Alterations in Anatomical Covariance in the Prematurely Born

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

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

Hypoconnectivity between anterior insula and amygdala associates with future vulnerabilities in social development in a neurodiverse sample of neonates

Altered resting state functional connectivity (FC) involving the anterior insula (aINS), a key node in the salience network, has been reported consistently in autism. Here we examined, for the first time, FC between the aINS and the whole brain in a sample of full-term, postmenstrual age (PMA) matched neonates (mean 44.0 weeks, SD = 1.5) who due to family history have high likelihood (HL) for developing autism (n = 12) and in controls (n = 41) without family history of autism (low likelihood, LL). Behaviors associated with autism were evaluated between 12 and 18 months (M = 17.3 months, SD = 2.5) in a subsample (25/53) of participants using the First Year Inventory (FYI). Compared to LL controls, HL neonates showed hypoconnectivity between left aINS and left amygdala. Lower connectivity between the two nodes was associated with higher FYI risk scores in the social domain (r(25) = -0.561, p = .003) and this association remained robust when maternal mental health factors were considered. Considering that a subsample of LL participants (n = 14/41) underwent brain imaging during the fetal period at PMA 31 and 34 weeks, in an exploratory analysis, we evaluated prospectively development of the LaINS-Lamy connectivity and found that the two areas strongly coactivate throughout the third trimester of pregnancy. The study identifies left lateralized anterior insula-amygdala connectivity as a potential target of further investigation into neural circuitry that enhances likelihood of future onset of social behaviors associated with autism during neonatal and potentially prenatal periods.

Effects of Smoking Status and State on Intrinsic Connectivity

BACKGROUND

Smoking behavior during the first 24 hours of a quit attempt is a significant predictor of longer-term abstinence, yet little is known about the neurobiology of early tobacco abstinence. Specifically, the effects of acute tobacco deprivation and reinstatement on brain function-particularly at the level of large-scale network dynamics and assessed across the entire brain-remain incompletely understood. To address this gap, this study used a mixed within- and between-subjects design to assess the effects of smoking status (yes/no smoker) and state (deprived vs. satiated) on whole-brain patterns of intrinsic connectivity.

METHODS

Participants included 42 tobacco smokers who underwent resting-state functional magnetic resonance imaging following overnight abstinence (deprived state) and following smoking reinstatement (satiated state, randomized order across participants). Sixty healthy control nonsmokers underwent a single resting-state scan using the same acquisition parameters. Functional connectivity data were analyzed using both a canonical network-of-interest approach and a whole-brain, data-driven approach, i.e., intrinsic connectivity distribution.

RESULTS

Network-of-interest-based analyses indicated decreased functional connectivity within frontoparietal and salience networks among smokers relative to nonsmokers as well as effects of smoking state on default mode connectivity. In addition, intrinsic connectivity distribution analyses identified novel between-group differences in subcortical-cerebellar and corticocerebellar networks that were largely smoking state dependent.

CONCLUSIONS

These data demonstrate the importance of considering smoking state and the utility of using both theory- and data-driven analysis approaches. These data provide much-needed insight into the functional neurobiology of early abstinence, which may be used in the development of novel treatments.

Nonlinear manifold learning in functional magnetic resonance imaging uncovers a low-dimensional space of brain dynamics

Large-scale brain dynamics are believed to lie in a latent, low-dimensional space. Typically, the embeddings of brain scans are derived independently from different cognitive tasks or resting-state data, ignoring a potentially large-and shared-portion of this space. Here, we establish that a shared, robust, and interpretable low-dimensional space of brain dynamics can be recovered from a rich repertoire of task-based functional magnetic resonance imaging (fMRI) data. This occurs when relying on nonlinear approaches as opposed to traditional linear methods. The embedding maintains proper temporal progression of the tasks, revealing brain states and the dynamics of network integration. We demonstrate that resting-state data embeds fully onto the same task embedding, indicating similar brain states are present in both task and resting-state data. Our findings suggest analysis of fMRI data from multiple cognitive tasks in a low-dimensional space is possible and desirable.

