Atypical Brain Development Research Articles

Hierarchical Complexity of the Macro-Scale Neonatal Brain.

The human adult structural connectome has a rich nodal hierarchy, with highly diverse connectivity patterns aligned to the diverse range of functional specializations in the brain. The emergence of this hierarchical complexity in human development is unknown. Here, we substantiate the hierarchical tiers and hierarchical complexity of brain networks in the newborn period, assess correspondences with hierarchical complexity in adulthood, and investigate the effect of preterm birth, a leading cause of atypical brain development and later neurocognitive impairment, on hierarchical complexity. We report that neonatal and adult structural connectomes are both composed of distinct hierarchical tiers and that hierarchical complexity is greater in term born neonates than in preterms. This is due to diversity of connectivity patterns of regions within the intermediate tiers, which consist of regions that underlie sensorimotor processing and its integration with cognitive information. For neonates and adults, the highest tier (hub regions) is ordered, rather than complex, with more homogeneous connectivity patterns in structural hubs. This suggests that the brain develops first a more rigid structure in hub regions allowing for the development of greater and more diverse functional specialization in lower level regions, while connectivity underpinning this diversity is dysmature in infants born preterm.

Apigenin as a Candidate Prenatal Treatment for Trisomy 21: Effects in Human Amniocytes and the Ts1Cje Mouse Model

Human fetuses with trisomy 21 (T21) have atypical brain development that is apparent sonographically in the second trimester. We hypothesize that by analyzing and integrating dysregulated gene expression and pathways common to humans with Down syndrome (DS) and mouse models we can discover novel targets for prenatal therapy. Here, we tested the safety and efficacy of apigenin, identified with this approach, in both human amniocytes from fetuses with T21 and in the Ts1Cje mouse model. Invitro, T21 cells cultured with apigenin had significantly reduced oxidative stress and improved antioxidant defense response. Invivo, apigenin treatment mixed with chow was administered prenatally to the dams and fed to the pups over their lifetimes. There was no significant increase in birth defects or pup deaths resulting from prenatal apigenin treatment. Apigenin significantly improved several developmental milestones and spatial olfactory memory in Ts1Cje neonates. In addition, we noted sex-specific effects on exploratory behavior and long-term hippocampal memory in adult mice, and males showed significantly more improvement than females. We demonstrated that the therapeutic effects of apigenin are pleiotropic, resulting in decreased oxidative stress, activation of pro-proliferative and pro-neurogenic genes (KI67, Nestin, Sox2, and PAX6), reduction of the pro-inflammatory cytokines INFG, IL1A, and IL12P70 through the inhibition of NFκB signaling, increase of the anti-inflammatory cytokines IL10 and IL12P40, and increased expression of the angiogenic and neurotrophic factors VEGFA and IL7. These studies provide proof of principle that apigenin has multiple therapeutic targets in preclinical models ofDS.

The Developmental Chronnecto-Genomics (Dev-CoG) study: A multimodal study on the developing brain

Brain development has largely been studied through unimodal analysis of neuroimaging data, providing independent results for structural and functional data. However, structure clearly impacts function and vice versa, pointing to the need for performing multimodal data collection and analysis to improve our understanding of brain development, and to further inform models of typical and atypical brain development across the lifespan. Ultimately, such models should also incorporate genetic and epigenetic mechanisms underlying brain structure and function, although currently this area is poorly specified. To this end, we are reporting here a multi-site, multi-modal dataset that captures cognitive function, brain structure and function, and genetic and epigenetic measures to better quantify the factors that influence brain development in children originally aged 9–14 years. Data collection for the Developmental Chronnecto-Genomics (Dev-CoG) study (http://devcog.mrn.org/) includes cognitive, emotional, and social performance scales, structural and functional MRI, diffusion MRI, magnetoencephalography (MEG), and saliva collection for DNA analysis of single nucleotide polymorphisms (SNPs) and DNA methylation patterns. Across two sites (The Mind Research Network and the University of Nebraska Medical Center), data from over 200 participants were collected and these children were re-tested annually for at least 3 years. The data collection protocol, sample demographics, and data quality measures for the dataset are presented here. The sample will be made freely available through the collaborative informatics and neuroimaging suite (COINS) database at the conclusion of the study.

