Longitudinal analysis of neural network development in preterm infants

Regularized-Ncut: Robust and homogeneous functional parcellation of neonate and adult brain networks

Brain network parcellation based on resting-state functional MRI (rs-fMRI) is affected by noise, resulting in spurious small patches and decreased functional homogeneity within each network. Obtaining robust and homogeneous parcellation of neonate brain is more difficult, because neonate rs-fMRI is associated with relatively higher level of noise and no prior knowledge from a functional neonate atlas is available as spatial constraints. To meet these challenges, we developed a novel data-driven Regularized Normalized-cut (RNcut) method. RNcut is formulated by adding two regularization terms, a smoothing term using Markov random fields and a small-patch removal term, to conventional normalized-cut (Ncut) method. The RNcut and competing methods were tested with simulated datasets with known ground truth and then applied to both adult and neonate rs-fMRI datasets. Based on the parcellated networks generated by RNcut, intra-network connectivity was quantified. The test results from simulated datasets demonstrated that the RNcut method is more robust (p < 0.01) to noise and can delineate parcellated functional networks with significantly better (p < 0.01) spatial contiguity and significantly higher (p < 0.01) functional homogeneity than competing methods. Application of RNcut to neonate and adult rs-fMRI dataset revealed distinctive functional brain organization of neonate brains from that of adult brains. Collectively, we developed a novel data-driven RNcut method by integrating conventional Ncut with two regularization terms, generating robust and homogeneous functional parcellation without imposing spatial constraints. A broad range of brain network applications and analyses, especially neonate and infant brain parcellation with noisy and large sample of datasets, can potentially benefit from this RNcut method.

Development of Brain Networks In Utero: Relevance for Common Neural Disorders

Magnetic resonance imaging, histological, and gene analysis approaches in living and nonliving human fetuses and in prematurely born neonates have provided insight into the staged processes of prenatal brain development. Increased understanding of micro- and macroscale brain network development before birth has spurred interest in understanding the relevance of prenatal brain development to common neurological diseases. Questions abound as to the sensitivity of the intrauterine brain to environmental programming, to windows of plasticity, and to the prenatal origin of disorders of childhood that involve disruptions in large-scale network connectivity. Much of the available literature on human prenatal neural development comes from cross-sectional or case studies that are not able to resolve the longitudinal consequences of individual variation in brain development before birth. This review will 1) detail specific methodologies for studying the human prenatal brain, 2) summarize large-scale human prenatal neural network development, integrating findings from across a variety of experimental approaches, 3) explore the plasticity of the early developing brain as well as potential sex differences in prenatal susceptibility, and 4) evaluate opportunities to link specific prenatal brain developmental processes to the forms of aberrant neural connectivity that underlie common neurological disorders of childhood.

Emerging atypicalities in functional connectivity of language-related networks in young infants at high familial risk for ASD

Prior studies have demonstrated that infants and toddlers who later go on to develop autism spectrum disorder (ASD) show atypical functional connectivity as well as altered neural processing of language and other auditory stimuli, but the timeline underlying the emergence of these altered developmental trajectories is still unclear. Here we used resting-state fMRI (rsfMRI) during natural sleep to examine the longitudinal development of functional connectivity in language-related networks from 1.5 to 9 months of age. We found that functional connectivity of networks that underlie the integration of sensory and motor representations, which is crucial for language development, is disrupted in infants at high familial risk (HR) for developing ASD as early as 1.5 months of age. By 9 months of age, HR infants showed hyperconnectivity between auditory and somatosensory regions whereas low risk (LR) infants displayed greater intrahemispheric connectivity between auditory cortex and higher-order temporal regions as well as the hippocampus. Furthermore, while LR infants showed robust changes in functional connectivity during the first year of life with increasing long-range connectivity accompanied by decreasing short-range connectivity over time, HR infants displayed limited developmental changes. Our findings demonstrate that early disruptions in the development of language-related network connectivity may provide an early marker for the later emergence of ASD symptomatology.

Age and Sex Influences Gamma-aminobutyric Acid Concentrations in the Developing Brain of Very Premature Infants

Gamma-aminobutyric acid (GABA) and glutamate are principal neurotransmitters essential for late gestational brain development and may play an important role in prematurity-related brain injury. In vivo investigation of GABA in the preterm infant with standard proton magnetic resonance spectroscopy (1H-MRS) has been limited due to its low concentrations in the developing brain, and overlap in the spectrum by other dominant metabolites. We describe early postnatal profiles of in vivo GABA and glutamate concentrations in the developing preterm brain measured by using the J-difference editing technique, Mescher-Garwood point resolved spectroscopy. We prospectively enrolled very preterm infants born ≤32 weeks gestational age and non-sedated 1H-MRS (echo time 68 ms, relaxation time 2000 ms, 256 signal averages) was acquired on a 3 Tesla magnetic resonance imaging scanner from a right frontal lobe voxel. Concentrations of GABA + (with macromolecules) was measured from the J-difference spectra; whereas glutamate and composite glutamate + glutamine (Glx) were measured from the unedited (OFF) spectra and reported in institutional units. We acquired 42 reliable spectra from 38 preterm infants without structural brain injury [median gestational age at birth of 28.0 (IQR 26.0, 28.9) weeks; 19 males (50%)] at a median postmenstrual age of 38.4 (range 33.4 to 46.4) weeks. With advancing post-menstrual age, the concentrations of glutamate OFF increased significantly, adjusted for co-variates (generalized estimating equation β = 0.22, p = 0.02). Advancing postnatal weeks of life at the time of imaging positively correlated with GABA + (β = 0.06, p = 0.02), glutamate OFF (β = 0.11, p = 0.02) and Glx OFF (β = 0.12, p = 0.04). Male infants had higher GABA + (1.66 ± 0.07 vs. 1.33 ± 0.11, p = 0.01) concentrations compared with female infants. For the first time, we report the early ex-utero developmental profile of in vivo GABA and glutamate stratified by age and sex in the developing brain of very preterm infants. This data may provide novel insights into the pathophysiology of neurodevelopmental disabilities reported in preterm infants even in the absence of structural brain injury.

The Emergence of Hierarchical Somatosensory Processing in Late Prematurity

The somatosensory system has a hierarchical organization. Information processing increases in complexity from the contralateral primary sensory cortex to bilateral association cortices and this is represented by a sequence of somatosensory-evoked potentials recorded with scalp electroencephalographies. The mammalian somatosensory system matures over the early postnatal period in a rostro-caudal progression, but little is known about the development of hierarchical information processing in the human infant brain. To investigate the normal human development of the somatosensory hierarchy, we recorded potentials evoked by mechanical stimulation of hands and feet in 34 infants between 34 and 42 weeks corrected gestational age, with median postnatal age of 3 days. We show that the shortest latency potential was evoked for both hands and feet at all ages with a contralateral somatotopic source in the primary somatosensory cortex (SI). However, the longer latency responses, localized in SI and beyond, matured with age. They gradually emerged for the foot and, although always present for the hand, showed a shift from purely contralateral to bilateral hemispheric activation. These results demonstrate the rostro-caudal development of human somatosensory hierarchy and suggest that the development of its higher tiers is complete only just before the time of normal birth.

Functional brain connectivity in ex utero premature infants compared to in utero fetuses

Brain structural changes in premature infants appear before term age. Functional differences between premature infants and healthy fetuses during this period have yet to be explored. Here, we examined brain connectivity using resting state functional MRI in 25 very premature infants (VPT; gestational age at birth <32 weeks) and 25 healthy fetuses with structurally normal brain MRIs. Resting state data were evaluated using seed-based correlation analysis and network-based statistics using 23 regions of interest (ROIs) per hemisphere. Functional connectivity strength, the Pearson correlation between blood oxygenation level dependent signals over time across all ROIs, was compared between groups. In both cohorts, connectivity between homotopic ROIs showed a decreasing medial to lateral gradient. The cingulate cortex, medial temporal lobe and the basal ganglia shared the strongest connections. In premature infants, connections involving superior temporal, hippocampal, and occipital areas, among others, were stronger compared to fetuses. Premature infants showed stronger connectivity in sensory input and stress-related areas suggesting that extra-uterine environment exposure alters the development of select neural networks in the absence of structural brain injury.

