Stereotaxic Magnetic Resonance Imaging Brain Atlases for Infants from 3 to 12 Months

Prosodic cues enhance infants' sensitivity to nonadjacent regularities

In language, grammatical dependencies often hold between items that are not immediately adjacent to each other. Acquiring these nonadjacent dependencies is crucial for learning grammar. However, there are potentially infinitely many dependencies in the language input. How does the infant brain solve this computational learning problem? Here, we demonstrate that while rudimentary sensitivity to nonadjacent regularities may be present relatively early, robust and reliable learning can only be achieved when convergent statistical and perceptual, specifically prosodic cues, are both present, helping the infant brain detect the building blocks that form a nonadjacent dependency. This study contributes to our understanding of the neural foundations of rule learning that pave the way for language acquisition.

Frontal asymmetry assessed in infancy using functional near-infrared spectroscopy is associated with emotional and behavioral problems in early childhood

Frontal asymmetry (FA), the difference in brain activity between the left versus right frontal areas, is thought to reflect approach versus avoidance motivation. This study (2012-2021) used functional near-infrared spectroscopy to investigate if infant (Mage  = 7.63 months; N = 90; n = 48 male; n = 75 White) FA in the dorsolateral prefrontal cortex relates to psychopathology in later childhood (Mage  = 62.05 months). Greater right FA to happy faces was associated with increased internalizing (η2  = .09) and externalizing (η2  = .06) problems at age 5 years. Greater right FA to both happy and fearful faces was associated with an increased likelihood of a lifetime anxiety diagnosis (R2  > .13). FA may be an informative and early-emerging marker for psychopathology.

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.

Age-related changes in diffuse optical tomography sensitivity profiles from childhood to adulthood

SIGNIFICANCE

Diffuse optical tomography (DOT) uses near-infrared light spectroscopy to measure changes in cerebral hemoglobin concentration. Anatomical interpretations of the brain location that generates the hemodynamic signal require accurate descriptions of the DOT sensitivity to the underlying cortex. DOT sensitivity profiles are different in infants compared with adults. However, the descriptions of DOT sensitivity profiles from early childhood to adulthood are lacking despite the continuous head and brain development.

AIM

We aim to investigate age-related differences in DOT sensitivity profiles in individuals aged from 2 to 34 years with narrow age ranges of 0.5 or 1 year.

APPROACH

We implemented existing photon migration simulation methods and computed source-detector channel DOT sensitivity using age-appropriate, realistic head models.

RESULTS

DOT sensitivity profiles change systematically as a function of source-detector separation distance for all age groups. Children displayed distinctive DOT sensitivity profiles compared to older individuals, and the differences were enhanced at larger separation distances.

CONCLUSIONS

The findings have important implications for the design of source-detector placement and image reconstruction. Age-appropriate realistic head models should be used to provide anatomical guidance for standalone DOT data. Using age-inappropriate head models will have more negative impacts on estimation accuracy in younger children.

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.

Cortical Source Analysis of Event-Related Potentials: A Developmental Approach

Cortical source analysis of electroencephalographic (EEG) signals has become an important tool in the analysis of brain activity. The aim of source analysis is to reconstruct the cortical generators (sources) of the EEG signal recorded on the scalp. The quality of the source reconstruction relies on the accuracy of the forward problem, and consequently the inverse problem. An accurate forward solution is obtained when an appropriate imaging modality (i.e., structural magnetic resonance imaging - MRI) is used to describe the head geometry, precise electrode locations are identified with 3D maps of the sensor positions on the scalp, and realistic conductivity values are determined for each tissue type of the head model. Together these parameters contribute to the definition of realistic head models. Here, we describe the steps necessary to reconstruct the cortical generators of the EEG signal recorded on the scalp. We provide an example of source reconstruction of event-related potentials (ERPs) during a face-processing task performed by a 6-month-old infant. We discuss the adjustments necessary to perform source analysis with measures different from the ERPs. The proposed pipeline can be applied to the investigation of different cognitive tasks in both younger and older participants.

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.