A Novel Method for High-Dimensional Anatomical Mapping of Extra-Axial Cerebrospinal Fluid: Application to the Infant Brain.

Cerebrospinal fluid (CSF) plays an essential role in early postnatal brain development. Extra-axial CSF (EA-CSF) volume, which is characterized by CSF in the subarachnoid space surrounding the brain, is a promising marker in the early detection of young children at risk for neurodevelopmental disorders. Previous studies have focused on global EA-CSF volume across the entire dorsal extent of the brain, and not regionally-specific EA-CSF measurements, because no tools were previously available for extracting local EA-CSF measures suitable for localized cortical surface analysis. In this paper, we propose a novel framework for the localized, cortical surface-based analysis of EA-CSF. The proposed processing framework combines probabilistic brain tissue segmentation, cortical surface reconstruction, and streamline-based local EA-CSF quantification. The quantitative analysis of local EA-CSF was applied to a dataset of typically developing infants with longitudinal MRI scans from 6 to 24 months of age. There was a high degree of consistency in the spatial patterns of local EA-CSF across age using the proposed methods. Statistical analysis of local EA-CSF revealed several novel findings: several regions of the cerebral cortex showed reductions in EA-CSF from 6 to 24 months of age, and specific regions showed higher local EA-CSF in males compared to females. These age-, sex-, and anatomically-specific patterns of local EA-CSF would not have been observed if only a global EA-CSF measure were utilized. The proposed methods are integrated into a freely available, open-source, cross-platform, user-friendly software tool, allowing neuroimaging labs to quantify local extra-axial CSF in their neuroimaging studies to investigate its role in typical and atypical brain development.

Maternal influences on fetal brain development: The role of nutrition, infection and stress, and the potential for intergenerational consequences

An optimal early life environment is crucial for ensuring ideal neurodevelopmental outcomes. Brain development consists of a finely tuned series of spatially and temporally constrained events, which may be affected by exposure to a sub-optimal intra-uterine environment. Evidence suggests brain development may be particularly vulnerable to factors such as maternal nutrition, infection and stress during pregnancy. In this review, we discuss how maternal factors such as these can affect brain development and outcome in offspring, and we also identify evidence which suggests that the outcome can, in many cases, be stratified by socio-economic status (SES), with individuals in lower brackets typically having a worse outcome. We consider the relevant epidemiological evidence and draw parallels to mechanisms suggested by preclinical work where appropriate. We also discuss possible transgenerational effects of these maternal factors and the potential mechanisms involved. We conclude that modifiable factors such as maternal nutrition, infection and stress are important contributors to atypical brain development and that SES also likely has a key role.

Atypical age-related changes in cortical thickness in autism spectrum disorder

Recent longitudinal neuroimaging and neurophysiological studies have shown that tracking relative age-related changes in neural signals, rather than a static snapshot of a neural measure, could offer higher sensitivity for discriminating typically developing (TD) individuals from those with autism spectrum disorder (ASD). It is not clear, however, which aspects of age-related changes (trajectories) would be optimal for identifying atypical brain development in ASD. Using a large cross-sectional data set (Autism Brain Imaging Data Exchange [ABIDE] repository; releases I and II), we aimed to explore age-related changes in cortical thickness (CT) in TD and ASD populations (age range 6–30 years old). Cortical thickness was estimated from T1-weighted MRI images at three scales of spatial coarseness (three parcellations with different numbers of regions of interest). For each parcellation, three polynomial models of age-related changes in CT were tested. Specifically, to characterize alterations in CT trajectories, we compared the linear slope, curvature, and aberrancy of CT trajectories across experimental groups, which was estimated using linear, quadratic, and cubic polynomial models, respectively. Also, we explored associations between age-related changes with ASD symptomatology quantified as the Autism Diagnostic Observation Schedule (ADOS) scores. While no overall group differences in cortical thickness were observed across the entire age range, ASD and TD populations were different in terms of age-related changes, which were located primarily in frontal and tempo-parietal areas. These atypical age-related changes were also associated with ADOS scores in the ASD group and used to predict ASD from TD development. These results indicate that the curvature is the most reliable feature for localizing brain areas developmentally atypical in ASD with a more pronounced effect with symptomatology and is the most sensitive in predicting ASD development.