Non-pharmacological strategies to obtain usable magnetic resonance images in non-sedated infants: Systematic review and meta-analysis

BACKGROUND

Although the use of sedation is commonly practiced to keep infants still while receiving magnetic resonance imaging, non-pharmacological strategies are a potential alternative.

OBJECTIVES

The purpose of this study was to determine the success rate of obtaining usable magnetic resonance images in infants with the sole use of non-pharmacological strategies.

DESIGN

Systematic literature review and meta-analysis SETTING: A search was conducted in PubMed, CINAHL and Cochrane Library.

PARTICIPANTS

Human infants from birth to 24 months of age who did not receive any sedation or anesthesia during magnetic resonance imaging METHOD: Articles that reported the success rate of obtaining usable images were included.

RESULTS

Of the 521 non-duplicate articles found, 58 articles were included in the systematic review with sample sizes ranging from 2-457, an average success rate of 87.8%, and an average scan time of 30 min. The most common non-pharmacological technique included feeding and swaddling infants before imaging to encourage infants to sleep during the scan. Meta-analysis performed on 53 articles comprising 3,410 infants found a success rate of 87%, but significant heterogeneity was found (I² = 98.30%). It was more difficult to obtain usable images solely with non-pharmacological techniques if infants were critically ill or a structural magnetic resonance imaging of the brain was required.

CONCLUSION

Non-pharmacological techniques are effective for obtaining usable magnetic resonance imaging scans in most but not all infants. Tweetable abstract: Non-pharmacological techniques are effective for obtaining usable magnetic resonance imaging scans in most infants.

Atypical neuromagnetic resting activity associated with thalamic volume and cognitive outcome in very preterm children

Children born very preterm, even in the absence of overt brain injury or major impairment, are at increased risk of cognitive difficulties. This risk is associated with developmental disruptions of the thalamocortical system during critical periods while in the neonatal intensive care unit. The thalamus is an important structure that not only relays sensory information but acts as a hub for integration of cortical activity which regulates cortical power across a range of frequencies. In this study, we investigate the association between atypical power at rest in children born very preterm at school age using magnetoencephalography (MEG), neurocognitive function and structural alterations related to the thalamus using MRI. Our results indicate that children born extremely preterm have higher power at slow frequencies (delta and theta) and lower power at faster frequencies (alpha and beta), compared to controls born full-term. A similar pattern of spectral power was found to be associated with poorer neurocognitive outcomes, as well as with normalized T1 intensity and the volume of the thalamus. Overall, this study provides evidence regarding relations between structural alterations related to very preterm birth, atypical oscillatory power at rest and neurocognitive difficulties at school-age children born very preterm.

Transient Arousal Modulations Contribute to Resting-State Functional Connectivity Changes Associated with Head Motion Parameters

Correlations of resting-state functional magnetic resonance imaging (rsfMRI) signals are being widely used for assessing the functional brain connectivity in health and disease. However, an association was recently observed between rsfMRI connectivity modulations and the head motion parameters and regarded as a causal relationship, which has raised serious concerns about the validity of many rsfMRI findings. Here, we studied the origin of this rsfMRI-motion association and its relationship to arousal modulations. By using a template-matching method to locate arousal-related fMRI changes, we showed that the effects of high motion time points on rsfMRI connectivity are largely due to their significant overlap with arousal-affected time points. The finding suggests that the association between rsfMRI connectivity and the head motion parameters arises from their comodulations at transient arousal modulations, and this information is critical not only for proper interpretation of motion-associated rsfMRI connectivity changes, but also for controlling the potential confounding effects of arousal modulation on rsfMRI metrics.

System-Specific Patterns of Thalamocortical Connectivity in Early Brain Development as Revealed by Structural and Functional MRI

The normal development of thalamocortical connections plays a critical role in shaping brain connectivity in the prenatal and postnatal periods. Recent studies using advanced magnetic resonance imaging (MRI) techniques in neonates and infants have shown that abnormal thalamocortical connectivity is associated with adverse neurodevelopmental outcomes. However, all these studies have focused on a single neuroimaging modality, overlooking the dynamic relationship between structure and function at this early stage. Here, we study the relationship between structural and functional thalamocortical connectivity patterns derived from healthy full-term infants scanned with diffusion-weighted MRI and resting-state functional MRI within the first weeks of life (mean gestational age = 39.3 ± 1.2 weeks; age at scan = 24.2 ± 7.9 days). Our results show that while there is, in general, good spatial agreement between both MRI modalities, there are regional variations that are system-specific: regions involving primary-sensory cortices exhibit greater structural/functional overlap, whereas higher-order association areas such as temporal and posterior parietal cortices show divergence in spatial patterns of each modality. This variability illustrates the complementarity of both modalities and highlights the importance of multimodal approaches.

Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity

Denoising fMRI data requires assessment of frame-to-frame head motion and removal of the biases motion introduces. This is usually done through analysis of the parameters calculated during retrospective head motion correction (i.e., 'motion' parameters). However, it is increasingly recognized that respiration introduces factitious head motion via perturbations of the main (B0) field. This effect appears as higher-frequency fluctuations in the motion parameters (>0.1 ​Hz, here referred to as 'HF-motion'), primarily in the phase-encoding direction. This periodicity can sometimes be obscured in standard single-band fMRI (TR 2.0-2.5 ​s) due to aliasing. Here we examined (1) how prevalent HF-motion effects are in seven single-band datasets with TR from 2.0 to 2.5 ​s and (2) how HF-motion affects functional connectivity. We demonstrate that HF-motion is more common in older adults, those with higher body mass index, and those with lower cardiorespiratory fitness. We propose a low-pass filtering approach to remove the contamination of high frequency effects from motion summary measures, such as framewise displacement (FD). We demonstrate that in most datasets this filtering approach saves a substantial amount of data from FD-based frame censoring, while at the same time reducing motion biases in functional connectivity measures. These findings suggest that filtering motion parameters is an effective way to improve the fidelity of head motion estimates, even in single band datasets. Particularly large data savings may accrue in datasets acquired in older and less fit participants.

Resting-state networks of the neonate brain identified using independent component analysis

Resting-state functional magnetic resonance imaging (rs-fMRI) has been successfully used to probe the intrinsic functional organization of the brain and to study brain development. Here, we implemented a combination of individual and group independent component analysis (ICA) of FSL on a 6-min resting-state data set acquired from 21 naturally sleeping term-born (age 26 ± 6.7 d), healthy neonates to investigate the emerging functional resting-state networks (RSNs). In line with the previous literature, we found evidence of sensorimotor, auditory/language, visual, cerebellar, thalmic, parietal, prefrontal, anterior cingulate as well as dorsal and ventral aspects of the default-mode-network. Additionally, we identified RSNs in frontal, parietal, and temporal regions that have not been previously described in this age group and correspond to the canonical RSNs established in adults. Importantly, we found that careful ICA-based denoising of fMRI data increased the number of networks identified with group-ICA, whereas the degree of spatial smoothing did not change the number of identified networks. Our results show that the infant brain has an established set of RSNs soon after birth.

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.

