Neuroimaging In Infants Research Articles

A Novel Registration Framework for Aligning Longitudinal Infant Brain Tensor Images.

Registering longitudinal infant brain images is challenging, as the infant brain undergoes rapid changes in size, shape and tissue contrast in the first months and years of life. Diffusion tensor images (DTI) have relatively consistent tissue properties over the course of infancy compared to commonly used T1 or T2-weighted images, presenting great potential for infant brain registration. Moreover, groupwise registration has been widely used in infant neuroimaging studies to reduce bias introduced by predefined atlases that may not be well representative of samples under study. To date, however, no methods have been developed for groupwise registration of tensor-based images. Here, we propose a novel registration approach to groupwise align longitudinal infant DTI images to a sample-specific common space. Longitudinal infant DTI images are first clustered into more homogenous subgroups based on image similarity using Louvain clustering. DTI scans are then aligned within each subgroup using standard tensor-based registration. The resulting images from all subgroups are then further aligned onto a sample-specific common space. Results show that our approach significantly improved registration accuracy both globally and locally compared to standard tensor-based registration and standard fractional anisotropy-based registration. Additionally, clustering based on image similarity yielded significantly higher registration accuracy compared to no clustering, but comparable registration accuracy compared to clustering based on chronological age. By registering images groupwise to reduce registration bias and capitalizing on the consistency of features in tensor maps across early infancy, our groupwise registration framework facilitates more accurate alignment of longitudinal infant brain images.

Maternal COVID-19 Infection Associated with Fetal Systemic Inflammatory Complications in COVID-19-Negative Neonates: A Case-Series.

This study aimed to examine fetal and neonatal inflammatory and neurologic complications associated with maternal coronavirus disease 2019 (COVID-19) infection. Case-series using a convenience sample of neonates cared for in a large referral-based children's hospital neonatal intensive care unit between September 2021 and May 2022. We identified seven neonates with exposure to maternal severe acute respiratory syndrome related coronavirus 2 (SARS-CoV-2) and a presentation consistent with inflammatory complications. All had some degree of neurologic injury with neuroimaging findings including restricted diffusion indicating injury in the white matter, cortex, deep gray structures, and splenium of the corpus callosum as well as intracranial hemorrhage. In addition, many infants had cytopenia and abnormal coagulation studies. Placental pathology, when available, revealed inflammation, clot with calcifications, and hematomas with associated infarcts. Neonates born to mothers with SARS-CoV-2, even when negative for the virus themselves, may have complications consistent with a systemic inflammatory syndrome. Placental pathology as well as neurologic imaging in infants with neurologic findings may help to support this diagnosis. · A systemic inflammatory response may cause illness in babies born to mothers with a history of COVID-19.. · Inflammatory markers and placental pathology are helpful in supporting this diagnosis.. · Consider neuroimaging in infants of mothers with a history of COVID-19 with neurologic findings..

Maternal childhood maltreatment: associations to offspring brain volume and white matter connectivity.

The deleterious effects of adversity are likely intergenerational, such that one generation's adverse experiences can affect the next. Epidemiological studies link maternal adversity to offspring depression and anxiety, possibly via transmission mechanisms that influence offspring fronto-limbic connectivity. However, studies have not thoroughly disassociated postnatal exposure effects nor considered the role of offspring sex. We utilized infant neuroimaging to test the hypothesis that maternal childhood maltreatment (CM) would be associated with increased fronto-limbic connectivity in infancy and tested brain-behavior associations in childhood. Ninety-two dyads participated (32 mothers with CM, 60 without; 52 infant females, 40 infant males). Women reported on their experiences of CM and non-sedated sleeping infants underwent MRIs at 2.44 ± 2.74 weeks. Brain volumes were estimated via structural MRI and white matter structural connectivity (fiber counts) via diffusion MRI with probabilistic tractography. A subset of parents (n = 36) reported on children's behaviors at age 5.17 ± 1.73 years. Males in the maltreatment group demonstrated greater intra-hemispheric fronto-limbic connectivity (b = 0.96, p= 0.008, [95%CI 0.25, 1.66]), no differences emerged for females. Fronto-limbic connectivity was related to somatic complaints in childhood only for males (r = 0.673, p = 0.006). Our findings suggest that CM could have intergenerational associations to offspring brain development, yet mechanistic studies are needed.