The Application of Connectome-Based Predictive Modeling to the Maternal Brain: Implications for Mother-Infant Bonding

Maternal bonding early postpartum lays an important foundation for child development. Changing brain structure and function during pregnancy and postpartum may underscore maternal bonding. We employed connectome-based predictive modeling (CPM) to measure brain functional connectivity and predict self-reported maternal bonding in mothers at 2 and 8 months postpartum. At 2 months, CPM predicted maternal anxiety in the bonding relationship: Greater integration between cerebellar and motor-sensory-auditory networks and between frontoparietal and motor-sensory-auditory networks were associated with more maternal anxiety toward their infant. Furthermore, greater segregation between the cerebellar and frontoparietal, and within the motor-sensory-auditory networks, was associated with more maternal anxiety regarding their infant. We did not observe CPM prediction of maternal bonding impairments or rejection/anger toward the infant. Finally, considering 2 and 8 months of data, changes in network connectivity were associated with changes in maternal anxiety in the bonding relationship. Our results suggest that changing connectivity among maternal brain networks may provide insight into the mother-infant bond, specifically in the context of anxiety and the representation of the infant in the mother's mind. These findings provide an opportunity to mechanistically investigate approaches to enhance the connectivity of these networks to optimize the representational and behavioral quality of the caregiving relationship.

Morphological Development Trajectory and Structural Covariance Network of the Human Fetal Cortical Plate during the Early Second Trimester

During the early second trimester, the cortical plate, or "the developing cortex", undergoes immensely complex and rapid development to complete its major complement of neurons. However, morphological development of the cortical plate and the precise patterning of brain structural covariance networks during this period remain unexplored. In this study, we used 7.0 T high-resolution magnetic resonance images of brain specimens ranging from 14 to 22 gestational weeks to manually segment the cortical plate. Thickness, area expansion, and curvature (i.e., folding) across the cortical plate regions were computed, and correlations of thickness values among different cortical plate regions were measured to analyze fetal cortico-cortical structural covariance throughout development of the early second trimester. The cortical plate displayed significant increases in thickness and expansions in area throughout all regions but changes of curvature in only certain major sulci. The topological architecture and network properties of fetal brain covariance presented immature and inefficient organizations with low degree of integration and high degree of segregation. Altogether, our results provide novel insight on the developmental patterning of cortical plate thickness and the developmental origin of brain network architecture throughout the early second trimester.

Decreased amygdala volume in adults after premature birth

Premature-born infants have impaired amygdala structure, presumably due to increased stress levels of premature birth mediated by the amygdala. However, accounting for lifelong plasticity of amygdala, it is unclear whether such structural changes persist into adulthood. To address this problem, we stated the following questions: first, are whole amygdala volumes reduced in premature-born adults? And second, as adult anxiety traits are often increased after prematurity and linked with amygdala structure, are alterations in amygdala associated with adults' anxiety traits after premature birth? We addressed these questions by automated amygdala segmentation of MRI volumes in 101 very premature-born adults (< 32 weeks of gestation and/or birth weight below 1500 g) and 108 full-term controls at 26 years of age of a prospectively and longitudinally collected cohort. We found significantly lower whole amygdala volumes in premature-born adults. While premature-born adults had significantly higher T score for avoidant personality reflecting increased social anxiety trait, this trait was not correlated with amygdala volume alterations. Results demonstrate reduced amygdala volumes in premature born adults. Data suggest lasting effects of prematurity on amygdala structure.

Association of Maternal Prepregnancy Body Mass Index With Fetal Growth and Neonatal Thalamic Brain Connectivity Among Adolescent and Young Women

Importance

Higher maternal prepregnancy body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is associated with adverse long-term outcomes for offspring, including obesity, poorer cognitive and social abilities, and increased risk of psychiatric disorders. Less clear is whether higher maternal BMI disrupts fetal growth and brain development.

Objective

To investigate the association of maternal prepregnancy BMI with fetal growth and neonatal functional connectivity.

Design, Setting, and Participants

This prospective longitudinal cohort study was conducted from 2012 to 2017. Participants included nulliparous pregnant adolescent and young adult women, aged 14 to 19 years who were recruited in the second trimester through Columbia University Irving Medical Center and Weill Cornell Medical College. Women received routine prenatal care and had no major health problems at the time of recruitment. Data were analyzed from January 2018 to March 2020.

Exposures

Maternal prepregnancy BMI.