Correlates of Normal and Abnormal General Movements in Infancy and Long-Term Neurodevelopment of Preterm Infants: Insights from Functional Connectivity Studies at Term Equivalence

Preterm infants born before 32 weeks gestation have increased risks for neurodevelopmental impairment at two years of age. How brain function differs between preterm infants with normal or impaired development is unknown. However, abnormal spontaneous motor behavior at 12-15 weeks post-term age is associated with neurodevelopmental impairment. We imaged brain blood oxygen level-dependent signals at term-equivalent age in 62 infants born at <32 weeks gestation and explored whether resting state functional connectivity (rsFC) differed with performances on the General Movement Assessment (GMA) at 12-15 weeks, and Bayley III scores at two years of corrected age. Infants with aberrant general movements exhibited decreased rsFC between the basal ganglia and regions in parietal and frontotemporal lobes. Infants with normal Bayley III cognitive scores exhibited increased rsFC between the basal ganglia and association cortices in parietal and occipital lobes compared with cognitively impaired children. Infants with normal motor scores exhibited increased rsFC between the basal ganglia and visual cortices, compared with children with motor impairment. Thus, the presence of abnormal general movements is associated with region-specific differences in rsFC at term. The association of abnormal long-term neurodevelopmental outcomes with decreased rsFC between basal ganglia and sub-score specific cortical regions may provide biomarkers of neurodevelopmental trajectory and outcome.

A Computational Role for Top-Down Modulation from Frontal Cortex in Infancy

Recent findings have shown that full-term infants engage in top-down sensory prediction, and these predictions are impaired as a result of premature birth. Here, we use an associative learning model to uncover the neuroanatomical origins and computational nature of this top-down signal. Infants were exposed to a probabilistic audiovisual association. We find that both groups (full term, preterm) have a comparable stimulus-related response in sensory and frontal lobes and track prediction error in their frontal lobes. However, preterm infants differ from their full-term peers in weaker tracking of prediction error in sensory regions. We infer that top-down signals from the frontal lobe to the sensory regions carry information about prediction error. Using computational learning models and comparing neuroimaging results from full-term and preterm infants, we have uncovered the computational content of top-down signals in young infants when they are engaged in a probabilistic associative learning.

Correction of respiratory artifacts in MRI head motion estimates

Head motion represents one of the greatest technical obstacles in magnetic resonance imaging (MRI) of the human brain. Accurate detection of artifacts induced by head motion requires precise estimation of movement. However, head motion estimates may be corrupted by artifacts due to magnetic main field fluctuations generated by body motion. In the current report, we examine head motion estimation in multiband resting state functional connectivity MRI (rs-fcMRI) data from the Adolescent Brain and Cognitive Development (ABCD) Study and comparison 'single-shot' datasets. We show that respirations contaminate movement estimates in functional MRI and that respiration generates apparent head motion not associated with functional MRI quality reductions. We have developed a novel approach using a band-stop filter that accurately removes these respiratory effects from motion estimates. Subsequently, we demonstrate that utilizing a band-stop filter improves post-processing fMRI data quality. Lastly, we demonstrate the real-time implementation of motion estimate filtering in our FIRMM (Framewise Integrated Real-Time MRI Monitoring) software package.

Threat bias and resting state functional connectivity of the amygdala and bed nucleus stria terminalis

BACKGROUND

Previous research has distinguished the activations of the amygdala and bed nucleus of stria terminalis (BNST) during threat-related contingencies. However, how intrinsic connectivities of the amygdala and BNST relate to threat bias remains unclear. Here, we investigated how resting state functional connectivity (rsFC) of the amygdala and BNST in healthy controls (HC) and patients with anxiety-related disorders (PAD) associate with threat bias in a dot-probe task.

METHODS

Imaging and behavioral data of 30 PAD and 83 HC were obtained from the Nathan Kline Institute - Rockland sample and processed according to published routines. All imaging results were evaluated at voxel p < 0.001 and cluster p < 0.05, FWE corrected in SPM.

RESULTS

PAD and HC did not show differences in whole brain rsFC with either the amygdala or BNST. In linear regressions threat bias was positively correlated with amygdala-thalamus/anterior cingulate cortex (ACC) rsFC in HC but not PAD, and with BNST-caudate rsFC in PAD but not HC. Slope tests confirmed group differences in the correlations between threat bias and amygdala-thalamus/ACC as well as BNST-caudate rsFC.

LIMITATIONS

As only half of the patients included were diagnosed with comorbid anxiety, the current findings need to be considered with the clinical heterogeneity and require replication in populations specifically with anxiety disorders.

CONCLUSIONS

Together, these results suggest amygdala and BNST connectivities as new neural markers of anxiety disorders. Whereas amygdala-thalamus/ACC rsFC support adaptive regulation of threat response in the HC, BNST-caudate rsFC may reflect maladaptive neural processes that are dominated by anticipatory anxiety.

Portable, field-based neuroimaging using high-density diffuse optical tomography

Behavioral and cognitive tests in individuals who were malnourished as children have revealed malnutrition-related deficits that persist throughout the lifespan. These findings have motivated recent neuroimaging investigations that use highly portable functional near-infrared spectroscopy (fNIRS) instruments to meet the demands of brain imaging experiments in low-resource environments and enable longitudinal investigations of brain function in the context of long-term malnutrition. However, recent studies in healthy subjects have demonstrated that high-density diffuse optical tomography (HD-DOT) can significantly improve image quality over that obtained with sparse fNIRS imaging arrays. In studies of both task activations and resting state functional connectivity, HD-DOT is beginning to approach the data quality of fMRI for superficial cortical regions. In this work, we developed a customized HD-DOT system for use in malnutrition studies in Cali, Colombia. Our results evaluate the performance of the HD-DOT instrument for assessing brain function in a cohort of malnourished children. In addition to demonstrating portability and wearability, we show the HD-DOT instrument's sensitivity to distributed brain responses using a sensory processing task and measurements of homotopic functional connectivity. Task-evoked responses to the passive word listening task produce activations localized to bilateral superior temporal gyrus, replicating previously published work using this paradigm. Evaluating this localization performance across sparse and dense reconstruction schemes indicates that greater localization consistency is associated with a dense array of overlapping optical measurements. These results provide a foundation for additional avenues of investigation, including identifying and characterizing a child's individual malnutrition burden and eventually contributing to intervention development.

Developmental Pathoconnectomics and Advanced Fetal MRI

Developmental pathoconnectomics is an emerging field that aims to unravel the events leading to and outcome from disrupted brain connectivity development. Advanced magnetic resonance imaging (MRI) technology enables the portrayal of human brain connectivity before birth and has the potential to offer novel insights into normal and pathological human brain development. This review gives an overview of the currently used MRI techniques for connectomic imaging, with a particular focus on recent studies that have successfully translated these to the in utero or postmortem fetal setting. Possible mechanisms of how pathologies, maternal, or environmental factors may interfere with the emergence of the connectome are considered. The review highlights the importance of advanced image post processing and the need for reproducibility studies for connectomic imaging. Further work and novel data-sharing efforts would be required to validate or disprove recent observations from in utero connectomic studies, which are typically limited by low case numbers and high data drop out. Novel knowledge with regard to the ontogenesis, architecture, and temporal dynamics of the human brain connectome would lead to the more precise understanding of the etiological background of neurodevelopmental and mental disorders. To achieve this goal, this review considers the growing evidence from advanced fetal connectomic imaging for the increased vulnerability of the human brain during late gestation for pathologies that might lead to impaired connectome development and subsequently interfere with the development of neural substrates serving higher cognition.

Neonatal Functional and Structural Connectivity Are Associated with Cerebral Palsy at Two Years of Age

OBJECTIVE

The accuracy of structural magnetic resonance imaging (MRI) to predict later cerebral palsy (CP) in newborns with perinatal brain injury is variable. Diffusion tensor imaging (DTI) and task-based functional MRI (fMRI) show promise as predictive tools. We hypothesized that infants who later developed CP would have reduced structural and functional connectivity as compared with those without CP.

STUDY DESIGN

We performed DTI and fMRI using a passive motor task at 40 to 48 weeks' postmenstrual age in 12 infants with perinatal brain injury. CP was diagnosed at age 2 using a standardized examination.