Infants differentially extract rules from language

Infants readily extract linguistic rules from speech. Here, we ask whether this advantage extends to linguistic stimuli that do not rely on the spoken modality. To address this question, we first examine whether infants can differentially learn rules from linguistic signs. We show that, despite having no previous experience with a sign language, six-month-old infants can extract the reduplicative rule (AA) from dynamic linguistic signs, and the neural response to reduplicative linguistic signs differs from reduplicative visual controls, matched for the dynamic spatiotemporal properties of signs. We next demonstrate that the brain response for reduplicative signs is similar to the response to reduplicative speech stimuli. Rule learning, then, apparently depends on the linguistic status of the stimulus, not its sensory modality. These results suggest that infants are language-ready. They possess a powerful rule system that is differentially engaged by all linguistic stimuli, speech or sign.

devfOLD: a toolbox for designing age-specific fNIRS channel placement

Significance: Near-infrared spectroscopy (NIRS) is a noninvasive technique that uses scalp-placed sensors to measure cerebral hemoglobin concentration. Commercial NIRS instruments do not allow for whole-head coverage and do not intrinsically indicate which brain areas generate the NIRS signal. Hence, the challenge is to design source-detector channel arrangement that maximizes sensitivity to a given brain region of interest (ROI). Existing methods for optimizing channel placement design have been developed using adult head models. Thus, they have limited utility for developmental research. Aim: We aim to build an application from an existing toolbox (fOLD) that guides NIRS channel configuration based on age group, stereotaxic atlas, and ROI (devfOLD). Approach: The devfOLD provides NIRS channel-to-ROI specificity computed using photon propagation simulation with realistic head models from infant, child, and adult age groups. Results: Cortical locations and user-specified specificity cut-off values influence the between-age consistency and differences in the ROI-to-channel correspondence among the example infant and adult age groups. Conclusions: The study highlights the importance of incorporating age-specific head models for optimizing NIRS channel configurations. The devfOLD toolbox is publicly shared and compatible with multiple operating systems.

Investigating developmental changes in scalp-to-cortex correspondence using diffuse optical tomography sensitivity in infancy

Significance: Diffuse optical tomography (DOT) uses near-infrared light spectroscopy (NIRS) to measure changes in cerebral hemoglobin concentration. Anatomical interpretations of NIRS data require accurate descriptions of the cranio-cerebral relations and DOT sensitivity to the underlying cortical structures. Such information is limited for pediatric populations because they undergo rapid head and brain development. Aim: We aim to investigate age-related differences in scalp-to-cortex distance and mapping between scalp locations and cortical regions of interest (ROIs) among infants (2 weeks to 24 months with narrow age bins), children (4 and 12 years), and adults (20 to 24 years). Approach: We used spatial scalp projection and photon propagation simulation methods with age-matched realistic head models based on MRIs. Results: There were age-group differences in the scalp-to-cortex distances in infancy. The developmental increase was magnified in children and adults. There were systematic age-related differences in the probabilistic mappings between scalp locations and cortical ROIs. Conclusions: Our findings have important implications in the design of sensor placement and making anatomical interpretations in NIRS and fNIRS research. Age-appropriate, realistic head models should be used to provide anatomical guidance for standalone DOT data in infants.

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.

Signatures of brain plasticity supporting language recovery after perinatal arterial ischemic stroke

Brain imaging methods such as functional Magnetic Resonance Imaging (fMRI) and Diffusion Tensor Imaging (DTI) have already been used to decipher the functional and structural brain changes occurring during normal language development. However, little is known about the differentiation of the language network after an early lesion. While in adults, stroke over the left hemisphere generally induces post-stroke aphasia, it is not always the case when a stroke occurs in the perinatal period, thus revealing a remarkable plastic power of the language network during early development. In particular, the role of perilesional tissues, as opposed to undamaged brain areas in the functional recovery of language functions after an early insult, remains unclear. In this review article, we provide an overview of the extant literature using functional and structural neuroimaging data revealing the signatures of brain plasticity underlying near-normal language development.

Structural templates for imaging EEG cortical sources in infants

Electroencephalographic (EEG) source reconstruction is a powerful approach that allows anatomical localization of electrophysiological brain activity. Algorithms used to estimate cortical sources require an anatomical model of the head and the brain, generally reconstructed using magnetic resonance imaging (MRI). When such scans are unavailable, a population average can be used for adults, but no average surface template is available for cortical source imaging in infants. To address this issue, we introduce a new series of 13 anatomical models for subjects between zero and 24 months of age. These templates are built from MRI averages and boundary element method (BEM) segmentation of head tissues available as part of the Neurodevelopmental MRI Database. Surfaces separating the pia mater, the gray matter, and the white matter were estimated using the Infant FreeSurfer pipeline. The surface of the skin as well as the outer and inner skull surfaces were extracted using a cube marching algorithm followed by Laplacian smoothing and mesh decimation. We post-processed these meshes to correct topological errors and ensure watertight meshes. Source reconstruction with these templates is demonstrated and validated using 100 high-density EEG recordings from 7-month-old infants. Hopefully, these templates will support future studies on EEG-based neuroimaging and functional connectivity in healthy infants as well as in clinical pediatric populations.