Main Outcomes and Measures

The main outcomes were fetal growth, measured as estimated fetal weight, and neonatal functional connectivity, measured using magnetic resonance imaging. Prepregnancy BMI and fetal ultrasonographic measurements were obtained from electronic health record review. Resting-state brain imaging data were acquired in infants within the first month of postnatal life. Functional connectivity was measured using intrinsic functional distribution and seed-based methods.

Results

Among 129 women recruited, 105 had ultrasonographic data from at least 2 points and were included in analyses. The mean (SD) age at delivery was 17.82 (1.31) years. Maternal prepregnancy BMI was positively associated with the slope of estimated fetal weight (β = 0.668; 95% CI, 0.163 to 1.175; P = .01) but not with fetal head circumference (β = -0.004; 95% CI, -0.024 to 0.016; P = .70). In a subsample of 45 infants with magnetic resonance imaging data, maternal prepregnancy BMI was positively correlated with global connectivity in the left thalamus. Using this thalamic region as a seed, higher maternal BMI was associated with greater local thalamic (both hemispheres) and lower frontothalamic connectivity.

Conclusions and Relevance

These results suggest that maternal prepregnancy BMI was associated with the development of regulation of body weight and thalamic functional brain connectivity in offspring even during fetal development.

Gestational Age is Dimensionally Associated with Structural Brain Network Abnormalities Across Development

Prematurity is associated with diverse developmental abnormalities, yet few studies relate cognitive and neurostructural deficits to a dimensional measure of prematurity. Leveraging a large sample of children, adolescents, and young adults (age 8-22 years) studied as part of the Philadelphia Neurodevelopmental Cohort, we examined how variation in gestational age impacted cognition and brain structure later in development. Participants included 72 preterm youth born before 37 weeks' gestation and 206 youth who were born at term (37 weeks or later). Using a previously-validated factor analysis, cognitive performance was assessed in three domains: (1) executive function and complex reasoning, (2) social cognition, and (3) episodic memory. All participants completed T1-weighted neuroimaging at 3 T to measure brain volume. Structural covariance networks were delineated using non-negative matrix factorization, an advanced multivariate analysis technique. Lower gestational age was associated with both deficits in executive function and reduced volume within 11 of 26 structural covariance networks, which included orbitofrontal, temporal, and parietal cortices as well as subcortical regions including the hippocampus. Notably, the relationship between lower gestational age and executive dysfunction was accounted for in part by structural network deficits. Together, these findings emphasize the durable impact of prematurity on cognition and brain structure, which persists across development.

Associations between different dimensions of prenatal distress, neonatal hippocampal connectivity, and infant memory

Prenatal maternal distress-an umbrella concept encompassing multiple negative psychological states including stress, anxiety, and depression-is a substantial prenatal exposure. Consistent across preclinical and human studies, the hippocampus displays alterations due to prenatal distress. Nevertheless, most prenatal distress studies do not focus on multiple dimensions of, have not examined hippocampal functional connectivity in association with, and do not consider observer-based functional outcomes related to distress. We investigated the effects of different dimensions of prenatal distress in pregnant adolescents, a population at high risk for distress, in association with neonatal hippocampal connectivity and infant memory. In pregnant adolescents (n = 42), we collected four measures of distress (perceived stress, depression, pregnancy-specific distress, and 24-h ambulatory salivary cortisol) during the 2nd and 3rd trimesters. Resting-state imaging data were acquired in their infants at 40-44 weeks post-menstrual age. Functional connectivity was measured from hippocampal seeds. Memory abilities were obtained at 4 months using the mobile conjugate reinforcement task. Shared across different dimensions of maternal distress, increased 3rd trimester maternal distress associated with weaker hippocampal-cingulate cortex connectivity and stronger hippocampal-temporal lobe connectivity. Perceived stress inversely correlated while hippocampal-cingulate cortex connectivity positively correlated with infant memory. Increased cortisol-collected during the 2nd, but not the 3rd, trimester-associated with weaker hippocampal-cingulate cortex connectivity and stronger hippocampal-temporal lobe connectivity. Different dimensions of prenatal maternal distress likely contribute shared and unique effects to shaping infant brain and behavior.

