Longitudinal analysis of neural network development in preterm infants

Individual patterns of functional connectivity in neonates as revealed by surface-based Bayesian modeling

Resting-state functional connectivity is a widely used approach to study the functional brain network organization during early brain development. However, the estimation of functional connectivity networks in individual infants has been rather elusive due to the unique challenges involved with functional magnetic resonance imaging (fMRI) data from young populations. Here, we use fMRI data from the developing Human Connectome Project (dHCP) database to characterize individual variability in a large cohort of term-born infants (N = 289) using a novel data-driven Bayesian framework. To enhance alignment across individuals, the analysis was conducted exclusively on the cortical surface, employing surface-based registration guided by age-matched neonatal atlases. Using 10 minutes of resting-state fMRI data, we successfully estimated subject-level maps for fourteen brain networks/subnetworks along with individual functional parcellation maps that revealed differences between subjects. We also found a significant relationship between age and mean connectivity strength in all brain regions, including previously unreported findings in higher-order networks. These results illustrate the advantages of surface-based methods and Bayesian statistical approaches in uncovering individual variability within very young populations.

Spatiotemporal cerebral blood flow dynamics underlies emergence of the limbic-sensorimotor-association cortical gradient in human infancy

Infant cerebral blood flow (CBF) delivers nutrients and oxygen to fulfill brain energy consumption requirements for the fastest period of postnatal brain development across the lifespan. However, organizing principle of whole-brain CBF dynamics during infancy remains obscure. Leveraging a unique cohort of 100+ infants with high-resolution arterial spin labeled MRI, we found the emergence of the cortical hierarchy revealed by the highest-resolution infant CBF maps available to date. Infant CBF across cortical regions increased in a biphasic pattern with initial rapid and sequentially slower rate, with break-point ages increasing along the limbic-sensorimotor-association cortical gradient. Increases in CBF in sensorimotor cortices were associated with enhanced language and motor skills, and frontoparietal association cortices for cognitive skills. The study discovered emergence of the hierarchical limbic-sensorimotor-association cortical gradient in infancy, and offers standardized reference of infant brain CBF and insight into the physiological basis of cortical specialization and real-world infant developmental functioning.

Functional connectivity development in the prenatal and neonatal stages measured by functional magnetic resonance imaging: A systematic review

The prenatal and neonatal periods are two of the most important developmental stages of the human brain. It is therefore crucial to understand normal brain development and how early connections are established during these periods, in order to advance the state of knowledge on altered brain development and eventually identify early brain markers of neurodevelopmental disorders and diseases. In this systematic review (Prospero ID: CRD42024511365), we compiled resting state functional magnetic resonance imaging (fMRI) studies in healthy fetuses and neonates, in order to outline the main characteristics of typical development of the functional brain connectivity during the prenatal and neonatal periods. A systematic search of five databases identified a total of 12 573 articles. Of those, 28 articles met pre-established selection criteria based determined by the authors after surveying and compiling the major limitations reported within the literature. Inclusion criteria were: (1) resting state studies; (2) presentation of original results; (3) use of fMRI with minimum one Tesla; (4) a population ranging from 20 weeks of GA to term birth (around 37-42 weeks of PMA); (5) singleton pregnancy with normal development (absence of any complications known to alter brain development). Exclusion criteria were: (1) preterm studies; (2) post-mortem studies; (3) clinical or pathological studies; (4) twin studies; (5) papers with a sole focus on methodology (i.e. focused on tool and analysis development); (6) volumetric studies; (7) activation map studies; (8) cortical analysis studies; (9) conference papers. A risk of bias assessment was also done to evaluate each article's methodological rigor. 1877 participants were included across all the reviewed articles. Results consistently revealed a developmental gradient of increasing functional brain connectivity from posterior to anterior regions and from proximal-to-distal regions. A decrease in local small-world organization shortly after birth was also observed; small-world characteristics were present in fetuses and newborns, but appeared weaker in the latter group. Also, the posterior-to-anterior gradient could be associated with earlier development of the sensorimotor networks in the posterior regions while more complex higher-order networks (e.g. attention-related) mature later in the anterior regions. The main limitations of this systematic review stem from the inherent limitations of functional imaging in fetuses, mainly: unevenly distributed populations and limited sample sizes; fetal movements in the womb and other imaging obstacles; and a large voxel resolution when imaging a small brain. Another limitation specific to this review is the relatively small number of included articles compared to very a large search result, which may have led to relevant articles having been overlooked.

A subset of brain regions within adult functional connectivity networks demonstrate high reliability across early development

The human cerebral cortex contains groups of areas that support sensory, motor, cognitive, and affective functions, often categorized as functional networks. These areas show stronger internal and weaker external functional connectivity (FC) and exhibit similar FC profiles within rather than between networks. Previous studies have demonstrated the development of these networks from nascent forms present before birth to their mature, adult-like topography in childhood. However, analyses often still use definitions based on adult functional networks. We aim to assess how this might lead to the misidentification of functional networks and explore potential consequences and solutions. Our findings suggest that even though adult networks provide only a marginally better than-chance description of the infant FC organization, misidentification was largely driven by specific areas. By restricting functional networks to areas showing adult-like network clustering, we observed consistent within-network FC both within and across scans and throughout development. Additionally, these areas were spatially closer to locations with low variability in network identity among adults. Our analysis aids in understanding the potential consequences of using adult networks "as is" and provides guidance for future research on selecting and utilizing functional network models based on the research question and scenario.

Assessing Postural Control From Birth to Adulthood Among Individuals Born Preterm: A Systematic Review

Premature life exposure, meaning an immature central nervous system, presents a significant challenge for the development of postural control and, in turn, overall motor development. Preventing motor delay thus requires identifying, characterizing, and quantifying deficit in postural control as early as possible. In our study, we reviewed the procedures used in past studies to assess postural control among individuals born preterm, specifically the characterization of participants, the instruments and motor tasks involved, the types of data collected and analyzed, and the outcomes. To that end, we performed a literature search on PubMed, Wiley Online Library, Web of Science, and Scopus using Boolean logic and assessed the quality of the studies with a standardized assessment based on the Strengthening the Reporting of Observational Studies in Epidemiology guidelines and the Cochrane Handbook for Systematic Reviews of Interventions. Of 35 potential studies, 24 were included; all evaluated infants born preterm, but six did not include a control group of full-term infants. Although the heterogeneity of measurements, variability of instruments, and divergence in motor tasks examined limit definitive conclusions based on quantitative synthesis and the generalization of the results, most studies revealed dysfunctional postural control among individuals born preterm.

Perceptual Awareness in Human Infants: What is the Evidence?

Perceptual awareness in infants during the first year of life is understudied, despite the philosophical, scientific, and clinical importance of understanding how and when consciousness emerges during human brain development. Although parents are undoubtedly convinced that their infant is conscious, the lack of adequate experimental paradigms to address this question in preverbal infants has been a hindrance to research on this topic. However, recent behavioral and brain imaging studies have shown that infants are engaged in complex learning from an early age and that their brains are more structured than traditionally thought. I will present a rapid overview of these results, which might provide indirect evidence of early perceptual awareness and then describe how a more systematic approach to this question could stand within the framework of global workspace theory, which identifies specific signatures of conscious perception in adults. Relying on these brain signatures as a benchmark for conscious perception, we can deduce that it exists in the second half of the first year, whereas the evidence before the age of 5 months is less solid, mainly because of the paucity of studies. The question of conscious perception before term remains open, with the possibility of short periods of conscious perception, which would facilitate early learning. Advances in brain imaging and growing interest in this subject should enable us to gain a better understanding of this important issue in the years to come.

Neuronal Coupling Modes Show Differential Development in the Early Cortical Activity Networks of Human Newborns

The third trimester is a critical period for the development of functional networks that support the lifelong neurocognitive performance, yet the emergence of neuronal coupling in these networks is poorly understood. Here, we used longitudinal high-density electroencephalographic recordings from preterm infants during the period from 33 to 45 weeks of conceptional age (CA) to characterize early spatiotemporal patterns in the development of local cortical function and the intrinsic coupling modes [ICMs; phase-phase (PPCs), amplitude-amplitude (AACs), and phase-amplitude correlations (PACs)]. Absolute local power showed a robust increase with CA across the full frequency spectrum, while local PACs showed sleep state-specific, biphasic development that peaked a few weeks before normal birth. AACs and distant PACs decreased globally at nearly all frequencies. In contrast, the PPCs showed frequency- and region-selective development, with an increase of coupling strength with CA between frontal, central, and occipital regions at low-delta and alpha frequencies together with a wider-spread decrease at other frequencies. Our findings together present the spectrally and spatially differential development of the distinct ICMs during the neonatal period and provide their developmental templates for future basic and clinical research.