Neural responses to happy, fearful and angry faces of varying identities in 5- and 7-month-old infants

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fNIRS and looking responses to emotional faces were measured in 5- and 7-month-olds.

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Emotional faces had varying identities within happy, angry, and fearful blocks.

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Temporo-parietal and frontal activations were observed, particularly to happy faces.

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Infants looked longer to the mouth region of angry faces.

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No difference in behavior or neural activity observed between 5- and 7-month-olds.

The processing of facial emotion is an important social skill that develops throughout infancy and early childhood. Here we investigate the neural underpinnings of the ability to process facial emotion across changes in facial identity in cross-sectional groups of 5- and 7-month-old infants. We simultaneously measured neural metabolic, behavioral, and autonomic responses to happy, fearful, and angry faces of different female models using functional near-infrared spectroscopy (fNIRS), eye-tracking, and heart rate measures. We observed significant neural activation to these facial emotions in a distributed set of frontal and temporal brain regions, and longer looking to the mouth region of angry faces compared to happy and fearful faces. No differences in looking behavior or neural activations were observed between 5- and 7-month-olds, although several exploratory, age-independent associations between neural activations and looking behavior were noted. Overall, these findings suggest more developmental stability than previously thought in responses to emotional facial expressions of varying identities between 5- and 7-months of age.

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.

White matter extension of the Melbourne Children's Regional Infant Brain atlas: M-CRIB-WM

Brain atlases providing standardised identification of neonatal brain regions are key in investigating neurological disorders of early childhood. Our previously developed Melbourne Children's Regional Infant Brain (M-CRIB) and M-CRIB 2.0 neonatal brain atlases provide standardised parcellation of 100 brain regions including cortical, subcortical, and cerebellar regions. The aim of this study was to extend M-CRIB atlas coverage to include 54 white matter (WM) regions. Participants were 10 healthy term-born neonates that were used to create the initial M-CRIB atlas. WM regions were manually segmented based on T₂ images and co-registered diffusion tensor imaging-based, direction-encoded colour maps. Our labelled regions imitate the Johns Hopkins University neonatal atlas, with minor anatomical modifications. All segmentations were reviewed and approved by a paediatric radiologist and a neurosurgery research fellow for anatomical accuracy. The resulting neonatal WM atlas comprises 54 WM regions: 24 paired regions, and six unpaired regions comprising five corpus callosum subdivisions, and one pontine crossing tract. Detailed protocols for manual WM parcellations are provided, and the M-CRIB-WM atlas is presented together with the existing M-CRIB cortical, subcortical, and cerebellar parcellations in 10 individual neonatal MRI data sets. The novel M-CRIB-WM atlas, along with the M-CRIB cortical and subcortical atlases, provide neonatal whole brain MRI coverage in the first multi-subject manually parcellated neonatal atlas compatible with atlases commonly used at older time points. The M-CRIB-WM atlas is publicly available, providing a valuable tool that will help facilitate neuroimaging research into neonatal brain development in both healthy and diseased states.

Right Structural and Functional Reorganization in Four-Year-Old Children with Perinatal Arterial Ischemic Stroke Predict Language Production

Brain imaging methods have contributed to shed light on the mechanisms of recovery after early brain insult. The assumption that the unaffected right hemisphere can take over language functions after left perinatal stroke is still under debate. Here, we report how patterns of brain structural and functional reorganization were associated with language outcomes in a group of four-year-old children with left perinatal arterial ischemic stroke (PAIS). Specifically, we gathered specific fine-grained developmental measures of receptive and productive aspects of language as well as standardized measures of cognitive development. We also collected structural neuroimaging data as well as functional activations during a passive listening story-telling fMRI task and a resting state session (rs-fMRI). Children with a left perinatal stroke showed larger lateralization indices of both structural and functional connectivity of the dorsal language pathway towards the right hemisphere that, in turn, were associated with better language outcomes. Importantly, the pattern of structural asymmetry was significantly more right-lateralized in children with a left perinatal brain insult than in a group of matched healthy controls. These results strongly suggest that early lesions of the left dorsal pathway and the associated perisylvian regions can induce the interhemispheric transfer of language functions to right homolog regions. This study provides combined evidence of structural and functional brain reorganization of language networks after early stroke with strong implications for neurobiological models of language development.