Differential Resting State Connectivity Responses to Glycemic State in Type 1 Diabetes

CONTEXT

Individuals with type 1 diabetes mellitus (T1DM) have alterations in brain activity that have been postulated to contribute to the adverse neurocognitive consequences of T1DM; however, the impact of T1DM and hypoglycemic unawareness on the brain's resting state activity remains unclear.

OBJECTIVE

To determine whether individuals with T1DM and hypoglycemia unawareness (T1DM-Unaware) had changes in the brain resting state functional connectivity compared to healthy controls (HC) and those with T1DM and hypoglycemia awareness (T1DM-Aware).

DESIGN

Observational study.

SETTING

Academic medical center.

PARTICIPANTS

27 individuals with T1DM and 12 HC volunteers participated in the study.

INTERVENTION

All participants underwent blood oxygenation level dependent (BOLD) resting state functional magnetic brain imaging during a 2-step hyperinsulinemic euglycemic (90 mg/dL)-hypoglycemic (60 mg/dL) clamp.

OUTCOME

Changes in resting state functional connectivity.

RESULTS

Using 2 separate methods of functional connectivity analysis, we identified distinct differences in the resting state brain responses to mild hypoglycemia between HC, T1DM-Aware, and T1DM-Unaware participants, particularly in the angular gyrus, an integral component of the default mode network (DMN). Furthermore, changes in angular gyrus connectivity also correlated with greater symptoms of hypoglycemia (r = 0.461, P = 0.003) as well as higher scores of perceived stress (r = 0.531, P = 0.016).

CONCLUSION

These findings provide evidence that individuals with T1DM have changes in the brain's resting state connectivity patterns, which may be further associated with differences in awareness to hypoglycemia. These changes in connectivity may be associated with alterations in functional outcomes among individuals with T1DM.

Prefrontal Cortical and Behavioral Adaptations to Surgical Delivery Mediated by Metabolic Principles

We previously observed an association between mode of delivery and brain mitochondrial mechanisms in pups. We also showed that mitochondrial processes impact adult behavior. However, no experimental data is available to causally connect mode of delivery with cellular processes of neurons in the cerebral cortex and adult behavior. Here we show that surgical delivery of pups alters mitochondrial dynamics and spine synapses of layer 3 pyramidal neurons of the prefrontal cortex compared to the values of mice delivered vaginally. These alterations in ultrastructure seen in adult mice delivered surgically were associated with the development of behavioral phenotypes resembling those characteristic of animal models of psychiatric illness. This included impaired performance in prepulse inhibition as well as hyperlocomotion in the open field and elevated plus maze tests. Knocking out a mitochondria-related gene, UCP-2, blocked cellular and behavioral adaptations induced by surgical delivery. These results highlight a crucial role for brain mitochondrial adaptations in the process of birth to affect neuronal circuitry in support of normal and altered adult behaviors. Further, these findings were supported with neuroimaging data from human neonates delivered vaginally and surgically, suggesting that the murine findings have human clinical relevance.

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.

Lower synaptic density is associated with depression severity and network alterations

Synaptic loss and deficits in functional connectivity are hypothesized to contribute to symptoms associated with major depressive disorder (MDD) and post-traumatic stress disorder (PTSD). The synaptic vesicle glycoprotein 2A (SV2A) can be used to index the number of nerve terminals, an indirect estimate of synaptic density. Here, we used positron emission tomography (PET) with the SV2A radioligand [11C]UCB-J to examine synaptic density in n = 26 unmedicated individuals with MDD, PTSD, or comorbid MDD/PTSD. The severity of depressive symptoms was inversely correlated with SV2A density, and individuals with high levels of depression showing lower SV2A density compared to healthy controls (n = 21). SV2A density was also associated with aberrant network function, as measured by magnetic resonance imaging (MRI) functional connectivity. This is the first in vivo evidence linking lower synaptic density to network alterations and symptoms of depression. Our findings provide further incentive to evaluate interventions that restore synaptic connections to treat depression.

