Development of the spontaneous activity transients and ongoing cortical activity in human preterm babies

Resting state electroencephalographic brain activity in neonates can predict age and is indicative of neurodevelopmental outcome

OBJECTIVE

Electroencephalography (EEG) can be used to estimate neonates' biological brain age. Discrepancies between postmenstrual age and brain age, termed the brain age gap, can potentially quantify maturational deviation. Existing brain age EEG models are not well suited to clinical cot-side use for estimating neonates' brain age gap due to their dependency on relatively large data and pre-processing requirements.

METHODS

We trained a deep learning model on resting state EEG data from preterm neonates with normal neurodevelopmental Bayley Scale of Infant and Toddler Development (BSID) outcomes, using substantially reduced data requirements. We subsequently tested this model in two independent datasets from two clinical sites.

RESULTS

In both test datasets, using only 20 min of resting-state EEG activity from a single channel, the model generated accurate age predictions: mean absolute error = 1.03 weeks (p-value = 0.0001) and 0.98 weeks (p-value = 0.0001). In one test dataset, where 9-month follow-up BSID outcomes were available, the average neonatal brain age gap in the severe abnormal outcome group was significantly larger than that of the normal outcome group: difference in mean brain age gap = 0.50 weeks (p-value = 0.04).

CONCLUSIONS

These findings demonstrate that the deep learning model generalises to independent datasets from two clinical sites, and that the model's brain age gap magnitudes differ between neonates with normal and severe abnormal follow-up neurodevelopmental outcomes.

SIGNIFICANCE

The magnitude of neonates' brain age gap, estimated using only 20 min of resting state EEG data from a single channel, can encode information of clinical neurodevelopmental value.

Spatiotemporal patterns in cortical development: Age, puberty, and individual variability from 9 to 13 years of age

Humans and nonhuman primate studies suggest that timing and tempo of cortical development varies neuroanatomically along a sensorimotor-to-association (S-A) axis. Prior human studies have reported a principal S-A axis across various modalities, but largely rely on cross-sectional samples with wide age-ranges. Here, we investigate developmental changes and individual variability in cortical organization along the S-A axis between the ages of 9-13 years using a large, longitudinal sample (N = 2487-3747, 46-50% female) from the Adolescent Brain Cognitive Development Study (ABCD Study®). This work assesses multiple aspects of neurodevelopment indexed by changes in cortical thickness, cortical microarchitecture, and resting-state functional fluctuations. First, we evaluated S-A organization in age-related changes and, then, computed individual-level S-A alignment in brain changes and assessing differences therein due to age, sex, and puberty. Varying degrees of linear and quadratic age-related brain changes were identified along the S-A axis. Yet, these patterns of cortical development were overshadowed by considerable individual variability in S-A alignment. Even within individuals, there was little correspondence between S-A patterning across the different aspects of neurodevelopment investigated (i.e., cortical morphology, microarchitecture, function). Some of the individual variation in developmental patterning of cortical morphology and microarchitecture was explained by age, sex, and pubertal development. Altogether, this work contextualizes prior findings that regional age differences do progress along an S-A axis at a group level, while highlighting broad variation in developmental change between individuals and between aspects of cortical development, in part due to sex and puberty.

Significance Statement

Understanding normative patterns of adolescent brain change, and individual variability therein, is crucial for disentangling healthy and abnormal development. We used longitudinal human neuroimaging data to study several aspects of neurodevelopment during early adolescence and assessed their organization along a sensorimotor-to-association (S-A) axis across the cerebral cortex. Age differences in brain changes were linear and curvilinear along this S-A axis. However, individual-level sensorimotor-association alignment varied considerably, driven in part by differences in age, sex, and pubertal development.

Quantitative analysis of high-frequency activity in neonatal EEG

OBJECTIVE

To determine the presence and potential utility of independent high-frequency activity recorded from scalp electrodes in the electroencephalogram (EEG) of newborns.