Development of Microstructural and Morphological Cortical Profiles in the Neonatal Brain.

Interruptions to neurodevelopment during the perinatal period may have long-lasting consequences. However, to be able to investigate deviations in the foundation of proper connectivity and functional circuits, we need a measure of how this architecture evolves in the typically developing brain. To this end, in a cohort of 241 term-born infants, we used magnetic resonance imaging to estimate cortical profiles based on morphometry and microstructure over the perinatal period (37–44 weeks postmenstrual age, PMA). Using the covariance of these profiles as a measure of inter-areal network similarity (morphometric similarity networks; MSN), we clustered these networks into distinct modules. The resulting modules were consistent and symmetric, and corresponded to known functional distinctions, including sensory–motor, limbic, and association regions, and were spatially mapped onto known cytoarchitectonic tissue classes. Posterior regions became more morphometrically similar with increasing age, while peri-cingulate and medial temporal regions became more dissimilar. Network strength was associated with age: Within-network similarity increased over age suggesting emerging network distinction. These changes in cortical network architecture over an 8-week period are consistent with, and likely underpin, the highly dynamic processes occurring during this critical period. The resulting cortical profiles might provide normative reference to investigate atypical early brain development.

Thalamic Nuclei Volumes in Psychotic Disorders and Youth With Psychosis Spectrum Symptoms

Several influential models posit that the pathophysiology of psychosis includes thalamic association nuclei and that thalamic abnormalities are due, at least in part, to atypical brain development, and related to mechanisms of cognitive impairment. While multiple lines of evidence are consistent with thalamic involvement in psychosis, evidence that association nuclei are differentially affected is sparse.

Automatic Measurement of Extra-Axial CSF from Infant MRI Data.

The quantification of cerebrospinal fluid (CSF) in the human brain has shown to play an important role in early postnatal brain development. Extra-axial fluid (EA-CSF), which is characterized by CSF in the subarachnoid space, is a promising marker for the early detection of children at risk for neurodevelopmental disorders, such as Autism Spectrum Disorder (ASD). Yet, non-ventricular CSF quantification, in particular extra-axial CSF quantification, is not supported in the major neuro-imaging software solutions, such as FreeSurfer. Most current structural image analysis packages mask out the extra-axial CSF space in one of the first pre-processing steps. A quantitative protocol was previously developed by our group to objectively measure the volume of total EA-CSF volume using a pipeline workflow implemented in a series of python scripts. While this solution worked for our specific lab, a graphical user interface-based tool is necessary to facilitate the computation of extra-axial CSF volume across a wide array of neuroimaging studies and research labs. This paper presents the development of a novel open-source, cross-platform, user-friendly software tool, called Auto-EACSF, for the automatic computation of such extra-axial CSF volume. Auto-EACSF allows neuroimaging labs to quantify extra-axial CSF in their neuroimaging studies in order to investigate its role in normal and atypical brain development.

Invited Review: Factors associated with atypical brain development in preterm infants: insights from magnetic resonance imaging.