Inhibition abilities and functional brain connectivity in school-aged term-born and preterm-born children

BACKGROUND

Inhibition abilities are known to have impact on self-regulation, behavior, and academic success, and they are frequently impaired in children born preterm. We investigated the possible contributions of resting-state functional brain connectivity to inhibition following preterm birth.

METHODS

Forty-four preterm and 59 term-born participants aged 8-13 years were administered two inhibition tasks and resting-state functional MRI was performed. Functional connectivity (FC) networks were compared between groups using network-based statistics. Associations of FCNs and inhibition abilities were investigated through multivariate linear regression models accounting for the interaction between birth status and inhibition.

RESULTS

NBS revealed weaker FC in children born preterm compared to term-born peers in connections between motor and supplementary motor regions, frontal lobe, precuneus, and insula. Irrespective of birth status, connections between the cerebellum, frontal, and occipital lobes and inter-lobar, subcortical, intra-hemispheric long-range connections were positively correlated with one of the two inhibition tasks.

CONCLUSIONS

Preterm birth results in long-term alterations of FC at network level but these FCN alterations do not specifically account for inhibition problems in children born very preterm.

IMPACT

Irrespective of birth status, significant associations were found between the subdomain of response inhibition and functional connectivity in some subnetworks. A group comparisons of functional brain connectivity measured by rsfMRI in school-aged children born very preterm and at term. The investigation of network-level functional connectivity at rest does not appear adequate to explain differences in inhibition abilities between children born very preterm and at term, hence other imaging techniques might be more suited to explore the underlying neural mechanisms of inhibition abilities in school-aged children born very preterm.

Characterizing Large-Scale Human Circuit Development with In Vivo Neuroimaging

Large-scale coordinated patterns of neural activity are crucial for the integration of information in the human brain and to enable complex and flexible human behavior across the life span. Through recent advances in noninvasive functional magnetic resonance imaging (fMRI) methods, it is now possible to study this activity and how it emerges in the living fetal brain across the second half of human gestation. This work has demonstrated that functional activity in the fetal brain has several features in keeping with highly organized networks of activity, which are undergoing a highly programmed and rapid sequence of development before birth, in which long-range connections emerge and core features of the mature functional connectome (such as hub regions and a gradient organization) are established. In this review, the findings of these studies are summarized, their relationship to the known changes in developmental neurobiology is considered, and considerations for future work in the context of limitations to the fMRI approach are presented.

Regional homogeneity as a marker of sensory cortex dysmaturity in preterm infants

Atypical perinatal sensory experience in preterm infants is thought to increase their risk of neurodevelopmental disabilities by altering the development of the sensory cortices. Here, we used resting-state fMRI data from preterm and term-born infants scanned between 32 and 48 weeks post-menstrual age to assess the effect of early ex-utero exposure on sensory cortex development. Specifically, we utilized a measure of local correlated-ness called regional homogeneity (ReHo). First, we demonstrated that the brain-wide distribution of ReHo mirrors the known gradient of cortical maturation. Next, we showed that preterm birth differentially reduces ReHo across the primary sensory cortices. Finally, exploratory analyses showed that the reduction of ReHo in the primary auditory cortex of preterm infants is related to increased risk of autism at 18 months. In sum, we show that local connectivity within sensory cortices has different developmental trajectories, is differentially affected by preterm birth, and may be associated with later neurodevelopment.

Development of neonatal connectome dynamics and its prediction for cognitive and language outcomes at age 2

The functional brain connectome is highly dynamic over time. However, how brain connectome dynamics evolves during the third trimester of pregnancy and is associated with later cognitive growth remains unknown. Here, we use resting-state functional Magnetic Resonance Imaging (MRI) data from 39 newborns aged 32 to 42 postmenstrual weeks to investigate the maturation process of connectome dynamics and its role in predicting neurocognitive outcomes at 2 years of age. Neonatal brain dynamics is assessed using a multilayer network model. Network dynamics decreases globally but increases in both modularity and diversity with development. Regionally, module switching decreases with development primarily in the lateral precentral gyrus, medial temporal lobe, and subcortical areas, with a higher growth rate in primary regions than in association regions. Support vector regression reveals that neonatal connectome dynamics is predictive of individual cognitive and language abilities at 2  years of age. Our findings highlight network-level neural substrates underlying early cognitive development.

Diffusion-tensor-imaging 1-year-old and 2-year-old infant brain atlases with comprehensive gray and white matter labels

Human infancy is marked by fastest postnatal brain structural changes. It also coincides with the onset of many neurodevelopmental disorders. Atlas-based automated structure labeling has been widely used for analyzing various neuroimaging data. However, the relatively large and nonlinear neuroanatomical differences between infant and adult brains can lead to significant offsets of the labeled structures in infant brains when adult brain atlas is used. Age-specific 1- and 2-year-old brain atlases covering all major gray and white matter (GM and WM) structures with diffusion tensor imaging (DTI) and structural MRI are critical for precision medicine for infant population yet have not been established. In this study, high-quality DTI and structural MRI data were obtained from 50 healthy children to build up three-dimensional age-specific 1- and 2-year-old brain templates and atlases. Age-specific templates include a single-subject template as well as two population-averaged templates from linear and nonlinear transformation, respectively. Each age-specific atlas consists of 124 comprehensively labeled major GM and WM structures, including 52 cerebral cortical, 10 deep GM, 40 WM, and 22 brainstem and cerebellar structures. When combined with appropriate registration methods, the established atlases can be used for highly accurate automatic labeling of any given infant brain MRI. We demonstrated that one can automatically and effectively delineate deep WM microstructural development from 3 to 38 months by using these age-specific atlases. These established 1- and 2-year-old infant brain DTI atlases can advance our understanding of typical brain development and serve as clinical anatomical references for brain disorders during infancy.

Spatiotemporal cerebral blood flow dynamics underlies emergence of the limbic-sensorimotor-association cortical gradient in human infancy

Infant cerebral blood flow (CBF) delivers nutrients and oxygen to fulfill brain energy consumption requirements for the fastest period of postnatal brain development across lifespan. However, organizing principle of whole-brain CBF dynamics during infancy remains obscure. Leveraging a unique cohort of 100+ infants with high-resolution arterial spin labeled MRI, we found the emergence of the cortical hierarchy revealed by highest-resolution infant CBF maps available to date. Infant CBF across cortical regions increased in a biphasic pattern with initial rapid and sequentially slower rate, with break-point ages increasing along the limbic-sensorimotor-association cortical gradient. Increases in CBF in sensorimotor cortices were associated with enhanced language and motor skills, and frontoparietal association cortices for cognitive skills. The study discovered emergence of the hierarchical limbic-sensorimotor-association cortical gradient in infancy, and offers standardized reference of infant brain CBF and insight into the physiological basis of cortical specialization and real-world infant developmental functioning.

Neonatal brain dynamic functional connectivity in term and preterm infants and its association with early childhood neurodevelopment

Brain dynamic functional connectivity characterises transient connections between brain regions. Features of brain dynamics have been linked to emotion and cognition in adult individuals, and atypical patterns have been associated with neurodevelopmental conditions such as autism. Although reliable functional brain networks have been consistently identified in neonates, little is known about the early development of dynamic functional connectivity. In this study we characterise dynamic functional connectivity with functional magnetic resonance imaging (fMRI) in the first few weeks of postnatal life in term-born (n = 324) and preterm-born (n = 66) individuals. We show that a dynamic landscape of brain connectivity is already established by the time of birth in the human brain, characterised by six transient states of neonatal functional connectivity with changing dynamics through the neonatal period. The pattern of dynamic connectivity is atypical in preterm-born infants, and associated with atypical social, sensory, and repetitive behaviours measured by the Quantitative Checklist for Autism in Toddlers (Q-CHAT) scores at 18 months of age.

