Microstructure of the Default Mode Network in Preterm Infants

Prenatal depressive symptoms are associated with altered structural brain networks in infants and moderated by infant sleep

BACKGROUND

The prevalence of prenatal depressive symptoms has more than doubled during the COVID-19 pandemic, raising substantial concerns about child outcomes including sleep problems and altered brain development. The objective of this work was to determine relationships between prenatal depressive symptoms, infant brain network structure, and infant sleep.

METHODS

Pregnant individuals were recruited as part of the Pregnancy during the Pandemic (PdP) study. Maternal depressive symptoms were measured in pregnancy and postpartum. When infants of those participants were 3 months of age (n=66; 26 females), infants underwent diffusion magnetic resonance imaging and infant sleep was evaluated. Using tractography, we calculated structural connectivity matrices for the default mode (DMN) and limbic networks. We examined associations between graph theory metrics of infant brain networks and prenatal maternal depressive symptoms, with infant sleep as a moderator.

RESULTS

Prenatal depressive symptoms were negatively related to average DMN clustering coefficient and local efficiency in infant brains. Infant sleep duration was related to DMN global efficiency and moderated the relationship between prenatal depressive symptoms and density of limbic connections such that infants who slept less had a more negative relationship between prenatal depressive symptoms and local brain connectivity.

CONCLUSIONS

Prenatal depressive symptoms appear to impact early topological development in brain networks important for emotion regulation. In the limbic network, sleep duration moderated this relationship, suggesting sleep may play a role in infant brain network development.

Early-life stress exposure and large-scale covariance brain networks in extremely preterm-born infants

The stressful extrauterine environment following premature birth likely has far-reaching and persistent adverse consequences. The effects of early "third-trimester" ex utero stress on large-scale brain networks' covariance patterns may provide a potential avenue to understand how early-life stress following premature birth increases risk or resilience. We evaluated the impact of early-life stress exposure (e.g., quantification of invasive procedures) on maturational covariance networks (MCNs) between 30 and 40 weeks of gestational age in 180 extremely preterm-born infants (<28 weeks of gestation; 43.3% female). We constructed MCNs using covariance of gray matter volumes between key nodes of three large-scale brain networks: the default mode network (DMN), executive control network (ECN), and salience network (SN). Maturational coupling was quantified by summating the number of within- and between-network connections. Infants exposed to high stress showed significantly higher SN but lower DMN maturational coupling, accompanied by DMN-SN decoupling. Within the SN, the insula, amygdala, and subthalamic nucleus all showed higher maturational covariance at the nodal level. In contrast, within the DMN, the hippocampus, parahippocampal gyrus, and fusiform showed lower coupling following stress. The decoupling between DMN-SN was observed between the insula/anterior cingulate cortex and posterior parahippocampal gyrus. Early-life stress showed longitudinal network-specific maturational covariance patterns, leading to a reprioritization of developmental trajectories of the SN at the cost of the DMN. These alterations may enhance the ability to cope with adverse stimuli in the short term but simultaneously render preterm-born individuals at a higher risk for stress-related psychopathology later in life.

A methodological scoping review of the integration of fMRI to guide dMRI tractography. What has been done and what can be improved: A 20-year perspective

Combining MRI modalities is a growing trend in neurosciences. It provides opportunities to investigate the brain architecture supporting cognitive functions. Integrating fMRI activation to guide dMRI tractography offers potential advantages over standard tractography methods. A quick glimpse of the literature on this topic reveals that this technique is challenging, and no consensus or "best practices" currently exist, at least not within a single document. We present the first attempt to systematically analyze and summarize the literature of 80 studies that integrated task-based fMRI results to guide tractography, over the last two decades. We report 19 findings that cover challenges related to sample size, microstructure modelling, seeding methods, multimodal space registration, false negatives/positives, specificity/validity, gray/white matter interface and more. These findings will help the scientific community (1) understand the strengths and limitations of the approaches, (2) design studies using this integrative framework, and (3) motivate researchers to fill the gaps identified. We provide references toward best practices, in order to improve the overall result's replicability, sensitivity, specificity, and validity.