METHODS

We compare interburst intervals and continuous activity at different frequencies for EEGs retrospectively recorded at 256 Hz from 4 newborn groups: 1) 36 preterms (<32 weeks' gestational age, GA); 2) 12 preterms (32-37 weeks' GA); 3) 91 healthy full terms; 4) 15 full terms with hypoxic-ischemic encephalopathy (HIE). At 4 standard frequency bands (delta, 0.5-3 Hz; theta, 3-8 Hz; alpha, 8-15 Hz; beta, 15-30 Hz) and 3 higher-frequency bands (gamma1, 30-48 Hz; gamma2, 52-99 Hz; gamma3, 107-127 Hz), we compared power spectral densities (PSDs), quantitative features, and machine learning model performance. Feature selection and further machine learning methods were performed on one cohort.

RESULTS

We found significant (P < 0.01) differences in PSDs, quantitative analysis, and machine learning modelling at the higher-frequency bands. Machine learning models using only high-frequency features performed best in preterm groups 1 and 2 with a median (95% confidence interval, CI) Matthews correlation coefficient (MCC) of 0.71 (0.12-0.88) and 0.66 (0.36-0.76) respectively. Interburst interval-detector models using both high- and standard-bandwidths produced the highest median MCCs in all four groups. High-frequency features were largely independent of standard-bandwidth features, with only 11/84 (13.1%) of correlations statistically significant. Feature selection methods produced 7 to 9 high-frequency features in the top 20 feature set.

CONCLUSIONS

This is the first study to identify independent high-frequency activity in newborn EEG using in-depth quantitative analysis. Expanding the EEG bandwidths of analysis has the potential to improve both quantitative and machine-learning analysis, particularly in preterm EEG.

Feasibility of automated early postnatal sleep staging in extremely and very preterm neonates using dual-channel EEG

OBJECTIVE

To investigate the feasibility of automated sleep staging based on quantitative analysis of dual-channel electroencephalography (EEG) for extremely and very preterm infants during their first postnatal days.

METHODS

We enrolled 17 preterm neonates born between 25 and 30 weeks of gestational age. Three-hour behavioral sleep observations and simultaneous dual-channel EEG monitoring were conducted for each infant within their first 72 hours after birth. Four kinds of representative and complementary quantitative EEG (qEEG) metrics (i.e., bursting, synchrony, spectral power, and complexity) were calculated and compared between active sleep, quiet sleep, and wakefulness. All analyses were performed in offline mode.

RESULTS

In separate comparison analyses, significant differences between sleep-wake states were found for bursting, spectral power and complexity features. The automated sleep-wake state classifier based on the combination of all qEEG features achieved a macro-averaged area under the curve of receiver operating characteristic of 74.8%. The complexity features contributed the most to sleep-wake state classification.

CONCLUSIONS

It is feasible to distinguish between sleep-wake states within the first 72 postnatal hours for extremely and very preterm infants using qEEG metrics.

SIGNIFICANCE

Our findings offer the possibility of starting personalized care dependent on preterm infants' sleep-wake states directly after birth, potentially yielding long-run benefits for their developmental outcomes.

Dendritic Spines: Synaptogenesis and Synaptic Pruning for the Developmental Organization of Brain Circuits

Synaptic overproduction and elimination is a regular developmental event in the mammalian brain. In the cerebral cortex, synaptic overproduction is almost exclusively correlated with glutamatergic synapses located on dendritic spines. Therefore, analysis of changes in spine density on different parts of the dendritic tree in identified classes of principal neurons could provide insight into developmental reorganization of specific microcircuits.The activity-dependent stabilization and selective elimination of the initially overproduced synapses is a major mechanism for generating diversity of neural connections beyond their genetic determination. The largest number of overproduced synapses was found in the monkey and human cerebral cortex. The highest (exceeding adult values by two- to threefold) and most protracted overproduction (up to third decade of life) was described for associative layer IIIC pyramidal neurons in the human dorsolateral prefrontal cortex.Therefore, the highest proportion and extraordinarily extended phase of synaptic spine overproduction is a hallmark of neural circuitry in human higher-order associative areas. This indicates that microcircuits processing the most complex human cognitive functions have the highest level of developmental plasticity. This finding is the backbone for understanding the effect of environmental impact on the development of the most complex, human-specific cognitive and emotional capacities, and on the late onset of human-specific neuropsychiatric disorders, such as autism and schizophrenia.

