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

Harmonizing multisite neonatal diffusion-weighted brain MRI data for developmental neuroscience

Large diffusion-weighted brain MRI (dMRI) studies in neonates are crucial for developmental neuroscience. Our aim was to investigate the utility of ComBat, an empirical Bayes tool for multisite harmonization, in removing site effects from white matter (WM) dMRI measures in healthy infants born at 37 gestational weeks+ 0 days-42 weeks+ 6 days from the Theirworld Edinburgh Birth Cohort (n = 86) and Developing Human Connectome Project (n = 287). Skeletonized fractional anisotropy (FA), mean, axial and radial diffusivity (MD, AD, RD) maps were harmonized. Differences between voxel-wise metrics, skeleton means and histogram widths (5th-95th percentile) were assessed before and after harmonization, as well as variance associated with gestational age at birth and scan. Before harmonization, large cohort differences were observed. Harmonization removed all voxel-wise differences from MD maps and all metric means and histogram widths, however small voxel-wise differences (<1.5 % of voxels) remained in FA, AD and RD. We detected significant relationships between GA at birth and all metrics. When comparing single site and multisite harmonized datasets of equal sample sizes, harmonized data resulted in smaller standardized regression coefficients. ComBat could enable unprecedented sample sizes in developmental neuroscience, offering new horizons for biomarker discovery and validation, understanding typical and atypical brain development, and assessing neuroprotective therapies.

Precision Functional Mapping to Advance Developmental Psychiatry Research

Many psychiatric conditions have their roots in early development. Individual differences in prenatal brain function (which is influenced by a combination of genetic risk and the prenatal environment) likely interact with individual differences in postnatal experience, resulting in substantial variation in brain functional organization and development in infancy. Neuroimaging has been a powerful tool for understanding typical and atypical brain function and holds promise for uncovering the neurodevelopmental basis of psychiatric illness; however, its clinical utility has been relatively limited thus far. A substantial challenge in this endeavor is the traditional approach of averaging brain data across groups despite individuals varying in their brain organization, which likely obscures important clinically relevant individual variation. Precision functional mapping (PFM) is a neuroimaging technique that allows the capture of individual-specific and highly reliable functional brain properties. Here, we discuss how PFM, through its focus on individuals, has provided novel insights for understanding brain organization across the life span and its promise in elucidating the neural basis of psychiatric disorders. We first summarize the extant literature on PFM in normative populations, followed by its limited utilization in studying psychiatric conditions in adults. We conclude by discussing the potential for infant PFM in advancing developmental precision psychiatry applications, given that many psychiatric disorders start during early infancy and are associated with changes in individual-specific functional neuroanatomy. By exploring the intersection of PFM, development, and psychiatric research, this article underscores the importance of individualized approaches in unraveling the complexities of brain function and improving clinical outcomes across development.

ESR Essentials: advanced MR safety in vulnerable patients-practice recommendations by the European Society for Magnetic Resonance in Medicine and Biology

For every patient, the MR safety evaluation should include the assessment of risks in three key areas, each corresponding to a specific hazard posed by the electromagnetic fields generated by the MR scanner: ferromagnetic attraction and displacement by the static field; stimulation, acoustic noise, and device interaction by the gradient fields; and bulk and focal heating by the radiofrequency field. MR safety guidelines and procedures are typically designed around the "average" patient: adult, responsive, and of typical habitus. For this type of patient, we can safely expect that a detailed history can identify metallic objects inside and outside the body, verbal contact during the scan can detect signs of discomfort from heating or acoustic noise, and safety calculations performed by the scanner can prevent hyperthermia. However, for some less common patient categories, these assumptions do not hold. For instance, patients with larger habitus, febrile patients, or pregnant people are more subject to bulk heating and require more conservative MR protocols, while at the same time presenting challenges during positioning and preparation. Other vulnerable categories are infants, children, and patients unable to communicate, who might require screening for ferromagnetic objects with other imaging modalities or dedicated equipment. This paper will provide guidance to implement appropriate safety margins in the workflow and scanning protocols in various vulnerable patient categories that are sometimes overlooked in basic MR safety guidance documents. CLINICAL RELEVANCE STATEMENT: Special care in the implementation of MR safety procedures is of paramount importance in the handling of patients. While most institutions have streamlined operations in place, some vulnerable patient categories require specific considerations to obtain images of optimal quality while minimizing the risks derived by exposure to the MR environment. KEY POINTS: Patients unable to effectively communicate need to be carefully screened for foreign objects. Core temperature management is important in specific patient categories. There are no hard quantitative criteria that make a patient fall into a specific vulnerable category. Protocols and procedures need to be adaptable.