Task-based functional neuroimaging in infants: a systematic review.

Infancy is characterized by rapid neurological transformations leading to consolidation of lifelong function capabilities. Studying the infant brain is crucial for understanding how these mechanisms develop during this sensitive period. We review the neuroimaging modalities used with infants in stimulus-induced activity paradigms specifically, for the unique opportunity the latter provide for assessment of brain function. Conducted a systematic review of literature published between 1977-2021, via a comprehensive search of four major databases. Standardized appraisal tools and inclusion/exclusion criteria were set according to the PRISMA guidelines. Two-hundred and thirteen papers met the criteria of the review process. The results show clear evidence of overall cumulative growth in the number of infant functional neuroimaging studies, with electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to be the most utilized and fastest growing modalities with behaving infants. However, there is a high level of exclusion rates associated with technical limitations, leading to limited motor control studies (about ) in this population. Although the use of functional neuroimaging modalities with infants increases, there are impediments to effective adoption of existing technologies with this population. Developing new imaging modalities and experimental designs to monitor brain activity in awake and behaving infants is vital.

Towards imaging the infant brain at play

ABSTRACT Infants’ first-person experiences are crucial to early cognitive and neural development. To a vast extent, these early experiences involve play, which in infancy takes the form of object exploration. While at the behavioral level infant play has been studied both using specific tasks and in naturalistic scenarios, the neural correlates of object exploration have largely been studied in highly controlled task settings. These neuroimaging studies did not tap into the complexities of everyday play and what makes object exploration so important for development. Here, we review selected infant neuroimaging studies, spanning from typical, highly controlled screen-based studies on object perception to more naturalistic designs and argue for the importance of studying the neural correlates of key behaviors such as object exploration and language comprehension in naturalistic settings. We suggest that the advances in technology and analytic approaches allow measuring the infant brain at play with the use of functional near-infrared spectroscopy (fNIRS). Naturalistic fNIRS studies offer a new and exciting avenue to studying infant neurocognitive development in a way that will draw us away from our laboratory constructs and into an infant’s everyday experiences that support their development.

Minor head trauma in infants — how accurate is cranial ultrasound performed by trained radiologists?

Correct management of infants after minor head trauma is crucial to minimize the risk to miss clinically important traumatic brain injury (ciTBI). Current practices typically involve CT or in-hospital surveillance. Cranial ultrasound (CUS) provides a radiation-free and fast alternative. This study examines the accuracy of radiologist-performed CUS to detect skull fracture (SF) and/or intracranial hemorrhage (ICH). An inconspicuous CUS followed by an uneventful clinical course would allow exclusion of ciTBI with a great certainty. This monocentric, retrospective, observational study analyzed CUS in infants (< 12 months) after minor head trauma at Bern University Children’s Hospital, between 7/2013 and 8/2020. The primary outcome was the sensitivity and specificity of CUS in detecting SF and/or ICH by comparison to the clinical course and to additional neuroimaging. Out of a total of 325 patients, 73% (n = 241) had a normal CUS, 17% (n = 54) were found with SF, and ICH was diagnosed in 2.2% patients (n = 7). Two patients needed neurosurgery and three patients deteriorated clinically during surveillance. Additional imaging was performed in 35 patients. The sensitivity of CUS was 93% ([0.83, 0.97] 95% CI) and the specificity 98% ([0.95, 0.99] 95% CI). All false-negative cases originated in missed SF without clinical deterioration; no ICH was missed. Conclusion: This study shows high accuracy of CUS in exclusion of SF and ICH, which can cause ciTBI. Therefore, CUS offers a reliable method of neuroimaging in infants after minor head trauma and gives reassurance to reduce the duration of in-hospital surveillance.What is Known:• Minor head trauma can cause clinically important traumatic brain injury in infants, and the management of these cases is a challenge for the treating physician. • Cranial ultrasound (CUS) is regularly used in neonatology, but its accuracy after head trauma in infants is controversial. What is New:• CUS performed by a trained radiologist can exclude findings related to clinically important traumatic brain injury (ciTBI) with high sensitivity and specificity. It therefore offers reassurance in the management of infants after minor head trauma.