Data-Driven Analysis of Functional Connectivity Reveals a Potential Auditory Verbal Hallucination Network

Schizophrenia is a severe global health problem, with over half of such patients experiencing auditory verbal hallucinations (AVHs). A better understanding of the neural correlates differentiating patients experiencing AVHs from patients not experiencing AVHs and healthy controls may identify targets that lead to better treatment strategies for AVHs. Employing 2 data-driven, voxel-based measure of functional connectivity, we studied 46 patients with schizophrenia or schizoaffective disorder (28 experiencing AVHs and 18 not experiencing AVHs). Twenty healthy controls matched for age, gender, ethnicity, education level, handedness, and estimated verbal intelligence were included for comparison. The intrinsic connectivity distribution (ICD) was used to model each voxel's connectivity to the rest of the brain using a Weibull distribution. To investigate lateralization of connectivity, we used cross-hemisphere ICD, a method that separates the contribution of each hemisphere to interrogate connectivity laterality. Patients with AVHs compared with patients without AVHs exhibited significantly decreased whole-brain connectivity in the medial prefrontal cortex and posterior cingulate cortex, less lateralized connectivity in left putamen, and more lateralized connectivity in left interior frontal gyrus. Correlations with Auditory Hallucination Rating Scale (AHRS) and post hoc seed connectivity analyses revealed significantly altered network connectivity. Using the results from all analyses comparing the patient groups and correlations with AHRS, we identified a potential AVH network, consisting of 25 nodes, showing substantial overlap with the default mode network and language processing networks. This network as a whole, instead of individual nodes, may represent actionable targets for interventions.

Resting-state functional connectivity predicts neuroticism and extraversion in novel individuals

The personality dimensions of neuroticism and extraversion are strongly associated with emotional experience and affective disorders. Previous studies reported functional magnetic resonance imaging (fMRI) activity correlates of these traits, but no study has used brain-based measures to predict them. Here, using a fully cross-validated approach, we predict novel individuals’ neuroticism and extraversion from functional connectivity (FC) data observed as they simply rested during fMRI scanning. We applied a data-driven technique, connectome-based predictive modeling (CPM), to resting-state FC data and neuroticism and extraversion scores (self-reported NEO Five Factor Inventory) from 114 participants of the Nathan Kline Institute Rockland sample. After dividing the whole brain into 268 nodes using a predefined functional atlas, we defined each individual’s FC matrix as the set of correlations between the activity timecourses of every pair of nodes. CPM identified networks consisting of functional connections correlated with neuroticism and extraversion scores, and used strength in these networks to predict a left-out individual’s scores. CPM predicted neuroticism and extraversion in novel individuals, demonstrating that patterns in resting-state FC reveal trait-level measures of personality. CPM also revealed predictive networks that exhibit some anatomical patterns consistent with past studies and potential new brain areas of interest in personality.

Influences on the Test-Retest Reliability of Functional Connectivity MRI and its Relationship with Behavioral Utility

Best practices are currently being developed for the acquisition and processing of resting-state magnetic resonance imaging data used to estimate brain functional organization—or “functional connectivity.” Standards have been proposed based on test–retest reliability, but open questions remain. These include how amount of data per subject influences whole-brain reliability, the influence of increasing runs versus sessions, the spatial distribution of reliability, the reliability of multivariate methods, and, crucially, how reliability maps onto prediction of behavior. We collected a dataset of 12 extensively sampled individuals (144 min data each across 2 identically configured scanners) to assess test–retest reliability of whole-brain connectivity within the generalizability theory framework. We used Human Connectome Project data to replicate these analyses and relate reliability to behavioral prediction. Overall, the historical 5-min scan produced poor reliability averaged across connections. Increasing the number of sessions was more beneficial than increasing runs. Reliability was lowest for subcortical connections and highest for within-network cortical connections. Multivariate reliability was greater than univariate. Finally, reliability could not be used to improve prediction; these findings are among the first to underscore this distinction for functional connectivity. A comprehensive understanding of test–retest reliability, including its limitations, supports the development of best practices in the field.

Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder

Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC-vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder.

