The association of maternal-infant interactive behavior, dyadic frontal alpha asymmetry, and maternal anxiety in a smartphone-adapted still face paradigm.

Mother-infant interactions form a strong basis for emotion regulation development in infants. These interactions can be affected by various factors, including maternal postnatal anxiety. Electroencephalography (EEG) hyperscanning allows for simultaneous assessment of mother-infant brain-to-behavior association during stressful events, such as the still-face paradigm (SFP). This study aimed at investigating dyadic interactive behavior and brain-to-behavior association across SFP and identifying neural correlates of mother-infant interactions in the context of maternal postnatal anxiety. We measured frontal alpha asymmetry (FAA), a physiological correlate of emotion regulation and a potential marker of risk for psychopathology. To emulate real-life interactions, EEG and behavioral data were collected from 38 mother-infant dyads during a smartphone-adapted dual-SFP. Although the behavioral data showed a clear still-face effect for the smartphone-adapted SFP, this was not reflected in the infant or maternal FAA. Brain-to-behavior data showed higher infant negative affect being associated with more infant leftward FAA during the still-face episodes. Finally, mothers with higher postnatal anxiety showed more right FAA during the first still-face episode, suggesting negative affectivity and a need to withdraw from the situation. Our results form a baseline for further research assessing the effects of maternal postnatal anxiety on infants' FAA and dyadic interactive behavior.

Maternal anxiety during pregnancy is associated with weaker prefrontal functional connectivity in adult offspring.

BACKGROUND: The connectome, constituting a unique fingerprint of a person's brain, may be influenced by its prenatal environment, potentially affecting later-life resilience and mental health. METHODS: We conducted a prospective resting-state functional Magnetic Resonance Imaging study in 28-year-old offspring (N = 49) of mothers whose anxiety was monitored during pregnancy. Two offspring anxiety subgroups were defined: "High anxiety" (n = 13) group versus "low-to-medium anxiety" (n = 36) group, based on maternal self-reported state anxiety at 12-22 weeks of gestation. To predict resting-state functional connectivity of 32 by 32 ROIs, maternal state anxiety during pregnancy was included as a predictor in general linear models for both ROI-to-ROI and graph theoretical metrics. Sex, birth weight and postnatal anxiety were included as covariates. RESULTS: Higher maternal anxiety was associated with weaker functional connectivity of medial prefrontal cortex with left inferior frontal gyrus (t = 3.45, pFDR < 0.05). Moreover, network-based statistics (NBS) confirmed our finding and revealed an additional association of weaker connectivity between left lateral prefontal cortex with left somatosensory motor gyrus in the offspring. While our results showed a general pattern of lower functional connectivity in adults prenatally exposed to maternal anxiety, we did not observe significant differences in global brain networks between groups. CONCLUSIONS: Weaker (medial) prefrontal cortex functional connectivity in the high anxiety adult offspring group suggests a long-term negative impact of prenatal exposure to high maternal anxiety, extending into adulthood. To prevent mental health problems at population level, universal primary prevention strategies should aim at lowering maternal anxiety during pregnancy.

Brains in Sync: Practical Guideline for Parent-Infant EEG During Natural Interaction.

Parent-infant EEG is a novel hyperscanning paradigm to measure social interaction simultaneously in the brains of parents and infants. The number of studies using parent-infant dual-EEG as a theoretical framework to measure brain-to-brain synchrony during interaction is rapidly growing, while the methodology for measuring synchrony is not yet uniform. While adult dual-EEG methodology is quickly improving, open databases, tutorials, and methodological validations for dual-EEG with infants are largely missing. In this practical guide, we provide a step-by-step manual on how to implement and run parent-infant EEG paradigms in a neurodevelopmental laboratory in naturalistic settings (e.g., free interactions). Next, we highlight insights on the variety of choices that can be made during (pre)processing dual-EEG data, including recommendations on interpersonal neural coupling metrics and interpretations of the results. Moreover, we provide an exemplar dataset of two mother-infant dyads during free interactions ("free play") that may serve as practice material. Instead of providing a critical note, we would like to move the field of parent-infant EEG forward and be transparent about the challenges that come along with the exciting opportunity to study the development of our social brain within the naturalistic context of dual-EEG.