Neural Network Functional Interactions Mediate or Suppress White Matter–Emotional Behavior Relationships in Infants

BackgroundElucidating the neural basis of infant positive emotionality and negative emotionality can identify biomarkers of pathophysiological risk. Our goal was to determine how functional interactions among large-scale networks supporting emotional regulation influence white matter (WM) microstructural–emotional behavior relationships in 3-month-old infants. We hypothesized that microstructural–emotional behavior relationships would be differentially mediated or suppressed by underlying resting-state functional connectivity (rsFC), particularly between default mode network and central executive network structures. MethodsThe analytic sample comprised primary caregiver–infant dyads (52 infants [42% female, mean age at scan = 15.10 weeks]), with infant neuroimaging and emotional behavior assessments conducted at 3 months. Infant WM and rsFC were assessed by diffusion-weighted imaging/tractography and resting-state magnetic resonance imaging during natural, nonsedated sleep. The Infant Behavior Questionnaire-Revised provided measures of infant positive emotionality and negative emotionality. ResultsAfter significant WM–emotional behavior relationships were observed, multimodal analyses were performed using whole-brain voxelwise mediation. Results revealed that greater cingulum bundle volume was significantly associated with lower infant positive emotionality (β = −0.263, p = .031); however, a pattern of lower rsFC between central executive network and default mode network structures suppressed this otherwise negative relationship. Greater uncinate fasciculus volume was significantly associated with lower infant negative emotionality (β = −0.296, p = .022); however, lower orbitofrontal cortex–amygdala rsFC suppressed this otherwise negative relationship, while greater orbitofrontal cortex–central executive network rsFC mediated this relationship. ConclusionsFunctional interactions among neural networks have an important influence on WM microstructural–emotional behavior relationships in infancy. These relationships can elucidate neural mechanisms that contribute to future behavioral and emotional problems in childhood.

Detection of Global Brain Injury Using Point-of-Care Neonatal MRI Scanner.

Conventional magnetic resonance imaging (MRI) neuroimaging of infants is complicated by the need to transport infants outside the neonatal intensive care unit (NICU), often to distant areas of the hospital. The main aim of this study was to evaluate and compare scoring of images from a novel 1T MRI, which enables neuroimaging within the NICU, with those from a conventional MRI. The second aim of this study was to document improved expediency, and thereby greater patient safety, as reflected by decreased transport time. Thirty premature infants (mean gestational age: 28.8 ± 2.1 weeks) were scanned consecutively on the novel 1T and 1.5T conventional scanners at term-equivalent age. Orthogonal T1- and T2-weighted images were acquired and reviewed. A global brain abnormality score (Kidokoro) was assigned independently to all images by two radiologists. Interrater agreement was evaluated using the kappa statistic and interscanner agreement was evaluated by Bland-Altman analysis. Transport time to and from both scanners was monitored and compared. Weighted kappas were 0.77 (standard error of measurement [SEM] 0.08; confidence interval [CI]: 0.62-0.92) and 0.86 (SEM: 0.07; CI: 0.73-1), for the 1T and 1.5T scanners, respectively, reflecting substantial interrater agreement. Bland-Altman analysis showed excellent agreement between the two scanners.Transport time was 8 ± 6 minutes for the 1T MRI versus 46 ± 21 minutes for the conventional MRI (p < 0.00001). No adverse events were recorded during transport. Standard transport times will vary from institution to institution. Kidokoro scores are similar when comparing images obtained from a 1T MRI with those of a conventional 1.5T MRI, reflecting comparable image quality. Transport time was significantly decreased using the 1T neonatal MRI.