Neural Correlates of Novelty-Evoked Distress in 4-Month-Old Infants: A Synthetic Cohort Study

BACKGROUND

Observational assessments of infant temperament have provided unparalleled insight into prediction of risk for social anxiety. However, it is challenging to administer and score these assessments alongside high-quality infant neuroimaging data. In the current study, we aimed to identify infant resting-state functional connectivity associated with both parent report and observed behavioral estimates of infant novelty-evoked distress.

METHODS

Using data from the OIT (Origins of Infant Temperament) study, which includes deep phenotyping of infant temperament, we identified parent-report measures that were associated with observed novelty-evoked distress. These parent-report measures were then summarized into a composite score used for imaging analysis. Our infant magnetic resonance imaging sample was a synthetic cohort, harmonizing data from 2 functional magnetic resonance imaging studies of 4-month-old infants (OIT and BCP [Baby Connectome Project]; n = 101), both of which included measures of parent-reported temperament. Brain-behavior associations were evaluated using enrichment, a statistical approach that quantifies the clustering of brain-behavior associations within network pairs.

RESULTS

Results demonstrated that parent-report composites of novelty-evoked distress were significantly associated with 3 network pairs: dorsal attention-salience/ventral attention, dorsal attention-default mode, and dorsal attention-control. These network pairs demonstrated negative associations with novelty-evoked distress, indicating that less connectivity between these network pairs was associated with greater novelty-evoked distress. Additional analyses demonstrated that dorsal attention-control network connectivity was associated with observed novelty-evoked distress in the OIT sample (n = 38).

CONCLUSIONS

Overall, this work is broadly consistent with existing work and implicates dorsal attention network connectivity in novelty-evoked distress. This study provides novel data on the neural basis of infant novelty-evoked distress.

Mapping Early Brain-Body Interactions: Associations of Fetal Heart Rate Variation with Newborn Brainstem, Hypothalamic, and Dorsal Anterior Cingulate Cortex Functional Connectivity

The autonomic nervous system (ANS) regulates the body's physiology, including cardiovascular function. As the ANS develops during the second to third trimester, fetal heart rate variability (HRV) increases while fetal heart rate (HR) decreases. In this way, fetal HR and HRV provide an index of fetal ANS development and future neurobehavioral regulation. Fetal HR and HRV have been associated with child language ability and psychomotor development behavior in toddlerhood. However, their associations with postbirth autonomic brain systems, such as the brainstem, hypothalamus, and dorsal anterior cingulate cortex (dACC), have yet to be investigated even though brain pathways involved in autonomic regulation are well established in older individuals. We assessed whether fetal HR and HRV were associated with the brainstem, hypothalamic, and dACC functional connectivity in newborns. Data were obtained from 60 pregnant individuals (ages 14-42) at 24-27 and 34-37 weeks of gestation using a fetal actocardiograph to generate fetal HR and HRV. During natural sleep, their infants (38 males and 22 females) underwent a fMRI scan between 40 and 46 weeks of postmenstrual age. Our findings relate fetal heart indices to brainstem, hypothalamic, and dACC connectivity and reveal connections with widespread brain regions that may support behavioral and emotional regulation. We demonstrated the basic physiologic association between fetal HR indices and lower- and higher-order brain regions involved in regulatory processes. This work provides the foundation for future behavioral or physiological regulation research in fetuses and infants.

