Brains for all the ages: structural neurodevelopment in infants and children from a life-span perspective

A Radiomic Approach for Evaluating Intra-Subgroup Heterogeneity in SHH and Group 4 Pediatric Medulloblastoma: A Preliminary Multi-Institutional Study

Medulloblastoma (MB) is the most frequent malignant brain tumor in children with extensive heterogeneity that results in varied clinical outcomes. Recently, MB was categorized into four molecular subgroups, WNT, SHH, Group 3, and Group 4. While SHH and Group 4 are known for their intermediate prognosis, studies have reported wide disparities in patient outcomes within these subgroups. This study aims to create a radiomic prognostic signature, medulloblastoma radiomics risk (mRRisk), to identify the risk levels within the SHH and Group 4 subgroups, individually, for reliable risk stratification. Our hypothesis is that this signature can comprehensively capture tumor characteristics that enable the accurate identification of the risk level. In total, 70 MB studies (48 Group 4, and 22 SHH) were retrospectively curated from three institutions. For each subgroup, 232 hand-crafted features that capture the entropy, surface changes, and contour characteristics of the tumor were extracted. Features were concatenated and fed into regression models for risk stratification. Contrasted with Chang stratification that did not yield any significant differences within subgroups, significant differences were observed between two risk groups in Group 4 (p = 0.04, Concordance Index (CI) = 0.82) on the cystic core and non-enhancing tumor, and SHH (p = 0.03, CI = 0.74) on the enhancing tumor. Our results indicate that radiomics may serve as a prognostic tool for refining MB risk stratification, towards improved patient care.

Diffusion-tensor-imaging 1-year-old and 2-year-old infant brain atlases with comprehensive gray and white matter labels

Human infancy is marked by fastest postnatal brain structural changes. It also coincides with the onset of many neurodevelopmental disorders. Atlas-based automated structure labeling has been widely used for analyzing various neuroimaging data. However, the relatively large and nonlinear neuroanatomical differences between infant and adult brains can lead to significant offsets of the labeled structures in infant brains when adult brain atlas is used. Age-specific 1- and 2-year-old brain atlases covering all major gray and white matter (GM and WM) structures with diffusion tensor imaging (DTI) and structural MRI are critical for precision medicine for infant population yet have not been established. In this study, high-quality DTI and structural MRI data were obtained from 50 healthy children to build up three-dimensional age-specific 1- and 2-year-old brain templates and atlases. Age-specific templates include a single-subject template as well as two population-averaged templates from linear and nonlinear transformation, respectively. Each age-specific atlas consists of 124 comprehensively labeled major GM and WM structures, including 52 cerebral cortical, 10 deep GM, 40 WM, and 22 brainstem and cerebellar structures. When combined with appropriate registration methods, the established atlases can be used for highly accurate automatic labeling of any given infant brain MRI. We demonstrated that one can automatically and effectively delineate deep WM microstructural development from 3 to 38 months by using these age-specific atlases. These established 1- and 2-year-old infant brain DTI atlases can advance our understanding of typical brain development and serve as clinical anatomical references for brain disorders during infancy.

Conduction velocity, G-ratio, and extracellular water as microstructural characteristics of autism spectrum disorder

The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a new approach to calculating axonal conduction velocity termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel formulation for calculating aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.

Conduction Velocity, G-ratio, and Extracellular Water as Microstructural Characteristics of Autism Spectrum Disorder

The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a novel metric termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel neuroimaging metric, aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.

Sensory processing of native and non-native phonotactic patterns in the alpha and beta frequency bands

The phonotactic patterns of one's native language are established within cortical network processing during development. Sensory processing of native language phonotactic patterns established in memory may be modulated by top-down signals within the alpha and beta frequency bands. To explore sensory processing of phonotactic patterns in the alpha and beta frequency bands, electroencephalograms (EEGs) were recorded from native Polish and native English-speaking adults as they listened to spoken nonwords within same and different nonword pairs. The nonwords contained three phonological sequence onsets that occur in the Polish and English languages (/pət/, /st/, /sət/) and one onset sequence /pt/, which occurs in Polish but not in English onsets. Source localization modeling was used to transform 64-channel EEGs into brain source-level channels. Spectral power values in the low frequencies (2-29 Hz) were analyzed in response to the first nonword in nonword pairs within the context of counterbalanced listening-task conditions, which were presented on separate testing days. For the with-task listening condition, participants performed a behavioral task to the second nonword in the pairs. For the without-task condition participants were only instructed to listen to the stimuli. Thus, in the with-task condition, the first nonword served as a cue for the second nonword, the target stimulus. The results revealed decreased spectral power in the beta frequency band for the with-task condition compared to the without-task condition in response to native language phonotactic patterns. In contrast, the task-related suppression effects in response to the non-native phonotactic pattern /pt/ for the English listeners extended into the alpha frequency band. These effects were localized to source channels in left auditory cortex, the left anterior temporal cortex and the occipital pole. This exploratory study revealed a pattern of results that, if replicated, suggests that native language speech perception is supported by modulations in the alpha and beta frequency bands.

Multimodal study of the neural sources of error monitoring in adolescents and adults

The ability to monitor performance during a goal-directed behavior differs among children and adults in ways that can be measured with several tasks and techniques. As well, recent work has shown that individual differences in error monitoring moderate temperamental risk for anxiety and that this moderation changes with age. We investigated age differences in neural responses linked to performance monitoring using a multimodal approach. The approach combined functional MRI and source localization of event-related potentials (ERPs) in 12-year-old, 15-year-old, and adult participants. Neural generators of two components related to performance and error monitoring, the N2 and ERN, lay within specific areas of fMRI clusters. Whereas correlates of the N2 component appeared similar across age groups, age-related differences manifested in the location of the generators of the ERN component. The dorsal anterior cingulate cortex (dACC) was the predominant source location for the 12-year-old group; this area manifested posteriorly for the 15-year-old and adult groups. A fMRI-based ROI analysis confirmed this pattern of activity. These results suggest that changes in the underlying neural mechanisms are related to developmental changes in performance monitoring.

A radiofrequency coil for infants and toddlers

Infants and toddlers are a challenging population upon which to perform magnetic resonance imaging (MRI) of the brain, both in research and clinical settings. Because of the large range in head size during the early years of development, paediatric neuro-MRI requires a radiofrequency (RF) coil, or set of coils, that is tailored to head size to provide the highest image quality. Mitigating techniques must also be employed to reduce and correct for subject motion. This manuscript describes an RF coil with a tailored mechanical-electrical design that can adapt to the head size of 3-month-old infants to 3-year-old toddlers. The RF coil was designed with tight-fitting coil elements to improve the signal-to-noise ratio (SNR) in comparison with commercially available adult head coils, while simultaneously aiding in immobilization. The coil was designed without visual obstruction to facilitate an unimpeded view of the child's face and the potential application of camera or motion-tracking systems. Despite the lack of elements over the face, the paediatric coil produced higher SNR over most of the brain compared with adult coils, including more than twofold in the periphery. Acceleration rates of fourfold in each Cartesian direction could be achieved. High SNR allowed for short acquisition times through accelerated imaging protocols and reduced the probability of motion during a scan. Modification of the acquisition protocol, with immobilization of the head through the adjustable coil geometry, and subsequently being combined with a motion-tracking system, provides a compelling platform for scanning paediatric populations without sedation and with improved image quality.