Altered resting-state functional connectivity in newborns with hypoxic ischemic encephalopathy assessed using high-density functional near-infrared spectroscopy

Hypoxic-ischemic encephalopathy (HIE) results from a lack of oxygen to the brain during the perinatal period. HIE can lead to mortality and various acute and long-term morbidities. Improved bedside monitoring methods are needed to identify biomarkers of brain health. Functional near-infrared spectroscopy (fNIRS) can assess resting-state functional connectivity (RSFC) at the bedside. We acquired resting-state fNIRS data from 21 neonates with HIE (postmenstrual age [PMA] = 39.96), in 19 neonates the scans were acquired post-therapeutic hypothermia (TH), and from 20 term-born healthy newborns (PMA = 39.93). Twelve HIE neonates also underwent resting-state functional magnetic resonance imaging (fMRI) post-TH. RSFC was calculated as correlation coefficients amongst the time courses for fNIRS and fMRI data, respectively. The fNIRS and fMRI RSFC maps were comparable. RSFC patterns were then measured with graph theory metrics and compared between HIE infants and healthy controls. HIE newborns showed significantly increased clustering coefficients, network efficiency and modularity compared to controls. Using a support vector machine algorithm, RSFC features demonstrated good performance in classifying the HIE and healthy newborns in separate groups. Our results indicate the utility of fNIRS-connectivity patterns as potential biomarkers for HIE and fNIRS as a new bedside tool for newborns with HIE.

Optimal approaches to analyzing functional MRI data in glioma patients

BACKGROUND

Resting-state fMRI is increasingly used to study the effects of gliomas on the functional organization of the brain. A variety of preprocessing techniques and functional connectivity analyses are represented in the literature. However, there so far has been no systematic comparison of how alternative methods impact observed results.

NEW METHOD

We first surveyed current literature and identified alternative analytical approaches commonly used in the field. Following, we systematically compared alternative approaches to atlas registration, parcellation scheme, and choice of graph-theoretical measure as regards differentiating glioma patients (N = 59) from age-matched reference subjects (N = 163).

RESULTS

Our results suggest that non-linear, as opposed to affine registration, improves structural match to an atlas, as well as measures of functional connectivity. Functionally- as opposed to anatomically-derived parcellation schemes maximized the contrast between glioma patients and reference subjects. We also demonstrate that graph-theoretic measures strongly depend on parcellation granularity, parcellation scheme, and graph density.

COMPARISON WITH EXISTING METHODS AND CONCLUSIONS

Our current work primarily focuses on technical optimization of rs-fMRI analysis in glioma patients and, therefore, is fundamentally different from the bulk of papers discussing glioma-induced functional network changes. We report that the evaluation of glioma-induced alterations in the functional connectome strongly depends on analytical approaches including atlas registration, choice of parcellation scheme, and graph-theoretical measures.

Functional parcellation of the neonatal cortical surface

The cerebral cortex is organized into distinct but interconnected cortical areas, which can be defined by abrupt differences in patterns of resting state functional connectivity (FC) across the cortical surface. Such parcellations of the cortex have been derived in adults and older infants, but there is no widely used surface parcellation available for the neonatal brain. Here, we first demonstrate that existing parcellations, including surface-based parcels derived from older samples as well as volume-based neonatal parcels, are a poor fit for neonatal surface data. We next derive a set of 283 cortical surface parcels from a sample of n = 261 neonates. These parcels have highly homogenous FC patterns and are validated using three external neonatal datasets. The Infomap algorithm is used to assign functional network identities to each parcel, and derived networks are consistent with prior work in neonates. The proposed parcellation may represent neonatal cortical areas and provides a powerful tool for neonatal neuroimaging studies.

Growth in early infancy drives optimal brain functional connectivity which predicts cognitive flexibility in later childhood

Functional brain network organization, measured by functional connectivity (FC), reflects key neurodevelopmental processes for healthy development. Early exposure to adversity, e.g. undernutrition, affects neurodevelopment, observable via disrupted FC, and leads to poorer outcomes from preschool age onward. We assessed longitudinally the impact of early growth trajectories on developmental FC in a rural Gambian population from age 5 to 24 months. To investigate how these early trajectories relate to later childhood outcomes, we assessed cognitive flexibility at 3-5 years. We observed that early physical growth before the fifth month of life drove optimal developmental trajectories of FC that in turn predicted cognitive flexibility at pre-school age. In contrast to previously studied developmental populations, this Gambian sample exhibited long-range interhemispheric FC that decreased with age. Our results highlight the measurable effects that poor growth in early infancy has on brain development and the subsequent impact on pre-school age cognitive development, underscoring the need for early life interventions throughout global settings of adversity.

Arachidonic and docosahexaenoic acid supplementation and brain maturation in preterm infants; a double blind RCT

BACKGROUND

Arachidonic acid (ARA) and docosahexaenoic acid (DHA) are important structural components of neural cellular membranes and possess anti-inflammatory properties. Very preterm infants are deprived of the enhanced placental supply of these fatty acids, but the benefit of postnatal supplementation on brain development is uncertain. The aim of this study was to test the hypothesis that early enteral supplementation with ARA and DHA in preterm infants improves white matter (WM) microstructure assessed by diffusion-weighted MRI at term equivalent age.

METHODS

In this double-blind, randomized controlled trial, infants born before 29 weeks gestational age were allocated to either 100 mg/kg ARA and 50 mg/kg DHA (ARA:DHA group) or medium chain triglycerides (control). Supplements were started on the second day of life and provided until 36 weeks postmenstrual age. The primary outcome was brain maturation assessed by diffusion tensor imaging (DTI) using Tract-Based Spatial Statistics (TBSS) analysis.

RESULTS

We included 120 infants (60 per group) in the trial; mean (range) gestational age was 26+3 (22+6 - 28+6) weeks and postmenstrual age at scan was 41+3 (39+1 - 47+0) weeks. Ninety-two infants underwent MRI imaging, and of these, 90 had successful T1/T2 weighted MR images and 74 had DTI data of acceptable quality. TBSS did not show significant differences in mean or axial diffusivity between the groups, but demonstrated significantly higher fractional anisotropy in several large WM tracts in the ARA:DHA group, including corpus callosum, the anterior and posterior limb of the internal capsula, inferior occipitofrontal fasciculus, uncinate fasciculus, and the inferior longitudinal fasciculus. Radial diffusivity was also significantly lower in several of the same WM tracts in the ARA:DHA group.

CONCLUSION

This study suggests that supplementation with ARA and DHA at doses matching estimated fetal accretion rates improves WM maturation compared to control treatment, but further studies are needed to ascertain any functional benefit.

CLINICAL TRIAL REGISTRATION

www.

CLINICALTRIALS

gov; ID:NCT03555019.

Resting-State Functional MRI and PET Imaging as Noninvasive Tools to Study (Ab)Normal Neurodevelopment in Humans and Rodents

Neurodevelopmental disorders (NDDs) are a group of complex neurologic and psychiatric disorders. Functional and molecular imaging techniques, such as resting-state functional magnetic resonance imaging (rs-fMRI) and positron emission tomography (PET), can be used to measure network activity noninvasively and longitudinally during maturation in both humans and rodent models. Here, we review the current knowledge on rs-fMRI and PET biomarkers in the study of normal and abnormal neurodevelopment, including intellectual disability (ID; with/without epilepsy), autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD), in humans and rodent models from birth until adulthood, and evaluate the cross-species translational value of the imaging biomarkers. To date, only a few isolated studies have used rs-fMRI or PET to study (abnormal) neurodevelopment in rodents during infancy, the critical period of neurodevelopment. Further work to explore the feasibility of performing functional imaging studies in infant rodent models is essential, as rs-fMRI and PET imaging in transgenic rodent models of NDDs are powerful techniques for studying disease pathogenesis, developing noninvasive preclinical imaging biomarkers of neurodevelopmental dysfunction, and evaluating treatment-response in disease-specific models.

Functional parcellation of the neonatal brain

The cerebral cortex is organized into distinct but interconnected cortical areas, which can be defined by abrupt differences in patterns of resting state functional connectivity (FC) across the cortical surface. Such parcellations of the cortex have been derived in adults and older infants, but there is no widely used surface parcellation available for the neonatal brain. Here, we first demonstrate that adult- and older infant-derived parcels are a poor fit with neonatal data, emphasizing the need for neonatal-specific parcels. We next derive a set of 283 cortical surface parcels from a sample of n=261 neonates. These parcels have highly homogenous FC patterns and are validated using three external neonatal datasets. The Infomap algorithm is used to assign functional network identities to each parcel, and derived networks are consistent with prior work in neonates. The proposed parcellation may represent neonatal cortical areas and provides a powerful tool for neonatal neuroimaging studies.