Preterm birth (PTB) is a leading cause of neurodevelopmental and neurocognitive impairment in childhood and is closely associated with psychiatric disease. The biological and environmental factors that confer risk and resilience for healthy brain development and long‐term outcome after PTB are uncertain, which presents challenges for risk stratification and for the discovery and evaluation of neuroprotective strategies. Neonatal magnetic resonance imaging reveals a signature of PTB that includes dysconnectivity of neural networks and atypical development of cortical and deep grey matter structures. Here we provide a brief review of perinatal factors that are associated with the MRI signature of PTB. We consider maternal and foetal factors including chorioamnionitis, foetal growth restriction, socioeconomic deprivation and prenatal alcohol, drug and stress exposures; and neonatal factors including co‐morbidities of PTB, nutrition, pain and medication during neonatal intensive care and variation conferred by the genome/epigenome. Association studies offer the first insights into pathways to adversity and resilience after PTB. Future challenges are to analyse quantitative brain MRI data with collateral biological and environmental data in study designs that support causal inference, and ultimately to use the output of such analyses to stratify infants for clinical trials of therapies designed to improve outcome.

Canadian Paediatric Society clinical practice recommendations for assessment of children and youth with autism spectrum disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social communication, restricted interests, and repetitive patterns of behaviour as well as unusual sensory sensitivities or interests. ASD is a diverse and multifaceted condition that varies in both expression across individuals and in its long-term trajectory, which contributes to challenges in patient assessment. Accurate and timely diagnosis is essential to promoting optimal functioning and long-term outcomes by allowing children and youth with ASD to access evidence-based interventions. As well, common health and emotional-behavioural comorbidities associated with ASD contribute to functional impairments, reduced quality of life and family stress, thus warranting holistic approaches to paediatric care. ASD has a strong biological basis, with clear evidence of atypical early brain development and underlying genetic and other etiological influences. However, diagnostic biomarkers have not yet been characterized. Like other conditions defined by the Diagnostic and Statistical Manual of Mental Disorders – 5 (DSM-5), assessment and diagnosis of ASD rely heavily on behavioural features and clinical judgement. Thus, clinical assessment practices have important implications, both for individual children and families (e.g., timeliness of diagnosis and access to treatment services) and for society (e.g., resource allocation and costs). There is a need to adopt strategies that address the current needs of Canadian children and build community capacity, even though there are outstanding questions regarding the long-term outcomes associated with various assessment approaches (e.g., family experience, need for reassessment). Hence, we recommend a ‘best practice’ approach that represents the consensus of an interdisciplinary task force, based on currently available evidence, and consideration of regional and provincial variation in service structure as well as general strengths within the Canadian health system.

Apparent thinning of human visual cortex during childhood is associated with myelination

Human cortex appears to thin during childhood development. However, the underlying microstructural mechanisms are unknown. Using functional magnetic resonance imaging (fMRI), quantitative MRI (qMRI), and diffusion MRI (dMRI) in children and adults, we tested what quantitative changes occur to gray and white matter in ventral temporal cortex (VTC) from childhood to adulthood, and how these changes relate to cortical thinning. T1 relaxation time from qMRI and mean diffusivity (MD) from dMRI provide independent and complementary measurements of microstructural properties of gray and white matter tissue. In face- and character-selective regions in lateral VTC, T1 and MD decreased from age 5 to adulthood in mid and deep cortex, as well as in their adjacent white matter. T1 reduction also occurred longitudinally in children's brain regions. T1 and MD decreases 1) were consistent with tissue growth related to myelination, which we verified with adult histological myelin stains, and 2) were correlated with apparent cortical thinning. In contrast, in place-selective cortex in medial VTC, we found no development of T1 or MD after age 5, and thickness was related to cortical morphology. These findings suggest that lateral VTC likely becomes more myelinated from childhood to adulthood, affecting the contrast of MR images and, in turn, the apparent gray-white boundary. These findings are important because they suggest that VTC does not thin during childhood but instead gets more myelinated. Our data have broad ramifications for understanding both typical and atypical brain development using advanced in vivo quantitative measurements and clinical conditions implicating myelin.