Cortical Source Analysis of the Face Sensitive N290 ERP Component in Infants at High Risk for Autism

Appropriate head models for cortical source analysis were investigated and applied to source analyses examining the neural bases of the face-sensitive N290 event-related potential (ERP) component in infants at high risk for autism spectrum disorder (ASD). This included infant siblings of children with ASD (ASIBs) and infants with fragile X syndrome (FXS). First, alternative head models for use with ASIBs and FXS were investigated. Head models created from the infant's own MRI were examined in relation to five head models based on average MRI templates. The results of the head model comparison identified group-specific (i.e., ASIB or FXS) head models created from a large collection of structural MRIs as the best substitution for the head model created from the participant's own structural MRI. Second, the cortical source analysis was completed on N290 data collected from a previous study to investigate brain areas associated with face sensitive ERP responses. Participants' own MRIs were used for head models when available, and the group-specific head model was used when the participants' own MRIs were not available. The results provide evidence for unique patterns of neural activation during face processing across infants at high and low risk for ASD and across etiologically distinct high-risk groups. All infants demonstrated greater activation to faces than toys in brain areas most associated with specialized face processing. Infants with FXS displayed higher levels of activation to faces across all areas analyzed, while ASIBs show more muted levels of activation. Overall, the results of the current study demonstrate the importance of group-specific head models for accurate cortical source analysis in infants at high risk for ASD. This also allows for further research on early distinctions in brain function based on risk status.

EEG functional connectivity analysis in the source space

There is a growing interest in using electroencephalography (EEG) and source modeling to investigate functional interactions among cortical processes, particularly when dealing with pediatric populations. This paper introduces two pipelines that have been recently used to conduct EEG FC analysis in the cortical source space. The analytic streams of these pipelines can be summarized into the following steps: 1) cortical source reconstruction of high-density EEG data using realistic magnetic resonance imaging (MRI) models created with age-appropriate MRI templates; 2) segmentation of reconstructed source activities into brain regions of interest; and 3) estimation of FC in age-related frequency bands using robust EEG FC measures, such as weighted phase lag index and orthogonalized power envelope correlation. In this paper we demonstrate the two pipelines with resting-state EEG data collected from children at 12 and 36 months of age. We also discuss the advantages and limitations of the methods/techniques integrated into the pipelines. Given there is a need in the research community for open-access analytic toolkits that can be used for pediatric EEG data, programs and codes used for the current analysis are made available to the public.

Evaluating Head Models for Cortical Source Localization of the Face-Sensitive N290 Component in Infants

Accurate cortical source localization of event-related potentials (ERPs) requires using realistic head models constructed from the participant's structural magnetic resonance imaging (MRI). A challenge in developmental studies is the limited accessibility of participant-specific MRIs. The present study compared source localization of infants' N290 ERP activities estimated using participant-specific head models with a series of substitute head models. The N290 responses to faces relative to toys were measured in 36 infants aged at 4.5, 7.5, 9, and 12 months. The substitutes were individual-based head models constructed from age-matched MRIs with closely matched ("close") or different ("far") head measures with the participants, age-appropriate average template, and age-inappropriate average templates. The greater source responses to faces than toys at the middle fusiform gyrus (mFG) estimated using participant-specific head models were preserved in individual-based head models, but not average templates. The "close" head models yielded the best fit with the participant-specific head models in source activities at the mFG and across face-processing-related regions of interest (ROIs). The age-appropriate average template showed mixed results, not supporting the stimulus effect but showed topographical distributions across the ROIs like the participant-specific head models. The "close" head models are the most optimal substitute for participant-specific MRIs.

A Chinese multi-modal neuroimaging data release for increasing diversity of human brain mapping

The big-data use is becoming a standard practice in the neuroimaging field through data-sharing initiatives. It is important for the community to realize that such open science effort must protect personal, especially facial information when raw neuroimaging data are shared. An ideal tool for the face anonymization should not disturb subsequent brain tissue extraction and further morphological measurements. Using the high-resolution head images from magnetic resonance imaging (MRI) of 215 healthy Chinese, we discovered and validated a template effect on the face anonymization. Improved facial anonymization was achieved when the Chinese head templates but not the Western templates were applied to obscure the faces of Chinese brain images. This finding has critical implications for international brain imaging data-sharing. To facilitate the further investigation of potential culture-related impacts on and increase diversity of data-sharing for the human brain mapping, we released the 215 Chinese multi-modal MRI data into a database for imaging Chinese young brains, namely'I See your Brains (ISYB)', to the public via the Science Data Bank ( https://doi.org/10.11922/sciencedb.00740 ).

Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review

Currently, information and communication technology (ICT) allows health institutions to reach disadvantaged groups in rural areas using sensing and artificial intelligence (AI) technologies. Applications of these technologies are even more essential for maternal and infant health, since maternal and infant health is vital for a healthy society. Over the last few years, researchers have delved into sensing and artificially intelligent healthcare systems for maternal and infant health. Sensors are exploited to gauge health parameters, and machine learning techniques are investigated to predict the health conditions of patients to assist medical practitioners. Since these healthcare systems deal with large amounts of data, significant development is also noted in the computing platforms. The relevant literature reports the potential impact of ICT-enabled systems for improving maternal and infant health. This article reviews wearable sensors and AI algorithms based on existing systems designed to predict the risk factors during and after pregnancy for both mothers and infants. This review covers sensors and AI algorithms used in these systems and analyzes each approach with its features, outcomes, and novel aspects in chronological order. It also includes discussion on datasets used and extends challenges as well as future work directions for researchers.

Growth charts of brain morphometry for preschool children

Brain development from 1 to 6 years of age anchors a wide range of functional capabilities and carries early signs of neurodevelopmental disorders. However, quantitative models for depicting brain morphology changes and making individualized inferences are lacking, preventing the identification of early brain atypicality during this period. With a total sample size of 285, we characterized the age-dependence of the cortical thickness and subcortical volume in neurologically normal children and constructed quantitative growth charts of all brain regions for preschool children. While the cortical thickness of most brain regions decreased with age, the entorhinal and parahippocampal regions displayed an inverted-U shape of age-dependence. Compared to the cortical thickness, the normalized volume of subcortical regions exhibited more divergent trends, with some regions increasing, some decreasing, and some displaying inverted-U-shaped trends. The growth curve models for all brain regions demonstrated utilities in identifying brain atypicality. The percentile measures derived from the growth curves facilitate the identification of children with developmental speech and language disorders with an accuracy of 0.875 (area under the receiver operating characteristic curve: 0.943). Our results fill the knowledge gap in brain morphometrics in a critical development period and provide an avenue for individualized brain developmental status evaluation with demonstrated sensitivity.

Acoustic-level and language-specific processing of native and non-native phonological sequence onsets in the low gamma and theta-frequency bands

Acoustic structures associated with native-language phonological sequences are enhanced within auditory pathways for perception, although the underlying mechanisms are not well understood. To elucidate processes that facilitate perception, time-frequency (T-F) analyses of EEGs obtained from native speakers of English and Polish were conducted. Participants listened to same and different nonword pairs within counterbalanced attend and passive conditions. Nonwords contained the onsets /pt/, /pət/, /st/, and /sət/ that occur in both the Polish and English languages with the exception of /pt/, which never occurs in the English language in word onset. Measures of spectral power and inter-trial phase locking (ITPL) in the low gamma (LG) and theta-frequency bands were analyzed from two bilateral, auditory source-level channels, created through source localization modeling. Results revealed significantly larger spectral power in LG for the English listeners to the unfamiliar /pt/ onsets from the right hemisphere at early cortical stages, during the passive condition. Further, ITPL values revealed distinctive responses in high and low-theta to acoustic characteristics of the onsets, which were modulated by language exposure. These findings, language-specific processing in LG and acoustic-level and language-specific processing in theta, support the view that multi scale temporal processing in the LG and theta-frequency bands facilitates speech perception.

