Biology subjects

Pulli, E. P.

Publications and source records attributed to Pulli, E. P..

15 recordsLinked to original sources

bioRxiv2026

Cortical gray matter density at age five associated with preceding early longitudinal language profiles: A Voxel-based morphometry analysis of the FinnBrain Birth Cohort Study

Previous studies exploring the connection between early language development and brain anatomy have shown that cortical areas relating to individual differences in language skills are diverse and vary depending on the age of child. However, due to lack of large longitudinal samples, current literature is limited in answering the extent to which individual differences in language development prior to school age are reflected in areas of the cortex. To fill this gap, we compared gray matter density between participants that belonged to different longitudinally defined language profiles from 14 months to five years of age in a large population-based sample. Participants were 166 children from the FinnBrain Birth Cohort Study who had longitudinal language data from 14 months to five years of age and magnetic resonance imaging data at five years of age. Three groups of language development were used as per our prior study: persistent low, stable average, and stable high. Voxel-based morphometry metrics were calculated using SPM12 and the three language profile groups were compared to one another. Covariates included sex and age at brain scan. The statistics were thresholded at p < 0.01 and false discovery rate corrected at the cluster level. Of the three longitudinal language profiles, the stable high group had higher gray matter density than the persistent low group in the right superior frontal gyrus. No differences were found between the stable average and stable high groups, nor persistent low and stable average groups. The identified superior frontal cortical area belongs to executive functions neural network. This finding adds to the cumulating evidence that individual differences in language development are reflected in growth of gray matter supporting general processing ability rather than specialized language regions. The results suggest that cognitive development and early language development are linked through shared principles of neural growth, identifiable already at age five. Key pointsO_LIAn association between early language development from 14 months to five years of age and gray matter density differences of the right superior frontal gyrus was found at the age of five years. Children following the strongest language trajectory were more likely to exhibit higher gray matter density of the right superior frontal gyrus than children following the weakest trajectory. C_LIO_LIAs the superior frontal gyrus is part of executive functions network, we propose that individual differences in early language development are more defined by general learning mechanisms supported by those networks, rather than language specific pathways. C_LI

neuroscience↗

bioRxiv2026

Functional connectome harmonics capture early brain organization and maturity in neonates

The functional organization of the human brain is established early, yet the ontogeny of its large-scale functional gradients remains unclear. Using resting-state fMRI data from 714 neonates in the Developing Human Connectome Project, we mapped neonatal brain gradients via functional connectome harmonics (FCH). We identified adult-like sensory-to-multimodal and cognitive gradient patterns present at birth. Applying three FCH-derived metrics--entropy, power, and energy--we found that power and energy were higher in term-born compared to preterm neonates, while entropy was elevated in preterms. These metrics predicted up to ~30% of postmenstrual age, indicating their biological relevance. Our findings reveal that the neonatal brain possesses a robust gradient architecture underpinning early functional organization, offering novel biomarkers for assessing brain maturity and the impact of prematurity on neurodevelopment.

neuroscience↗

bioRxiv2026

Functional connectome harmonics and dynamic connectivity maps of the preadolescent brain

The maturation of large-scale functional brain networks during preadolescence underpins critical cognitive and behavioral development. However, the spatial and temporal organization of these networks in this age group remains incompletely characterized. Here we applied Functional Connectome Harmonics (FCH) and Leading Eigenvector Dynamics Analysis (LEiDA) to resting-state fMRI data from over 11,000 children aged 9-10 years in the ABCD Study. FCH revealed hierarchical spatial gradients spanning cortical and subcortical regions, while LEiDA identified recurrent dynamic brain states aligned with canonical intrinsic connectivity networks. Linking these spatial and temporal components, we established a low-dimensional harmonic scaffold constraining brain dynamics during this developmental window. These findings provide a large-scale spatiotemporal reference framework of preadolescent functional brain organization, offering a foundation for characterizing neurodevelopmental benchmarks and early neural markers relevant to adolescent mental health.

neuroscience↗

bioRxiv2025

Exposure to Maternal Pre- and Postnatal Psychological Distress: Associations with Brain Structure in 5-year-old Children