RESULTS

Five infants had CP at 2 years of age, and seven did not have CP. Tract-based spatial statistics showed a widespread reduction of fractional anisotropy (FA) in almost all white matter tracts in the CP group. Using the median FA value in the corticospinal tracts as a cutoff, FA was 100% sensitive and 86% specific to predict CP compared with a sensitivity of 60 to 80% and a specificity of 71% for structural MRI. During fMRI, the CP group had reduced functional connectivity from the right supplemental motor area as compared with the non-CP group.

CONCLUSION

DTI and fMRI obtained soon after birth are potential biomarkers to predict CP in newborns with perinatal brain injury.

Variable functional connectivity architecture of the preterm human brain: Impact of developmental cortical expansion and maturation

Functional connectivity (FC) is known to be individually unique and to reflect cognitive variability. Although FC can serve as a valuable correlate and potential predictor of (patho-) physiological nervous function in high-risk constellations, such as preterm birth, templates for individualized FC analysis are lacking, and knowledge about the capacity of the premature brain to develop FC variability is limited. In a cohort of prospectively recruited, preterm-born infants undergoing magnetic resonance imaging close to term-equivalent age, we show that the overall pattern could be reliably detected with a broad range of interindividual FC variability in regions of higher-order cognitive functions (e.g., association cortices) and less interindividual variability in unimodal regions (e.g., visual and motor cortices). However, when comparing the preterm and adult brains, some brain regions showed a marked shift in variability toward adulthood. This shift toward greater variability was strongest in cognitive networks like the attention and frontoparietal networks and could be partially predicted by developmental cortical expansion. Furthermore, FC variability was reflected by brain tissue characteristics indicating cortical maturation. Brain regions with high functional variability (e.g., the inferior frontal gyrus and temporoparietal junction) displayed lower cortical maturation at birth compared with somatosensory cortices. In conclusion, the overall pattern of interindividual variability in FC is already present preterm; however, some brain regions show increased variability toward adulthood, identifying characteristic patterns, such as in cognitive networks. These changes are related to postnatal cortical expansion and maturation, allowing for environmental and developmental factors to translate into marked individual differences in FC.

Individualised MRI training for paediatric neuroimaging: A child-focused approach

Magnetic Resonance Imaging (MRI) in paediatric cohorts is often complicated by reluctance to enter the scanner and head motion-related imaging artefacts. The process is particularly challenging for children with neurodevelopmental disorders where coping with novel task demands in an unfamiliar setting may be more difficult due to symptom-related deficits or distress. These issues often give rise to excessive head motion that can significantly reduce the quality of images acquired, or render data unusable. Here we report an individualised MRI training procedure that enables children with Autism Spectrum Disorders (ASD) to better tolerate the MRI scanner environment based on a child-focused approach and individualised familiarisation strategies, including a pre-visit interview, familiarisation package, and personalised rewards. A medical imaging mobile application was utilised to familiarise participants to multi-sensory aspects of the neuroimaging experience through a variety of themed mini-games and activities. The MRI training procedure was implemented for monozygotic twins (n = 12; 6 twin pairs; age range 7.1–12.9 years) concordant or discordant for ASD. MRI image quality indices were better or comparable to images acquired from a large independent multi-centre ASD cohort. Present findings are promising and suggest that child-focused strategies could improve the quality of paediatric neuroimaging in clinical populations.

Functional Connectome of the Fetal Brain

Large-scale functional connectome formation and reorganization is apparent in the second trimester of pregnancy, making it a crucial and vulnerable time window in connectome development. Here we identified which architectural principles of functional connectome organization are initiated before birth, and contrast those with topological characteristics observed in the mature adult brain. A sample of 105 pregnant women participated in human fetal resting-state fMRI studies (fetal gestational age between 20 and 40 weeks). Connectome analysis was used to analyze weighted network characteristics of fetal macroscale brain wiring. We identified efficient network attributes, common functional modules, and high overlap between the fetal and adult brain network. Our results indicate that key features of the functional connectome are present in the second and third trimesters of pregnancy. Understanding the organizational principles of fetal connectome organization may bring opportunities to develop markers for early detection of alterations of brain function.SIGNIFICANCE STATEMENT The fetal to neonatal period is well known as a critical stage in brain development. Rapid neurodevelopmental processes establish key functional neural circuits of the human brain. Prenatal risk factors may interfere with early trajectories of connectome formation and thereby shape future health outcomes. Recent advances in MRI have made it possible to examine fetal brain functional connectivity. In this study, we evaluate the network topography of normative functional network development during connectome genesis in utero Understanding the developmental trajectory of brain connectivity provides a basis for understanding how the prenatal period shapes future brain function and disease dysfunction.

Identifying reproducible individual differences in childhood functional brain networks: An ABCD study

The 21-site Adolescent Brain Cognitive Development (ABCD) study provides an unparalleled opportunity to characterize functional brain development via resting-state functional connectivity (RSFC) and to quantify relationships between RSFC and behavior. This multi-site data set includes potentially confounding sources of variance, such as differences between data collection sites and/or scanner manufacturers, in addition to those inherent to RSFC (e.g., head motion). The ABCD project provides a framework for characterizing and reproducing RSFC and RSFC-behavior associations, while quantifying the extent to which sources of variability bias RSFC estimates. We quantified RSFC and functional network architecture in 2,188 9-10-year old children from the ABCD study, segregated into demographically-matched discovery (N = 1,166) and replication datasets (N = 1,022). We found RSFC and network architecture to be highly reproducible across children. We did not observe strong effects of site; however, scanner manufacturer effects were large, reproducible, and followed a "short-to-long" association with distance between regions. Accounting for potential confounding variables, we replicated that RSFC between several higher-order networks was related to general cognition. In sum, we provide a framework for how to characterize RSFC-behavior relationships in a rigorous and reproducible manner using the ABCD dataset and other large multi-site projects.

Disrupted Visual Cortex Neurophysiology Following Very Preterm Birth

BACKGROUND

Visual regions develop rapidly in utero and throughout early childhood, but very preterm (VPT) birth can disrupt the typical maturation of primary cortices, with VPT children exhibiting mild visual impairments in early life and throughout development. This is thought to be due to dysfunctional maturation of occipital cortices. A way to readily index brain function is to examine neural oscillations; these mechanisms play a central role in the modeling and pruning of connections, providing an intrinsic temporal structure that refines the precise alignment of spiking, processing information in the brain, and coordinating networks.

METHODS

Using magnetoencephalography, we examined regional oscillatory patterns and functional coupling in VPT and full-term children. Five minutes of eyes-open resting-state data were acquired from 27 VPT and 32 full-term children at 8 years of age.

RESULTS

As hypothesized, the VPT group, when compared with control children, had elevated theta-band power, while alpha amplitude envelope coupling, a marker of connectivity, was found to be decreased.

CONCLUSIONS

These results support the hypothesis of spectral slowing in VPT children and more broadly suggest that the developmental arc of visual neurophysiology is disrupted by VPT birth. We conclude that these deficits underlie difficulties in complex visual perceptual processing evident during childhood and beyond.

Distinctions among real and apparent respiratory motions in human fMRI data

Head motion estimates in functional magnetic resonance imaging (fMRI) scans appear qualitatively different with sub-second image sampling rates compared to the multi-second sampling rates common in the past. Whereas formerly the head appeared still for much of a scan with brief excursions from baseline, the head now appears to be in constant motion, and motion estimates often seem to divulge little information about what is happening in a scan. This constant motion has been attributed to respiratory oscillations that do not alias at faster sampling rates, and investigators are divided on the extent to which such motion is "real" motion or only "apparent" pseudomotion. Some investigators have abandoned the use of motion estimates entirely due to these considerations. Here we investigate the properties of motion in several fMRI datasets sampled at rates between 720 and 1160 ms, and describe 5 distinct kinds of respiratory motion: 1) constant real respiratory motion in the form of head nodding most evident in vertical position and pitch, which can be very large; 2) constant pseudomotion at the same respiratory rate as real motion, occurring only in the phase encode direction; 3) punctate real motions occurring at times of very deep breaths; 4) a low-frequency pseudomotion in only the phase encode direction at and after very deep breaths; 5) slow modulation of vertical and anterior-posterior head position by the respiratory envelope. We reformulate motion estimates in light of these considerations and obtain good concordance between motion estimates, physiologic records, image quality measures, and events evident in the fMRI signals. We demonstrate how variables describing respiration or body habitus separately scale with distinct kinds of head motion. We also note heritable aspects of respiration and motion.