Novel MRI deformation-heterogeneity radiomic features are associated with molecular subgroups and overall survival in pediatric medulloblastoma: Preliminary findings from a multi-institutional study

Introduction

Medulloblastoma (MB) is a malignant, heterogenous brain tumor. Advances in molecular profiling have led to identifying four molecular subgroups of MB (WNT, SHH, Group 3, Group 4), each with distinct clinical behaviors. We hypothesize that (1) aggressive MB tumors, growing heterogeneously, induce pronounced local structural deformations in the surrounding parenchyma, and (b) these local deformations as captured on Gadolinium (Gd)-enhanced-T1w MRI are independently associated with molecular subgroups, as well as overall survival in MB patients.

Methods

In this work, a total of 88 MB studies from 2 institutions were analyzed. Following tumor delineation, Gd-T_1w scan for every patient was registered to a normal age-specific T_1w-MRI template via deformable registration. Following patient-atlas registration, local structural deformations in the brain parenchyma were obtained for every patient by computing statistics from deformation magnitudes obtained from every 5mm annular region, 0 < d < 60 mm, where d is the distance from the tumor infiltrating edge.

Results

Multi-class comparison via ANOVA yielded significant differences between deformation magnitudes obtained for Group 3, Group 4, and SHH molecular subgroups, observed up to 60-mm outside the tumor edge. Additionally, Kaplan-Meier survival analysis showed that the local deformation statistics, combined with the current clinical risk-stratification approaches (molecular subgroup information and Chang's classification), could identify significant differences between high-risk and low-risk survival groups, achieving better performance results than using any of these approaches individually.

Discussion

These preliminary findings suggest there exists significant association of our tumor-induced deformation descriptor with overall survival in MB, and that there could be an added value in using the proposed radiomic descriptor along with the current risk classification approaches, towards more reliable risk assessment in pediatric MB.

The Influence of the Head Model Conductor on the Source Localization of Auditory Evoked Potentials

The accuracy of EEG source analysis reconstruction improves when a realistic head volume conductor is modeled. In this study we investigated how the progressively more complex head representations influence the spatial localization of auditory-evoked potentials (AEPs). Fourteen young-adult participants with normal hearing performed the AEP task. Individualized head models were obtained from structural MRI and diffusion-weighted imaging scans collected in a separate session. AEPs were elicited by 1 k Hz and 4 k Hz tone bursts during a passive-listening tetanizing paradigm. We compared the amplitude of the N1 and P2 components before and after 4 min of tetanic-stimulation with 1 k Hz sounds. Current density reconstruction values of both components were investigated in the primary auditory cortex and adjacent areas. Furthermore, we compared the signal topography and magnitude obtained with 10 different head models on the EEG forward solution. Starting from the simplest model (scalp, skull, brain), we investigated the influence of modeling the CSF, distinguishing between GM and WM conductors, and including anisotropic WM values. We localized the activity of AEPs within the primary auditory cortex, but not in adjacent areas. The inclusion of the CSF compartment had the strongest influence on the source reconstruction, whereas white matter anisotropy led to a smaller improvement. We conclude that individualized realistic head models provide the best solution for the forward solution when modeling the CSF conductor.

Exploring the relationship between metal exposure, BDNF, and behavior in adolescent males

BACKGROUND

Brain-derived neurotrophic factor (BDNF) plays an important role in brain development by regulating multiple pathways within the central nervous system. In the Human Biomonitoring for Europe Project (HBM4EU), this neurotrophin is being implemented as a novel effect biomarker to evaluate the potential threats of environmental chemicals on neurodevelopment.

OBJECTIVES

To explore the relationships among exposure to environmental metals, BDNF biomarkers at two levels of biological complexity, and behavioral function in adolescent males.

METHODS

Data were gathered from 125 adolescents on: spot urine sample total concentrations of the neurotoxic metal(oid)s arsenic (As), cadmium (Cd), mercury (Hg), and lead (Pb); serum BDNF protein concentrations; and concurrent behavioral functioning according to the Child Behavior Check List (CBCL/6-18). In 113 of the participants, information was also collected on blood BDNF DNA methylation at six CpGs. Associations were evaluated by multivariate linear regression analysis adjusted for confounders.

RESULTS

As, Cd, Hg, and Pb were detected in 100%, 98.5%, 97.0%, and 89.5% of urine samples, respectively. Median serum BDNF concentration was 32.6 ng/mL, and total percentage of BDNF gene methylation was 3.8%. In the adjusted models, urinary As was non-linearly associated with more internalizing problems and Cd with more externalizing behaviors. The percentage BDNF DNA methylation at CPGs #5 and the mean percentage CpG methylation increased across As tertiles (p-trend = 0.04 and 0.03, respectively), while 2nd tertile and 3rd tertile of Cd concentrations were associated with lower serum BDNF and higher CpG3 methylation percentage. Additionally, when BDNF was categorized in tertiles, serum BDNF at the 3rd tertile was associated with fewer behavioral problems, particularly withdrawn (p-trend = 0.04), social problems (p-trend = 0.12), and thought problems (p-trend = 0.04).

CONCLUSION

Exposure to As and Cd was associated with BDNF gene DNA methylation BDNF gene and serum BDNF, respectively. Associations with DNA methylation may be attributable to a higher variability over time in circulating BDNF concentrations than in the methylation status of this gene. Caution should be taken when interpreting the results relating postnatal Pb and Hg to behavioral functioning. Further studies are needed to verify these findings.

A Scoping Review of Clinical Studies in Infants Fed Formulas Containing Palm Oil or Palm Olein and Sn-2 Palmitate

BACKGROUND

Palmitic acid (PA; 16:0) is added to infant formula in the form of palm oil/palm olein (PO/POL) and stereospecific numbered-2 palmitate (SN2). Several studies have examined the effects of PO/POL and or SN2 in formulas on health outcomes, mainly growth, digestion, and absorption of nutrients. However, the roles of PA, PO/POL, and SN2 on neurodevelopment remains unknown.

OBJECTIVES

The objective of this scoping review was to map out studies in infants fed formula with PO/POL or SN2 to identify current knowledge on the role of PA in infant nutrition, specifically neurodevelopment.

METHODS

Data sources, including Medline, Embase, CAB Abstracts, and the Cochrane Database, were searched. Eligible articles were randomized controlled trials (RCTs) and observational studies examining outcomes in term singleton infants fed formula containing PO/POL or SN2. Studies examining preterm infants or infants with infections, mixed-feeding interventions, or outcomes not concerned with PO/POL or SN2 were excluded. Screening and data extraction were performed by 2 independent reviewers, and results were charted into 10 outcome categories.

RESULTS

We identified 28 RCTs and 2 observational studies. Only 1 RCT examined a neurodevelopmental outcome, reporting infants fed SN2 formula had higher fine motor skill scores compared to those fed a vegetable oil formula with a lower amount of SN2; however, only after adjustment for maternal education and at an earlier, but not a later time point. Anthropometric measures do not appear to be influenced by PO/POL or SN2 within formulas. Alternatively, it was reported that infants fed PO/POL within formulas had a decreased absorption of calcium, total fat, and PA compared to those fed vegetable oil formulas. However, studies were heterogenous, making it difficult to isolate the effects of PO/POL or SN2 in formulas.

CONCLUSIONS

Our review reiterates the need for future studies to address the effects of PO/POL and SN2 on neurodevelopment in infants. This study is registered at Open Science Framework as osf.io/697he.