Real-time motion monitoring improves functional MRI data quality in infants

Imaging the infant brain with MRI has improved our understanding of early neurodevelopment. However, head motion during MRI acquisition is detrimental to both functional and structural MRI scan quality. Though infants are typically scanned while asleep, they commonly exhibit motion during scanning causing data loss. Our group has shown that providing MRI technicians with real-time motion estimates via Framewise Integrated Real-Time MRI Monitoring (FIRMM) software helps obtain high-quality, low motion fMRI data. By estimating head motion in real time and displaying motion metrics to the MR technician during an fMRI scan, FIRMM can improve scanning efficiency. Here, we compared average framewise displacement (FD), a proxy for head motion, and the amount of usable fMRI data (FD ≤ 0.2 mm) in infants scanned with (n = 407) and without FIRMM (n = 295). Using a mixed-effects model, we found that the addition of FIRMM to current state-of-the-art infant scanning protocols significantly increased the amount of usable fMRI data acquired per infant, demonstrating its value for research and clinical infant neuroimaging.

The Incidence and Characteristics of Perinatal Stroke in Beijing: A Multicenter Study.

ObjectiveTo assess the incidence, risk factors, and clinical characteristics of perinatal stroke in Beijing.MethodsThis multicenter prospective study included all the live births from 17 representative maternal delivery hospitals in Beijing from March 1, 2019 to February 29, 2020. Neonates with a stroke were assigned to the study group. Clinical data, including general information, clinical manifestations, and risk factors, were collected. Up until 18 months after birth, neonates were routinely assessed according to the Ages and Stages Questionnaire (ASQ) and/or the Bayley scale. Statistical analysis was done using the chi-squared, t-tests, and logistic regression analysis using SPSS version 26.0.OutcomesIn total, 27 cases were identified and the incidence of perinatal stroke in Beijing was 1/2,660 live births, including 1/5,985 for ischemic stroke and 1/4,788 for hemorrhagic stroke. Seventeen cases (62.96%) of acute symptomatic stroke and convulsions within 72 h (10 cases, 37.04%) were the most common presentations. Ten patients showed no neurological symptoms and were found to have had a stroke through routine cranial ultrasonography after being hospitalized for non-neurological diseases. The risk factors include primiparity, placental or uterine abruption/acute chorioamnionitis, intrauterine distress, asphyxia, and severe infection. In the study group, 11.1% (3/27) of patients had adverse neurodevelopmental outcomes. The patients in the study group had lower scores for the ASQ than those in the control group in the communication, gross, and fine motor dimensions.ConclusionThe incidence of perinatal stroke in Beijing was consistent with that in other countries. Routine neuroimaging of infants with risk factors may enable identification of asymptomatic strokes in more patients. Patients who have suffered from a stroke may have neurological sequelae; therefore, early detection, treatment, and regular follow-ups are beneficial for improving their recovery outcomes.

(Un)common space in infant neuroimaging studies: A systematic review of infant templates.

In neuroimaging, spatial normalization is an important step that maps an individual's brain onto a template brain permitting downstream statistical analyses. Yet, in infant neuroimaging, there remain several technical challenges that have prevented the establishment of a standardized template for spatial normalization. Thus, many different approaches are used in the literature. To quantify the popularity and variability of these approaches in infant neuroimaging studies, we performed a systematic review of infant magnetic resonance imaging (MRI) studies from 2000 to 2020. Here, we present results from 834 studies meeting inclusion criteria. Studies were classified into (a) processing data in single subject space, (b) using an off the shelf, or “off the shelf,” template, (c) creating a study specific template, or (d) using a hybrid of these methods. We found that across the studies in the systematic review, single subject space was the most used (no common space). This was the most used common space for diffusion‐weighted imaging and structural MRI studies while functional MRI studies preferred off the shelf atlases. We found a pattern such that more recently published studies are more commonly using off the shelf atlases. When considering special populations, preterm studies most used single subject space while, when no special populations were being analyzed, an off the shelf template was most common. The most used off the shelf templates were the UNC Infant Atlases (24%). Using a systematic review of infant neuroimaging studies, we highlight a lack of an established “standard” template brain in these studies.