Spectral slowing is associated with working memory performance in children born very preterm

Children born very preterm (VPT) often demonstrate selective difficulties in working memory (WM), which may underlie academic difficulties observed in this population. Despite this, few studies have investigated the functional networks underlying WM in young children born VPT, a period when cognitive deficits become apparent. Using magnetoencephalography, we examined the networks underlying the maintenance of visual information in 6-year-old VPT (n = 15) and full-term (FT; n = 20) children. Although task performance was similar, VPT children engaged different oscillatory mechanisms during WM maintenance. Within the FT group, we observed higher mean whole-brain connectivity in the alpha-band during the retention (i.e. maintenance) interval associated with correct compared to incorrect responses. VPT children showed reduced whole-brain alpha synchrony, and a different network organization with fewer connections. In the theta-band, VPT children demonstrated a slight increase in whole-brain connectivity during WM maintenance, and engaged similar network hubs as FT children in the alpha-band, including the left dorsolateral prefrontal cortex and superior temporal gyrus. These findings suggest that VPT children rely on the theta-band to support similar task performance. Altered oscillatory mechanisms may reflect a less mature pattern of functional recruitment underlying WM in VPT children, which may affect the processing in complex ecological situations.

Characteristics of respiratory measures in young adults scanned at rest, including systematic changes and "missed" deep breaths

Breathing rate and depth influence the concentration of carbon dioxide in the blood, altering cerebral blood flow and thus functional magnetic resonance imaging (fMRI) signals. Such respiratory fluctuations can have substantial influence in studies of fMRI signal covariance in subjects at rest, the so-called "resting state functional connectivity" technique. If respiration is monitored during fMRI scanning, it is typically done using a belt about the subject's abdomen to record abdominal circumference. Several measures have been derived from these belt records, including the windowed envelope of the waveform (ENV), the windowed variance in the waveform (respiration variation, RV), and a measure of the amplitude of each breath divided by the cycle time of the breath (respiration volume per time, RVT). Any attempt to gauge respiratory contributions to fMRI signals requires a respiratory measure, but little is known about how these measures compare to each other, or how they perform beyond the small studies in which they were initially proposed. Here, we examine the properties of these measures in hundreds of healthy young adults scanned for an hour each at rest, a subset of the Human Connectome Project chosen for having high-quality physiological records. We find: 1) ENV, RV, and RVT are all correlated, and ENV and RV are more highly correlated to each other than to RVT; 2) respiratory events like deep breaths exhibit characteristic heart rate elevations, fMRI signal changes, head motions, and image quality abnormalities time-locked to large deflections in the belt traces; 3) all measures can "miss" deep breaths; 4) RVT "misses" deep breaths more than ENV or RV; 5) all respiratory measures change systematically over the course of a 14.4-min scan. We discuss the implications of these findings for the literature and ways to move forward in modeling respiratory influences on fMRI scans.

Health Care Professionals' Perceptions about Sensory-Based Interventions in the NICU

OBJECTIVE

The main objective of this article is to define perceptions of health care professionals regarding current use of sensory-based interventions in the neonatal intensive care unit (NICU).

STUDY DESIGN

A multidisciplinary group of NICU health care professionals (n = 108) defined the types of sensory-based interventions used in their NICU, the postmenstrual age (PMA) sensory-based interventions are administered, conditions under which sensory-based interventions are used, and personnel who administer sensory-based interventions.

RESULTS

The most commonly reported tactile intervention was infant holding (88% of respondents), the most common auditory intervention was recorded music/singing (69% of respondents), the most common kinesthetic intervention was occupational and physical therapy (85% of respondents), and the most common vestibular intervention was infant swings (86% of respondents). Tactile interventions were initiated most often at 24 to 26 weeks PMA (74% of respondents), auditory interventions at 30 to 32 weeks (60% of respondents), kinesthetic interventions at 30 to 32 weeks (76% of respondents), vestibular interventions at 33 to 34 weeks (86% of respondents), and visual interventions at 32 to 36 weeks (72% of respondents). Conditions under which sensory-based interventions were administered, and personnel who provided them, varied across settings.

CONCLUSION

Varied use of sensory-based interventions in the NICU were reported. While this study was limited by biased sampling and the identification of health care professionals' perceptions but not real-world practice, this information can be used to build a comprehensive approach to positive sensory exposures in the NICU.

Altered Functional Brain Network Integration, Segregation, and Modularity in Infants Born Very Preterm at Term-Equivalent Age

OBJECTIVES

To determine the functional network organization of the brain in infants born very preterm at term-equivalent age and to relate network alterations to known clinical risk factors for poor neurologic outcomes in prematurity.

STUDY DESIGN

Resting-state functional magnetic resonance imaging data from 66 infants born very preterm (gestational age <32 weeks and birth weight <1500 g) and 66 healthy neonates born at full term, acquired as part of a prospective, cross-sectional study, were compared at term age using graph theory. Features of resting-state networks, including integration, segregation, and modularity, were derived from correlated hemodynamic activity arising from 93 cortical and subcortical regions of interest and compared between groups.

RESULTS

Despite preserved small-world topology and modular organization, resting-state networks of infants born very preterm at term-equivalent age were less segregated and less integrated than those of infants born full term. Chronic respiratory illness (ie, bronchopulmonary dysplasia and the length of oxygen support) was associated with decreased global efficiency and increased path lengths (P < .05). In both cohorts, 4 functional modules with similar composition were observed (parietal/temporal, frontal, subcortical/limbic, and occipital). The density of connections in 3 of the 4 modules was decreased in the very preterm network (P < .01); however, in the occipital/visual cortex module, connectivity was increased in infants born very preterm relative to control infants (P < .0001).

CONCLUSIONS

Early exposure to the ex utero environment is associated with altered resting-state network functional organization in infants born very preterm at term-equivalent age, likely reflecting disrupted brain maturational processes.

Social Adjustment in Adolescents Born Very Preterm: Evidence for a Cognitive Basis of Social Problems

OBJECTIVE

To increase the understanding of social adjustment and autism spectrum disorder symptoms in adolescents born very preterm by studying the role of emotion recognition and cognitive control processes in the relation between very preterm birth and social adjustment.

STUDY DESIGN

A Dutch cohort of 61 very preterm and 61 full-term adolescents aged 13 years participated. Social adjustment was rated by parents, teachers, and adolescents and autism spectrum disorder symptoms by parents. Emotion recognition was assessed with a computerized task including pictures of child faces expressing anger, fear, sadness, and happiness with varying intensity. Cognitive control was assessed using a visuospatial span, antisaccade, and sustained attention to response task. Performance measures derived from these tasks served as indicators of a latent cognitive control construct, which was tested using confirmatory factor analysis. Mediation analyses were conducted with emotion recognition and cognitive control as mediators of the relation between very preterm birth and social problems.

RESULTS

Very preterm adolescents showed more parent- and teacher-rated social problems and increased autism spectrum disorder symptomatology than controls. No difference in self-reported social problems was observed. Moreover, very preterm adolescents showed deficits in emotion recognition and cognitive control compared with full-term adolescents. The relation between very preterm birth and parent-rated social problems was significantly mediated by cognitive control but not by emotion recognition. Very preterm birth was associated with a 0.67-SD increase in parent-rated social problems through its negative effect on cognitive control.