A multimodal approach to the study of children treated for posterior fossa tumor: A review of the literature and a pilot study

OBJECTIVE

The aims of the present study were: (1) to review the literature on long-lasting cognitive sequelae in children treated for Posterior Fossa Tumor and (2) to investigate anatomic functional relations in a case series of 7 children treated for PFT using magnetic resonance imaging (MRI) post-processing methods.

METHODS

We retrospectively analyzed MRIs of children who underwent complete surgical resection of PFT and performed extensive neuropsychological evaluation. Tumor, ventricular volumes, and VPS insertion site were drawn on T1 volumetric MRI scans and normalized to a pediatric template. Children showed worse performances on tasks tapping executive functions, memory, visuo-motor precision, and expressive language.

RESULTS

Volumes of interest related to these functions showed a maximum overlap on the left vermis and the lateral ventricle enlargement, except for impaired narrative fluency -which was associated with left lateral ventricle enlargement- and narrative memory -which was related to the right vermis and the enlarged fourth ventricle.

CONCLUSION

Results suggest that anatomic functional relations in children treated for PFT are related to a combination of different pathophysiological factors.

Age-related changes in diffuse optical tomography sensitivity profiles in infancy

Diffuse optical tomography uses near-infrared light spectroscopy to measure changes in cerebral hemoglobin concentration. Anatomical interpretations of the location that generates the hemodynamic signal requires accurate descriptions of diffuse optical tomography sensitivity to the underlying cortical structures. Such information is limited for pediatric populations because they undergo rapid head and brain development. The present study used photon propagation simulation methods to examine diffuse optical tomography sensitivity profiles in realistic head models among infants ranging from 2 weeks to 24 months with narrow age bins, children (4 and 12 years) and adults (20 to 24 years). The sensitivity profiles changed systematically with the source-detector separation distance. The peak of the sensitivity function in the head was largest at the smallest separation distance and decreased as separation distance increased. The fluence value dissipated more quickly with sampling depth at the shorter source-detector separations than the longer separation distances. There were age-related differences in the shape and variance of sensitivity profiles across a wide range of source-detector separation distances. Our findings have important implications in the design of sensor placement and diffuse optical tomography image reconstruction in (functional) near-infrared light spectroscopy research. Age-appropriate realistic head models should be used to provide anatomical guidance for standalone near-infrared light spectroscopy data in infants.

Does participant's age impact on tDCS induced fields? Insights from computational simulations

Objective: Understanding the induced current flow from transcranial direct current stimulation (tDCS) is essential for determining the optimal dose and treatment. Head tissue conductivities play a key role in the resulting electromagnetic fields. However, there exists a complicated relationship between skull conductivity and participant age, that remains unclear. We explored how variations in skull electrical conductivities, particularly as a suggested function of age, affected tDCS induced electric fields.Approach: Simulations were employed to compare tDCS outcomes for different intensities across head atlases of varying age. Three databases were chosen to demonstrate differing variability in skull conductivity with age and how this may affect induced fields. Differences in tDCS electric fields due to proposed age-dependent skull conductivity variation, as well as deviations in grey matter, white matter and scalp, were compared and the most influential tissues determined.Main results: tDCS induced peak electric fields significantly negatively correlated with age, exacerbated by employing proposed age-appropriate skull conductivity (according to all three datasets). Uncertainty in skull conductivity was the most sensitive to changes in peak fields with increasing age. These results were revealed to be directly due to changing skull conductivity, rather than head geometry alone. There was no correlation between tDCS focality and age.Significance: Accurate and individualised head anatomy andin vivoskull conductivity measurements are essential for modelling tDCS induced fields. In particular, age should be taken into account when considering stimulation dose to precisely predict outcomes.

Longitudinal infant fNIRS channel-space analyses are robust to variability parameters at the group-level: An image reconstruction investigation

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First investigation of validity of longitudinal infant channel-space fNIRS analysis.

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Novel image reconstruction analysis conducted.

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Variability in array position is dominant factor driving different inferences.

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Channel-space fNIRS analyses robust to implicit assumptions at group-level.

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Hope to encourage more widespread use of image reconstruction in infant analyses.

The first 1000 days from conception to two-years of age are a critical period in brain development, and there is an increasing drive for developing technologies to help advance our understanding of neurodevelopmental processes during this time. Functional near-infrared spectroscopy (fNIRS) has enabled longitudinal infant brain function to be studied in a multitude of settings. Conventional fNIRS analyses tend to occur in the channel-space, where data from equivalent channels across individuals are combined, which implicitly assumes that head size and source-detector positions (i.e. array position) on the scalp are constant across individuals. The validity of such assumptions in longitudinal infant fNIRS analyses, where head growth is most rapid, has not previously been investigated. We employed an image reconstruction approach to analyse fNIRS data collected from a longitudinal cohort of infants in The Gambia aged 5- to 12-months. This enabled us to investigate the effect of variability in both head size and array position on the anatomical and statistical inferences drawn from the data at both the group- and the individual-level. We also sought to investigate the impact of group size on inferences drawn from the data. We found that variability in array position was the driving factor between differing inferences drawn from the data at both the individual- and group-level, but its effect was weakened as group size increased towards the full cohort size (N = 53 at 5-months, N = 40 at 8-months and N = 45 at 12-months). We conclude that, at the group sizes in our dataset, group-level channel-space analysis of longitudinal infant fNIRS data is robust to assumptions about head size and array position given the variability in these parameters in our dataset. These findings support a more widespread use of image reconstruction techniques in longitudinal infant fNIRS studies.

Development of brain atlases for early-to-middle adolescent collision-sport athletes

Human brains develop across the life span and largely vary in morphology. Adolescent collision-sport athletes undergo repetitive head impacts over years of practices and competitions, and therefore may exhibit a neuroanatomical trajectory different from healthy adolescents in general. However, an unbiased brain atlas targeting these individuals does not exist. Although standardized brain atlases facilitate spatial normalization and voxel-wise analysis at the group level, when the underlying neuroanatomy does not represent the study population, greater biases and errors can be introduced during spatial normalization, confounding subsequent voxel-wise analysis and statistical findings. In this work, targeting early-to-middle adolescent (EMA, ages 13-19) collision-sport athletes, we developed population-specific brain atlases that include templates (T1-weighted and diffusion tensor magnetic resonance imaging) and semantic labels (cortical and white matter parcellations). Compared to standardized adult or age-appropriate templates, our templates better characterized the neuroanatomy of the EMA collision-sport athletes, reduced biases introduced during spatial normalization, and exhibited higher sensitivity in diffusion tensor imaging analysis. In summary, these results suggest the population-specific brain atlases are more appropriate towards reproducible and meaningful statistical results, which better clarify mechanisms of traumatic brain injury and monitor brain health for EMA collision-sport athletes.

Neural and behavioral effects of perceptual load on auditory selective attention

Healthy adults performed an auditory version of the flanker task under low versus high perceptual load while behavioral and electrophysiological measures were recorded. Participants experienced less attentional interference under low load than high load, whether analyses were performed between tasks (Garner interference; found in accuracy and RT), between stimuli (flanker congruity; found in accuracy), or between sequences (Gratton effect; found in accuracy). Analysis of event-related potentials to the distractor (flanker), which was physically identical across load conditions, revealed load modulation of tasks effects in the P1 component (peak amplitude and latency), an early perceptual component peaking approximately 75 ms after distractor onset. As in behavioral performance, ERP analyses showed that auditory attentional disruption in P1 was significantly smaller under low perceptual load. Dipole source analysis suggested activation of prefrontal inhibitory control during low load and default mode network during high load. The results are in keeping with the predictions of tectonic theory (Melara & Algom, 2003), but inconsistent with expectations derived from perceptual load theory (Lavie, 1995).