Infant neuroscience: how to measure brain activity in the youngest minds

The functional properties of the infant brain are poorly understood. Recent advances in cognitive neuroscience are opening new avenues for measuring brain activity in human infants. These include novel uses of existing technologies such as electroencephalography (EEG) and magnetoencephalography (MEG), the availability of newer technologies including functional near-infrared spectroscopy (fNIRS) and optically pumped magnetometry (OPM), and innovative applications of functional magnetic resonance imaging (fMRI) in awake infants during cognitive tasks. In this review article we catalog these available non-invasive methods, discuss the challenges and opportunities encountered when applying them to human infants, and highlight the potential they may ultimately hold for advancing our understanding of the youngest minds.

Sex Differences in the Brain's White Matter Microstructure during Development assessed using Advanced Diffusion MRI Models

Typical sex differences in white matter (WM) microstructure during development are incompletely understood. Here we evaluated sex differences in WM microstructure during typical brain development using a sample of neurotypical individuals across a wide developmental age (N=239, aged 5-22 years). We used the conventional diffusion-weighted MRI (dMRI) model, diffusion tensor imaging (DTI), and two advanced dMRI models, the tensor distribution function (TDF) and neurite orientation dispersion density imaging (NODDI) to assess WM microstructure. WM microstructure exhibited significant, regionally consistent sex differences across the brain during typical development. Additionally, the TDF model was most sensitive in detecting sex differences. These findings highlight the importance of considering sex in neurodevelopmental research and underscore the value of the advanced TDF model.

Multi-level fMRI analysis applied to hemispheric specialization in the language network, functional areas, and their behavioral correlations in the ABCD sample

Prior research suggests that the organization of the language network in the brain is left-dominant and becomes more lateralized with age and increasing language skill. The age at which specific components of the language network become adult-like varies depending on the abilities they subserve. So far, a large, developmental study has not included a language task paradigm, so we introduce a method to study resting-state laterality in the Adolescent Brain Cognitive Development (ABCD) study. Our approach mixes source timeseries between left and right homotopes of the (1) inferior frontal and (2) middle temporal gyri and (3) a region we term "Wernicke's area" near the supramarginal gyrus. Our large subset sample size of ABCD (n = 6153) allows improved reliability and validity compared to previous, smaller studies of brain-behavior associations. We show that behavioral metrics from the NIH Youth Toolbox and other resources are differentially related to tasks with a larger linguistic component over ones with less (e.g., executive function-dominant tasks). These baseline characteristics of hemispheric specialization in youth are critical for future work determining the correspondence of lateralization with language onset in earlier stages of development.

Newborn Brain Function and Early Emerging Callous-Unemotional Traits

Importance

Children with high callous-unemotional traits are more likely to develop severe and persistent conduct problems; however, the newborn neurobiology underlying early callous-unemotional traits remains unknown. Understanding the neural mechanisms that precede the development of callous-unemotional traits could help identify at-risk children and encourage development of novel treatments.

Objective

To determine whether newborn brain function is associated with early-emerging empathy, prosociality, and callous-unemotional traits.

Design, Setting, and Participants

In this prospective, longitudinal cohort study, pregnant women were recruited from obstetric clinics in St Louis, Missouri, from September 1, 2017, to February 28, 2020, with longitudinal data collected until March 20, 2023. Mothers were recruited during pregnancy. Newborns underwent brain magnetic resonance imaging shortly after birth. Mothers completed longitudinal follow-up when the children were aged 1, 2, and 3 years.

Exposures

The sample was enriched for exposure to socioeconomic disadvantage.

Main Outcome and Measure

Functional connectivity between hypothesized brain regions was assessed using newborn-specific networks and voxel-based connectivity analyses. Children's callous-unemotional traits were measured using the Inventory of Callous-Unemotional Traits. Empathy and prosociality were assessed using the Infant and Toddler Socio-Emotional Assessment.