Quantitative MRI Analyses of Regional Brain Growth in Living Fetuses with Down Syndrome.

Down syndrome (DS) is the most common liveborn autosomal chromosomal anomaly and is a major cause of developmental disability. Atypical brain development and the resulting intellectual disability originate during the fetal period. Perinatal interventions to correct such aberrant development are on the horizon in preclinical studies. However, we lack tools to sensitively measure aberrant structural brain development in living human fetuses with DS. In this study, we aimed to develop safe and precise neuroimaging measures to monitor fetal brain development in DS. We measured growth patterns of regional brain structures in 10 fetal brains with DS (29.1 ± 4.2, weeks of gestation, mean ± SD, range 21.7~35.1) and 12 control fetuses (25.2 ± 5.0, range 18.6~33.3) using regional volumetric analysis of fetal brain MRI. All cases with DS had confirmed karyotypes. We performed non-linear regression models to compare fitted regional growth curves between DS and controls. We found decreased growth trajectories of the cortical plate (P= 0.033), the subcortical parenchyma (P= 0.010), and the cerebellar hemispheres (P< 0.0001) in DS compared to controls. This study provides proof of principle that regional volumetric analysis of fetal brain MRI facilitates successful evaluation of brain development in living fetuses with DS.

Abnormal Left-Hemispheric Sulcal Patterns Correlate with Neurodevelopmental Outcomes in Subjects with Single Ventricular Congenital Heart Disease.

Neurodevelopmental abnormalities are the most common noncardiac complications in patients with congenital heart disease (CHD). Prenatal brain abnormalities may be due to reduced oxygenation, genetic factors, or less commonly, teratogens. Understanding the contribution of these factors is essential to improve outcomes. Because primary sulcal patterns are prenatally determined and under strong genetic control, we hypothesized that they are influenced by genetic variants in CHD. In this study, we reveal significant alterations in sulcal patterns among subjects with single ventricle CHD (n= 115, 14.7 ± 2.9years [mean ± standard deviation]) compared with controls (n= 45, 15.5 ± 2.4years) using a graph-based pattern-analysis technique. Among patients with CHD, the left hemisphere demonstrated decreased sulcal pattern similarity to controls in the left temporal and parietal lobes, as well as the bilateral frontal lobes. Temporal and parietal lobes demonstrated an abnormally asymmetric left-right pattern of sulcal basin area in CHD subjects. Sulcal pattern similarity to control was positively correlated with working memory, processing speed, and executive function. Exome analysis identified damaging de novo variants only in CHD subjects with more atypical sulcal patterns. Together, these findings suggest that sulcal pattern analysis may be useful in characterizing genetically influenced, atypical early brain development and neurodevelopmental risk in subjects with CHD.

Autism is a prenatal disorder: Evidence from late gestation brain overgrowth.

This retrospective study aimed to specify the critical period for atypical brain development in individuals with autism spectrum disorder (ASD) using prenatal and postnatal head growth parameters. The sample consisted of 80 Caucasian, unrelated, idiopathic patients with ASD born after 1995. Fetal ultrasound parameters (head circumference [HC], abdominal circumference, and femur length) were obtained during the second and third trimesters of gestation. HC at birth and postnatal parameters at 12 and 24 months of age were also collected. Head overgrowth, assessed by HC, was highlighted during the second (20-26 weeks of amenorrhea) and third (28-36 weeks of amenorrhea) trimesters. Normal growth of body fetal parameters indicated that head overgrowth was not because of overall body overgrowth. Moreover, postnatal results replicated previously and reported head overgrowth. A critical time window for atypical brain development in autism is hypothesized to begin from the 22nd week of amenorrhea. This period is critical for cortical lamination and glial activation. A pathophysiological cascade is suggested with interactions between candidate genes and environmental factors. Autism Research 2018, 11: 1635-1642. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: It is now widely acknowledged in the scientific community, that autism is a neurodevelopmental disorder. Recent evidence from animal and pathological studies has implicated the in utero period. However, the precise time of onset of abnormal brain development remains unknown. This retrospective study reports novel findings, identifying an atypical head growth trajectory in children with autism, during the in utero period (after the 22nd week of amenorrhea). In the same children, postnatal head overgrowth was also observed. Late gestation is identified as a critical period for atypical brain development underlying autism symptoms.