Maternal Immune Activation During the Third Trimester Is Associated with Neonatal Functional Connectivity of the Salience Network and Fetal to Toddler Behavior

Prenatal maternal immune activation (MIA) is associated with altered brain development and risk of psychiatric disorders in offspring. Translational human studies of MIA are few in number. Alterations of the salience network have been implicated in the pathogenesis of the same psychiatric disorders associated with MIA. If MIA is pathogenic, then associated abnormalities in the salience network should be detectable in neonates immediately after birth. We tested the hypothesis that third trimester MIA of adolescent women who are at risk for high stress and inflammation is associated with the strength of functional connectivity in the salience network of their neonate. Thirty-six women underwent blood draws to measure interleukin-6 (IL-6) and C-reactive protein (CRP) and electrocardiograms to measure fetal heart rate variability (FHRV) at 34-37 weeks gestation. Resting-state imaging data were acquired in the infants at 40-44 weeks postmenstrual age (PMA). Functional connectivity was measured from seeds placed in the anterior cingulate cortex and insula. Measures of cognitive development were obtained at 14 months PMA using the Bayley Scales of Infant and Toddler Development-Third Edition (BSID-III). Both sexes were studied. Regions in which the strength of the salience network correlated with maternal IL-6 or CRP levels included the medial prefrontal cortex, temporoparietal junction, and basal ganglia. Maternal CRP level correlated inversely with FHRV acquired at the same gestational age. Maternal CRP and IL-6 levels correlated positively with measures of cognitive development on the BSID-III. These results suggest that MIA is associated with short- and long-term influences on offspring brain and behavior.SIGNIFICANCE STATEMENT Preclinical studies in rodents and nonhuman primates and epidemiological studies in humans suggest that maternal immune activation (MIA) alters the development of brain circuitry and associated behaviors, placing offspring at risk for psychiatric illness. Consistent with preclinical findings, we show that maternal third trimester interleukin-6 and C-reactive protein levels are associated with neonatal functional connectivity and with both fetal and toddler behavior. MIA-related functional connectivity was localized to the salience, default mode, and frontoparietal networks, which have been implicated in the pathogenesis of psychiatric disorders. Our results suggest that MIA alters functional connectivity in the neonatal brain, that those alterations have consequences for cognition, and that these findings may provide pathogenetic links between preclinical and epidemiological studies associating MIA with psychiatric risk in offspring.

Cerebellar and prefrontal cortical alterations in PTSD: structural and functional evidence

BACKGROUND

Neuroimaging studies have revealed that disturbances in network organization of key brain regions may underlie cognitive and emotional dysfunction in posttraumatic stress disorder (PTSD). Examining both brain structure and function in the same population may further our understanding of network alterations in PTSD.

METHODS

We used tensor-based morphometry (TBM) and intrinsic connectivity distribution (ICD) to identify regions of altered volume and functional connectivity in unmedicated individuals with PTSD (n=21) and healthy comparison (HC) participants (n=18). These regions were then used as seeds for follow-up anatomical covariance and functional connectivity analyses.

RESULTS

Smaller volume in the cerebellum and weaker structural covariance between the cerebellum seed and middle temporal gyrus were observed in the PTSD group. Individuals with PTSD also exhibited lower whole-brain connectivity in the cerebellum, dorsolateral prefrontal cortex (dlPFC) and medial prefrontal cortex (mPFC). Functional connectivity in the cerebellum and grey matter volume in the dlPFC were negatively correlated with PTSD severity as measured by the DSM-5 PTSD checklist (PCL-5; r= -.0.77, r=-0.79). Finally, seed connectivity revealed weaker connectivity within nodes of the central executive network (right and left dlPFC), and between nodes of the default mode network (mPFC and cerebellum) and the supramarginal gyrus, in the PTSD group.

CONCLUSION

We demonstrate structural and functional alterations in PTSD converging on the PFC and cerebellum. Whilst PFC alterations are relatively well established in PTSD, the cerebellum has not generally been considered a key region in PTSD. Our findings add to a growing evidence base implicating cerebellar involvement in the pathophysiology of PTSD.

Structured Spontaneity: Building Circuits in the Human Prenatal Brain

Early brain activity is crucial for neurogenesis and the development of brain networks. However, it has been challenging to localize regions in the developing human brain that contribute to spontaneous waves of neuronal activity. Recently, Arichi and colleagues reported that the temporal and heteromodal insular cortices have a central role in propagating these neural instructional signals.