CONCLUSIONS

The present findings provide strong evidence for a central role of impaired cognitive control in the social problems of adolescents born very preterm.

Developing, mature, and unique functions of the child's brain in reading and mathematics

Cognitive development research shows that children use basic "child-unique" strategies for reading and mathematics. This suggests that children's neural processes will differ qualitatively from those of adults during this developmental period. The goals of the current study were to 1) establish whether a within-subjects neural dissociation between reading and mathematics exists in early childhood as it does in adulthood, and 2) use a novel, developmental intersubject correlation method to test for "child-unique", developing, and adult-like patterns of neural activation within those networks. Across multiple tasks, children's reading and mathematics activity converged in prefrontal cortex, but dissociated in temporal and parietal cortices, showing similarities to the adult pattern of dissociation. "Child-unique" patterns of neural activity were observed in multiple regions, including the anterior temporal lobe and inferior frontal gyri, and showed "child-unique" profiles of functional connectivity to prefrontal cortex. This provides a new demonstration that "children are not just little adults" - the developing brain is not only quantitatively different from adults, it is also qualitatively different.

Maternal pomegranate juice intake and brain structure and function in infants with intrauterine growth restriction: A randomized controlled pilot study

Polyphenol-rich pomegranate juice has been shown to have benefit as a neuroprotectant in animal models of neonatal hypoxic-ischemia. No published studies have investigated maternal polyphenol administration as a potential neuroprotectant in at-risk newborns, such as those with intrauterine growth restriction (IUGR). This was a randomized, placebo-controlled, double-blind pilot study to investigate the impact of maternal pomegranate juice intake in pregnancies with IUGR, on newborn brain structure and function at term-equivalent age (TEA). Mothers with IUGR at 24-34 weeks' gestation were recruited from Barnes-Jewish Hospital obstetrical clinic. Consented mothers were randomized to treatment (8 oz. pomegranate juice) or placebo (8 oz. polyphenol-free juice) and continued to take juice daily from enrollment until delivery (mean 20.1 and 27.1 days, respectively). Infants underwent brain MRI at TEA (36-41 weeks' gestation). Brain measures were compared between groups including: brain injury score, brain metrics, brain volumes, diffusion tensor imaging and resting state functional connectivity. Statistical analyses were undertaken as modified intention-to-treat (including randomized participants who received their allocated intervention and whose infants received brain MRI) and per-protocol (including participants who strictly adhered to the protocol, based on metabolite status). Seventy-seven mothers were randomized to treatment (n = 40) or placebo (n = 37). Of these, 28 and 27 infants, respectively, underwent term-equivalent MRI. There were no group differences in brain injury, metrics or volumes. However, treatment subjects displayed reduced diffusivity within the anterior and posterior limbs of the internal capsule compared with placebo. Resting state functional connectivity demonstrated increased correlation and covariance within several networks in treatment subjects, with alterations most apparent in the visual network in per-protocol analyses. Direct effects on health were not found. In conclusion, maternal pomegranate juice intake in pregnancies with known IUGR was associated with altered white matter organization and functional connectivity in the infant brain, suggesting differences in brain structure and function following in utero pomegranate juice exposure, warranting continued investigation. Clinical trial registration. NCT00788866, registered November 11, 2008, initial participant enrollment August 21, 2012.

Neonatal functional brain maturation in the context of perioperative critical care and pain management: A case report

INTRODUCTION

Remarkable plasticity during the first year of life imparts heighted vulnerability of the developing infant brain. Application of resting-state functional magnetic resonance imaging (rs-fMRI) in infants may contribute to our understanding of neuroplastic changes associated with therapeutic interventions and/or brain insults. In addition to showing clinically relevant incidental brain MRI findings, the objective of our pilot study was to test feasibility of rs-fMRI methods at this early age in the context of pediatric perioperative critical care.

METHODS

We report the case of a former 33-week premature infant born with long-gap esophageal atresia that underwent complex perioperative critical care (Foker process) requiring prolonged post-operative sedation and whom presented with incidental subdural hematoma. Rs-fMRI data was acquired before (at 1-month corrected age) and after (at 2.25-months corrected age) complex perioperative care. We evaluated resting-state functional connectivity (RSFC) using graph theory to explore the complex structure of brain networks.

RESULTS

A transient increase in head circumference coincided temporally with lifting of sedation and initiation of sedation drugs weaning, and qualified for hydrocephalus (93%) but not macrocephaly (>95%). RSFC analysis identified networks spatially consistent with those previously described in the literature, with notable pre-post-treatment qualitative differences in correlated and anticorrelated spontaneous brain activity.

DISCUSSION

Current definitions of macrocephaly may require lower threshold criteria for monitoring of critically ill infants. Although we demonstrate that available rs-fMRI could be effectively applied in a critically ill infant in the setting of brain pathology, future group-level studies should investigate RSFC to evaluate maintenance of network homeostasis during development of both healthy and critically ill infants.

Resting-State fMRI Networks in Children with Tuberous Sclerosis Complex

BACKGROUND AND PURPOSE

There are no published studies examining resting state networks (RSNs) and their relationship with neurodevelopmental metrics in tuberous sclerosis complex (TSC). We aimed to identify major resting-state functional magnetic resonance imaging (rs-fMRI) networks in infants with TSC and correlate network analyses with neurodevelopmental assessments, autism diagnosis, and seizure history.

METHODS

Rs-fMRI data from 34 infants with TSC, sedated with propofol during the scan, were analyzed to identify auditory, motor, and visual RSNs. We examined the correlations between auditory, motor, and visual RSNs at approximately 11.5 months, neurodevelopmental outcome at approximately 18.5 months, and diagnosis of autism spectrum disorders at approximately 36 months of age.

RESULTS

RSNs were obtained in 76.5% (26/34) of infants. We observed significant negative correlations between auditory RSN and auditory comprehension test scores (p = .038; r = -.435), as well as significant positive correlations between motor RSN and gross motor skills test scores (p = .023; r = .564). Significant positive correlations between motor RSNs and gross motor skills (p = .012; r = .754) were observed in TSC infants without autism, but not in TSC infants with autism, which could suggest altered motor processing. There were no significant differences in RSNs according to seizure history.

CONCLUSIONS

Negative correlation between auditory RSN, as well as positive correlation between motor RSN and developmental outcome measures might reflect different brain mechanisms and, when identified, may be helpful in predicting later function. A larger study of TSC patients with a healthy control group is needed before auditory and motor RSNs could be considered as neurodevelopmental outcome biomarkers.

SyMRI detects delayed myelination in preterm neonates

OBJECTIVES

The software "SyMRI" generates different MR contrasts and characterizes tissue properties based on a single acquisition of a multi-dynamic multi-echo (MDME)-FLAIR sequence. The aim of this study was to assess the applicability of "SyMRI" in the assessment of myelination in preterm and term-born neonates. Furthermore, "SyMRI" was compared with conventional MRI.

METHODS

A total of 30 preterm and term-born neonates were examined at term-equivalent age using a standardized MRI protocol. MDME sequence (acquisition time, 5 min, 24 s)-based post-processing was performed using "SyMRI". Myelination was assessed by scoring seven brain regions on quantitative T1-/T2-maps, generated by "SyMRI" and on standard T1-/T2-weighted images, acquired separately. Analysis of covariance (ANCOVA) (covariate, gestational age (GA) at MRI (GAMRI)) was used for group comparison.

RESULTS

In 25/30 patients (83.3%) (18 preterm and seven term-born neonates), "SyMRI" acquisitions were successfully performed. "SyMRI"-based myelination scores were significantly lower in preterm compared with term-born neonates (ANCOVA: T1: F(1, 22) = 7.420, p = 0.012; T2: F(1, 22) = 5.658, p = 0.026). "SyMRI"-based myelination scores positively correlated with GAMRI (T1: r = 0.662, n = 25, p ≤ 0.001; T2: r = 0.676, n = 25, p ≤ 0.001). The myelination scores based on standard MRI did not correlate with the GAMRI. No significant differences between preterm and term-born neonates were detectable.