OUP accepted manuscript

One of the great frontiers of consciousness science is understanding how early consciousness arises in the development of the human infant. The reciprocal relationship between the default mode network and fronto-parietal networks—the dorsal attention and executive control network—is thought to facilitate integration of information across the brain and its availability for a wide set of conscious mental operations. It remains unknown whether the brain mechanism of conscious awareness is instantiated in infants from birth. To address this gap, we investigated the development of the default mode and fronto-parietal networks and of their reciprocal relationship in neonates. To understand the effect of early neonate age on these networks, we also assessed neonates born prematurely or before term-equivalent age. We used the Developing Human Connectome Project, a unique Open Science dataset which provides a large sample of neonatal functional MRI data with high temporal and spatial resolution. Resting state functional MRI data for full-term neonates (n = 282, age 41.2 weeks ± 12 days) and preterm neonates scanned at term-equivalent age (n = 73, 40.9 weeks ± 14.5 days), or before term-equivalent age (n = 73, 34.6 weeks ± 13.4 days), were obtained from the Developing Human Connectome Project, and for a reference adult group (n = 176, 22–36 years), from the Human Connectome Project. For the first time, we show that the reciprocal relationship between the default mode and dorsal attention network was present at full-term birth or term-equivalent age. Although different from the adult networks, the default mode, dorsal attention and executive control networks were present as distinct networks at full-term birth or term-equivalent age, but premature birth was associated with network disruption. By contrast, neonates before term-equivalent age showed dramatic underdevelopment of high-order networks. Only the dorsal attention network was present as a distinct network and the reciprocal network relationship was not yet formed. Our results suggest that, at full-term birth or by term-equivalent age, infants possess key features of the neural circuitry that enables integration of information across diverse sensory and high-order functional modules, giving rise to conscious awareness. Conversely, they suggest that this brain infrastructure is not present before infants reach term-equivalent age. These findings improve understanding of the ontogeny of high-order network dynamics that support conscious awareness and of their disruption by premature birth.

Early protein intake predicts functional connectivity and neurocognition in preterm born children

Nutritional intake can promote early neonatal brain development in very preterm born neonates (< 32 weeks’ gestation). In a group of 7-year-old very preterm born children followed since birth, we examined whether early nutrient intake in the first weeks of life would be associated with long-term brain function and neurocognitive skills at school age. Children underwent resting-state functional MRI (fMRI), intelligence testing (Wechsler Intelligence Scale for Children, 5th Ed) and visual-motor processing (Beery-Buktenica, 5th Ed) at 7 years. Relationships were assessed between neonatal macronutrient intakes, functional connectivity strength between thalamic and default mode networks (DMN), and neuro-cognitive function using multivariable regression. Greater functional connectivity strength between thalamic networks and DMN was associated with greater intake of protein in the first week (β = 0.17; 95% CI 0.11, 0.23, p < 0.001) but lower intakes of fat (β = − 0.06; 95% CI − 0.09, − 0.02, p = 0.001) and carbohydrates (β = − 0.03; 95% CI − 0.04, − 0.01, p = 0.003). Connectivity strength was also associated with protein intake during the first month (β = 0.22; 95% CI 0.06, 0.37, p = 0.006). Importantly, greater thalamic-DMN connectivity strength was associated with higher processing speed indices (β = 26.9; 95% CI 4.21, 49.49, p = 0.02) and visual processing scores (β = 9.03; 95% CI 2.27, 15.79, p = 0.009). Optimizing early protein intake may contribute to promoting long-term brain health in preterm-born children.

The cingulum in very preterm infants relates to language and social-emotional impairment at 2 years of term-equivalent age

•

Maturation of specific WM tracts in preterm individuals differs from those of term controls.

•

The elastic net logistic regression model was used to identify altered white matter tracts in the preterm brain.

•

The alteration of the cingulum in the preterm at near-term correlate with neurodevelopmental scores at 18–22 months of age.

Background

Relative to full-term infants, very preterm infants exhibit disrupted white matter (WM) maturation and problems related to development, including motor, cognitive, social-emotional, and receptive and expressive language processing.

Objective

The present study aimed to determine whether regional abnormalities in the WM microstructure of very preterm infants, as defined relative to those of full-term infants at a near-term age, are associated with neurodevelopmental outcomes at the age of 18–22 months.