BackgroundMaternal mental health is an important contributor to child neurodevelopment. While there are multiple studies on prenatal exposure, early postnatal exposure has received little attention in neuroimaging research. Methods5-year-old children (n = 173) were recruited from the FinnBrain Birth Cohort study. Maternal distress was assessed using questionnaires on depressive and anxiety symptoms at 14, 24 and 34 gestational weeks and postnatally at 3, 6 and 24 months. T1-weighted structural images were processed using a voxel-based morphometry pipeline to map associations between maternal distress exposure and regional gray matter (GM) volumes, while accounting for potential confounders. ResultsWe found widespread associations between maternal distress symptoms and offspring brain morphology. Higher prenatal distress at 14 gestational weeks was positively associated with regional GM volume in the right superior parietal lobe and precuneus. In contrast, postnatal distress at 3 months was negatively associated with GM volumes in multiple motor regions, the left anterior insula, right superior frontal areas and supramarginal gyrus. Postnatal distress at 6 months demonstrated a positive relationship with GM volumes in the right calcarine and lingual gyri, while distress at 24 months was negatively associated with GM volumes in the left supramarginal and right superior frontal gyri. ConclusionsThis study provides support for hypotheses proposing that fetal and early life exposure to maternal distress can influence the structural development of the brain. Furthermore, it highlights the role of early postnatal period and calls for further research into this so far overlooked period and pathways that explain the associations.

neuroscience↗

bioRxiv2025

skiftiTools: An R package for reading, writing, analysing, and visualising, tract-based spatial statistics (TBSS) derived diffusion MR images

skiftiTools processes three- and four-dimensional neuroimaging data, facilitating advanced statistical modelling with voxelwise data in any software of choice. Tract-Based Spatial Statistics (TBSS) is a conventionally used tool to make statistical calculations in voxel space for brain imaging data. While pre-existing software packages provide support for general linear model based statistics, there is a clear need for more sophisticated modeling. skiftiTools writes subject-per-volume NIfTI files as tab-separated value ASCII files, which are easily readable by most commonly used statistical tools such as R language (RStudio), SPSS, SAS, and GraphPad Prism. This facilitates a wide range of voxel-level statistical analyses from TBSS data, including estimation of standardised effect sizes, clustering, dimensionality reduction, non-linear and machine learning predictive modelling, which we showcase in this article using FinnBrain and developing Human Connectome Project diffusion MRI data. After statistical processing, the resulting ASCII data can then be read again for visualization. The package supports NIfTI image format, tab-separated ASCII format, and its own stand-alone format for efficient disk usage. It is open source (https://github.com/haanme/skiftiTools), built on R-language and has easy installation from Rs CRAN package repository. In addition, we provide basic functions available in Docker containers for further platform independence. HighlightsO_LIThe skiftiTools R package is an open-source, user-friendly interface for analysing voxelwise diffusion tensor imaging (DTI) data following tract-based spatial statistics (TBSS) processing C_LIO_LIIt supports reading, writing, visualization, mathematical operations, and data manipulation and thus allows comprehensive conventional and advanced statistics, including machine learning C_LIO_LIskiftiTools bridges a critical gap between statistical tools in R and voxelwise neuroimaging data - including comparable means to perform multiple comparison corrections and much needed possibility to use non-linear statistics C_LI

neuroscience↗

bioRxiv2025

Charting structural brain asymmetry across the human lifespan

Lateralization is a fundamental principle of structural brain organization. In vivo imaging of brain asymmetry is essential for deciphering lateralized brain functions and their disruption in neurodevelopmental and neurodegenerative disorders. Here, we present a normative framework for benchmarking brain asymmetry across the lifespan, developed from an aggregated sample of 128 primary neuroimaging studies, including 177,701 scans from 138,231 individuals, jointly spanning the age range from 20 post menstrual weeks to 102 years. This resource includes comprehensive, hemisphere-specific brain growth charts for multiple neuroimaging phenotypes: regional cortical grey matter volume, thickness, surface area, and subcortical volumes. Our findings reveal distinct spatial patterns of asymmetry, with early leftward asymmetry observed in association cortices and late rightward asymmetry in sensory regions. These trajectories support theories of the neuroplasticity of asymmetry and the role of both genetic and environmental factors in shaping brain lateralization. Additionally, we provide tools to generate asymmetry centile scores, which allow the quantification of individual deviations from typical asymmetry throughout the lifespan and can be applied to unseen data or clinical populations. We demonstrate the utility of these models by highlighting group-level differences in asymmetry in autism spectrum disorder, schizophrenia, and Alzheimers disease, and exploring genetic correlations with hemispheric specialization. To facilitate further research, we have made this normative framework freely available as an interactive open-access resource (upon publication), offering an essential tool to advance both basic and clinical neuroscience.