Relationships between variance in electroencephalography relative power and developmental status in infants with typical development and at risk for developmental disability: An observational study

Background: Electroencephalography (EEG) is a non-invasive tool that has the potential to identify and quantify atypical brain development. We introduce a new measure here, variance of relative power of resting-state EEG. We sought to assess whether variance of relative power of resting-state EEG could predict i) classification of infants as typical development (TD) or at risk (AR) for developmental disability, and ii) Bayley developmental scores at the same visit or future visits. Methods: A total of 22 infants with TD participated, aged between 38 and 203 days. In addition, 11 infants broadly at risk participated (6 high-risk pre-term, 4 low-risk pre-term, 1 high-risk full-term), aged between 40 and 225 days of age (adjusted for prematurity). We used EEG to measure resting-state brain function across months. We calculated variance of relative power as the standard deviation of the relative power across each of the 32 EEG electrodes. The Bayley Scales of Infant Development (3 rd edition) was used to measure developmental level. Infants were measured 1-6 times each, with 1 month between measurements. Results: Our main findings were: i) variance of relative power of resting state EEG can predict classification of infants as TD or AR, and ii) variance of relative power of resting state EEG can predict Bayley developmental scores at the same visit (Bayley raw fine motor, Bayley raw cognitive, Bayley total raw score, Bayley motor composite score) and at a future visit (Bayley raw fine motor). Conclusions: This was a preliminary, exploratory, small study. Our results support variance of relative power of resting state EEG as an area of interest for future study as a biomarker of neurodevelopmental status and as a potential outcome measure for early intervention.

Relationships between variance in electroencephalography relative power and developmental status in infants with typical development and at risk for developmental disability: An observational study

Background: Electroencephalography (EEG) is a non-invasive tool that has the potential to identify and quantify atypical brain development. We introduce a new measure here, variance of relative power of resting-state EEG. We sought to assess whether variance of relative power of resting-state EEG could predict i) classification of infants as typical development (TD) or at risk (AR) for developmental disability, and ii) Bayley developmental scores at the same visit or future visits. Methods: A total of 22 infants with TD participated, aged between 38 and 203 days. In addition, 11 infants broadly at risk participated (6 high-risk pre-term, 4 low-risk pre-term, 1 high-risk full-term), aged between 40 and 225 days of age (adjusted for prematurity). We used EEG to measure resting-state brain function across months. We calculated variance of relative power as the standard deviation of the relative power across each of the 32 EEG electrodes. The Bayley Scales of Infant Development (3 rd edition) was used to measure developmental level. Infants were measured 1-6 times each, with 1 month between measurements. Results: Our main findings were: i) variance of relative power of resting state EEG can predict classification of infants as TD or AR, and ii) variance of relative power of resting state EEG can predict Bayley developmental scores at the same visit (Bayley raw fine motor, Bayley raw cognitive, Bayley total raw score, Bayley motor composite score) and at a future visit (Bayley raw fine motor). Conclusions: This was a preliminary, exploratory, small study. Our results support variance of relative power of resting state EEG as an area of interest for future study as a biomarker of neurodevelopmental status and as a potential outcome measure for early intervention.