In sync with your child: The potential of parent-child electroencephalography in developmental research.

Healthy interaction between parent and child is foundational for the child's socioemotional development. Recently, an innovative paradigm shift in electroencephalography (EEG) research has enabled the simultaneous measurement of neural activity in caregiver and child. This dual-EEG or hyperscanning approach, termed parent-child dual-EEG, combines the strength of both behavioral observations and EEG methods. In this review, we aim to inform on the potential of dual-EEG in parents and children (0-6 years) for developmental researchers. We first provide a general overview of the dual-EEG technique and continue by reviewing the first empirical work on the emerging field of parent-child dual-EEG, discussing the limited but fascinating findings on parent-child brain-to-behavior and brain-to-brain synchrony. We then continue by providing an overview of dual-EEG analysis techniques, including the technical challenges and solutions one may encounter. We finish by discussing the potential of parent-child dual-EEG for the future of developmental research. The analysis of multiple EEG data is technical and challenging, but when performed well, parent-child EEG may transform the way we understand how caregiver and child connect on a neurobiological level. Importantly, studying objective physiological measures of parent-child interactions could lead to the identification of novel brain-to-brain synchrony markers of interaction quality.

Preterm infants with isolated cerebellar hemorrhage show bilateral cortical alterations at term equivalent age.

The cerebellum is connected to numerous regions of the contralateral side of the cerebrum. Motor and cognitive deficits following neonatal cerebellar hemorrhages (CbH) in extremely preterm neonates may be related to remote cortical alterations, following disrupted cerebello-cerebral connectivity as was previously shown within six CbH infants. In this retrospective case series study, we used MRI and advanced surface-based analyses to reconstruct gray matter (GM) changes in cortical thickness and cortical surface area in extremely preterm neonates (median age = 26; range: 24.9-26.7 gestational weeks) with large isolated unilateral CbH (N = 5 patients). Each CbH infant was matched with their own preterm infant cohort (range: 20-36 infants) based on sex and gestational age at birth. On a macro level, our data revealed that the contralateral cerebral hemisphere of CbH neonates did not show less cortical thickness or cortical surface area than their ipsilateral cerebral hemisphere at term. None of the cases differed from their matched cohort groups in average cortical thickness or average cortical surface area in the ipsilateral or contralateral cerebral hemisphere. On a micro (i.e. vertex) level, we established high variability in significant local cortical GM alteration patterns across case-cohort groups, in which the cases showed thicker or bigger volume in some regions, among which the caudal middle frontal gyrus, insula and parahippocampal gyrus, and thinner or less volume in other regions, among which the cuneus, precuneus and supratentorial gyrus. This study highlights that cerebellar injury during postnatal stages may have  widespread bilateral influence on the early maturation of cerebral cortical regions, which implicate complex cerebello-cerebral interactions to be present at term birth.

Functional Connectome of the Fetal Brain.

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

Multiscale examination of cytoarchitectonic similarity and human brain connectivity.

The human brain comprises an efficient communication network, with its macroscale connectome organization argued to be directly associated with the underlying microscale organization of the cortex. Here, we further examine this link in the human brain cortex by using the ultrahigh-resolution BigBrain dataset; 11,660 BigBrain profiles of laminar cell structure were extracted from the BigBrain data and mapped to the MRI based Desikan-Killiany atlas used for macroscale connectome reconstruction. Macroscale brain connectivity was reconstructed based on the diffusion-weighted imaging dataset from the Human Connectome Project and cross-correlated to the similarity of laminar profiles. We showed that the BigBrain profile similarity between interconnected cortical regions was significantly higher than those between nonconnected regions. The pattern of BigBrain profile similarity across the entire cortex was also found to be strongly correlated with the pattern of cortico-cortical connectivity at the macroscale. Our findings suggest that cortical regions with higher similarity in the laminar cytoarchitectonic patterns have a higher chance of being connected, extending the evidence for the linkage between macroscale connectome organization and microscale cytoarchitecture.

Hubs in the human fetal brain network.