Early Diagnostics and Early Intervention in Neurodevelopmental Disorders-Age-Dependent Challenges and Opportunities

This review discusses early diagnostics and early intervention in developmental disorders in the light of brain development. The best instruments for early detection of cerebral palsy (CP) with or without intellectual disability are neonatal magnetic resonance imaging, general movements assessment at 2-4 months and from 2-4 months onwards, the Hammersmith Infant Neurological Examination and Standardized Infant NeuroDevelopmental Assessment. Early detection of autism spectrum disorders (ASD) is difficult; its first signs emerge at the end of the first year. Prediction with the Modified Checklist for Autism in Toddlers and Infant Toddler Checklist is possible to some extent and improves during the second year, especially in children at familial risk of ASD. Thus, prediction improves substantially when transient brain structures have been replaced by permanent circuitries. At around 3 months the cortical subplate has dissolved in primary motor and sensory cortices; around 12 months the cortical subplate in prefrontal and parieto-temporal cortices and cerebellar external granular layer have disappeared. This review stresses that families are pivotal in early intervention. It summarizes evidence on the effectiveness of early intervention in medically fragile neonates, infants at low to moderate risk, infants with or at high risk of CP and with or at high risk of ASD.

Development, validation, and pilot MRI safety study of a high-resolution, open source, whole body pediatric numerical simulation model

Numerical body models of children are used for designing medical devices, including but not limited to optical imaging, ultrasound, CT, EEG/MEG, and MRI. These models are used in many clinical and neuroscience research applications, such as radiation safety dosimetric studies and source localization. Although several such adult models have been reported, there are few reports of full-body pediatric models, and those described have several limitations. Some, for example, are either morphed from older children or do not have detailed segmentations. Here, we introduce a 29-month-old male whole-body native numerical model, "MARTIN", that includes 28 head and 86 body tissue compartments, segmented directly from the high spatial resolution MRI and CT images. An advanced auto-segmentation tool was used for the deep-brain structures, whereas 3D Slicer was used to segment the non-brain structures and to refine the segmentation for all of the tissue compartments. Our MARTIN model was developed and validated using three separate approaches, through an iterative process, as follows. First, the calculated volumes, weights, and dimensions of selected structures were adjusted and confirmed to be within 6% of the literature values for the 2-3-year-old age-range. Second, all structural segmentations were adjusted and confirmed by two experienced, sub-specialty certified neuro-radiologists, also through an interactive process. Third, an additional validation was performed with a Bloch simulator to create synthetic MR image from our MARTIN model and compare the image contrast of the resulting synthetic image with that of the original MRI data; this resulted in a "structural resemblance" index of 0.97. Finally, we used our model to perform pilot MRI safety simulations of an Active Implantable Medical Device (AIMD) using a commercially available software platform (Sim4Life), incorporating the latest International Standards Organization guidelines. This model will be made available on the Athinoula A. Martinos Center for Biomedical Imaging website.

Electroencephalography source localization analysis in epileptic children during a visual working-memory task

We localize the sources of brain activity of children with epilepsy based on electroencephalograph (EEG) recordings acquired during a visual discrimination working memory task. For the numerical solution of the inverse problem, with the aid of age-specific MRI scans processed from a publicly available database, we use and compare three regularization numerical methods, namely the standardized low resolution brain electromagnetic tomography (sLORETA), the weighted minimum norm estimation (wMNE) and the dynamic statistical parametric mapping (dSPM). We show that all three methods provide the same spatio-temporal patterns of differences between the groups of epileptic and control children. In particular, our analysis reveals statistically significant differences between the two groups in regions of the parietal cortex indicating that these may serve as "biomarkers" for diagnostic purposes and ultimately localized treatment.

Construction and validation of a database of head models for functional imaging of the neonatal brain

The neonatal brain undergoes dramatic structural and functional changes over the last trimester of gestation. The accuracy of source localisation of brain activity recorded from the scalp therefore relies on accurate age-specific head models. Although an age-appropriate population-level atlas could be used, detail is lost in the construction of such atlases, in particular with regard to the smoothing of the cortical surface, and so such a model is not representative of anatomy at an individual level. In this work, we describe the construction of a database of individual structural priors of the neonatal head using 215 individual-level datasets at ages 29-44 weeks postmenstrual age from the Developing Human Connectome Project. We have validated a method to segment the extra-cerebral tissue against manual segmentation. We have also conducted a leave-one-out analysis to quantify the expected spatial error incurred with regard to localising functional activation when using a best-matching individual from the database in place of a subject-specific model; the median error was calculated to be 8.3 mm (median absolute deviation 3.8 mm). The database can be applied for any functional neuroimaging modality which requires structural data whereby the physical parameters associated with that modality vary with tissue type and is freely available at www.ucl.ac.uk/dot-hub.

The functional brain networks that underlie visual working memory in the first two years of life

Visual working memory (VWM) is a central cognitive system used to compare views of the world and detect changes in the local environment. This system undergoes dramatic development in the first two years; however, we know relatively little about the functional organization of VWM at the level of the brain. Here, we used image-based functional near-infrared spectroscopy (fNIRS) to test four hypotheses about the spatial organization of the VWM network in early development. Four-month-olds, 1-year-olds, and 2-year-olds completed a VWM task while we recorded neural activity from 19 cortical regions-of-interest identified from a meta-analysis of the adult fMRI literature on VWM. Results showed significant task-specific functional activation near 6 of 19 ROIs, revealing spatial consistency in the brain regions activated in our study and brain regions identified to be part of the VWM network in adult fMRI studies. Working memory related activation was centered on bilateral anterior intraparietal sulcus (aIPS), left temporoparietal junction (TPJ), and left ventral occipital complex (VOC), while visual exploratory measures were associated with activation in right dorsolateral prefrontal cortex, left TPJ, and bilateral IPS. Results show that a distributed brain network underlies functional changes in VWM in infancy, revealing new insights into the neural mechanisms that support infants’ improved ability to remember visual information and to detect changes in an on-going visual stream.

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A distributed brain network underlies functional changes in VWM in infancy and toddlerhood.

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This network shows robust engagement of similar brain regions identified in fMRI studies with adults as early as four months.

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Working memory related activation was centered on bilateral anterior intraparietal sulcus, left temporoparietal junction, and left ventral occipital complex

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Visual exploratory measures were associated with activation in right dorsolateral prefrontal cortex, bilateral anterior intraparietal sulcus, and left temporoparietal junction.

Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands

A diverse set of white matter connections supports seamless transitions between cognitive states. However, it remains unclear how these connections guide the temporal progression of large-scale brain activity patterns in different cognitive states. Here, we analyze the brain's trajectories across a set of single time point activity patterns from functional magnetic resonance imaging data acquired during the resting state and an n-back working memory task. We find that specific temporal sequences of brain activity are modulated by cognitive load, associated with age, and related to task performance. Using diffusion-weighted imaging acquired from the same subjects, we apply tools from network control theory to show that linear spread of activity along white matter connections constrains the probabilities of these sequences at rest, while stimulus-driven visual inputs explain the sequences observed during the n-back task. Overall, these results elucidate the structural underpinnings of cognitively and developmentally relevant spatiotemporal brain dynamics.