Results

A total of 283 children (mean [SD] gestational age, 38 [2] weeks; 159 male [56.2%]; 2 Asian [0.7%], 171 Black [60%], 7 Hispanic or Latino [2.5%], 106 White [38%], 4 other racial or ethnic group [1.4%]) were included in the analysis. Stronger newborn functional connectivity between the cingulo-opercular network (CO) and medial prefrontal cortex (mPFC) was associated with higher callous-unemotional traits at age 3 years (β = 0.31; 95% CI, 0.17-0.41; P < .001). Results persisted when accounting for parental callous-unemotional traits and child externalizing symptoms. Stronger newborn CO-mPFC connectivity was also associated with lower empathy and lower prosociality at ages 1, 2, and 3 years using multilevel models (β = -0.12; 95% CI, -0.21 to -0.04; P = .004 and β = -0.20; 95% CI, -0.30 to -0.10; P < .001, respectively).

Conclusions and Relevance

Newborn functional connectivity was associated with early-emerging empathy, prosociality, and callous-unemotional traits, even when accounting for parental callous-unemotional traits and child externalizing symptoms. Understanding the neurobiological underpinnings of empathy, prosociality, and callous-unemotional traits at the earliest developmental point may help early risk stratification and novel intervention development.

Consciousness in the cradle: on the emergence of infant experience

Although each of us was once a baby, infant consciousness remains mysterious and there is no received view about when, and in what form, consciousness first emerges. Some theorists defend a 'late-onset' view, suggesting that consciousness requires cognitive capacities which are unlikely to be in place before the child's first birthday at the very earliest. Other theorists defend an 'early-onset' account, suggesting that consciousness is likely to be in place at birth (or shortly after) and may even arise during the third trimester. Progress in this field has been difficult, not just because of the challenges associated with procuring the relevant behavioral and neural data, but also because of uncertainty about how best to study consciousness in the absence of the capacity for verbal report or intentional behavior. This review examines both the empirical and methodological progress in this field, arguing that recent research points in favor of early-onset accounts of the emergence of consciousness.

Concurrent and prospective associations between infant frontoparietal and default mode network connectivity and negative affectivity

Emotion dysregulation is linked to differences in frontoparietal (FPN) and default mode (DMN) brain network functioning. These differences may be identifiable early in development. Temperamental negative affectivity has been identified as a precursor to later emotion dysregulation, though the underlying neurodevelopmental mechanism is unknown. The present study explores concurrent and prospective associations between FPN and DMN connectivity in infants and measures of negative affectivity. 72 infants underwent 5.03-13.28 min of resting state fMRI during natural sleep (M±SD age=4.90 ± 0.84 weeks; 54% male; usable data=9.92 ± 2.15 min). FPN and DMN intra- and internetwork connectivity were computed using adult network assignments. Crying was obtained from both parent-report and day-long audio recordings. Temperamental negative affectivity was obtained from a parent-report questionnaire. In this preregistered study, based on analyses conducted with a subset of this data (N = 32), we hypothesized that greater functional connectivity within and between FPN and DMN would be associated with greater negative affectivity. In the full sample we did not find support for these hypotheses. Instead, greater DMN intranetwork connectivity at age one month was associated with lower concurrent parent-reported crying and temperamental negative affectivity at age six months (ßs>-0.35, ps<.025), but not crying at age six months. DMN intranetwork connectivity was also negatively associated with internalizing symptoms at age eighteen-months (ß=-0.58, p = .012). FPN intra- and internetwork connectivity was not associated with negative affectivity measures after accounting for covariates. This work furthers a neurodevelopmental model of emotion dysregulation by suggesting that infant functional connectivity at rest is associated with later emotional functioning.

Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer

Predictive models in neuroimaging are increasingly designed with the intent to improve risk stratification and support interventional efforts in psychiatry. Many of these models have been developed in samples of children school-aged or older. Nevertheless, despite growing evidence that altered brain maturation during the fetal, infant, and toddler (FIT) period modulates risk for poor mental health outcomes in childhood, these models are rarely implemented in FIT samples. Applications of predictive modeling in children of these ages provide an opportunity to develop powerful tools for improved characterization of the neural mechanisms underlying development. To facilitate the broader use of predictive models in FIT neuroimaging, we present a brief primer and systematic review on the methods used in current predictive modeling FIT studies. Reflecting on current practices in more than 100 studies conducted over the past decade, we provide an overview of topics, modalities, and methods commonly used in the field and under-researched areas. We then outline ethical and future considerations for neuroimaging researchers interested in predicting health outcomes in early life, including researchers who may be relatively new to either advanced machine learning methods or using FIT data. Altogether, the last decade of FIT research in machine learning has provided a foundation for accelerating the prediction of early-life trajectories across the full spectrum of illness and health.

An Opportunity to Increase Collaborative Science in Fetal, Infant, and Toddler Neuroimaging

The field of fetal, infant, and toddler (FIT) neuroimaging research—including magnetic resonance imaging (MRI), electroencephalography (EEG), magnetoencephalography, and functional near-infrared spectroscopy, among others—offers pioneering insights into early brain development and has grown in popularity over the past 2 decades. In broader neuroimaging research, multisite collaborative projects, data sharing, and open-source code have increasingly become the norm, fostering big data, consensus standards, and rapid knowledge transfer and development. Given the aforementioned benefits, along with recent initiatives from funding agencies to support multisite and multimodal FIT neuroimaging studies, the FIT field now has the opportunity to establish sustainable, collaborative, and open science practices. By combining data and resources, we can tackle the most pressing issues of the FIT field, including small effect sizes, replicability problems, generalizability issues, and the lack of field standards for data collection, processing, and analysis—together. Thus, the goals of this commentary are to highlight some of the potential barriers that have waylaid these efforts and to discuss the emerging solutions that have the potential to revolutionize how we work together to study the developing brain early in life.

Baby Brains at Work: How Task-Based Functional Magnetic Resonance Imaging Can Illuminate the Early Emergence of Psychiatric Risk

Psychiatric disorders are complex, often emerging from multiple atypical processes within specified domains over the course of development. Characterizing the development of the neural circuits supporting these domains may help break down the components of complex disorders and reveal variations in functioning associated with psychiatric risk. This review highlights the current and potential role of infant task-based functional magnetic resonance imaging (fMRI) in elucidating the developmental neurobiology of psychiatric disorders. Task-fMRI measures evoked brain activity in response to specific stimuli through changes in the blood oxygen level-dependent signal. First, we review extant studies using task fMRI from birth through the first few years of life and synthesize current evidence for when, where, and how different neural computations are performed across the infant brain. Neural circuits for sensory perception, the perception of abstract categories, and the detection of statistical regularities have been characterized with task fMRI in infants, providing developmental context for identifying and interpreting variation in the functioning of neural circuits related to psychiatric risk. Next, we discuss studies that specifically examine variation in the functioning of these neural circuits during infancy in relation to risk for psychiatric disorders. These studies reveal when maturation of specific neural circuits diverges, the influence of environmental risk factors, and the potential utility for task fMRI to facilitate early treatment or prevention of later psychiatric problems. Finally, we provide considerations for future infant task-fMRI studies with the potential to advance understanding of both functioning of neural circuits during infancy and subsequent risk for psychiatric disorders.

Sex-specific inflammatory and white matter effects of prenatal opioid exposure: a pilot study

BACKGROUND

Preclinical data demonstrate that opioids modulate brain reward signaling through an inflammatory cascade, but this relationship has yet to be studied in opioid-exposed neonates.