Multiscale entropy as a metric of brain maturation in a large cohort of typically developing children born preterm using longitudinal high-density EEG in the first two years of life

Objective.We aimed to analyze whether complexity of brain electrical activity (EEG) measured by multiscale entropy (MSE) increases with brain maturation during the first two years of life. We also aimed to investigate whether this complexity shows regional differences across the brain, and whether changes in complexity are influenced by extrauterine life experience duration.Approach.We measured MSE of EEG signals recorded longitudinally using a high-density setup (64 or 128 electrodes) in 84 typically developing infants born preterm (<32 weeks' gestation) from term age to two years. We analyzed the complexity index and maximum value of MSE over increasing age, across brain regions, and in function of extrauterine life duration, and used correlation matrices as a metric of functional connectivity of the cerebral cortex.Main results.We found an increase of strong inter-channel correlation of MSE (R > 0.8) with increasing age. Regional analysis showed significantly increased MSE between 3 and 24 months of corrected age in the posterior and middle regions with respect to the anterior region. We found a weak relationship (adjusted R²= 0.135) between MSE and extrauterine life duration.Significance.These findings suggest that brain functional connectivity increases with maturation during the first two years of life. EEG complexity shows regional differences with earlier maturation of the visual cortex and brain regions involved in joint attention than of regions involved in cognitive analysis, abstract thought, and social behavior regulation. Finally, our MSE analysis suggested only a weak influence of early extrauterine life experiences (prior to term age) on EEG complexity.

Microfluidics for Neuronal Cell and Circuit Engineering

The widespread adoption of microfluidic devices among the neuroscience and neurobiology communities has enabled addressing a broad range of questions at the molecular, cellular, circuit, and system levels. Here, we review biomedical engineering approaches that harness the power of microfluidics for bottom-up generation of neuronal cell types and for the assembly and analysis of neural circuits. Microfluidics-based approaches are instrumental to generate the knowledge necessary for the derivation of diverse neuronal cell types from human pluripotent stem cells, as they enable the isolation and subsequent examination of individual neurons of interest. Moreover, microfluidic devices allow to engineer neural circuits with specific orientations and directionality by providing control over neuronal cell polarity and permitting the isolation of axons in individual microchannels. Similarly, the use of microfluidic chips enables the construction not only of 2D but also of 3D brain, retinal, and peripheral nervous system model circuits. Such brain-on-a-chip and organoid-on-a-chip technologies are promising platforms for studying these organs as they closely recapitulate some aspects of in vivo biological processes. Microfluidic 3D neuronal models, together with 2D in vitro systems, are widely used in many applications ranging from drug development and toxicology studies to neurological disease modeling and personalized medicine. Altogether, microfluidics provide researchers with powerful systems that complement and partially replace animal models.

CARFS7: A guide and proforma for reading a preterm neonate's EEG

OBJECTIVES

The important role of the EEG in preterm and term babies in investigating brain function and seizures, predicting outcomes, evaluating therapeutic interventions and decision-making is being increasingly acknowledged. Development of the brain in the last trimester of pregnancy results in rapid changes in the EEG patterns in this period. Acquiring and interpreting the EEG of a preterm baby can be challenging. The aim of this study was to develop a proforma titled CARFS⁷ (Continuity, Amplitude, Reactivity, Frequency, Synchrony, Symmetry, Sleep, Sharps, Shapes, Size and Seizures) to enable neurologists to read EEGs of premature babies with greater confidence, ease and accuracy and produce a report more easily repeatable and homogenous among operators.

METHODS

The CARFS⁷proforma was developed based on a literature review and the personal experience of the authors. The parameters of the EEG evaluated and scored in the proforma are Continuity, Amplitude, Reactivity/Variability, Frequency, Synchrony, Symmetry, Sleep, Sharps, Shapes/Patterns, Size and Seizures. We also assessed the interrater reliability of the proposed scoring system incorporated in the proforma.