CONCLUSIONS

"SyMRI" is a highly promising MR technique for neonatal brain imaging. "SyMRI" is superior to conventional MR sequences in the visual detection of delayed myelination in preterm neonates.

KEY POINTS

• By providing multiple MR contrasts, "SyMRI" is a time-saving method in neonatal brain imaging. • Differences concerning the myelination in term-born and preterm infants are visually detectable on T1-/T2-weighted maps generated by "SyMRI". • "SyMRI" allows a faster and more sensitive assessment of myelination compared with standard MR sequences.

Prediction in infants and adults: A pupillometry study

Adults use both bottom-up sensory inputs and top-down signals to generate predictions about future sensory inputs. Infants have also been shown to make predictions with simple stimuli and recent work has suggested top-down processing is available early in infancy. However, it is unknown whether this indicates that top-down prediction is an ability that is continuous across the lifespan or whether an infant's ability to predict is different from an adult's, qualitatively or quantitatively. We employed pupillometry to provide a direct comparison of prediction abilities across these disparate age groups. Pupil dilation response (PDR) was measured in 6-month olds and adults as they completed an identical implicit learning task designed to help learn associations between sounds and pictures. We found significantly larger PDR for visual omission trials (i.e. trials that violated participants' predictions without the presentation of new stimuli to control for bottom-up signals) compared to visual present trials (i.e. trials that confirmed participants' predictions) in both age groups. Furthermore, a computational learning model that is closely linked to prediction error (Rescorla-Wagner model) demonstrated similar learning trajectories suggesting a continuity of predictive capacity and learning across the two age groups.

Functional and structural connectivity of the brain in very preterm babies: relationship with gestational age and body and brain growth

BACKGROUND

Structural and functional changes of the brain have been reported in premature babies.

OBJECTIVE

To evaluate the relationship of functional and structural connectivity with gestational age, body growth and brain maturation in very preterm babies.

MATERIALS AND METHODS

We studied 18 very preterm babies (gestational age: mean ± standard deviation, 29.7±1.7 weeks). We examined functional connectivity by multivariate pattern analysis of resting-state functional MRI data. We assessed structural connectivity by analysis of diffusion tensor imaging data and probabilistic tractography.

RESULTS

The average functional connectivity of the medial orbitofrontal cortex with the rest of the brain was positively associated with gestational age (P<0.001). Fractional anisotropy of the right inferior fronto-occipital fasciculus was positively associated with head circumference at term-equivalent age. Structural connectivity of the inferior fronto-occipital fasciculus with the medial orbitofrontal cortex was positively associated with head circumference at term-equivalent age. Body weight at term-equivalent age was the only independent predictor of average structural connectivity of the medial orbitofrontal cortex with the rest of the brain (P=0.020).

CONCLUSION

Structural and functional connectivity of the medial orbitofrontal cortex with the rest of the brain depend on body growth and degree of prematurity, respectively.

Functional Brain Parcellations of the Infant Brain and the Associated Developmental Trends

Resting-state functional connectivity studies have dramatically improved our understanding of the early human brain functional development during the past decade. However, one emerging problem that could potentially impede future progresses in the field is the definition of regions of interest (ROI), since it is well known that functional connectivity estimation can be seriously contaminated by within-ROI signal heterogeneity. In this study, based on a large-scale rsfMRI data set in human infants (230 neonates, 143 1-year olds, and 107 2-year olds), we aimed to derive a set of anatomically constrained, infant-specific functional brain parcellations using functional connectivity-based clustering. Our results revealed significantly higher levels of signal homogeneity within the newly defined functional parcellations compared with other schemes. Importantly, the global functional connectivity patterns associated with the newly defined functional subunits demonstrated significantly increasing levels of differentiation with age, confirming increasing levels of local specialization. Subsequent whole brain connectivity analysis revealed intriguing patterns of regional-level functional connectivity developments and system-level hub redistribution during infancy. Overall, the newly derived infant-specific functional brain parcellations and the associated novel developmental patterns will likely prove valuable for future early developmental studies using the functional connectivity technique.

Supporting and enhancing NICU sensory experiences (SENSE): Defining developmentally-appropriate sensory exposures for high-risk infants

INTRODUCTION

There is evidence to support the use of positive sensory exposures (music, touch, skin-to-skin) with preterm infants in the neonatal intensive care unit (NICU), but strategies to improve their consistent use are lacking. The Supporting and Enhancing NICU Sensory Experiences (SENSE) program was developed to promote consistent, age-appropriate, responsive, and evidence-based positive sensory exposures for the preterm infant every day of NICU hospitalization.

METHODS

A systematic and rigorous process of development of the SENSE program included an integrative review of evidence on sensory exposures in the NICU, stakeholder feedback, expert opinion, and focus groups.

RESULTS

SENSE implementation materials consist of parent education materials, tailored doses of sensory exposures for each postmenstrual age, an infant assessment of tolerance, bedside logs and implementation considerations for integrating the SENSE program into the NICU.

DISCUSSION

Research is needed to evaluate the SENSE program as an implementation strategy and to assess its impact on parent and infant outcomes.

Changes of functional response in sensorimotor cortex of preterm and full-term infants during the first year: An fNIRS study

BACKGROUND

Motor impairments are frequently associated with preterm birth and interfere in acquisition of essential skills to global development. Using Near Infrared Spectroscopy (NIRS), the study of neural correlates of motor development in early stages of life are feasible in an ecological assessment.

AIMS

To evaluate changes in cortical activity in response to a sensorimotor stimulation in preterm and full-term infants at 6 and 12 months of age.

STUDY DESIGN

A longitudinal study was conducted with 22 infants (12 preterm and 10 full-term). Hemodynamic activity during sensorimotor task (8 blocks of 8 s of vibration applied to infant's right hand) was measured by Functional Near Infrared Spectroscopy (fNIRS). The optical probe consisted of 84 channels positioned according to the international 10-20 system coordinates, covering the frontal (38 channels), parietal (16 channels), temporal (22 channels) and occipital (8 channels) lobes of both hemispheres.

RESULTS

Preterm and full-term infants exhibited differences of location of the activation as well on the hemodynamic response in both the evaluated age groups.

CONCLUSIONS

Group differences in activation of sensorimotor cortex observed in this study demonstrate the potential of fNIRS application for preterm evaluation of motor development in children. Overall, the present work contributes to our understanding of cortical activation of cerebral motor skills spanning early ages in preterm-born children.

Music in premature infants enhances high-level cognitive brain networks

Preterm babies are cared for in neonatal intensive care units (NICU), which are busy places with a lot of mechanical noise increasingly recognized to disrupt normal brain development. NICUs therefore invest in developmental care procedures, with music for example, but neurobiological evidence for these interventions is missing. We present results from a clinical trial to study the effects of a music intervention on preterm infants’ brain development. Based on resting-state fMRI, we provide evidence that music enhanced connectivity in a brain circuitry involving the salience network with regions implicated in sensory and higher-order cognitive functions, previously found to be altered in preterm infants. To our knowledge, this study is unique in observing an impact of music on brain development in preterm newborns.

Neonatal intensive care units are willing to apply environmental enrichment via music for preterm newborns. However, no evidence of an effect of music on preterm brain development has been reported to date. Using resting-state fMRI, we characterized a circuitry of interest consisting of three network modules interconnected by the salience network that displays reduced network coupling in preterm compared with full-term newborns. Interestingly, preterm infants exposed to music in the neonatal intensive care units have significantly increased coupling between brain networks previously shown to be decreased in premature infants: the salience network with the superior frontal, auditory, and sensorimotor networks, and the salience network with the thalamus and precuneus networks. Therefore, music exposure leads to functional brain architectures that are more similar to those of full-term newborns, providing evidence for a beneficial effect of music on the preterm brain.