Time-resolved multivariate pattern analysis of infant EEG data: A practical tutorial

Time-resolved multivariate pattern analysis (MVPA), a popular technique for analyzing magneto- and electro-encephalography (M/EEG) neuroimaging data, quantifies the extent and time-course by which neural representations support the discrimination of relevant stimuli dimensions. As EEG is widely used for infant neuroimaging, time-resolved MVPA of infant EEG data is a particularly promising tool for infant cognitive neuroscience. MVPA has recently been applied to common infant imaging methods such as EEG and fNIRS. In this tutorial, we provide and describe code to implement time-resolved, within-subject MVPA with infant EEG data. An example implementation of time-resolved MVPA based on linear SVM classification is described, with accompanying code in Matlab and Python. Results from a test dataset indicated that in both infants and adults this method reliably produced above-chance accuracy for classifying stimuli images. Extensions of the classification analysis are presented including both geometric- and accuracy-based representational similarity analysis, implemented in Python. Common choices of implementation are presented and discussed. As the amount of artifact-free EEG data contributed by each participant is lower in studies of infants than in studies of children and adults, we also explore and discuss the impact of varying participant-level inclusion thresholds on resulting MVPA findings in these datasets.

Dear reviewers: Responses to common reviewer critiques about infant neuroimaging studies

The field of adult neuroimaging relies on well-established principles in research design, imaging sequences, processing pipelines, as well as safety and data collection protocols. The field of infant magnetic resonance imaging, by comparison, is a young field with tremendous scientific potential but continuously evolving standards. The present article aims to initiate a constructive dialog between researchers who grapple with the challenges and inherent limitations of a nascent field and reviewers who evaluate their work. We address 20 questions that researchers commonly receive from research ethics boards, grant, and manuscript reviewers related to infant neuroimaging data collection, safety protocols, study planning, imaging sequences, decisions related to software and hardware, and data processing and sharing, while acknowledging both the accomplishments of the field and areas of much needed future advancements. This article reflects the cumulative knowledge of experts in the FIT’NG community and can act as a resource for both researchers and reviewers alike seeking a deeper understanding of the standards and tradeoffs involved in infant neuroimaging.

Single Nucleotide Polymorphisms of Interleukins and Toll-like Receptors and Neuroimaging Results in Newborns with Congenital HCMV Infection.

Congenital cytomegalovirus infection (cCMV) is the most common intrauterine infection with central nervous system (CNS) involvement. There is limited data on the associations between Single Nucleotide Polymorphisms (SNPs) in genes involving the first-line defense mechanism and the risk of CNS damage during cCMV. We investigated the associations between neuroimaging findings and SNPs in genes encoding the following cytokines and cytokine receptors in 92 infants with cCMV: interleukins (IL1B rs16944, IL12B rs3212227, IL28B rs12979860), C-C motif chemokine ligand 2 (CCL2 rs1024611), dendritic cell-specific intercellular adhesion grabbing non-integrin (DC-SIGN rs735240), Toll-like receptors (TLR2 rs5743708, TLR4 rs4986791, TLR9 rs352140). The SNP of IL1B rs16944 (G/A) was associated with a reduced risk of ventriculomegaly on MRI (OR = 0.46, 95% CI, 0.22–0.95; p = 0.03) and cUS (OR = 0.38, 95% CI, 0.0–0.93; p = 0.034). Infants carrying heterozygous (T/C) genotype at IL28B rs12979860 had an increased risk of cystic lesions on cUS (OR = 3.31, 95% CI, 1.37–8.01; p = 0.0064) and MRI (OR = 4.97, 95% CI, 1.84–13.43; p = 0.001), and an increased risk of ventriculomegaly on MRI (OR = 2.46, 95% CI, 1.03–5.90; p = 0.04). No other associations between genotyped SNPs and neuroimaging results were found. This is the first study demonstrating new associations between SNPs of IL1B and IL28B and abnormal neuroimaging in infants with cCMV.