Face-sensitive brain responses in the first year of life

Cortical areas in the ventral visual pathway become selectively tuned towards the processing of faces compared to non-face stimuli beginning around 3 months of age and continuing over the first year. Studies using event-related potentials in the EEG (ERPs) have found an ERP component, the N290, that displays specificity for human faces. Other components, such as the P1, P400, and Nc have been studied to a lesser degree in their responsiveness to human faces. However, little is known about the systematic changes in the neural responses to faces during the first year of life, and the localization of these responses in infants' brain. We examined ERP responses to pictures of faces and objects in infants from 4.5 months through 12 months in a cross-sectional study. We investigated the activity of all the components reported to be involved in infant face processing, with particular interest to their amplitude variation and cortical localization. We identified neural regions responsible for the component through the application of cortical source localization methods. We found larger P1 and N290 responses to faces than objects, and these components were localized in the lingual and middle/posterior fusiform gyri, respectively. The amplitude of the P400 was not differentially sensitive to faces over objects. The Nc component was different for faces and objects, was influenced by the infant's attentional state, and localized in medial-anterior brain areas. The implications of these results are discussed in the identification of developmental ERP precursors to face processing.

Deep Cerebellar Transcranial Direct Current Stimulation of the Dentate Nucleus to Facilitate Standing Balance in Chronic Stroke Survivors-A Pilot Study

Objective: Cerebrovascular accidents are the second leading cause of death and the third leading cause of disability worldwide. We hypothesized that cerebellar transcranial direct current stimulation (ctDCS) of the dentate nuclei and the lower-limb representations in the cerebellum can improve functional reach during standing balance in chronic (>6 months’ post-stroke) stroke survivors. Materials and Methods: Magnetic resonance imaging (MRI) based subject-specific electric field was computed across a convenience sample of 10 male chronic (>6 months) stroke survivors and one healthy MRI template to find an optimal bipolar bilateral ctDCS montage to target dentate nuclei and lower-limb representations (lobules VII–IX). Then, in a repeated-measure crossover study on a subset of 5 stroke survivors, we compared 15 min of 2 mA ctDCS based on the effects on successful functional reach (%) during standing balance task. Three-way ANOVA investigated the factors of interest– brain regions, montages, stroke participants, and their interactions. Results: “One-size-fits-all” bipolar ctDCS montage for the clinical study was found to be PO9h–PO10h for dentate nuclei and Exx7–Exx8 for lobules VII–IX with the contralesional anode. PO9h–PO10h ctDCS performed significantly (alpha = 0.05) better in facilitating successful functional reach (%) when compared to Exx7–Exx8 ctDCS. Furthermore, a linear relationship between successful functional reach (%) and electric field strength was found where PO9h–PO10h montage resulted in a significantly (alpha = 0.05) higher electric field strength when compared to Exx7–Exx8 montage for the same 2 mA current. Conclusion: We presented a rational neuroimaging based approach to optimize deep ctDCS of the dentate nuclei and lower limb representations in the cerebellum for post-stroke balance rehabilitation. However, this promising pilot study was limited by “one-size-fits-all” bipolar ctDCS montage as well as a small sample size.

Sample sizes and population differences in brain template construction

Spatial normalization or deformation to a standard brain template is routinely used as a key module in various pipelines for the processing of magnetic resonance imaging (MRI) data. Brain templates are often constructed using MRI data from a limited number of subjects. Individual brains show significant variabilities in their morphology; thus, sample sizes and population differences are two key factors that influence brain template construction. To address these influences, we employed two independent groups from the Human Connectome Project (HCP) and the Chinese Human Connectome Project (CHCP) to quantify the impacts of sample sizes and population on brain template construction. We first assessed the effect of sample size on the construction of volumetric brain templates using data subsets from the HCP and CHCP datasets. We applied a voxel-wise index of the deformation variability and a logarithmically transformed Jacobian determinant to quantify the variability associated with the template construction and modeled the brain template variability as a power function of the sample size. At the system level, the frontoparietal control network and dorsal attention network demonstrated higher deformation variability and logged Jacobian determinants, whereas other primary networks showed lower variability. To investigate the population differences, we constructed Caucasian and Chinese standard brain atlases (namely, US200 and CN200). The two demographically matched templates, particularly the language-related areas, exhibited dramatic bilaterally in supramarginal gyri and inferior frontal gyri differences in their deformation variability and logged Jacobian determinant. Using independent data from the HCP and CHCP, we examined the segmentation and registration accuracy and observed significant reduction in the performance of the brain segmentation and registration when the population-mismatched templates were used in the spatial normalization. Our findings provide evidence to support the use of population-matched templates in human brain mapping studies. The US200 and CN200 templates have been released on the Neuroimage Informatics Tools and Resources Clearinghouse (NITRC) website (https://www.nitrc.org/projects/us200_cn200/).

Opioids affect the fetal brain: reframing the detoxification debate

Medication-assisted treatment is recommended for individuals with an opioid use disorder, including pregnant women. Medication-assisted treatment during pregnancy provides benefits to the mother and fetus, including better pregnancy outcomes, reduced illicit drug use, and improved prenatal care. An alternative approach, medically supervised withdrawal (detoxification), has, in recent reports, demonstrated a low risk of fetal death and low rates of relapse and neonatal abstinence syndrome. The rates of relapse and neonatal abstinence syndrome are questioned by many who view medically supervised withdrawal as unacceptable based on the concern for the potential adverse consequences of relapse to mother and baby. The impact of opioids on the fetal brain have not been integrated into this debate. Studies in animals and human brain tissues demonstrate opioid receptors in neurons, astroglia, and oligodendrocytes. Age-specific normative data from infants, children, and adults have facilitated investigation of the impact of opioids on the human brain in vivo. Collectively, these studies in animals, human neural tissue, adult brains, and the brains of children and newborns demonstrate that opioids adversely affect the human brain, primarily the developing oligodendrocyte and the processes of myelinization (white matter microstructure), connectivity between parts of the brain, and the size of multiple brain regions, including the basal ganglia, thalamus, and cerebellar white matter. These in vivo studies across the human lifespan suggest vulnerability of specific fronto-temporal-limbic and frontal-subcortical (basal ganglia and cerebellum) pathways that are also likely vulnerable in the human fetal brain. The long-term impact of these reproducible changes in the fetal brain in vivo is unclear, but the possibility of lasting injury has been suggested. In light of the recent data on medically supervised withdrawal and the emerging evidence suggesting adverse effects of opioids on the developing fetal brain, a new paradigm of care is needed that includes the preferred option of medication-assisted treatment but also the option of medically supervised opioid withdrawal for a select group of women. Both these treatment options should offer mental health and social services support throughout pregnancy. More research on both opioid exposure on the developing human brain and the impact of medically supervised withdrawal is required to identify appropriate candidates, optimal dose reduction regimens, and gestational age timing for initiating medically supervised withdrawal.

Growth faltering is associated with altered brain functional connectivity and cognitive outcomes in urban Bangladeshi children exposed to early adversity

BACKGROUND

Stunting affects more than 161 million children worldwide and can compromise cognitive development beginning early in childhood. There is a paucity of research using neuroimaging tools in conjunction with sensitive behavioral assays in low-income settings, which has hindered researchers' ability to explain how stunting impacts brain and behavioral development. We employed high-density EEG to examine associations among children's physical growth, brain functional connectivity (FC), and cognitive development.

METHODS

We recruited participants from an urban impoverished neighborhood in Dhaka, Bangladesh. One infant cohort consisted of 92 infants whose height (length) was measured at 3, 4.5, and 6 months; EEG data were collected at 6 months; and cognitive outcomes were assessed using the Mullen Scales of Early Learning at 27 months. A second, older cohort consisted of 118 children whose height was measured at 24, 30, and 36 months; EEG data were collected at 36 months; and Intelligence Quotient (IQ) scores were assessed at 48 months. Height-for-age (HAZ) z-scores were calculated based on the World Health Organization standard. EEG FC in different frequency bands was calculated in the cortical source space. Linear regression and longitudinal path analysis were conducted to test the associations between variables, as well as the indirect effect of child growth on cognitive outcomes via brain FC.