Denoising task-correlated head motion from motor-task fMRI data with multi-echo ICA

Motor-task functional magnetic resonance imaging (fMRI) is crucial in the study of several clinical conditions, including stroke and Parkinson's disease. However, motor-task fMRI is complicated by task-correlated head motion, which can be magnified in clinical populations and confounds motor activation results. One method that may mitigate this issue is multi-echo independent component analysis (ME-ICA), which has been shown to separate the effects of head motion from the desired BOLD signal but has not been tested in motor-task datasets with high amounts of motion. In this study, we collected an fMRI dataset from a healthy population who performed a hand grasp task with and without task-correlated amplified head motion to simulate a motor-impaired population. We analyzed these data using three models: single-echo (SE), multi-echo optimally combined (ME-OC), and ME-ICA. We compared the models' performance in mitigating the effects of head motion on the subject level and group level. On the subject level, ME-ICA better dissociated the effects of head motion from the BOLD signal and reduced noise. Both ME models led to increased t-statistics in brain motor regions. In scans with high levels of motion, ME-ICA additionally mitigated artifacts and increased stability of beta coefficient estimates, compared to SE. On the group level, all three models produced activation clusters in expected motor areas in scans with both low and high motion, indicating that group-level averaging may also sufficiently resolve motion artifacts that vary by subject. These findings demonstrate that ME-ICA is a useful tool for subject-level analysis of motor-task data with high levels of task-correlated head motion. The improvements afforded by ME-ICA are critical to improve reliability of subject-level activation maps for clinical populations in which group-level analysis may not be feasible or appropriate, for example in a chronic stroke cohort with varying stroke location and degree of tissue damage.

Language Exposure for Preterm Infants is Reduced Relative to Fetuses

OBJECTIVE

To assess changes and deficits in language and auditory exposures consequent to preterm birth and neonatal intensive care unit stay compared with exposures in utero among typically developing fetuses.

STUDY DESIGN

We analyzed over 23 000 hours of auditory exposure data in a cohort study of 27 typically-developing fetuses and 24 preterm infants. Extrauterine exposures for fetuses were captured by having pregnant women wear 24-hour audio recording devices. For preterm infants, recording devices were placed in the infant's crib. Multilevel linear regressions were conducted to test for group differences and effects of infant sex, maternal education, and mother' occupation. A linear mixed-effects model was used to test for an effect of speaker gender.

RESULTS

Fetuses were exposed to an estimated 2.6 ± 1.8 hours/day of nearby, predominantly female language, nearly 5 times greater than 32 ± 12 minutes/day estimated for preterm infants (P < .001). Preterm infants had greater daily exposure to electronic sounds (5.1 ± 2.5 vs 1.3 ± 0.6 hours; P < .001) and noise (4.4 ± 2.1 vs 2.9 ± 2.8 hours; P < .05), with 4.7 ± 3.9 hours/day of silence. Language and extrauterine sound exposure for fetuses showed a marked day/night cyclical pattern, with low exposure during nighttime hours, but preterm infants' exposures showed significantly less change across the 24-hour cycle (P < .001). Maternal occupation requiring frequent communication predicted greater language exposure (P < .05).

CONCLUSIONS

Our findings provide the first comparison of preterm infant auditory exposures to typically-developing fetuses. Some preterm infants may incur deficits of over 150 hours of language exposure over the preterm period. Given known effects of prenatal/preterm language exposure on neurobehavioral outcomes, this magnitude of deficit is alarming.

Indirect evidence for altered dopaminergic neurotransmission in very premature-born adults

While animal models indicate altered brain dopaminergic neurotransmission after premature birth, corresponding evidence in humans is scarce due to missing molecular imaging studies. To overcome this limitation, we studied dopaminergic neurotransmission changes in human prematurity indirectly by evaluating the spatial co-localization of regional alterations in blood oxygenation fluctuations with the distribution of adult dopaminergic neurotransmission. The study cohort comprised 99 very premature-born (<32 weeks of gestation and/or birth weight below 1500 g) and 107 full-term born young adults, being assessed by resting-state functional MRI (rs-fMRI) and IQ testing. Normative molecular imaging dopamine neurotransmission maps were derived from independent healthy control groups. We computed the co-localization of local (rs-fMRI) activity alterations in premature-born adults with respect to term-born individuals to different measures of dopaminergic neurotransmission. We performed selectivity analyses regarding other neuromodulatory systems and MRI measures. In addition, we tested if the strength of the co-localization is related to perinatal measures and IQ. We found selectively altered co-localization of rs-fMRI activity in the premature-born cohort with dopamine-2/3-receptor availability in premature-born adults. Alterations were specific for the dopaminergic system but not for the used MRI measure. The strength of the co-localization was negatively correlated with IQ. In line with animal studies, our findings support the notion of altered dopaminergic neurotransmission in prematurity which is associated with cognitive performance.

Fetal Frontolimbic Connectivity Prospectively Associates With Aggression in Toddlers

Background

Aggression is a major public health concern that emerges early in development and lacks optimized treatment, highlighting need for improved mechanistic understanding regarding the etiology of aggression. The present study leveraged fetal resting-state functional magnetic resonance imaging to identify candidate neurocircuitry for the onset of aggressive behaviors before symptom emergence.

Methods

Pregnant mothers were recruited during the third trimester of pregnancy to complete a fetal resting-state functional magnetic resonance imaging scan. Mothers subsequently completed the Child Behavior Checklist to assess child aggression at 3 years postpartum (n = 79). Independent component analysis was used to define frontal and limbic regions of interest.

Results

Child aggression was not related to within-network connectivity of subcortical limbic regions or within-medial prefrontal network connectivity in fetuses. However, weaker functional coupling between the subcortical limbic network and medial prefrontal network in fetuses was prospectively associated with greater maternal-rated child aggression at 3 years of age even after controlling for maternal emotion dysregulation and toddler language ability. We observed similar, but weaker, associations between fetal frontolimbic functional connectivity and toddler internalizing symptoms.

Conclusions

Neural correlates of aggressive behavior may be detectable in utero, well before the onset of aggression symptoms. These preliminary results highlight frontolimbic connections as potential candidate neurocircuitry that should be further investigated in relation to the unfolding of child behavior and psychiatric risk.

Longitudinal developmental trajectories of functional connectivity reveal regional distribution of distinct age effects in infancy

Prior work has shown that different functional brain networks exhibit different maturation rates, but little is known about whether and how different brain areas may differ in the exact shape of longitudinal functional connectivity growth trajectories during infancy. We used resting-state functional magnetic resonance imaging (fMRI) during natural sleep to characterize developmental trajectories of different regions using a longitudinal cohort of infants at 3 weeks (neonate), 1 year, and 2 years of age (n = 90; all with usable data at three time points). A novel whole brain heatmap analysis was performed with four mixed-effect models to determine the best fit of age-related changes for each functional connection: (i) growth effects: positive-linear-age, (ii) emergent effects: positive-log-age, (iii) pruning effects: negative-quadratic-age, and (iv) transient effects: positive-quadratic-age. Our results revealed that emergent (logarithmic) effects dominated developmental trajectory patterns, but significant pruning and transient effects were also observed, particularly in connections centered on inferior frontal and anterior cingulate areas that support social learning and conflict monitoring. Overall, unique global distribution patterns were observed for each growth model indicating that developmental trajectories for different connections are heterogeneous. All models showed significant effects concentrated in association areas, highlighting the dominance of higher-order social/cognitive development during the first 2 years of life.

Resting-State Functional Connectivity of the Dorsal and Ventral Striatum, Impulsivity, and Severity of Use in Recently Abstinent Cocaine-Dependent Individuals

BACKGROUND

Previous studies have focused on both ventral striatum (VS) and dorsal striatum (DS) in characterizing dopaminergic deficits in addiction. Animal studies suggest VS and DS dysfunction each in association with impulsive and compulsive cocaine use during early and later stages of addiction. However, few human studies have aimed to distinguish the roles of VS and DS dysfunction in cocaine misuse.

METHODS

We examined VS and DS resting-state functional connectivity (rsFC) of 122 recently abstinent cocaine-dependent individuals (CDs) and 122 healthy controls (HCs) in 2 separate cohorts. We followed published routines in imaging data analyses and evaluated the results at a corrected threshold with age, sex, years of drinking, and smoking accounted for.