METHODS

Saliva samples of 54 opioid-exposed and sex- and age-matched non-exposed neonates underwent transcriptomic analysis of inflammatory and reward genes. A subset of 22 neonates underwent brain magnetic resonance imaging (MRI) to evaluate white matter injury commonly associated with inflammatory response. Gene expression and brain MRI were compared between opioid- and non-exposed neonates and further stratified by sex and pharmacotherapy need.

RESULTS

Opioid-exposed females regardless of pharmacotherapy need had higher expression of inflammatory genes than their male counterparts, with notable differences in the expression of CCL2 and CXCL1 in females requiring pharmacotherapy (p = 0.01 and 0.06, respectively). Opioid-exposed males requiring pharmacotherapy had higher expression of DRD2 than exposed females (p = 0.07), validating our prior research. Higher expression of IL1β, IL6, TNFα, and IL10 was seen in opioid-exposed neonates with T1 white matter hyperintensity (WMH) compared to exposed neonates without WMH (p < 0.05).

CONCLUSION

Prenatal opioid exposure may promote inflammation resulting in changes in reward signaling and white matter injury in the developing brain, with unique sex-specific effects. The actions of opioids through non-neuronal pathways need further investigation.

IMPACT

Opioid-exposed neonates are at risk for punctate T1 white matter hyperintensity (WMH). Females carry a greater propensity for WMH. Salivary transcriptomic data showed significantly higher expression of inflammatory genes in opioid-exposed neonates with WMH than those without WMH, irrespective of pharmacotherapy need. Adding to prior studies, our findings suggest that prenatal opioid exposure may modulate white matter injury and reward signaling through a pro-inflammatory process that is sex specific. This novel study highlights the short-term molecular and structural effects of prenatal opioids and the need to elucidate the long-term impact of prenatal opioid exposure.

Patterns of Neural Functional Connectivity in Infants at Familial Risk of Developmental Dyslexia

Importance

Developmental dyslexia is a heritable learning disability affecting 7% to 10% of the general population and can have detrimental impacts on mental health and vocational potential. Individuals with dyslexia show altered functional organization of the language and reading neural networks; however, it remains unknown how early in life these neural network alterations might emerge.

Objective

To determine whether the early emergence of large-scale neural functional connectivity (FC) underlying long-term language and reading development is altered in infants with a familial history of dyslexia (FHD).

Design, Setting, and Participants

This cohort study included infants recruited at Boston Children's Hospital between May 2011 and February 2019. Participants underwent structural and resting-state functional magnetic resonance imaging in the Department of Radiology at Boston Children's Hospital. Infants with FHD were matched with infants without FHD based on age and sex. Data were analyzed from April 2019 to June 2021.

Exposures

FHD was defined as having at least 1 first-degree relative with a dyslexia diagnosis or documented reading difficulties.

Main Outcomes and Measures

Whole-brain FC patterns associated with 20 predefined cerebral regions important for long-term language and reading development were computed for each infant. Multivariate pattern analyses were applied to identify specific FC patterns that differentiated between infants with vs without FHD. For classification performance estimates, 99% CIs were calculated as the classification accuracy minus chance level.

Results

A total of 98 infants (mean [SD] age, 8.5 [2.3] months; 51 [52.0%] girls) were analyzed, including 35 infants with FHD and 63 infants without FHD. Multivariate pattern analyses identified distinct FC patterns between infants with vs without FHD in the left fusiform gyrus (classification accuracy, 0.55 [99% CI, 0.046-0.062]; corrected P < .001; Cohen d = 0.76). Connections linking left fusiform gyrus to regions in the frontal and parietal language and attention networks were among the paths with the highest contributions to the classification performance.

Conclusions and Relevance

These findings suggest that on the group level, FHD was associated with an early onset of atypical FC of regions important for subsequent word form recognition during reading acquisition. Longitudinal studies linking the atypical functional network and school-age reading abilities will be essential to further elucidate the ontogenetic mechanisms underlying the development of dyslexia.

(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.