RESULTS

In the older cohort, we found that HAZ was negatively related to brain FC in the theta and beta frequency bands, which in turn was negatively related to children's IQ score at 48 months. Longitudinal path analysis showed an indirect effect of HAZ on children's IQ via brain FC in both the theta and beta bands. There were no associations between HAZ and brain FC or cognitive outcomes in the infant cohort.

CONCLUSIONS

The association observed between child growth and brain FC may reflect a broad deleterious effect of malnutrition on children's brain development. The mediation effect of FC on the relation between child growth and later IQ provides the first evidence suggesting that brain FC may serve as a neural pathway by which biological adversity impacts cognitive development.

The neural correlates of orienting to walking direction in 6-month-old infants: An ERP study

The ability to detect social signals represents a first step to enter our social world. Behavioral evidence has demonstrated that 6-month-old infants are able to orient their attention toward the position indicated by walking direction, showing faster orienting responses toward stimuli cued by the direction of motion than toward uncued stimuli. The present study investigated the neural mechanisms underpinning this attentional priming effect by using a spatial cueing paradigm and recording EEG (Geodesic System 128 channels) from 6-month-old infants. Infants were presented with a central point-light walker followed by a single peripheral target. The target appeared randomly at a position either congruent or incongruent with the walking direction of the cue. We examined infants' target-locked event-related potential (ERP) responses and we used cortical source analysis to explore which brain regions gave rise to the ERP responses. The P1 component and saccade latencies toward the peripheral target were modulated by the congruency between the walking direction of the cue and the position of the target. Infants' saccade latencies were faster in response to targets appearing at congruent spatial locations. The P1 component was larger in response to congruent than to incongruent targets and a similar congruency effect was found with cortical source analysis in the parahippocampal gyrus and the anterior fusiform gyrus. Overall, these findings suggest that a type of biological motion like the one of a vertebrate walking on the legs can trigger covert orienting of attention in 6-month-old infants, enabling enhancement of neural activity related to visual processing of potentially relevant information as well as a facilitation of oculomotor responses to stimuli appearing at the attended location.

Early adversity in rural India impacts the brain networks underlying visual working memory

There is a growing need to understand the global impact of poverty on early brain and behavioural development, particularly with regard to key cognitive processes that emerge in early development. Although the impact of adversity on brain development can trap children in an intergenerational cycle of poverty, the massive potential for brain plasticity is also a source of hope: reliable, accessible, culturally agnostic methods to assess early brain development in low resource settings might be used to measure the impact of early adversity, identify infants for timely intervention and guide the development and monitor the effectiveness of early interventions. Visual working memory (VWM) is an early marker of cognitive capacity that has been assessed reliably in early infancy and is predictive of later academic achievement in Western countries. Here, we localized the functional brain networks that underlie VWM in early development in rural India using a portable neuroimaging system, and we assessed the impact of adversity on these brain networks. We recorded functional brain activity as young children aged 4-48 months performed a VWM task. Brain imaging results revealed localized activation in the frontal cortex, replicating findings from a Midwestern US sample. Critically, children from families with low maternal education and income showed weaker brain activity and poorer distractor suppression in canonical working memory areas in the left frontal cortex. Implications of this work are far-reaching: it is now cost-effective to localize functional brain networks in early development in low-resource settings, paving the way for novel intervention and assessment methods.

The neural sources of N170: Understanding timing of activation in face-selective areas

The N170 ERP component has been widely identified as a face-sensitive neural marker. Despite extensive investigations conducted to examine the neural sources of N170, there are two issues in prior literature: (a) few studies used individualized anatomy as head model for the cortical source analysis of the N170, and (b) the relationship between the N170 and face-selective regions from fMRI studies is unclear. Here, we addressed these questions by presenting pictures of faces and houses to the same group of healthy adults and recording structural MRI, fMRI, and high-density ERPs in separate sessions. Source analysis based on the participant's anatomy showed that the middle and posterior fusiform gyri were the primary neural sources for the face-sensitive aspects of the N170. Source analysis based on regions of interest from the fMRI revealed that the fMRI-defined fusiform face area was the major contributor to the N170. The current study suggests that the fusiform gyrus is a major neural contributor to the N170 ERP component and provides further insights about the spatiotemporal characteristics of face processing.

Beyond the Bayley: Neurocognitive Assessments of Development During Infancy and Toddlerhood

The use of global, standardized instruments is conventional among clinicians and researchers interested in assessing neurocognitive development. Exclusively relying on these tests for evaluating effects may underestimate or miss specific effects on early cognition. The goal of this review is to identify alternative measures for possible inclusion in future clinical trials and interventions evaluating early neurocognitive development. The domains included for consideration are attention, memory, executive function, language, and socioemotional development. Although domain-based tests are limited, as psychometric properties have not yet been well-established, this review includes tasks and paradigms that have been reliably used across various developmental psychology laboratories.

Semantic anomaly detection in school-aged children during natural sentence reading - A study of fixation-related brain potentials

In this study, we investigated the effects of context-related semantic anomalies on the fixation-related brain potentials of 12-13-year-old Finnish children in grade 6 during sentence reading. The detection of such anomalies is typically reflected in the N400 event-related potential. We also examined whether the representation invoked by the sentence context extends to the orthographic representation level by replacing the final words of the sentence with an anomalous word neighbour of a plausible word. The eye-movement results show that the anomalous word neighbours of plausible words cause similar first-fixation and gaze duration reactions, as do other anomalous words. Similarly, we observed frontal negativity in the fixation-related potential of the unrelated anomalous words and in the anomalous word neighbours. This frontal negativity was larger in both anomalous conditions than in the response elicited by the plausible condition. We thus show that the brain successfully uses context to separate anomalous words from plausible words on a single letter level during free reading. From the P600 response of the scalp waveform, we observed that the P600 was delayed in the anomalous word neighbour condition. We performed group-level decomposition on the data with ICA (independent component analysis) and analysed the time course and source structure of the decomposed data. This analysis of decomposed brain signals not only confirmed the delay of the P600 response but also revealed that the frontal negativity concealed s more typical and separate N400 response, which was similarly delayed in the anomalous word neighbour condition, as was the P600 response. Source analysis of these independent components implicated the right frontal eye field as the cortical source for the frontal negativity and the middle temporal and parietal regions as cortical sources for the components resembling the N400 and P600 responses. We interpret the delays present in N400 and P600 responses to anomalous word neighbours to reflect competition with the representation of the plausible word just one letter different.

Neural correlates of facial emotion processing in infancy

In the present study we examined the neural correlates of facial emotion processing in the first year of life using ERP measures and cortical source analysis. EEG data were collected cross-sectionally from 5- (N = 49), 7- (N = 50), and 12-month-old (N = 51) infants while they were viewing images of angry, fearful, and happy faces. The N290 component was found to be larger in amplitude in response to fearful and happy than angry faces in all posterior clusters and showed largest response to fear than the other two emotions only over the right occipital area. The P400 and Nc components were found to be larger in amplitude in response to angry than happy and fearful faces over central and frontal scalp. Cortical source analysis of the N290 component revealed greater cortical activation in the right fusiform face area in response to fearful faces. This effect started to emerge at 5 months and became well established at 7 months, but it disappeared at 12 months. The P400 and Nc components were primarily localized to the PCC/Precuneus where heightened responses to angry faces were observed. The current results suggest the detection of a fearful face in infants' brain can happen shortly (~200-290 ms) after the stimulus onset, and this process may rely on the face network and develop substantially between 5 to 7 months of age. The current findings also suggest the differential processing of angry faces occurred later in the P400/Nc time window, which recruits the PCC/Precuneus and is associated with the allocation of infants' attention.