RESULTS

CDs relative to HCs showed higher VS rsFC with the left inferior frontal cortex (IFC), lower VS rsFC with the hippocampus, and higher DS rsFC with the left orbitofrontal cortex. Region-of-interest analyses confirmed the findings in the 2 cohorts examined separately. In CDs, VS-left IFC and VS-hippocampus connectivity was positively and negatively correlated with average monthly cocaine use in the prior year, respectively. In the second cohort where participants were assessed with the Barratt Impulsivity Scale (BIS-11), VS-left IFC and VS-hippocampus connectivity was also positively and negatively correlated with BIS-11 scores in CDs. In contrast, DS-orbitofrontal cortex connectivity did not relate significantly to cocaine use metrics or BIS-11 scores.

CONCLUSION

These findings associate VS rsFC with impulsivity and the severity of recent cocaine use. How DS connectivity partakes in cocaine misuse remains to be investigated.

An Animal Model of Neonatal Intensive Care Unit Exposure to Light and Sound in the Preterm Infant

According to the World Health Organization, ∼15 million children are born prematurely each year. Many of these infants end up spending days to weeks in a neonatal intensive care unit (NICU). Infants who are born prematurely are often exposed to noise and light levels that affect their auditory and visual development. Children often have long-term impairments in cognition, visuospatial processing, hearing, and language. We have developed a rodent model of NICU exposure to light and sound using the Mongolian gerbil (Meriones unguiculatus), which has a low-frequency human-like audiogram and is altricial. To simulate preterm infancy, the eyes and ears were opened prematurely, and animals were exposed to the NICU-like sensory environment throughout the gerbil's cortical critical period of auditory development. After the animals matured into adults, auditory perceptual testing was carried out followed by auditory brainstem response recordings and then histology to assess the white matter morphology of various brain regions. Compared to normal hearing control animals, NICU sensory-exposed animals had significant impairments in learning at later stages of training, increased auditory thresholds reflecting hearing loss, and smaller cerebellar white matter volumes. These have all been reported in longitudinal studies of preterm infants. These preliminary results suggest that this animal model could provide researchers with an ethical way to explore the effects of the sensory environment in the NICU on the preterm infant's brain development.

The use of functional near-infrared spectroscopy in tracking neurodevelopmental trajectories in infants and children with or without developmental disorders: a systematic review

Understanding the neurodevelopmental trajectories of infants and children is essential for the early identification of neurodevelopmental disorders, elucidating the neural mechanisms underlying the disorders, and predicting developmental outcomes. Functional Near-Infrared Spectroscopy (fNIRS) is an infant-friendly neuroimaging tool that enables the monitoring of cerebral hemodynamic responses from the neonatal period. Due to its advantages, fNIRS is a promising tool for studying neurodevelopmental trajectories. Although many researchers have used fNIRS to study neural development in infants/children and have reported important findings, there is a lack of synthesized evidence for using fNIRS to track neurodevelopmental trajectories in infants and children. The current systematic review summarized 84 original fNIRS studies and showed a general trend of age-related increase in network integration and segregation, interhemispheric connectivity, leftward asymmetry, and differences in phase oscillation during resting-state. Moreover, typically developing infants and children showed a developmental trend of more localized and differentiated activation when processing visual, auditory, and tactile information, suggesting more mature and specialized sensory networks. Later in life, children switched from recruiting bilateral auditory to a left-lateralized language circuit when processing social auditory and language information and showed increased prefrontal activation during executive functioning tasks. The developmental trajectories are different in children with developmental disorders, with infants at risk for autism spectrum disorder showing initial overconnectivity followed by underconnectivity during resting-state; and children with attention-deficit/hyperactivity disorders showing lower prefrontal cortex activation during executive functioning tasks compared to their typically developing peers throughout childhood. The current systematic review supports the use of fNIRS in tracking the neurodevelopmental trajectories in children. More longitudinal studies are needed to validate the neurodevelopmental trajectories and explore the use of these neurobiomarkers for the early identification of developmental disorders and in tracking the effects of interventions.

Prenatal environment is associated with the pace of cortical network development over the first three years of life

Environmental influences on brain structure and function during early development have been well-characterized. In pre-registered analyses, we test the theory that socioeconomic status (SES) is associated with differences in trajectories of intrinsic brain network development from birth to three years (n = 261). Prenatal SES is associated with developmental increases in cortical network segregation, with neonates and toddlers from lower-SES backgrounds showing a steeper increase in cortical network segregation with age, consistent with accelerated network development. Associations between SES and cortical network segregation occur at the local scale and conform to a sensorimotor-association hierarchy of cortical organization. SES-associated differences in cortical network segregation are associated with language abilities at two years, such that lower segregation is associated with improved language abilities. These results yield key insight into the timing and directionality of associations between the early environment and trajectories of cortical development.

Socioeconomic disadvantage and parental mood/affective problems links negative parenting and executive dysfunction in children born very preterm

Poverty increases the risk of poorer executive function (EF) in children born full-term (FT). Stressors associated with poverty, including variability in parenting behavior, may explain links between poverty and poorer EF, but this remains unclear for children born very preterm (VPT). We examine socioeconomic and parental psychosocial adversity on parenting behavior, and whether these factors independently or jointly influence EF in children born VPT. At age five years, 154 children (VPT = 88, FT = 66) completed parent-child interaction and EF tasks. Parental sensitivity, intrusiveness, cognitive stimulation, and positive and negative regard were coded with the Parent-Child Interaction Rating Scale. Socioeconomic adversity spanned maternal demographic stressors, Income-to-Needs ratio, and Area Deprivation Index. Parents completed measures of depression, anxiety, inattention/hyperactivity, parenting stress, and social-communication interaction (SCI) problems. Parental SCI problems were associated with parenting behavior in parents of children born VPT, whereas socioeconomic adversity was significant in parents of FT children. Negative parenting behaviors, but not positive parenting behaviors, were related to child EF. This association was explained by parental depression/anxiety symptoms and socioeconomic adversity. Results persisted after adjustment for parent and child IQ. Findings may inform research on dyadic interventions that embed treatment for parental mood/affective symptoms and SCI problems to improve childhood EF.

Mapping cortical activations underlying covert and overt language production using high-density diffuse optical tomography

Gold standard neuroimaging modalities such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and more recently electrocorticography (ECoG) have provided profound insights regarding the neural mechanisms underlying the processing of language, but they are limited in applications involving naturalistic language production especially in developing brains, during face-to-face dialogues, or as a brain-computer interface. High-density diffuse optical tomography (HD-DOT) provides high-fidelity mapping of human brain function with comparable spatial resolution to that of fMRI but in a silent and open scanning environment similar to real-life social scenarios. Therefore, HD-DOT has potential to be used in naturalistic settings where other neuroimaging modalities are limited. While HD-DOT has been previously validated against fMRI for mapping the neural correlates underlying language comprehension and covert (i.e., "silent") language production, HD-DOT has not yet been established for mapping the cortical responses to overt (i.e., "out loud") language production. In this study, we assessed the brain regions supporting a simple hierarchy of language tasks: silent reading of single words, covert production of verbs, and overt production of verbs in normal hearing right-handed native English speakers (n = 33). First, we found that HD-DOT brain mapping is resilient to movement associated with overt speaking. Second, we observed that HD-DOT is sensitive to key activations and deactivations in brain function underlying the perception and naturalistic production of language. Specifically, statistically significant results were observed that show recruitment of regions in occipital, temporal, motor, and prefrontal cortices across all three tasks after performing stringent cluster-extent based thresholding. Our findings lay the foundation for future HD-DOT studies of imaging naturalistic language comprehension and production during real-life social interactions and for broader applications such as presurgical language assessment and brain-machine interfaces.

Ultra-high density imaging arrays for diffuse optical tomography of human brain improve resolution, signal-to-noise, and information decoding

Functional magnetic resonance imaging (fMRI) has dramatically advanced non-invasive human brain mapping and decoding. Functional near-infrared spectroscopy (fNIRS) and high-density diffuse optical tomography (HD-DOT) non-invasively measure blood oxygen fluctuations related to brain activity, like fMRI, at the brain surface, using more-lightweight equipment that circumvents ergonomic and logistical limitations of fMRI. HD-DOT grids have smaller inter-optode spacing (∼13 mm) than sparse fNIRS (∼30 mm) and therefore provide higher image quality, with spatial resolution ∼1/2 that of fMRI. Herein, simulations indicated reducing inter-optode spacing to 6.5 mm would further improve image quality and noise-resolution tradeoff, with diminishing returns below 6.5 mm. We then constructed an ultra-high-density DOT system (6.5-mm spacing) with 140 dB dynamic range that imaged stimulus-evoked activations with 30-50% higher spatial resolution and repeatable multi-focal activity with excellent agreement with participant-matched fMRI. Further, this system decoded visual stimulus position with 19-35% lower error than previous HD-DOT, throughout occipital cortex.