Functional imaging of the developing brain with wearable high-density diffuse optical tomography: A new benchmark for infant neuroimaging outside the scanner environment

Studies of cortical function in the awake infant are extremely challenging to undertake with traditional neuroimaging approaches. Partly in response to this challenge, functional near-infrared spectroscopy (fNIRS) has become increasingly common in developmental neuroscience, but has significant limitations including resolution, spatial specificity and ergonomics. In adults, high-density arrays of near-infrared sources and detectors have recently been shown to yield dramatic improvements in spatial resolution and specificity when compared to typical fNIRS approaches. However, most existing fNIRS devices only permit the acquisition of ~20–100 sparsely distributed fNIRS channels, and increasing the number of optodes presents significant mechanical challenges, particularly for infant applications. A new generation of wearable, modular, high-density diffuse optical tomography (HD-DOT) technologies has recently emerged that overcomes many of the limitations of traditional, fibre-based and low-density fNIRS measurements. Driven by the development of this new technology, we have undertaken the first study of the infant brain using wearable HD-DOT. Using a well-established social stimulus paradigm, and combining this new imaging technology with advances in cap design and spatial registration, we show that it is now possible to obtain high-quality, functional images of the infant brain with minimal constraints on either the environment or on the infant participants. Our results are consistent with prior low-density fNIRS measures based on similar paradigms, but demonstrate superior spatial localization, improved depth specificity, higher SNR and a dramatic improvement in the consistency of the responses across participants. Our data retention rates also demonstrate that this new generation of wearable technology is well tolerated by the infant population.

Multi-Regression based supervised sample selection for predicting baby connectome evolution trajectory from neonatal timepoint.

The connectional map of the baby brain undergoes dramatic changes over the first year of postnatal development, which makes its mapping a challenging task, let alone learning how to predict its evolution. Currently, learning models for predicting brain connectomic developmental trajectories remain broadly absent despite their great potential in spotting atypical neurodevelopmental disorders early. This is most likely due to the scarcity and often incompleteness of longitudinal infant neuroimaging studies for training such models. In this paper, we propose the first approach for progressively predicting longitudinal development of brain networks during the postnatal period solely from a baseline connectome around birth. To this end, a supervised multi-regression sample selection strategy is designed to learn how to identify the best set of neighbors of a testing baseline connectome to eventually predict its evolution trajectory at follow-up timepoints. However, given that the training dataset may have missing samples (connectomes) at certain timepoints, this may affect the training of the predictive model. To overcome this problem, we perform a low-rank tensor completion based on a robust principal component analysis to impute the missing training connectomes by linearly approximating similar complete training networks. In the prediction step, our sample selection strategy aims to preserve spatiotemporal relationships between consecutive timepoints. Therefore, the proposed method learns how to identify the set of the local closest neighbors to a target network by training an ensemble of bidirectional regressors leveraging temporal dependency between consecutive timepoints with a recall to the baseline observations to progressively predict the evolution of a testing network over time. Our method achieves the best prediction results and better captures the dynamic changes of each brain connectome over time in comparison to its ablated versions using leave-one-out cross-validation strategy.