The neural architecture of executive functions is established by middle childhood

Executive functions (EFs) are regulatory cognitive processes that support goal-directed thoughts and behaviors and that involve two primary networks of functional brain activity in adulthood: the fronto-parietal and cingulo-opercular networks. The current study assessed whether the same networks identified in adulthood underlie child EFs. Using task-based fMRI data from a diverse sample of N = 117 children and early adolescents (M age = 10.17 years), we assessed the extent to which neural activity was shared across switching, updating, and inhibition domains, and whether these patterns were qualitatively consistent with adult EF-related activity. Brain regions that were consistently engaged across switching, updating, and inhibition tasks closely corresponded to the cingulo-opercular and fronto-parietal networks identified in studies of adults. Isolating brain activity during more demanding task periods highlighted contributions of the dorsal anterior cingulate and anterior insular regions of the cingulo-opercular network. Results were independent of age and time-on-task effects. These results indicate that the two core brain networks that support EFs are in place by middle childhood, in agreement with resting-state findings of adultlike brain network organization. Improvement in EFs from middle childhood to adulthood, therefore, are likely due to quantitative changes in activity within these networks, rather than qualitative changes in the organization of the networks themselves. Improved knowledge of how the brain's functional organization supports EF in childhood has critical implications for understanding the maturation of cognitive abilities.

Development of brain functional connectivity and its relation to infant sustained attention in the first year of life

The study of brain functional connectivity is crucial to understanding the neural mechanisms underlying the improved behavioral performance and amplified ERP responses observed during infant sustained attention. Previous investigations on the development of functional brain connectivity during infancy are primarily confined to the use of functional and structural MRI techniques. The current study examined the relation between infant sustained attention and brain functional connectivity and their development during infancy with high-density EEG recordings. Fifty-nine infants were tested at 6 (N = 15), 8 (N =14), 10 (N = 17), and 12 (N = 13) months. Infant sustained attention was defined by measuring infant heart rate changes during infants' looking. Functional connectivity was estimated from the electrodes on the scalp and with reconstructed cortical source activities in brain regions. It was found that infant sustained attention was accompanied by attenuated functional connectivity in the dorsal attention and default mode networks in the alpha band. Graph theory analyses showed that there was an increase in path length and a decrease in clustering coefficient during infant sustained attention. The functional connectivity within the visual, somatosensory, dorsal attention, and ventral attention networks and graph theory measures of path length and clustering coefficient were found to increase with age. These findings suggest that infant sustained attention is accompanied by distinct patterns of brain functional connectivity. The current findings also suggest the rapid development of functional connectivity in brain networks during infancy.

Development of infant sustained attention and its relation to EEG oscillations: an EEG and cortical source analysis study

The current study examined the relation between infant sustained attention and infant EEG oscillations. Fifty-nine infants were tested at 6 (N = 15), 8 (N = 17), 10 (N = 14), and 12 (N = 13) months. Three attention phases, stimulus orienting, sustained attention, and attention termination, were defined based on infants' heart rate changes. Frequency analysis using simultaneously recorded EEG focused on infant theta (2-6 Hz), alpha (6-9 Hz), and beta (9-14 Hz) rhythms. Cortical source analysis of EEG oscillations was conducted with realistic infant MRI models. Theta synchronization was found over fontal pole, temporal, and parietal electrodes during infant sustained attention for 10 and 12 months. Alpha desynchronization was found over frontal, central and parietal electrodes during sustained attention. This alpha effect started to emerge at 10 months and became well established by 12 months. No difference was found for the beta rhythm between different attention phases. The theta synchronization effect was localized to the orbital frontal, temporal pole, and ventral temporal areas. The alpha desynchronization effect was localized to the brain regions composing the default mode network including the posterior cingulate cortex and precuneus, medial prefrontal cortex, and inferior parietal gyrus. The alpha desynchronization effect was also localized to the pre- and post-central gyri. The present study demonstrates a connection between infant sustained attention and EEG oscillatory activities.

'Developmental Delay' Reconsidered: The Critical Role of Age-Dependent, Co-variant Development

In memory of Annette Karmiloff-Smith . This paper reviews recent neurobiological research reporting structural co-variance and temporal dependencies in age-dependent gene expression, parameters of cortical maturation, long range connectivity and interaction of the biological network with the environment. This research suggests that age by size trajectories of brain structures relate to functional properties more than absolute sizes. In line with these findings, recent behavioral studies of typically developing children whose language development was delayed reported long term consequences of such delays. As for neurodevelopmental disorders, disrupted developmental timing and slow acquisitional pace are hallmarks of these populations. It is argued that these behavioral and neuro-biological results highlight the need to commit to a developmental model which will reflect the fact that temporal dependencies overseeing structural co-variance among developmental components are major regulatory factors of typical development of the brain/mind network. Consequently, the concept of 'developmental delay' in developmental theorizing needs to be reconsidered.

Bayesian automated cortical segmentation for neonatal MRI

Several attempts have been made in the past few years to develop and implement an automated segmentation of neonatal brain structural MRI. However, accurate automated MRI segmentation remains challenging in this population because of the low signal-to-noise ratio, large partial volume effects and inter-individual anatomical variability of the neonatal brain. In this paper, we propose a learning method for segmenting the whole brain cortical grey matter on neonatal T2-weighted images. We trained our algorithm using a neonatal dataset composed of 3 full-term and 4 preterm infants scanned at term equivalent age. Our segmentation pipeline combines the FAST algorithm from the FSL library software and a Bayesian segmentation approach to create a threshold matrix that minimizes the error of mislabeling brain tissue types. Our method shows promising results with our pilot training set. In both preterm and full-term neonates, automated Bayesian segmentation generates a smoother and more consistent parcellation compared to FAST, while successfully removing the subcortical structure and cleaning the edges of the cortical grey matter. This method show promising refinement of the FAST segmentation by considerably reducing manual input and editing required from the user, and further improving reliability and processing time of neonatal MR images. Further improvement will include a larger dataset of training images acquired from different manufacturers.

Development of the error-monitoring system from ages 9-35: Unique insight provided by MRI-constrained source localization of EEG

The ability to self-detect errors and dynamically adapt behavior is a cornerstone of higher-level cognition, requiring coordinated activity from a network of neural regions. However, disagreement exists over how the error-monitoring system develops throughout adolescence and early adulthood. The present report leveraged MRI-constrained EEG source localization to detail typical development of the error-monitoring system in a sample of 9-35 year-olds (n = 43). Participants performed a flanker task while high-density EEG was recorded; structural MRIs were also acquired for all participants. Analysis of the scalp-recorded EEG data revealed a frontocentral negativity (error-related negativity; ERN) immediately following errors for all participants, although the topography of the ERN varied with age. Source localization of the ERN time range revealed maximal activity within the posterior cingulate cortex (PCC) for all ages, consistent with recent evidence that the PCC provides a substantial contribution to the scalp-recorded ERN. Activity within a network of brain regions, including dorsal anterior cingulate, PCC, and parietal cortex, was predictive of improved performance following errors, regardless of age. However, additional activity within insula, orbitofrontal cortex and inferior frontal gyrus linearly increased with age. Together, these data suggest that the core error-monitoring system is online by early adolescence and remains relatively stable into adulthood. However, additional brain regions become embedded within this core network with age. These results serve as a model of typical development of the error-monitoring system from early adolescence into adulthood.