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.

Using functional near-infrared spectroscopy to assess social information processing in poor urban Bangladeshi infants and toddlers

Children living in low‐resource settings are at risk for failing to reach their developmental potential. While the behavioral outcomes of growing up in such settings are well‐known, the neural mechanisms underpinning poor outcomes have not been well elucidated, particularly in the context of low‐ and middle‐income countries. In this study, we measure brain metabolic responses to social and nonsocial stimuli in a cohort of 6‐ and 36‐month‐old Bangladeshi children. Study participants in both cohorts lived in an urban slum and were exposed to a broad range of adversity early in life including extreme poverty, malnutrition, recurrent infections, and low maternal education. We observed brain regions that responded selectively to social stimuli in both ages indicating that these specialized brain responses are online from an early age. We additionally show that the magnitude of the socially selective response is related to maternal education, maternal stress, and the caregiving environment. Ultimately our results suggest that a variety of psychosocial hazards have a measurable relationship with the developing social brain.

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.

Processing of structural neuroimaging data in young children: Bridging the gap between current practice and state-of-the-art methods

The structure of the brain is subject to very rapid developmental changes during early childhood. Pediatric studies based on Magnetic Resonance Imaging (MRI) over this age range have recently become more frequent, with the advantage of providing in vivo and non-invasive high-resolution images of the developing brain, toward understanding typical and atypical trajectories. However, it has also been demonstrated that application of currently standard MRI processing methods that have been developed with datasets from adults may not be appropriate for use with pediatric datasets. In this review, we examine the approaches currently used in MRI studies involving young children, including an overview of the rationale for new MRI processing methods that have been designed specifically for pediatric investigations. These methods are mainly related to the use of age-specific or 4D brain atlases, improved methods for quantifying and optimizing image quality, and provision for registration of developmental data obtained with longitudinal designs. The overall goal is to raise awareness of the existence of these methods and the possibilities for implementing them in developmental neuroimaging studies.

Evaluation of methods for volumetric analysis of pediatric brain data: The child pipeline versus adult-based approaches

Pediatric brain volumetric analysis based on Magnetic Resonance Imaging (MRI) is of particular interest in order to understand the typical brain development and to characterize neurodevelopmental disorders at an early age. However, it has been shown that the results can be biased due to head motion, inherent to pediatric data, and due to the use of methods based on adult brain data that are not able to accurately model the anatomical disparity of pediatric brains. To overcome these issues, we proposed childmetrix, a tool developed for the analysis of pediatric neuroimaging data that uses an age-specific atlas and a probabilistic model-based approach in order to segment the gray matter (GM) and white matter (WM). The tool was extensively validated on 55 scans of children between 5 and 6 years old (including 13 children with developmental dyslexia) and 10 pairs of test-retest scans of children between 6 and 8 years old and compared with two state-of-the-art methods using an adult atlas, namely icobrain (applying a probabilistic model-based segmentation) and Freesurfer (applying a surface model-based segmentation). The results obtained with childmetrix showed a better reproducibility of GM and WM segmentations and a better robustness to head motion in the estimation of GM volume compared to Freesurfer. Evaluated on two subjects, childmetrix showed good accuracy with 82-84% overlap with manual segmentation for both GM and WM, thereby outperforming the adult-based methods (icobrain and Freesurfer), especially for the subject with poor quality data. We also demonstrated that the adult-based methods needed double the number of subjects to detect significant morphological differences between dyslexics and typical readers. Once further developed and validated, we believe that childmetrix would provide appropriate and reliable measures for the examination of children's brain.