Prenatal hypoxia–ischemia decreases spatial memory and increases aggression during adolescence

Prenatal hypoxia-ischemia (HI) is a major cause of mortality and chronic neurological diseases in newborns. HI contributes to the emergence of several neurological disorders such as cognitive and behavioral deficits due to the atypical brain development. This study aimed at assessing the effects of prenatal HI on the spatial memory and aggression of rats during adolescence. Pregnant rats were divided into treatment and control groups. The rats of the treatment groups underwent unilateral ligation of the uterine artery on pregnancy day 7, 12, or 17. The offspring of these rats were tested for spatial memory and aggression when they reached 33 days of age. It has been found that the percentages of alternations in the Y-maze and the number of crossings in the Morris water maze tests of the HI groups were lower than those of the control groups. The total offense and defense aggression scores of the HI groups were higher than those of the control groups. In conclusion, the longer the duration of HI, the more deficits it causes in the spatial memory and aggression of rats during adolescence.

Relationships between variance in electroencephalography relative power and developmental status in infants with typical development and at risk for developmental disability: An observational study

Background: Electroencephalography (EEG) is a non-invasive tool that has the potential to identify and quantify atypical brain development. We introduce a new measure here, variance of relative power of resting-state EEG. We sought to assess whether variance of relative power of resting-state EEG could predict i) classification of infants as typical development (TD) or at risk (AR) for developmental disability, and ii) Bayley developmental scores at the same visit or future visits. Methods: A total of 22 infants with TD participated, aged between 38 and 203 days. In addition, 11 infants broadly at risk participated (6 high-risk pre-term, 4 low-risk pre-term, 1 high-risk full-term), aged between 40 and 225 days of age (adjusted for prematurity). We used EEG to measure resting-state brain function across months. We calculated variance of relative power as the standard deviation of the relative power across each of the 32 EEG electrodes. The Bayley Scales of Infant Development (3rd edition) was used to measure developmental level. Infants were measured 1-6 times each, with 1 month between measurements. Results: Our main findings were: i) variance of relative power of resting state EEG can predict classification of infants as TD or AR, and ii) variance of relative power of resting state EEG can predict Bayley developmental scores at the same visit (Bayley raw fine motor, Bayley raw cognitive, Bayley total raw score, Bayley motor composite score) and at a future visit (Bayley raw fine motor). Conclusions: This was a preliminary, exploratory, small study. Our results support variance of relative power of resting state EEG as an area of interest for future study as a biomarker of neurodevelopmental status and as a potential outcome measure for early intervention.

Neurobiology, not artifacts: Challenges and guidelines for imaging the high risk infant

The search for the brain-basis of atypical development in human infants is challenging because the process of imaging and the generation of the MR signal itself relies on assumptions that reflect biophysical properties of the brain tissue. These assumptions are not inviolate, have been questioned by recent empirical evidence from high risk infant-sibling studies, and to date remain largely underexamined at the between-group level. In particular, I consider recent work showing that infants at High vs. Low familial risk (HR vs. LR, respectively) for developing Autism Spectrum Disorders (ASD) have atypical patterns of head movements during an MR scan that are functionally important—they are linked to future learning trajectories in toddlerhood. Addressing head movement issues in neuroimaging analyses in infant research as well as understanding the causes of these movements from a developmental perspective requires acknowledging the complexity of this endeavor. For example, head movement signatures in infants can interact with experimental task conditions (such as listening to language compared to sleeping), autism risk, and age. How can new knowledge about newborns' individual, subject-specific behavioral differences which may impact MR signal acquisition and statistical inference ignite critical thinking for the field of infant brain imaging across the spectrum of typical and atypical development? Early behavioral differences between HR and LR infant cohorts that are often examples of “artifactual” confounds in MR work provide insight into nascent neurobiological differences, including biophysical tissue properties and hemodynamic response variability, in these and related populations at risk for atypical development. Are these neurobiological drivers of atypical development? This work identifies important knowledge gaps and suggests guidelines at the leading edge of baby imaging science to transform our understanding of atypical brain development in humans. The precise study of the neurobiological underpinnings of atypical development in humans calls for approaches including quantitative MRI (qMRI) pulse sequences, multi-modal imaging (including DTI, MRS, as well as MEG), and infant-specific HRF shapes when modeling BOLD signal.