Advances in neuroimaging and network analyses have lead to discovery of highly connected regions, or hubs, in the connectional architecture of the human brain. Whether these hubs emerge in utero, has yet to be examined. The current study addresses this question and aims to determine the location of neural hubs in human fetuses. Fetal resting-state fMRI data (N = 105) was used to construct connectivity matrices for 197 discrete brain regions. We discovered that within the connectional functional organization of the human fetal brain key hubs are emerging. Consistent with prior reports in infants, visual and motor regions were identified as emerging hub areas, specifically in cerebellar areas. We also found evidence for network hubs in association cortex, including areas remarkably close to the adult fusiform facial and Wernicke areas. Functional significance of hub structure was confirmed by computationally deleting hub versus random nodes and observing that global efficiency decreased significantly more when hubs were removed (p < .001). Taken together, we conclude that both primary and association brain regions demonstrate centrality in network organization before birth. While fetal hubs may be important for facilitating network communication, they may also form potential points of vulnerability in fetal brain development.

Multimodal analysis of cortical chemoarchitecture and macroscale fMRI resting-state functional connectivity.

The cerebral cortex is well known to display a large variation in excitatory and inhibitory chemoarchitecture, but the effect of this variation on global scale functional neural communication and synchronization patterns remains less well understood. Here, we provide evidence of the chemoarchitecture of cortical regions to be associated with large-scale region-to-region resting-state functional connectivity. We assessed the excitatory versus inhibitory chemoarchitecture of cortical areas as an ExIn ratio between receptor density mappings of excitatory (AMPA, M1 ) and inhibitory (GABAA , M2 ) receptors, computed on the basis of data collated from pioneering studies of autoradiography mappings as present in literature of the human (2 datasets) and macaque (1 dataset) cortex. Cortical variation in ExIn ratio significantly correlated with total level of functional connectivity as derived from resting-state functional connectivity recordings of cortical areas across all three datasets (human I: P = 0.0004; human II: P = 0.0008; macaque: P = 0.0007), suggesting cortical areas with an overall more excitatory character to show higher levels of intrinsic functional connectivity during resting-state. Our findings are indicative of the microscale chemoarchitecture of cortical regions to be related to resting-state fMRI connectivity patterns at the global system's level of connectome organization. Hum Brain Mapp 37:3103-3113, 2016. © 2016 Wiley Periodicals, Inc.

Cortical chemoarchitecture shapes macroscale effective functional connectivity patterns in macaque cerebral cortex.

The mammalian cortex is a complex system of-at the microscale level-interconnected neurons and-at the macroscale level-interconnected areas, forming the infrastructure for local and global neural processing and information integration. While the effects of regional chemoarchitecture on local cortical activity are well known, the effect of local neurotransmitter receptor organization on the emergence of large scale region-to-region functional interactions remains poorly understood. Here, we examined reports of effective functional connectivity-as measured by the action of strychnine administration acting on the chemical balance of cortical areas-in relation to underlying regional variation in microscale neurotransmitter receptor density levels in the macaque cortex. Linking cortical variation in microscale receptor density levels to collated information on macroscale functional connectivity of the macaque cortex, we show macroscale patterns of effective corticocortical functional interactions-and in particular, the strength of connectivity of efferent macroscale pathways-to be related to the ratio of excitatory and inhibitory neurotransmitter receptor densities of cortical areas. Our findings provide evidence for the microscale chemoarchitecture of cortical areas to have a direct stimulating influence on the emergence of macroscale functional connectivity patterns in the mammalian brain. Hum Brain Mapp 37:1856-1865, 2016. © 2016 Wiley Periodicals, Inc.

Connectomics in Schizophrenia: From Early Pioneers to Recent Brain Network Findings.

Schizophrenia has been conceptualized as a brain network disorder. The historical roots of connectomics in schizophrenia go back to the late 19th century, when influential scholars such as Theodor Meynert, Carl Wernicke, Emil Kraepelin, and Eugen Bleuler worked on a theoretical understanding of the multifaceted syndrome that is currently referred to as schizophrenia. Their work contributed to the understanding that symptoms such as psychosis and cognitive disorganization might stem from abnormal integration or dissociation due to disruptions in the brain's association fibers. As methods to test this hypothesis were long lacking, the claims of these early pioneers remained unsupported by empirical evidence for almost a century. In this review, we revisit and pay tribute to the old masters and, discussing recent findings from the developing field of disease connectomics, we examine how their pioneering hypotheses hold up in light of current evidence.