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bioRxiv2025

Neonatal White Matter Microstructure Predicts Infant Attention Disengagement from Fearful Faces

Infants develop an attentional bias towards faces already at birth, with further specification towards fearful faces emerging at 6 months and diminishing around 11 months of age. However, the neurobiological origins of attentional bias to fear are still poorly understood. To understand the neural structures underlying perception of facial expressions, the current study utilized newborn diffusion magnetic resonance images (N = 86; 41 females; = 27.15 days) and eye tracking from the same infants at 8-months ( = 8.75 months) as a behavioural measure. An overlap paradigm was used to measure attention disengagement from fearful, happy, and neutral faces. Tract-based spatial statistics revealed that higher white matter (WM) mean diffusivity in widespread regions across the brain was associated with lower attention disengagement from fearful faces. The same association was found with happy faces but was limited to only the splenium of the corpus callosum and sensorimotor pathways. Variance in neonatal WM microstructure may reflect individual differences in growth that is related to attentional bias development later in infancy.

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bioRxiv2024

Effortful control and cortical brain structure in 5-year-old children: findings from the FinnBrain birth cohort study

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, psychiatric and somatic health, finance, and criminal activity. The early brain correlates of EC are not widely studied, while a better understanding of them would aid in recognizing individuals at risk for maladaptive outcomes. 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 was statistically analysed with a vertex-wise general linear model. At the age of 5 years, EC and its subscales, Attentional focusing, Inhibitory control (INH), Low intensity pleasure (LIP) and perceptual sensitivity, were assessed via parental report using The Childrens Behaviour Questionnaire. We found positive associations between overall EC and cortical volume in the left superior parietal 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. The findings were driven by the EC subscales of INH and LIP with INH linking positively with left surface area and volume, and LIP linking with left cortical volume. 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 results differed significantly from previous findings in older children, highlighting the need for longitudinal studies to better understand the neural underpinnings of SR throughout development.

neuroscience↗

bioRxiv2024

Pre- and postnatal maternal depressive symptoms associate with localconnectivity of the left amygdala in 5-year-olds.

BackgroundMaternal depressive symptoms can influence brain development in offspring, prenatally through intrauterine programming, and postnatally through caregiving related mother-child interaction. MethodsThe 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. Childrens 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. ResultsWe found that maternal depressive symptoms were positively associated with ReHo values of the left amygdala. The association was highly localised and strongest with the maternal depressive symptoms at three months postnatal. Seed-based connectivity analysis did not reveal associations between distal connectivity of the left amygdala region and maternal depressive symptoms. ConclusionsThese results suggest that maternal depressive symptoms soon after birth may influence offsprings 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.

neuroscience↗

bioRxiv2024

The FinnBrain Multimodal Neonatal Template and Atlas Collection: T1, T2, and DTI brain templates, and accompanying cortical and subcortical atlases

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.

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bioRxiv2023

Attentional bias toward fearful faces is associated with maternal postnatal distress and alterations in white matter microstructure in 5-year-old females

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.

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bioRxiv2023

Parental childhood maltreatment associates with offspring left amygdala volume at early infancy

BackgroundChildhood maltreatment exposure (CME) and related trauma could be considered some of psychiatrys 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. MethodsAs 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. ResultsWe 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). ConclusionsOur 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.

neuroscience↗

bioRxiv2023

Structural brain correlates of non-verbal cognitive ability in 5-year-old children: findings from the FinnBrain Birth Cohort study

Non-verbal cognitive ability predicts multiple important life outcomes, e.g., 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 left caudal middle frontal and right pericalcarine regions, as well as surface area in left 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.

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bioRxiv2021

Subcortical brain segmentation in 5-year-old children: validation of FSL-FIRST and FreeSurfer against manual segmentation

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-FIRSTs Default pipeline were the most accurate, while FreeSurfers 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-FIRSTs 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.

neuroscience↗

bioRxiv2021

Feasibility of FreeSurfer processing for T1-weighted brain images of 5-year-olds: semiautomated protocol of FinnBrain Neuroimaging Lab

Pediatric neuroimaging is a quickly developing field that still faces important methodological challenges. One key challenge is the use of many different atlases, automated segmentation tools, manual edits in semiautomated protocols, and quality control protocols, which complicates comparisons between studies. In this article, we present our semiautomated segmentation protocol using FreeSurfer v6.0, ENIGMA consortium software, and the quality control protocol that was used in FinnBrain Birth Cohort Study. We used a dichotomous quality rating scale for inclusion and exclusion of images, and then 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 minor: less than 2% in all regions. Supplementary materials 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. Our semiautomated segmentation protocol provides high quality pediatric neuroimaging data and could help investigators working with similar data sets.

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