth Cohort Study and relies on the well-established FreeSurfer v6.0 and ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium tools. The participants were typically developing 5-year-olds [n = 134, 5.34 (SD 0.06) years, 62 girls]. Following a dichotomous quality rating scale for inclusion and exclusion of images, we explored the quality on a region of interest level to exclude all regions with major segmentation errors. The effects of manual edits on cortical thickness values were relatively minor: less than 2% in all regions. Supplementary Material cover registration and additional edit options in FreeSurfer and comparison to the computational anatomy toolbox (CAT12). Overall, we conclude that despite minor imperfections FreeSurfer can be reliably used to segment cortical metrics from T1-weighted images of 5-year-old children with appropriate quality assessment in place. However, custom templates may be needed to optimize the results for the subcortical areas. Through visual assessment on a level of individual regions of interest, our semiautomated segmentation protocol is hopefully helpful for investigators working with similar data sets, and for ensuring high quality pediatric neuroimaging data.

Developing accurate subcortical volumetric quantification tools is crucial for neurodevelopmental studies, as they could reduce the need for challenging and time-consuming manual segmentation. In this study the accuracy of two automated segmentation tools, FSL-FIRST (with three different boundary correction settings) and FreeSurfer were compared against manual segmentation of subcortical nuclei, including the hippocampus, amygdala, thalamus, putamen, globus pallidus, caudate and nucleus accumbens, using volumetric and correlation analyses in 80 5-year-olds. Both FSL-FIRST and FreeSurfer overestimated the volume on all structures except the caudate, and the accuracy varied depending on the structure. Small structures such as the amygdala and nucleus accumbens, which are visually difficult to distinguish, produced significant overestimations and weaker correlations with all automated methods. Larger and more readily distinguishable structures such as the caudate and putamen produced notably lower overestimations and stronger correlations. Overall, the segmentations performed by FSL-FIRST’s Default pipeline were the most accurate, while FreeSurfer’s results were weaker across the structures. In line with prior studies, the accuracy of automated segmentation tools was imperfect with respect to manually defined structures. However, apart from amygdala and nucleus accumbens, FSL-FIRST’s agreement could be considered satisfactory (Pearson correlation > 0.74, Intraclass correlation coefficient (ICC) > 0.68 and Dice Score coefficient (DSC) > 0.87) with highest values for the striatal structures (putamen, globus pallidus and caudate) (Pearson correlation > 0.77, ICC > 0.87 and DSC > 0.88, respectively). Overall, automated segmentation tools do not always provide satisfactory results, and careful visual inspection of the automated segmentations is strongly advised.

Objective: Inhibitory control (IC) is one important predictor of academic achievement and social-emotional development. IC develops rapidly in early childhood and is considered moderately stable from preschool-age onwards. The role of IC for child’s interaction skills, and its neural correlates in toddlerhood have not been widely studied. We explored the associations between child IC at 24 and 30 months and child interaction quality (responsiveness and involvement) with the mother at 30 months and conducted a preliminary exploration of structural neural correlates of IC and child interaction quality in a subsample of children.Method: We measured IC using the Snack Delay task and child interaction quality with the mother using the Emotional Availability Scales (EAS) at 30 months in a sample of N = 350 toddlers from the FinnBrain Birth Cohort Study. In a subsample, IC was measured also at 24 months (N = 27) and structural MRI scans were acquired at 18–24 months (N = 9). Voxel-based morphometry analysis at the threshold of p < .05 and FDR-corrected at alpha < .05 was performed to detect grey matter clusters associated with IC.Results: Better IC was positively related to better child interaction quality with the mother cross-sectionally at 30 months (B = .13, p = .007) and longitudinally between 24 and 30 months (B = .14, p = .044). For IC at 24 months, the analysis revealed a cluster with less grey matter in the right calcarine sulcus (p < .001). For IC at 30 months, clusters with more grey matter in the left cerebellum (p = .007), right middle frontal gyrus (p = .018) and right superior occipital gyrus (p = .037) were identified. Implications: These findings suggest that higher IC in toddlerhood is associated with better child interaction quality with the mother. They also give preliminary support for associations between IC and more grey matter in areas involved in frontoparietal network and visual processing. Replication studies are warranted.

The quality of mother-child interaction, especially maternal sensitivity in caregiving behavior, plays an important role in a child's later socioemotional development. Numerous studies have indicated associations between poor mother-child interaction and offspring brain structure and function, but more knowledge on how variation in the characteristics of early caregiving is associated with children's brain structure and function is needed. We investigated whether maternal sensitivity at 8 or 30 months is associated with functional connectivity in a child's brain at 5 years of age based on the FinnBrain Birth Cohort Study (17 and 39 mother-child dyads at 8 and 30 months, respectively, with an overlap of 13 dyads). Maternal sensitivity was assessed during a free play interaction using the Emotional Availability Scales at 8 and 30 months of the children's age. Task-free functional magnetic resonance imaging (fMRI) was acquired at the age of 5 years in 7-min scans while watching the Inscapes movie. Regional homogeneity (ReHo) maps were created from the fMRI data, and multiple regression analysis was performed to assess the relation between maternal sensitivity and ReHo. Maternal sensitivity at the age of 8 months was positively associated with children's ReHo values within the medial prefrontal cortex. Distal connectivity of this region showed no significant association with maternal sensitivity in a seed-based connectivity analysis. No associations were found between maternal sensitivity during toddlerhood and brain functional connectivity. Together, these results suggest that maternal sensitivity, especially in infancy, may influence offspring brain functional connectivity. However, studies with larger sample sizes are warranted.

Methodological aspects and effects of different imaging parameters on DTI (diffusion tensor imaging) results and their reproducibility have been recently studied comprehensively in adult populations. Although MR imaging of children's brains has become common, less interest has been focussed on researching whether adult-based optimised parameters and pre-processing protocols can be reliably applied to paediatric populations. Furthermore, DTI scalar values of preschool aged children are rarely reported. We gathered a DTI dataset from 5-year-old children (N = 49) to study the effect of the number of diffusion-encoding directions on the reliability of resultant scalar values with TBSS (tract-based spatial statistics) method. Additionally, the potential effect of within-scan head motion on DTI scalars was evaluated. Reducing the number of diffusion-encoding directions deteriorated both the accuracy and the precision of all DTI scalar values. To obtain reliable scalar values, a minimum of 18 directions for TBSS was required. For TBSS fractional anisotropy values, the intraclass correlation coefficient with two-way random-effects model (ICC[2,1]) for the subsets of 6 to 66 directions ranged between 0.136 [95%CI 0.0767;0.227] and 0.639 [0.542;0.740], whereas the corresponding values for subsets of 18 to 66 directions were 0.868 [0.815;0.913] and 0.995 [0.993;0.997]. Following the exclusion of motion-corrupted volumes, minor residual motion did not associate with the scalar values. A minimum of 18 diffusion directions is recommended to result in reliable DTI scalar results with TBSS. We suggest gathering extra directions in paediatric DTI to enable exclusion of volumes with motion artefacts and simultaneously preserve the overall data quality.