Gut microbiome and brain functional connectivity in infants-a preliminary study focusing on the amygdala

Recently, there has been a surge of interest in the possibility that microbial communities inhabiting the human gut could affect cognitive development and increase risk for mental illness via the "microbiome-gut-brain axis." Infancy likely represents a critical period for the establishment of these relationships, as it is the most dynamic stage of postnatal brain development and a key period in the maturation of the microbiome. Indeed, recent reports indicate that characteristics of the infant gut microbiome are associated with both temperament and cognitive performance. The neural circuits underlying these relationships have not yet been delineated. To address this gap, resting-state fMRI scans were acquired from 39 1-year-old human infants who had provided fecal samples for identification and relative quantification of bacterial taxa. Measures of alpha diversity were generated and tested for associations with measures of functional connectivity. Primary analyses focused on the amygdala as manipulation of the gut microbiota in animal models alters the structure and neurochemistry of this brain region. Secondary analyses explored functional connectivity of nine canonical resting-state functional networks. Alpha diversity was significantly associated with functional connectivity between the amygdala and thalamus and between the anterior cingulate cortex and anterior insula. These regions play an important role in processing/responding to threat. Alpha diversity was also associated with functional connectivity between the supplementary motor area (SMA, representing the sensorimotor network) and the inferior parietal lobule (IPL). Importantly, SMA-IPL connectivity also related to cognitive outcomes at 2 years of age, suggesting a potential pathway linking gut microbiome diversity and cognitive outcomes during infancy. These results provide exciting new insights into the gut-brain axis during early human development and should stimulate further studies into whether microbiome-associated changes in brain circuitry influence later risk for psychopathology.

High-density diffuse optical tomography for imaging human brain function

This review describes the unique opportunities and challenges for noninvasive optical mapping of human brain function. Diffuse optical methods offer safe, portable, and radiation free alternatives to traditional technologies like positron emission tomography or functional magnetic resonance imaging (fMRI). Recent developments in high-density diffuse optical tomography (HD-DOT) have demonstrated capabilities for mapping human cortical brain function over an extended field of view with image quality approaching that of fMRI. In this review, we cover fundamental principles of the diffusion of near infrared light in biological tissue. We discuss the challenges involved in the HD-DOT system design and implementation that must be overcome to acquire the signal-to-noise necessary to measure and locate brain function at the depth of the cortex. We discuss strategies for validation of the sensitivity, specificity, and reliability of HD-DOT acquired maps of cortical brain function. We then provide a brief overview of some clinical applications of HD-DOT. Though diffuse optical measurements of neurophysiology have existed for several decades, tremendous opportunity remains to advance optical imaging of brain function to address a crucial niche in basic and clinical neuroscience: that of bedside and minimally constrained high fidelity imaging of brain function.

On Training Deep 3D CNN Models with Dependent Samples in Neuroimaging

There is much interest in developing algorithms based on 3D convolutional neural networks (CNNs) for performing regression and classification with brain imaging data and more generally, with biomedical imaging data. A standard assumption in learning is that the training samples are independently drawn from the underlying distribution. In computer vision, where we have millions of training examples, this assumption is violated but the empirical performance may remain satisfactory. But in many biomedical studies with just a few hundred training examples, one often has multiple samples per participant and/or data may be curated by pooling datasets from a few different institutions. Here, the violation of the independent samples assumption turns out to be more significant, especially in small-to-medium sized datasets. Motivated by this need, we show how 3D CNNs can be modified to deal with dependent samples. We show that even with standard 3D CNNs, there is value in augmenting the network to exploit information regarding dependent samples. We present empirical results for predicting cognitive trajectories (slope and intercept) from morphometric change images derived from multiple time points. With terms which encode dependency between samples in the model, we get consistent improvements over a strong baseline which ignores such knowledge.

Verbal Fluency Is Affected by Altered Brain Lateralization in Adults Who Were Born Very Preterm

Language difficulties have been reported in children and adolescents who were born very preterm (<32 weeks’ gestation) and associated with an atypical lateralization of language processing, i.e., increased right-hemispheric engagement. This study used functional magnetic resonance imaging (fMRI) and spherical deconvolution tractography to study the hemodynamic responses associated with verbal fluency processing (easy and hard letter trials) and verbal fluency-related white matter fiber tracts in 64 very preterm born adults and 36 adult controls (mean age: 30 years). Tractography of the arcuate fasciculus (AF) and frontal aslant tract (FAT) was performed. Tracts were quantified in terms of mean volume, hindrance modulated orientational anisotropy, and lateralization, assessed using a laterality index (LI) to indicate hemispheric dominance. During verbal fluency fMRI, very preterm participants displayed decreased hemodynamic response suppression in both the Easy > Rest and Hard > Rest conditions, compared to controls, in superior temporal gyrus (STG), insula, thalamus, and sensorimotor cortex, particularly in the right hemisphere. At the whole-group level, decreased hemodynamic response suppression in the right sensorimotor cortex was associated with worse on-line performance on the hard letter trials. Increased left-laterality in the AF was present alongside increased right hemispheric hemodynamic response suppression in controls. When only right-handed participants were considered, decreased hemodynamic response suppression in the right STG during hard letter trials was related to weaker left and right FAT white matter integrity in the preterm group only. These results show that verbal fluency is affected by altered functional lateralization in adults who were born very preterm.

A multidimensional artefact-reduction approach to increase robustness of first-level fMRI analyses: Censoring vs. interpolating

BACKGROUND

This manuscript describes a new, multidimensional and data-driven approach to identify outlying datapoints from a first-level fMRI dataset.

NEW METHOD

Using three different indicators of data corruption (the fast variance component of DVARS [Δ%D-var], scan-to-scan total displacement [STS], and each scan's overall explained variance [R²]), it identifies outlying datapoints while being balanced using Akaike'c corrected criterion (AIC _C) to avoid overcorrection. We then explore the impact of censoring, interpolating, or both, to remove a bad scan's contribution to the final timeseries.

RESULTS AND COMPARISON WITH EXISTING METHODS

Our results (using three real-life datasets and extensive simulations) show that motion-corrupted datapoints as well as non-motion related image artefacts are detected reliably. Using several indicators is shown to be an advantage over existing single-indicator solutions in different settings. As a result of using our algorithm, stronger activation (as detected by both T-value and number of activated voxels) and an increase in the temporal signal-to-noise ratio can be seen. The effects of censoring and interpolation are distinct and complex.

CONCLUSIONS

The multidimensional approach described here is able to identify outlying datapoints in fMRI timeseries, with demonstrable positive effects on several outcome measures. While censoring datapoints may be preferable in many settings, the ultimate choice on which approach to choose may depend on the data at hand. Recommendations are provided for different scenarios.

Infant Brain Development Prediction With Latent Partial Multi-View Representation Learning

The early postnatal period witnesses rapid and dynamic brain development. However, the relationship between brain anatomical structure and cognitive ability is still unknown. Currently, there is no explicit model to characterize this relationship in the literature. In this paper, we explore this relationship by investigating the mapping between morphological features of the cerebral cortex and cognitive scores. To this end, we introduce a multi-view multi-task learning approach to intuitively explore complementary information from different time-points and handle the missing data issue in longitudinal studies simultaneously. Accordingly, we establish a novel model, latent partial multi-view representation learning. Our approach regards data from different time-points as different views and constructs a latent representation to capture the complementary information from incomplete time-points. The latent representation explores the complementarity across different time-points and improves the accuracy of prediction. The minimization problem is solved by the alternating direction method of multipliers. Experimental results on both synthetic and real data validate the effectiveness of our proposed algorithm.