Default mode network functional connectivity strength in utero and the association with fetal subcortical development

The default mode network is essential for higher-order cognitive processes and is composed of an extensive network of functional and structural connections. Early in fetal life, the default mode network shows strong connectivity with other functional networks; however, the association with structural development is not well understood. In this study, resting-state functional magnetic resonance imaging and anatomical images were acquired in 30 pregnant women with singleton pregnancies. Participants completed 1 or 2 MR imaging sessions, on average 3 weeks apart (43 data sets), between 28- and 39-weeks postconceptional ages. Subcortical volumes were automatically segmented. Activation time courses from resting-state functional magnetic resonance imaging were extracted from the default mode network, medial temporal lobe network, and thalamocortical network. Generalized estimating equations were used to examine the association between functional connectivity strength between default mode network-medial temporal lobe, default mode network-thalamocortical network, and subcortical volumes, respectively. Increased functional connectivity strength in the default mode network-medial temporal lobe network was associated with smaller right hippocampal, left thalamic, and right caudate nucleus volumes, but larger volumes of the left caudate. Increased functional connectivity strength in the default mode network-thalamocortical network was associated with smaller left thalamic volumes. The strong associations seen among the default mode network functional connectivity networks and regionally specific subcortical volume development indicate the emergence of short-range connectivity in the third trimester.

Memory reactivation and suppression modulate integration of the semantic features of related memories in hippocampus

Encoding an event that overlaps with a previous experience may involve reactivating an existing memory and integrating it with new information or suppressing the existing memory to promote formation of a distinct, new representation. We used fMRI during overlapping event encoding to track reactivation and suppression of individual, related memories. We further used a model of semantic knowledge based on Wikipedia to quantify both reactivation of semantic knowledge related to a previous event and formation of integrated memories containing semantic features of both events. Representational similarity analysis revealed that reactivation of semantic knowledge related to a prior event in posterior medial prefrontal cortex (pmPFC) supported memory integration during new learning. Moreover, anterior hippocampus (aHPC) formed integrated representations combining the semantic features of overlapping events. We further found evidence that aHPC integration may be modulated on a trial-by-trial basis by interactions between ventrolateral PFC and anterior mPFC, with suppression of item-specific memory representations in anterior mPFC inhibiting hippocampal integration. These results suggest that PFC-mediated control processes determine the availability of specific relevant memories during new learning, thus impacting hippocampal memory integration.

Supporting and Enhancing NICU Sensory Experiences (SENSE), 2nd Edition: An Update on Developmentally Appropriate Interventions for Preterm Infants

The Supporting and Enhancing NICU Sensory Experiences (SENSE) program promotes consistent, age-appropriate, responsive, and evidence-based positive sensory exposures for preterm infants each day of NICU hospitalization to optimize infant and parent outcomes. The initial development included an integrative review, stakeholder input (NICU parents and healthcare professionals), and feasibility focus groups. To keep the program updated and evidence-based, a review of the recent evidence and engagement with an advisory team will occur every 5 years to inform changes to the SENSE program. Prior to the launch of the 2nd edition of the SENSE program in 2022, information from a new integrative review of 57 articles, clinician feedback, and a survey identifying the barriers and facilitators to the SENSE program's implementation in a real-world context were combined to inform initial changes. Subsequently, 27 stakeholders (neonatologists, nurse practitioners, clinical nurse specialists, bedside nurses, occupational therapists, physical therapists, speech-language pathologists, and parents) carefully considered the suggested changes, and refinements were made until near consensus was achieved. While the 2nd edition is largely the same as the original SENSE program, the refinements include the following: more inclusive language, clarification on recommended minimum doses, adaptations to allow for variability in how hospitals achieve different levels of light, the addition of visual tracking in the visual domain, and the addition of position changes in the kinesthetic domain.

Progressive inflammation reduces high-frequency EEG activity and cortical dendritic arborisation in late gestation fetal sheep

BACKGROUND

Antenatal infection/inflammation is associated with disturbances in neuronal connectivity, impaired cortical growth and poor neurodevelopmental outcomes. The pathophysiological substrate that underpins these changes is poorly understood. We tested the hypothesis that progressive inflammation in late gestation fetal sheep would alter cortical neuronal microstructure and neural function assessed using electroencephalogram band power analysis.

METHODS

Fetal sheep (0.85 of gestation) were surgically instrumented for continuous electroencephalogram (EEG) recording and randomly assigned to repeated saline (control; n = 9) or LPS (0 h = 300 ng, 24 h = 600 ng, 48 h = 1200 ng; n = 8) infusions to induce inflammation. Sheep were euthanised 4 days after the first LPS infusion for assessment of inflammatory gene expression, histopathology and neuronal dendritic morphology in the somatosensory cortex.

RESULTS

LPS infusions increased delta power between 8 and 50 h, with reduced beta power from 18 to 96 h (P < 0.05 vs. control). Basal dendritic length, numbers of dendritic terminals, dendritic arborisation and numbers of dendritic spines were reduced in LPS-exposed fetuses (P < 0.05 vs. control) within the somatosensory cortex. Numbers of microglia and interleukin (IL)-1β immunoreactivity were increased in LPS-exposed fetuses compared with controls (P < 0.05). There were no differences in total numbers of cortical NeuN + neurons or cortical area between the groups.

CONCLUSIONS

Exposure to antenatal infection/inflammation was associated with impaired dendritic arborisation, spine number and loss of high-frequency EEG activity, despite normal numbers of neurons, that may contribute to disturbed cortical development and connectivity.

Music impacts brain cortical microstructural maturation in very preterm infants: A longitudinal diffusion MR imaging study

Preterm birth disrupts important neurodevelopmental processes occurring from mid-fetal to term-age. Musicotherapy, by enriching infants' sensory input, might enhance brain maturation during this critical period of activity-dependent plasticity. To study the impact of music on preterm infants' brain structural changes, we recruited 54 very preterm infants randomized to receive or not a daily music intervention, that have undergone a longitudinal multi-shell diffusion MRI acquisition, before the intervention (at 33 weeks' gestational age) and after it (at term-equivalent-age). Using whole-brain fixel-based (FBA) and NODDI analysis (n = 40), we showed a longitudinal increase of fiber cross-section (FC) and fiber density (FD) in all major cerebral white matter fibers. Regarding cortical grey matter, FD decreased while FC and orientation dispersion index (ODI) increased, reflecting intracortical multidirectional complexification and intracortical myelination. The music intervention resulted in a significantly higher longitudinal increase of FC and ODI in cortical paralimbic regions, namely the insulo-orbito-temporopolar complex, precuneus/posterior cingulate gyrus, as well as the auditory association cortex. Our results support a longitudinal early brain macro and microstructural maturation of white and cortical grey matter in preterm infants. The music intervention led to an increased intracortical complexity in regions important for socio-emotional development, known to be impaired in preterm infants.

The development of intrinsic timescales: A comparison between the neonate and adult brain

In human adults and other mammals, different brain regions have distinct intrinsic timescales over which they integrate information, from shorter in unimodal sensory-motor regions to longer in transmodal higher-order regions. These have been related to cognitive performance and clinical symptoms, but it remains unclear how they develop. We asked if there are regional differences in timescales at birth that could shape learning by acting as an inductive bias, or if they develop later as the temporal statistics of the environment are learned. We used resting-state fMRI to characterise timescales in human neonates and adults. They were highly consistent across two independent neonatal groups, but in both sensory-motor and higher order areas, timescales were longer in infants compared to adults, as might be expected from their less developed myelination, and recent evidence of longer neural segments in infants watching naturalistic stimuli. In adults, we replicated the finding that transmodal areas have longer timescales than sensory-motor areas, but in infants the opposite pattern was found, driven by long infant timescales in the somotomotor network. Across regions within single brain networks, both positive (limbic) and negative (visual) correlations were found between neonates and adults. In conclusion, neonatal timescales were found to be highly structured, but distinct from adults, suggesting they act as an inductive bias that favours learning on longer timescales, particularly in unimodal regions and then develop with experience or maturation. This "take it slow" initial approach might help human infants to create more regularised, holistic representations of the input less bound to fleeting details, which would favour the development of abstract and contextual representations.

Temporal dynamics predict symptom onset and cognitive decline in familial frontotemporal dementia

INTRODUCTION

We tested whether changes in functional networks predict cognitive decline and conversion from the presymptomatic prodrome to symptomatic disease in familial frontotemporal dementia (FTD).