Methods

We prospectively enrolled 89 very preterm infants (birth weight < 1500 g) and 43 normal full-term control infants born between 2016 and 2018. All infants underwent a structural brain magnetic resonance imaging scan at near-term age. The diffusion tensor imaging (DTI) metrics of the whole-brain WM tracts were extracted based on the neonatal probabilistic WM pathway. The elastic net logistic regression model was used to identify altered WM tracts in the preterm brain. We evaluated the associations between the altered WM microstructure at near-term age and motor, cognitive, social-emotional, and receptive and expressive language developments at 18–22 months of age, as measured using the Bayley Scales of Infant Development, Third Edition.

Results

We found that the elastic net logistic regression model could classify preterm and full-term neonates with an accuracy of 87.9% (corrected p < 0.008) using the DTI metrics in the pathway of interest with a 10% threshold level. The fractional anisotropy (FA) values of the body and splenium of the corpus callosum, middle cerebellar peduncle, left and right uncinate fasciculi, and right portion of the pathway between the premotor and primary motor cortices (premotor-PMC), as well as the mean axial diffusivity (AD) values of the left cingulum, were identified as contributive features for classification. Increased adjusted AD values in the left cingulum pathway were significantly correlated with language scores after false discovery rate (FDR) correction (r = 0.217, p = 0.043). The expressive language and social-emotional composite scores showed a significant positive correlation with the AD values in the left cingulum pathway (r = 0.226 [p = 0.036] and r = 0.31 [p = 0.003], respectively) after FDR correction.

Conclusion

Our approach suggests that the cingulum pathways of very preterm infants differ from those of full-term infants and significantly contribute to the prediction of the subsequent development of the language and social-emotional domains. This finding could improve our understanding of how specific neural substrates influence neurodevelopment at later ages, and individual risk prediction, thus helping to inform early intervention strategies that address developmental delay.

The enigmatic fetal subplate compartment forms an early tangential cortical nexus and provides the framework for construction of cortical connectivity

The most prominent transient compartment of the primate fetal cortex is the deep, cell-sparse, synapse-containing subplate compartment (SPC). The developmental role of the SPC and its extraordinary size in humans remain enigmatic. This paper evaluates evidence on the development and connectivity of the SPC and discusses its role in the pathogenesis of neurodevelopmental disorders. A synthesis of data shows that the subplate becomes a prominent compartment by its expansion from the deep cortical plate (CP), appearing well-delineated on MR scans and forming a tangential nexus across the hemisphere, consisting of an extracellular matrix, randomly distributed postmigratory neurons, multiple branches of thalamic and long corticocortical axons. The SPC generates early spontaneous non-synaptic and synaptic activity and mediates cortical response upon thalamic stimulation. The subplate nexus provides large-scale interareal connectivity possibly underlying fMR resting-state activity, before corticocortical pathways are established. In late fetal phase, when synapses appear within the CP, transient the SPC coexists with permanent circuitry. The histogenetic role of the SPC is to provide interactive milieu and capacity for guidance, sorting, "waiting" and target selection of thalamocortical and corticocortical pathways. The new evolutionary role of the SPC and its remnant white matter neurons is linked to the increasing number of associative pathways in the human neocortex. These roles attributed to the SPC are regulated using a spatiotemporal gene expression during critical periods, when pathogenic factors may disturb vulnerable circuitry of the SPC, causing neurodevelopmental cognitive circuitry disorders.

Inhibition is associated with whole-brain structural brain connectivity on network level in school-aged children born very preterm and at term