The emergence of top-down, sensory prediction during learning in infancy: A comparison of full-term and preterm infants

Prematurity alters developmental trajectories in preterm infants even in the absence of medical complications. Here, we use fNIRS and learning tasks to probe the nature of the developmental differences between preterm and full-term born infants. Our recent work has found that prematurity disrupts the ability to engage in top-down sensory prediction after learning. We now examine the neural changes during the learning that precede prediction. In full-terms, we found modulation of all cortical regions examined during learning (temporal, frontal, and occipital). By contrast, preterm infants had no evidence of neural changes in the occipital lobe selectively. This is striking as the learning task leads to the emergence of visual prediction. Moreover, the shape of individual infants' occipital lobe trajectories (regardless of prematurity) predicts subsequent visual prediction abilities. These results suggest that modulation of sensory cortices during learning is closely related to the emergence of top-down signals and further indicates that developmental differences in premature infants may be associated with deficits in top-down processing.

Advances, challenges, and promises in pediatric neuroimaging of neurodevelopmental disorders

Recent years have witnessed the proliferation of neuroimaging studies of neurodevelopmental disorders (NDDs), particularly of children with autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and Tourette's syndrome (TS). Neuroimaging offers immense potential in understanding the biology of these disorders, and how it relates to clinical symptoms. Neuroimaging techniques, in the long run, may help identify neurobiological markers to assist clinical diagnosis and treatment. However, methodological challenges have affected the progress of clinical neuroimaging. This paper reviews the methodological challenges involved in imaging children with NDDs. Specific topics include correcting for head motion, normalization using pediatric brain templates, accounting for psychotropic medication use, delineating complex developmental trajectories, and overcoming smaller sample sizes. The potential of neuroimaging-based biomarkers and the utility of implementing neuroimaging in a clinical setting are also discussed. Data-sharing approaches, technological advances, and an increase in the number of longitudinal, prospective studies are recommended as future directions. Significant advances have been made already, and future decades will continue to see innovative progress in neuroimaging research endeavors of NDDs.

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.

The Lateral Occipital Cortex Is Selective for Object Shape, Not Texture/Color, at Six Months

Understanding how the human visual system develops is crucial to understanding the nature and organization of our complex and varied visual representations. However, previous investigations of the development of the visual system using fMRI are primarily confined to a subset of the visual system (high-level vision: faces, scenes) and relatively late in visual development (starting at 4-5 years of age). The current study extends our understanding of human visual development by presenting the first systematic investigation of a mid-level visual region [the lateral occipital cortex (LOC)] in a population much younger than has been investigated in the past: 6 month olds. We use functional near-infrared spectroscopy (fNIRS), an emerging optical method for recording cortical hemodynamics, to perform neuroimaging with this very young population. Whereas previous fNIRS studies have suffered from imprecise neuroanatomical localization, we rely on the most rigorous MR coregistration of fNIRS data to date to image the infant LOC. We find surprising evidence that at 6 months the LOC has functional specialization that is highly similar to adults. Following Cant and Goodale (2007), we investigate whether the LOC tracks shape information and not other cues to object identity (e.g., texture/material). This finding extends evidence of LOC specialization from early childhood into infancy and earlier than developmental trajectories of high-level visual regions.SIGNIFICANCE STATEMENT Understanding visual development is crucial to understanding the nature of visual representations in the human brain. Previous studies of visual development have investigated children (4 years and older) and high-level visual areas. This study expands our knowledge of visual development by investigating the functional development of mid-level vision [lateral occipital cortex (LOC)] early in infancy. We find surprisingly adult-like functional specialization of the LOC by 6 months of age: infants exhibit shape selectivity, but not object selectivity, in this region.

The Relation between Infant Covert Orienting, Sustained Attention and Brain Activity

This study used measures of event-related potentials (ERPs) and cortical source analysis to examine the effect of covert orienting and sustained attention on 3- and 4.5-month-old infants' brain activity in a spatial cueing paradigm. Cortical source analysis was conducted with current density reconstruction using realistic head models created from age-appropriate infant MRIs. The validity effect was found in the P1 ERP component that was greater for valid than neutral trials in the electrodes contralateral to the visual targets when the stimulus onset asynchrony (SOA) was short. Cortical source analysis revealed greater current density amplitude around the P1 peak latency in the contralateral inferior occipital and ventral temporal regions for valid than neutral and invalid trials. The processing cost effect was found in the N1 ERP component that was greater for neutral than invalid trials in the short SOA condition. This processing cost effect was also shown in the current density amplitude around the N1 peak latency in the contralateral inferior and middle occipital and middle and superior temporal regions. Infant sustained attention was found to modulate infants' brain responses in covert orienting by enhancing the P1 ERP responses and current density amplitude in their cortical sources during sustained attention. These findings suggest that the neural mechanisms that underpin covert orienting already exist in 3- to 4.5-month-old, and they could be facilitated by infant sustained attention.