Volumetric grey matter alterations in adolescents and adults born very preterm suggest accelerated brain maturation

Previous research investigating structural neurodevelopmental alterations in individuals who were born very preterm demonstrated a complex pattern of grey matter changes that defy straightforward summary. Here we addressed this problem by characterising volumetric brain alterations in individuals who were born very preterm from adolescence to adulthood at three hierarchically related levels - global, modular and regional. We demarcated structural components that were either particularly resilient or vulnerable to the impact of very preterm birth. We showed that individuals who were born very preterm had smaller global grey matter volume compared to controls, with subcortical and medial temporal regions being particularly affected. Conversely, frontal and lateral parieto-temporal cortices were relatively resilient to the effects of very preterm birth, possibly indicating compensatory mechanisms. Exploratory analyses supported this hypothesis by showing a stronger association between lateral parieto-temporal volume and IQ in the very preterm group compared to controls. We then related these alterations to brain maturation processes. Very preterm individuals exhibited a higher maturation index compared to controls, indicating accelerated brain maturation and this was specifically associated with younger gestational age. We discuss how the findings of accelerated maturation might be reconciled with evidence of delayed maturation at earlier stages of development.

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Hierarchically related structural brain alterations in very preterm individuals span adolescence and adulthood.

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Structural volumetric components that showed resiliency in very preterm individuals were associated with higher IQ.

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Very preterm individuals showed accelerated brain maturation compared to a large dataset of term-born controls.

Event-Related Potentials Reflect Deficits in Lexical Access: The N200 in Prematurely Born School-Aged Children

OBJECTIVES

Children born preterm have a high prevalence of neurocognitive deficits early in life. We examined whether the neural correlates of lexical access are atypical in 9-year-old children born preterm, and whether the findings of acoustic mapping correlate with language- and attention-related skills.

PATIENTS AND METHODS

The subjects were fourteen 9-year-old children born preterm and 14 full-term, typically developing controls. Two auditory event-related potential (ERP) components, the N200 and the N400, were used to assess discrimination response and word recognition. A set of behavioral tests (naming ability, auditory attention, phonological processing, pseudoword repetition, and comprehension of instructions) was performed, and the results were compared with the amplitudes, latencies, and scalp distribution of the ERP results.

RESULTS

In prematurely born children, neurophysiological deficits were associated with difficulties in auditory discrimination. The N200 amplitude correlated significantly with auditory attention and pseudoword repetition. The scalp distribution of both the N200 and the N400 was broader in children born preterm than in the controls. Low scores in the neuropsychological tasks referred to difficulties in auditory processing and memory.

CONCLUSIONS

Children born preterm have difficulties in lexical access together with memory- and attention-related processes, which may have a longstanding impact on their school outcomes and academic skills.

Multi-modal analysis of functional connectivity and cerebral blood flow reveals shared and unique effects of propofol in large-scale brain networks

Anesthesia-induced changes in functional connectivity and cerebral blow flow (CBF) in large-scale brain networks have emerged as key markers of reduced consciousness. However, studies of functional connectivity disagree on which large-scale networks are altered or preserved during anesthesia, making it difficult to find a consensus amount studies. Additionally, pharmacological alterations in CBF could amplify or occlude changes in connectivity due to the shared variance between CBF and connectivity. Here, we used data-driven connectivity methods and multi-modal imaging to investigate shared and unique neural correlates of reduced consciousness for connectivity in large-scale brain networks. Rs-fMRI and CBF data were collected from the same subjects during an awake and deep sedation condition induced by propofol. We measured whole-brain connectivity using the intrinsic connectivity distribution (ICD), a method not reliant on pre-defined seed regions, networks of interest, or connectivity thresholds. The shared and unique variance between connectivity and CBF were investigated. Finally, to account for shared variance, we present a novel extension to ICD that incorporates cerebral blood flow (CBF) as a scaling factor in the calculation of global connectivity, labeled CBF-adjusted ICD). We observed altered connectivity in multiple large-scale brain networks including the default mode (DMN), salience, visual, and motor networks and reduced CBF in the DMN, frontoparietal network, and thalamus. Regional connectivity and CBF were significantly correlated during both the awake and propofol condition. Nevertheless changes in connectivity and CBF between the awake and deep sedation condition were only significantly correlated in a subsystem of the DMN, suggesting that, while there is significant shared variance between the modalities, changes due to propofol are relatively unique. Similar, but less significant, results were observed in the CBF-adjusted ICD analysis, providing additional evidence that connectivity differences were not fully explained by CBF. In conclusion, these results provide further evidence of alterations in large-scale brain networks are associated with reduced consciousness and suggest that different modalities capture unique aspects of these large scale changes.