Inhibition abilities are often impaired in children born very preterm. In typically-developing individuals, inhibition has been associated with structural brain connectivity (SC). As SC is frequently altered following preterm birth, this study investigated whether aberrant SC underlies inhibition deficits in school-aged children born very preterm. In a group of 67 very preterm participants aged 8-13 years and 69 term-born peers, inhibition abilities were assessed with two tasks. In a subgroup of 50 very preterm and 62 term-born participants, diffusion tensor imaging (DTI) data were collected. Using network-based statistics (NBS), mean fractional anisotropy (FA_mean) was compared between groups. Associations of FA_mean and inhibition abilities were explored through linear regression. The composite score of inhibition abilities was lower in the very preterm group (M ​= ​-0.4, SD ​= ​0.8) than in the term-born group (M ​= ​0.0, SD ​= ​0.8) but group differences were not significant when adjusting for age, sex and socio-economic status (β ​= ​-0.13, 95%-CI [-0.30, 0.04], p ​= ​0.13). In the very preterm group, FA_mean was significantly lower in a network comprising thalamo-frontal, thalamo-temporal, frontal, cerebellar and intra-hemispheric connections than in the term-born group (t ​= ​5.21, lowest p-value ​= ​0.001). Irrespective of birth status, a network comprising parietal, cerebellar and subcortical connections was positively associated with inhibition abilities (t ​= ​4.23, lowest p-value ​= ​0.02). Very preterm birth results in long-term alterations of SC at network-level. As networks underlying inhibition abilities do not overlap with those differing between the groups, FA_mean may not be adequate to explain inhibition problems in very preterm children. Future studies should combine complementary measures of brain connectivity to address neural correlates of inhibition abilities.

The Molecular Organization of Self-awareness: Paralimbic Dopamine-GABA Interaction

The electrophysiology of the paralimbic network ("default mode") for self-awareness has drawn much attention in the past couple of decades. In contrast, knowledge of the molecular organization of conscious experience has only lately come into focus. We here review newer data on dopaminergic control of awareness in humans, particularly in self-awareness. These results implicate mainly dopaminergic neurotransmission and the control of GABAergic function directly in the paralimbic network. The findings are important for understanding addiction, developmental disorders, and dysfunctional consciousness.

Altered working memory-related brain responses and white matter microstructure in extremely preterm-born children at school age

Preterm birth poses a risk for neurocognitive and behavioral development. Preterm children, who have not been diagnosed with neurological or cognitive deficits, enter normal schools and are expected to succeed as their term-born peers. Here we tested the hypotheses that despite an uneventful development after preterm birth, these children might exhibit subtle abnormalities in brain function and white-matter microstructure at school-age. We recruited 7.5-year-old children born extremely prematurely (<28 weeks' gestation), and age- and gender-matched term-born controls (≥37 weeks' gestation). We applied fMRI during working-memory (WM) tasks, and investigated white-matter microstructure with diffusion tensor imaging. Compared with controls, preterm-born children performed WM tasks less accurately, had reduced activation in several right prefrontal areas, and weaker deactivation of right temporal lobe areas. The weaker prefrontal activation correlated with poorer WM performance. Preterm-born children had higher fractional anisotropy (FA) and lower diffusivity than controls in several white-matter areas, and in the posterior cerebellum, the higher FA associated with poorer visuospatial test scores. In controls, higher FA and lower diffusivity correlated with faster WM performance. Together these findings demonstrate weaker WM-related brain activations and altered white matter microstructure in children born extremely preterm, who had normal global cognitive ability.

A machine learning investigation of volumetric and functional MRI abnormalities in adults born preterm

Imaging studies have characterized functional and structural brain abnormalities in adults after premature birth, but these investigations have mostly used univariate methods that do not account for hypothesized interdependencies between brain regions or quantify accuracy in identifying individuals. To overcome these limitations, we used multivariate machine learning to identify gray matter volume (GMV) and amplitude of low frequency fluctuations (ALFF) brain patterns that best classify young adults born very preterm/very low birth weight (VP/VLBW; n = 94) from those born full-term (FT; n = 92). We then compared the spatial maps of the structural and functional brain signatures and validated them by assessing associations with clinical birth history and basic cognitive variables. Premature birth could be predicted with a balanced accuracy of 80.7% using GMV and 77.4% using ALFF. GMV predictions were mediated by a pattern of subcortical and middle temporal reductions and volumetric increases of the lateral prefrontal, medial prefrontal, and superior temporal gyrus regions. ALFF predictions were characterized by a pattern including increases in the thalamus, pre- and post-central gyri, and parietal lobes, in addition to decreases in the superior temporal gyri bilaterally. Decision scores from each classification, assessing the degree to which an individual was classified as a VP/VLBW case, were predicted by the number of days in neonatal hospitalization and birth weight. ALFF decision scores also contributed to the prediction of general IQ, which highlighted their potential clinical significance. Combined, the results clarified previous research and suggested that primary subcortical and temporal damage may be accompanied by disrupted neurodevelopment of the cortex.