METHODS

For hypothesis generation, 36 participants with behavioral variant FTD (bvFTD) and 34 controls were recruited from one site. For hypothesis testing, we studied 198 symptomatic FTD mutation carriers, 341 presymptomatic mutation carriers, and 329 family members without mutations. We compared functional network dynamics between groups, with clinical severity and with longitudinal clinical progression.

RESULTS

We identified a characteristic pattern of dynamic network changes in FTD, which correlated with neuropsychological impairment. Among presymptomatic mutation carriers, this pattern of network dynamics was found to a greater extent in those who subsequently converted to the symptomatic phase. Baseline network dynamic changes predicted future cognitive decline in symptomatic participants and older presymptomatic participants.

DISCUSSION

Dynamic network abnormalities in FTD predict cognitive decline and symptomatic conversion.

HIGHLIGHTS

We investigated brain network predictors of dementia symptom onset Frontotemporal dementia results in characteristic dynamic network patterns Alterations in network dynamics are associated with neuropsychological impairment Network dynamic changes predict symptomatic conversion in presymptomatic carriers Network dynamic changes are associated with longitudinal cognitive decline.

Less is more: balancing noise reduction and data retention in fMRI with data-driven scrubbing

Functional MRI (fMRI) data may be contaminated by artifacts arising from a myriad of sources, including subject head motion, respiration, heartbeat, scanner drift, and thermal noise. These artifacts cause deviations from common distributional assumptions, introduce spatial and temporal outliers, and reduce the signal-to-noise ratio of the data-all of which can have negative consequences for the accuracy and power of downstream statistical analysis. Scrubbing is a technique for excluding fMRI volumes thought to be contaminated by artifacts and generally comes in two flavors. Motion scrubbing based on subject head motion-derived measures is popular but suffers from a number of drawbacks, among them the need to choose a threshold, a lack of generalizability to multiband acquisitions, and high rates of censoring of individual volumes and entire subjects. Alternatively, data-driven scrubbing methods like DVARS are based on observed noise in the processed fMRI timeseries and may avoid some of these issues. Here we propose "projection scrubbing", a novel data-driven scrubbing method based on a statistical outlier detection framework and strategic dimension reduction, including independent component analysis (ICA), to isolate artifactual variation. We undertake a comprehensive comparison of motion scrubbing with data-driven projection scrubbing and DVARS. We argue that an appropriate metric for the success of scrubbing is maximal data retention subject to reasonable performance on typical benchmarks such as the validity, reliability, and identifiability of functional connectivity. We find that stringent motion scrubbing yields worsened validity, worsened reliability, and produced small improvements to fingerprinting. Meanwhile, data-driven scrubbing methods tend to yield greater improvements to fingerprinting while not generally worsening validity or reliability. Importantly, however, data-driven scrubbing excludes a fraction of the number of volumes or entire sessions compared to motion scrubbing. The ability of data-driven fMRI scrubbing to improve data retention without negatively impacting the quality of downstream analysis has major implications for sample sizes in population neuroscience research.

Genetic and environmental factors influencing neonatal resting-state functional connectivity

Functional magnetic resonance imaging has been used to identify complex brain networks by examining the correlation of blood-oxygen-level-dependent signals between brain regions during the resting state. Many of the brain networks identified in adults are detectable at birth, but genetic and environmental influences governing connectivity within and between these networks in early infancy have yet to be explored. We investigated genetic influences on neonatal resting-state connectivity phenotypes by generating intraclass correlations and performing mixed effects modeling to estimate narrow-sense heritability on measures of within network and between-network connectivity in a large cohort of neonate twins. We also used backwards elimination regression and mixed linear modeling to identify specific demographic and medical history variables influencing within and between network connectivity in a large cohort of typically developing twins and singletons. Of the 36 connectivity phenotypes examined, only 6 showed narrow-sense heritability estimates greater than 0.10, with none being statistically significant. Demographic and obstetric history variables contributed to between- and within-network connectivity. Our results suggest that in early infancy, genetic factors minimally influence brain connectivity. However, specific demographic and medical history variables, such as gestational age at birth and maternal psychiatric history, may influence resting-state connectivity measures.

Systematic evaluation of head motion on resting-state functional connectivity MRI in the neonate

Reliability and robustness of resting state functional connectivity MRI (rs-fcMRI) relies, in part, on minimizing the influence of head motion on measured brain signals. The confounding effects of head motion on functional connectivity have been extensively studied in adults, but its impact on newborn brain connectivity remains unexplored. Here, using a large newborn data set consisting of 159 rs-fcMRI scans acquired in the Developing Brain Institute at Children's National Hospital and 416 scans from The Developing Human Connectome Project (dHCP), we systematically investigated associations between head motion and rs-fcMRI. Head motion during the scan significantly affected connectivity at sensory-related networks and default mode networks, and at the whole brain scale; the direction of motion effects varied across the whole brain. Comparing high- versus low-head motion groups suggested that head motion can impact connectivity estimates across the whole brain. Censoring of high-motion volumes using frame-wise displacement significantly reduced the confounding effects of head motion on neonatal rs-fcMRI. Lastly, in the dHCP data set, we demonstrated similar persistent associations between head motion and network connectivity despite implementing a standard denoising strategy. Collectively, our results highlight the importance of using rigorous head motion correction in preprocessing neonatal rs-fcMRI to yield reliable estimates of brain activity.

Using synthetic MR images for distortion correction

Functional MRI (fMRI) data acquired using echo-planar imaging (EPI) are highly distorted by magnetic field inhomogeneities. Distortion and differences in image contrast between EPI and T1-weighted and T2-weighted (T1w/T2w) images makes their alignment a challenge. Typically, field map data are used to correct EPI distortions. Alignments achieved with field maps can vary greatly and depends on the quality of field map data. However, many public datasets lack field map data entirely. Additionally, reliable field map data is often difficult to acquire in high-motion pediatric or developmental cohorts. To address this, we developed Synth, a software package for distortion correction and cross-modal image registration that does not require field map data. Synth combines information from T1w and T2w anatomical images to construct an idealized undistorted synthetic image with similar contrast properties to EPI data. This synthetic image acts as an effective reference for individual-specific distortion correction. Using pediatric (ABCD: Adolescent Brain Cognitive Development) and adult (MSC: Midnight Scan Club; HCP: Human Connectome Project) data, we demonstrate that Synth performs comparably to field map distortion correction approaches, and often outperforms them. Field map-less distortion correction with Synth allows accurate and precise registration of fMRI data with missing or corrupted field map information.

Examining resting-state network connectivity in children exposed to perinatal maternal adversity using anatomically weighted functional connectivity (awFC) analyses; A preliminary report

Introduction

Environmental perturbations during critical periods can have pervasive, organizational effects on neurodevelopment. To date, the literature examining the long-term impact of early life adversity has largely investigated structural and functional imaging data outcomes independently. However, emerging research points to a relationship between functional connectivity and the brain’s underlying structural architecture. For instance, functional connectivity can be mediated by the presence of direct or indirect anatomical pathways. Such evidence warrants the use of structural and functional imaging in tandem to study network maturation. Accordingly, this study examines the impact of poor maternal mental health and socioeconomic context during the perinatal period on network connectivity in middle childhood using an anatomically weighted functional connectivity (awFC) approach. awFC is a statistical model that identifies neural networks by incorporating information from both structural and functional imaging data.

Methods

Resting-state fMRI and DTI scans were acquired from children aged 7–9 years old.

Results

Our results indicate that maternal adversity during the perinatal period can affect offspring’s resting-state network connectivity during middle childhood. Specifically, in comparison to controls, children of mothers who had poor perinatal maternal mental health and/or low socioeconomic status exhibited greater awFC in the ventral attention network.

Discussion

These group differences were discussed in terms of the role this network plays in attention processing and maturational changes that may accompany the consolidation of a more adult-like functional cortical organization. Furthermore, our results suggest that there is value in using an awFC approach as it may be more sensitive in highlighting connectivity differences in developmental networks associated with higher-order cognitive and emotional processing, as compared to stand-alone FC or SC analyses.