Does prenatal stress alter the developing connectome?

Human neurodevelopment requires the organization of neural elements into complex structural and functional networks called the connectome. Emerging data suggest that prenatal exposure to maternal stress plays a role in the wiring, or miswiring, of the developing connectome. Stress-related symptoms are common in women during pregnancy and are risk factors for neurobehavioral disorders ranging from autism spectrum disorder, attention deficit hyperactivity disorder, and addiction, to major depression and schizophrenia. This review focuses on structural and functional connectivity imaging to assess the impact of changes in women's stress-based physiology on the dynamic development of the human connectome in the fetal brain.

Third Trimester Brain Growth in Preterm Infants Compared With In Utero Healthy Fetuses

BACKGROUND AND OBJECTIVES

Compared with term infants, preterm infants have impaired brain development at term-equivalent age, even in the absence of structural brain injury. However, details regarding the onset and progression of impaired preterm brain development over the third trimester are unknown. Our primary objective was to compare third-trimester brain volumes and brain growth trajectories in ex utero preterm infants without structural brain injury and in healthy in utero fetuses. As a secondary objective, we examined risk factors associated with brain volumes in preterm infants over the third-trimester postconception.

METHODS

Preterm infants born before 32 weeks of gestational age (GA) and weighing <1500 g with no evidence of structural brain injury on conventional MRI and healthy pregnant women were prospectively recruited. Anatomic T2-weighted brain images of preterm infants and healthy fetuses were parcellated into the following regions: cerebrum, cerebellum, brainstem, and intracranial cavity.

RESULTS

We studied 205 participants (75 preterm infants and 130 healthy control fetuses) between 27 and 39 weeks' GA. Third-trimester brain volumes were reduced and brain growth trajectories were slower in the ex utero preterm group compared with the in utero healthy fetuses in the cerebrum, cerebellum, brainstem, and intracranial cavity. Clinical risk factors associated with reduced brain volumes included dexamethasone treatment, the presence of extra-axial blood on brain MRI, confirmed sepsis, and duration of oxygen support.

CONCLUSIONS

These preterm infants exhibited impaired third-trimester global and regional brain growth in the absence of cerebral/cerebellar parenchymal injury detected by using conventional MRI.

Multisite reliability of MR-based functional connectivity

Recent years have witnessed an increasing number of multisite MRI functional connectivity (fcMRI) studies. While multisite studies provide an efficient way to accelerate data collection and increase sample sizes, especially for rare clinical populations, any effects of site or MRI scanner could ultimately limit power and weaken results. Little data exists on the stability of functional connectivity measurements across sites and sessions. In this study, we assess the influence of site and session on resting state functional connectivity measurements in a healthy cohort of traveling subjects (8 subjects scanned twice at each of 8 sites) scanned as part of the North American Prodrome Longitudinal Study (NAPLS). Reliability was investigated in three types of connectivity analyses: (1) seed-based connectivity with posterior cingulate cortex (PCC), right motor cortex (RMC), and left thalamus (LT) as seeds; (2) the intrinsic connectivity distribution (ICD), a voxel-wise connectivity measure; and (3) matrix connectivity, a whole-brain, atlas-based approach to assessing connectivity between nodes. Contributions to variability in connectivity due to subject, site, and day-of-scan were quantified and used to assess between-session (test-retest) reliability in accordance with Generalizability Theory. Overall, no major site, scanner manufacturer, or day-of-scan effects were found for the univariate connectivity analyses; instead, subject effects dominated relative to the other measured factors. However, summaries of voxel-wise connectivity were found to be sensitive to site and scanner manufacturer effects. For all connectivity measures, although subject variance was three times the site variance, the residual represented 60-80% of the variance, indicating that connectivity differed greatly from scan to scan independent of any of the measured factors (i.e., subject, site, and day-of-scan). Thus, for a single 5min scan, reliability across connectivity measures was poor (ICC=0.07-0.17), but increased with increasing scan duration (ICC=0.21-0.36 at 25min). The limited effects of site and scanner manufacturer support the use of multisite studies, such as NAPLS, as a viable means of collecting data on rare populations and increasing power in univariate functional connectivity studies. However, the results indicate that aggregation of fcMRI data across longer scan durations is necessary to increase the reliability of connectivity estimates at the single-subject level.