Challenges in pediatric neuroimaging

Pediatric neuroimaging is challenging due the rapid structural, metabolic, and functional changes that occur in the developing brain. A specially trained team is needed to produce high quality diagnostic images in children, due to their small physical size and immaturity. Patient motion, cooperation and medical condition dictate the methods and equipment used. A customized approach tailored to each child's age and functional status with the appropriate combination of dedicated staff, imaging hardware, and software is key; these range from low-tech techniques, such as feed and swaddle, to specialized small bore MRI scanners, MRI compatible incubators and neonatal head coils. New pre-and post-processing techniques can also compensate for the motion artifacts and low signal that often degrade neonatal scans.

White matter injury predicts disrupted functional connectivity and microstructure in very preterm born neonates

Objective

To determine whether the spatial extent and location of early-identified punctate white matter injury (WMI) is associated with regionally-specific disruptions in thalamocortical-connectivity in very-preterm born neonates.

Methods

37 very-preterm born neonates (median gestational age: 28.1 weeks; interquartile range [IQR]: 27–30) underwent early MRI (median age 32.9 weeks; IQR: 32–35), and WMI was identified in 13 (35%) neonates. Structural T1-weighted, resting-state functional Magnetic Resonance Imaging (rs-fMRI, n = 34) and Diffusion Tensor Imaging (DTI, n = 31) sequences were acquired using 3 T-MRI. A probabilistic map of WMI was developed for the 13 neonates demonstrating brain injury. A neonatal atlas was applied to the WMI maps, rs-fMRI and DTI analyses to extract volumetric, functional and microstructural data from regionally-specific brain areas. Associations of thalamocortical-network strength and alterations in fractional anisotropy (FA, a measure of white-matter microstructure) with WMI volume were assessed in general linear models, adjusting for age at scan and cerebral volumes.

Results

WMI volume in the superior (β = −0.007; p = .02) and posterior corona radiata (β = −0.01; p = .01), posterior thalamic radiations (β = −0.01; p = .005) and superior longitudinal fasciculus (β = −0.02; p = .001) was associated with reduced connectivity strength between thalamus and parietal resting-state networks. WMI volume in the left (β = −0.02; p = .02) and right superior corona radiata (β = −0.03; p = .008), left posterior corona radiata (β = −0.03; p = .01), corpus callosum (β = −0.11; p < .0001) and right superior longitudinal fasciculus (β = −0.02; p = .02) was associated with functional connectivity strength between thalamic and sensorimotor networks. Increased WMI volume was also associated with decreased FA values in the corpus callosum (β = −0.004, p = .015).

Conclusions

Regionally-specific alterations in early functional and structural network complexity resulting from WMI may underlie impaired outcomes.

•

Lesions in white matter pathways predicted altered functional connectivity.

•

White matter lesions predicted alterations in white matter microstructure.

•

Findings of lesion location and size were regionally-specific.

•

White matter lesion size and location may underlie later delays in development.

Neurofeedback and the Neural Representation of Self: Lessons From Awake State and Sleep

Neurofeedback has been around for half a century, but despite some promising results it is not yet widely appreciated. Recently, some of the concerns about neurofeedback have been addressed with functional magnetic resonance imaging and magnetoencephalography adding their contributions to the long history of neurofeedback with electroencephalography. Attempts to address other concerns related to methodological issues with new experiments and meta-analysis of earlier studies, have opened up new questions about its efficacy. A key concern about neurofeedback is the missing framework to explain how improvements in very different and apparently unrelated conditions are achieved. Recent advances in neuroscience begin to address this concern. A particularly promising approach is the analysis of resting state of fMRI data, which has revealed robust covariations in brain networks that maintain their integrity in sleep and even anesthesia. Aberrant activity in three brain wide networks (i.e., the default mode, central executive and salience networks) has been associated with a number of psychiatric disorders. Recent publications have also suggested that neurofeedback guides the restoration of “normal” activity in these three networks. Using very recent results from our analysis of whole night MEG sleep data together with key concepts from developmental psychology, cloaked in modern neuroscience terms, a theoretical framework is proposed for a neural representation of the self, located at the core of a double onion-like structure of the default mode network. This framework fits a number of old and recent neuroscientific findings, and unites the way attention and memory operate in awake state and during sleep. In the process, safeguards are uncovered, put in place by evolution, before any interference with the core representation of self can proceed. Within this framework, neurofeedback is seen as set of methods for restoration of aberrant activity in large scale networks. The framework also admits quantitative measures of improvements to be made by personalized neurofeedback protocols. Finally, viewed through the framework developed, neurofeedback’s safe nature is revealed while raising some concerns for interventions that attempt to alter the neural self-representation bypassing the safeguards evolution has put in place.