Maturation of large-scale brain systems over the first month of life

The period immediately after birth is a critical developmental window, capturing rapid maturation of brain structure and a child's earliest experiences. Large-scale brain systems are present at delivery, but how these brain systems mature during this narrow window (i.e. first weeks of life) marked by heightened neuroplasticity remains uncharted. Using multivariate pattern classification techniques and functional connectivity magnetic resonance imaging, we detected robust differences in brain systems related to age in newborns (n = 262; R2 = 0.51). Development over the first month of life occurred brain-wide, but differed and was more pronounced in brain systems previously characterized as developing early (i.e. sensorimotor networks) than in those characterized as developing late (i.e. association networks). The cingulo-opercular network was the only exception to this organizing principle, illuminating its early role in brain development. This study represents a step towards a normative brain "growth curve" that could be used to identify atypical brain maturation in infancy.

Association of Brain Microstructure and Functional Connectivity With Cognitive Outcomes and Postnatal Growth Among Early School-Aged Children Born With Extremely Low Birth Weight

IMPORTANCE

Postnatal growth may be associated with longitudinal brain development in children born preterm.

OBJECTIVE

To compare brain microstructure and functional connectivity strength with cognitive outcomes in association with postnatal growth among early school-aged children born preterm with extremely low birth weight.

DESIGN, SETTING, AND PARTICIPANTS

This single-center cohort study prospectively enrolled 38 children 6 to 8 years of age born preterm with extremely low birth weight: 21 with postnatal growth failure (PGF) and 17 without PGF. Children were enrolled, past records were retrospectively reviewed, and imaging data and cognitive assessments occurred from April 29, 2013, through February 14, 2017. Image processing and statistical analyses were conducted through November 2021.

EXPOSURE

Postnatal growth failure in the early neonatal period.

MAIN OUTCOMES AND MEASURES

Diffusion tensor images and resting-state functional magnetic resonance images were analyzed. Cognitive skills were tested using the Wechsler Intelligence Scale; executive function was assessed based on a composite score calculated from the synthetic composite of the Children's Color Trails Test, STROOP Color and Word Test, and Wisconsin Card Sorting Test; attention function was evaluated using the Advanced Test of Attention (ATA); and the Hollingshead Four Factor Index of Social Status-Child was estimated.

RESULTS

Twenty-one children born preterm with PGF (14 girls [66.7%]), 17 children born preterm without PGF (6 girls [35.3%]), and 44 children born full term (24 girls [54.5%]) were recruited. Attention function was less favorable in children with PGF than those without PGF (mean [SD] ATA score: children with PGF, 63.5 [9.4]; children without PGF, 55.7 [8.0]; P = .008). Significantly lower mean (SD) fractional anisotropy in the forceps major of the corpus callosum (0.498 [0.067] vs 0.558 [0.044] vs 0.570 [0.038]) and higher mean (SD) mean diffusivity in the left superior longitudinal fasciculus-parietal bundle (8.312 [0.318] vs 7.902 [0.455] vs 8.083 [0.393]; originally calculated as millimeter squared per second and rescaled 10 000 times as mean diffusivity × 10 000) were seen among children with PGF compared with children without PGF and controls, respectively. Decreased resting-state functional connectivity strength was observed in the children with PGF. The mean diffusivity of the forceps major of the corpus callosum significantly correlated with the attention measures (r = 0.225; P = .047). Functional connectivity strength between the left superior lateral occipital cortex and both superior parietal lobules correlated with cognitive outcomes of intelligence (right superior parietal lobule, r = 0.262; P = .02; and left superior parietal lobule, r = 0.286; P = .01) and executive function (right superior parietal lobule, r = 0.367; P = .002; and left superior parietal lobule, r = 0.324; P = .007). The ATA score was positively correlated with functional connectivity strength between the precuneus and anterior division of the cingulate gyrus (r = 0.225; P = .048); however, it was negatively correlated with functional connectivity strength between the posterior cingulate gyrus and both superior parietal lobules (the right superior parietal lobule [r = -0.269; P = .02] and the left superior parietal lobule [r = -0.338; P = .002]).

CONCLUSIONS AND RELEVANCE

This cohort study suggests that the forceps major of the corpus callosum and the superior parietal lobule were vulnerable regions in preterm infants. Preterm birth and suboptimal postnatal growth could have negative associations with brain maturation, including altered microstructure and functional connectivity. Postnatal growth may be associated with differences in long-term neurodevelopment among children born preterm.

Network-specific selectivity of functional connections in the neonatal brain

The adult human brain is organized into functional brain networks, groups of functionally connected segregated brain regions. A key feature of adult functional networks is long-range selectivity, the property that spatially distant regions from the same network have higher functional connectivity than spatially distant regions from different networks. Although it is critical to establish the status of functional networks and long-range selectivity during the neonatal period as a foundation for typical and atypical brain development, prior work in this area has been mixed. Although some studies report distributed adult-like networks, other studies suggest that neonatal networks are immature and consist primarily of spatially isolated regions. Using a large sample of neonates (n = 262), we demonstrate that neonates have long-range selective functional connections for the default mode, fronto-parietal, and dorsal attention networks. An adult-like pattern of functional brain networks is evident in neonates when network-detection algorithms are tuned to these long-range connections, when using surface-based registration (versus volume-based registration), and as per-subject data quantity increases. These results help clarify factors that have led to prior mixed results, establish that key adult-like functional network features are evident in neonates, and provide a foundation for studies of typical and atypical brain development.

Effect of Musical Stimulation on Placental Programming and Neurodevelopment Outcome of Preterm Infants: A Systematic Review

BACKGROUND

The fetal environment is modulated by the placenta, which integrates and transduces information from the maternal environment to the fetal developmental program and adapts rapidly to changes through epigenetic mechanisms that respond to internal (hereditary) and external (environmental and social) signals. Consequently, the fetus corrects the trajectory of own development. During the last trimester of gestation, plasticity shapes the fetal brain, and prematurity can alter the typical developmental trajectories. In this period, prevention through activity-inducing (e.g., music stimulation) interventions are currently tested. The purpose of this review is to describe the potentialities of music exposure on fetus, and on preterm newborns in the Neonatal Intensive Care Unit evaluating its influence on neurobehavioral development.

METHODS

Databases were searched from 2010 to 2022 for studies investigating mechanisms of placental epigenetic regulation and effects of music exposure on the fetus and pre-term neonates.

RESULTS

In this case, 28 selected papers were distributed into three research lines: studies on placental epigenetic regulation (13 papers), experimental studies of music stimulation on fetus or newborns (6 papers), and clinical studies on premature babies (9 papers). Placental epigenetic changes of the genes involved in the cortisol and serotonin response resulted associated with different neurobehavioral phenotypes in newborns. Prenatal music stimulation had positive effects on fetus, newborn, and pregnant mother while post-natal exposure affected the neurodevelopment of the preterm infants and parental interaction.

CONCLUSIONS

The results testify the relevance of environmental stimuli for brain development during the pre- and perinatal periods and the beneficial effects of musical stimulation that can handle the fetal programming and the main neurobehavioral disorders.

Resting-state functional MRI in multicenter studies on multiple sclerosis: a report on raw data quality and functional connectivity features from the Italian Neuroimaging Network Initiative

The Italian Neuroimaging Network Initiative (INNI) is an expanding repository of brain MRI data from multiple sclerosis (MS) patients recruited at four Italian MRI research sites. We describe the raw data quality of resting-state functional MRI (RS-fMRI) time-series in INNI and the inter-site variability in functional connectivity (FC) features after unified automated data preprocessing. MRI datasets from 489 MS patients and 246 healthy control (HC) subjects were retrieved from the INNI database. Raw data quality metrics included temporal signal-to-noise ratio (tSNR), spatial smoothness (FWHM), framewise displacement (FD), and differential variation in signals (DVARS). Automated preprocessing integrated white-matter lesion segmentation (SAMSEG) into a standard fMRI pipeline (fMRIPrep). FC features were calculated on pre-processed data and harmonized between sites (Combat) prior to assessing general MS-related alterations. Across centers (both groups), median tSNR and FWHM ranged from 47 to 84 and from 2.0 to 2.5, and median FD and DVARS ranged from 0.08 to 0.24 and from 1.06 to 1.22. After preprocessing, only global FC-related features were significantly correlated with FD or DVARS. Across large-scale networks, age/sex/FD-adjusted and harmonized FC features exhibited both inter-site and site-specific inter-group effects. Significant general reductions were obtained for somatomotor and limbic networks in MS patients (vs. HC). The implemented procedures provide technical information on raw data quality and outcome of fully automated preprocessing that might serve as reference in future RS-fMRI studies within INNI. The unified pipeline introduced little bias across sites and appears suitable for multisite FC analyses on harmonized network estimates.