Toward the automatic quantification of in utero brain development in 3D structural MRI: A review

Investigating the human brain in utero is important for researchers and clinicians seeking to understand early neurodevelopmental processes. With the advent of fast magnetic resonance imaging (MRI) techniques and the development of motion correction algorithms to obtain high-quality 3D images of the fetal brain, it is now possible to gain more insight into the ongoing maturational processes in the brain. In this article, we present a review of the major building blocks of the pipeline toward performing quantitative analysis of in vivo MRI of the developing brain and its potential applications in clinical settings. The review focuses on T1- and T2-weighted modalities, and covers state of the art methodologies involved in each step of the pipeline, in particular, 3D volume reconstruction, spatio-temporal modeling of the developing brain, segmentation, quantification techniques, and clinical applications. Hum Brain Mapp 38:2772-2787, 2017. © 2017 Wiley Periodicals, Inc.

Isolating the effects of surface vasculature in infant neuroimaging using short-distance optical channels: a combination of local and global effects

Functional near-infrared spectroscopy (fNIRS) records hemodynamic changes in the cortex arising from neurovascular coupling. However, (noninvasive) fNIRS recordings also record surface vascular signals arising from noncortical sources (e.g., in the skull, skin, dura, and other tissues located between the sensors and the brain). A current and important focus in the fNIRS community is determining how to remove these noncortical vascular signals to reduce noise and to prevent researchers from erroneously attributing responses to cortical sources. The current study is the first to test a popular method for removing signals from the surface vasculature (removing short, 1 cm, channel recordings from long, 3 cm, channel recordings) in human infants, a population frequently studied using fNIRS. We find evidence that this method does remove surface vasculature signals and indicates the presence of both local and global surface vasculature signals. However, we do not find that the removal of this information changes the statistical inferences drawn from the data. This latter result not only questions the importance of removing surface vasculature responses for empiricists employing this method, but also calls for future research using other tasks (e.g., ones with a weaker initial result) with this population and possibly additional methods for removing signals arising from the surface vasculature in infants.

A database of age-appropriate average MRI templates

This article summarizes a life-span neurodevelopmental MRI database. The study of neurostructural development or neurofunctional development has been hampered by the lack of age-appropriate MRI reference volumes. This causes misspecification of segmented data, irregular registrations, and the absence of appropriate stereotaxic volumes. We have created the "Neurodevelopmental MRI Database" that provides age-specific reference data from 2 weeks through 89 years of age. The data are presented in fine-grained ages (e.g., 3 months intervals through 1 year; 6 months intervals through 19.5 years; 5 year intervals from 20 through 89 years). The base component of the database at each age is an age-specific average MRI template. The average MRI templates are accompanied by segmented partial volume estimates for segmenting priors, and a common stereotaxic atlas for infant, pediatric, and adult participants. The database is available online (http://jerlab.psych.sc.edu/NeurodevelopmentalMRIDatabase/).

Coregistering functional near-infrared spectroscopy with underlying cortical areas in infants

Functional near-infrared spectroscopy (fNIRS) is becoming a popular tool in developmental neuroscience for mapping functional localized brain responses. However, as it cannot provide information about underlying anatomy, researchers have begun to conduct spatial registration of fNIRS channels to cortical anatomy in adults. The current work investigated this issue with infants by coregistering fNIRS and magnetic resonance imaging (MRI) data from 55 individuals. Our findings suggest that fNIRS channels can be reliably registered with regions in the frontal and temporal cortex of infants from 4 to 7 months of age. Although some macro-anatomical regions are difficult to consistently define, others are more stable and fNIRS channels on an age-appropriate MRI template are often consistent with individual infant MRIs. We have generated a standardized scalp surface map of fNIRS channel locators to reliably locate cortical regions for fNIRS developmental researchers. This new map can be used to identify the inferior frontal gyrus, superior temporal sulcus (STS) region [which includes the superior and middle temporal gyri (MTG) nearest to the STS], and MTG and temporal-parietal regions in 4- to 7-month-old infants. Future work will model data for the whole head, taking into account the properties of light transport in tissue, and expanding to different ages across development.