Decreased functional connectivity and structural deficit in alertness network with right-sided temporal lobe epilepsy

Patients with temporal lobe epilepsy (TLE) often suffer from alertness alterations. However, specific regions connected with alertness remain controversial, and whether these regions have structural impairment is also elusive. This study aimed to investigate the characteristics and neural mechanisms underlying the functions and structures of alertness network in patients with right-sided temporal lobe epilepsy (rTLE) by performing the attentional network test (ANT), resting-state functional magnetic resonance imaging (R-SfMRI), and diffusion tensor imaging (DTI).A total of 47 patients with rTLE and 34 healthy controls underwent ANT, R-SfMRI, and DTI scan. The seed-based functional connectivity (FC) method and deterministic tractography were used to analyze the data.Patients with rTLE had longer reaction times in the no-cue and double-cue conditions. However, no differences were noted in the alertness effect between the 2 groups. The patient group had lower FC compared with the control group in the right inferior parietal lobe (IPL), amygdala, and insula. Structural deficits were found in the right parahippocampal gyrus, superior temporal pole, insula, and amygdala in the patient group compared with the control group. Also significantly negative correlations were observed between abnormal fractional anisotropy (between the right insula and the superior temporal pole) and illness duration in the patients with rTLE.The findings of this study suggested abnormal intrinsic and phasic alertness, decreased FC, and structural deficits within the alerting network in the rTLE. This study provided new insights into the mechanisms of alertness alterations in rTLE.

Diagnostic accuracy of early magnetic resonance imaging to determine motor outcomes in infants born preterm: a systematic review and meta-analysis

AIM

To examine the diagnostic ability of early magnetic resonance imaging (MRI; <36wks postmenstrual age) to detect later adverse motor outcomes or cerebral palsy (CP) in infants born preterm.

METHOD

Studies of infants born preterm with MRI earlier than 36 weeks postmenstrual age and quantitative motor data or a diagnosis of CP at or beyond 1 year corrected age were identified. Study details were extracted and meta-analyses performed where possible. Quality of included studies was evaluated with the QUADAS-2 (a revised tool for the quality assessment of diagnostic accuracy studies).

RESULTS

Thirty-one articles met the inclusion criteria, five of which reported diagnostic accuracy and five reported data sufficient for calculation of diagnostic accuracy. Early structural MRI global scores detected a later diagnosis of CP with a pooled sensitivity of 100% (95% confidence interval [CI] 86-100) and a specificity of 93% (95% CI 59-100). Global structural MRI scores determined adverse motor outcomes with a pooled sensitivity of 89% (95% CI 44-100) and a specificity of 98% (95% CI 90-100). White matter scores determined adverse motor outcomes with a pooled sensitivity of 33% (95% CI 20-48) and a specificity of 83% (95% CI 78-88).

INTERPRETATION

Early structural MRI has reasonable sensitivity and specificity to determine adverse motor outcomes and CP in infants born preterm. Greater reporting of diagnostic accuracy in studies examining relationships with motor outcomes and CP is required to facilitate clinical utility of early MRI.

WHAT THIS PAPER ADDS

Early magnetic resonance imaging (MRI) has reasonable sensitivity and specificity to determine later adverse motor outcomes and cerebral palsy (CP). Detection of infants who progressed to CP was stronger than motor outcomes. Global MRI scores determined adverse motor outcomes more accurately than white matter scores. Few studies report diagnostic accuracy of early MRI findings. Diagnostic accuracy is required to draw clinically meaningful conclusions from early MRI studies.