16 Variability in lumbar punctures and neuroimaging in infants less than 90 days with acute bacterial meningitis at a provincial children’s hospital in Canada

Abstract Background Bacterial meningitis remains a significant cause of morbidity and mortality in infants, necessitating appropriate and timely investigations and treatment. Despite this, there are no current Canadian practice guidelines outlining the recommended management of infants with bacterial meningitis beyond empiric antimicrobial choice. As bacterial meningitis remains one of the most severe infectious diseases managed by general pediatricians, it warrants an attempt at practice standardization. Objectives The purpose of this study is to review and identify variation in the timing and frequency of lumbar punctures (LPs) and the use of neuroimaging for the management of bacterial meningitis for infants less than 90 days of age at BC Children’s &amp; Women’s Hospital (BCCWH). Design/Methods A retrospective chart review at BCCWH identified confirmed, presumed or possible bacterial meningitis in infants less than 90 days of age over a five-year period (2013-2018). Anonymized data was collected from medical charts, de-identified and stored in REDCap. Results Eighty-one patients were included. Fifty-three percent of all patients had a delay in receiving an initial LP. The most common reasons for delays were that the patient was too unstable (42%) or that the first LP attempt was unsuccessful (26%). Forty-six percent of all patients had only one LP while 36% had at least one repeat LP. Most repeat LPs were done within 7 days of diagnosis. Twenty-nine percent of patients had an end of treatment LPs. Of all patients, 80% had neuroimaging. Head ultrasound (US) was the most commonly used imaging modality for both first image (68%) and subsequent images (64%). Seventeen percent of patients received a CT scan and 15% an MRI as their first image. In most cases, there was no clear clinical indication for imaging noted other than a diagnosis of meningitis (44%). Conclusion This retrospective study confirms that there is variability in the management of bacterial meningitis with respect to lumbar punctures and neuroimaging in young infants. The findings demonstrate LPs are commonly delayed, and suggest a need to develop clearly defined criteria for evaluating instability before an initial LP. Furthermore, the findings raise concern regarding the common practice of ordering head ultrasound for meningitis, given lower sensitivity in detecting disease complications and therefore disputed clinical utility.

Sleep State Modulates Resting-State Functional Connectivity in Neonates.

The spontaneous cerebral activity that gives rise to resting-state networks (RSNs) has been extensively studied in infants in recent years. However, the influence of sleep state on the presence of observable RSNs has yet to be formally investigated in the infant population, despite evidence that sleep modulates resting-state functional connectivity in adults. This effect could be extremely important, as most infant neuroimaging studies rely on the neonate to remain asleep throughout data acquisition. In this study, we combine functional near-infrared spectroscopy with electroencephalography to simultaneously monitor sleep state and investigate RSNs in a cohort of healthy term born neonates. During active sleep (AS) and quiet sleep (QS) our newborn neonates show functional connectivity patterns spatially consistent with previously reported RSN structures. Our three independent functional connectivity analyses revealed stronger interhemispheric connectivity during AS than during QS. In turn, within hemisphere short-range functional connectivity seems to be enhanced during QS. These findings underline the importance of sleep state monitoring in the investigation of RSNs.

White Matter Injury and Structural Anomalies in Infants with Prenatal Opioid Exposue

Previous studies have not found structural injury or brain malformations in infants and children with prenatal opioid exposure. As part of an ongoing study evaluating neuroimaging in infants with prenatal opioid exposure, we reviewed structural brain MR imaging in 20 term infants with prenatal opioid exposure and 20 term controls at 4-8 weeks of age. We found that 8 of the 20 opioid-exposed infants had punctate white matter lesions or white matter signal abnormality on structural MR imaging, and 2 of the opioid-exposed infants had a septopreoptic fusion anomaly. No controls had white matter injury or structural malformations. Our findings underscore the importance of clinical neurodevelopmental follow-up and the need for more comprehensive imaging and long-term outcomes research following prenatal opioid exposure.

Neonatal neuroimaging after repair of congenital diaphragmatic hernia and long-term neurodevelopmental outcome

ObjectivePrevious outcome reports of congenital diaphragmatic hernia (CDH) have described neuroimaging anomalies and neurodevelopmental impairment. However, the link between imaging and outcome has not been described. We aimed to determine...