RESULTS

CARFS⁷ proforma incorporates a number of parameters that help evaluate the preterm EEG. The interrater reliability of the proposed scoring system in the CARFS⁷proforma was high.

CONCLUSIONS

CARFS⁷ is a user friendly proforma for reading EEGs in the preterm infant. Interrater reliability using Cohen's k shows high agreement between two child neurologists who independently rated the EEGs of 25 premature babies using this proforma. CARFS⁷ has the potential to provide, accurate, reproducible and valuable information on brain function in the preterm infant in clinical practice.

Functional Connectivity-Derived Optimal Gestational-Age Cut Points for Fetal Brain Network Maturity

The architecture of the human connectome changes with brain maturation. Pivotal to understanding these changes is defining developmental periods when transitions in network topology occur. Here, using 110 resting-state functional connectivity data sets from healthy fetuses between 19 and 40 gestational weeks, we estimated optimal gestational-age (GA) cut points for dichotomizing fetuses into 'young' and 'old' groups based on global network features. We computed the small-world index, normalized clustering and path length, global and local efficiency, and modularity from connectivity matrices comprised 200 regions and their corresponding pairwise connectivity. We modeled the effect of GA at scan on each metric using separate repeated-measures generalized estimating equations. Our modeling strategy involved stratifying fetuses into 'young' and 'old' based on the scan occurring before or after a selected GA (i.e., 28 to 33). We then used the quasi-likelihood independence criterion statistic to compare model fit between 'old' and 'young' cohorts and determine optimal cut points for each graph metric. Trends for all metrics, except for global efficiency, decreased with increasing gestational age. Optimal cut points fell within 30-31 weeks for all metrics coinciding with developmental events that include a shift from endogenous neuronal activity to sensory-driven cortical patterns.

Global Network Organization of the Fetal Functional Connectome

Recent advances in brain imaging have enabled non-invasive in vivo assessment of the fetal brain. Characterizing brain development in healthy fetuses provides baseline measures for identifying deviations in brain function in high-risk clinical groups. We examined 110 resting state MRI data sets from fetuses at 19 to 40 weeks' gestation. Using graph-theoretic techniques, we characterized global organizational features of the fetal functional connectome and their prenatal trajectories. Topological features related to network integration (i.e., global efficiency) and segregation (i.e., clustering) were assessed. Fetal networks exhibited small-world topology, showing high clustering and short average path length relative to reference networks. Likewise, fetal networks' quantitative small world indices met criteria for small-worldness (σ > 1, ω = [-0.5 0.5]). Along with this, fetal networks demonstrated global and local efficiency, economy, and modularity. A right-tailed degree distribution, suggesting the presence of central areas that are more highly connected to other regions, was also observed. Metrics, however, were not static during gestation; measures associated with segregation-local efficiency and modularity-decreased with advancing gestational age. Altogether, these suggest that the neural circuitry underpinning the brain's ability to segregate and integrate information exists as early as the late 2nd trimester of pregnancy and reorganizes during the prenatal period. Significance statement. Mounting evidence for the fetal origins of some neurodevelopmental disorders underscores the importance of identifying features of healthy fetal brain functional development. Alterations in prenatal brain connectomics may serve as early markers for identifying fetal-onset neurodevelopmental disorders, which in turn provide improved surveillance of at-risk fetuses and support the initiation of early interventions.

Relationship Between Early Functional and Structural Brain Developments and Brain Injury in Preterm Infants

Background

Recent studies explored the relationship between early brain function and brain morphology, based on the hypothesis that increased brain activity can positively affect structural brain development and that excitatory neuronal activity stimulates myelination.

Objective

To investigate the relationship between maturational features from early and serial aEEGs after premature birth and MRI metrics characterizing structural brain development and injury, measured around 30weeks postmenstrual age (PMA) and at term. Moreover, we aimed to verify whether previously developed maturational EEG features are related with PMA.

Design/Methods

One hundred six extremely preterm infants received bedside aEEGs during the first 72h and weekly until week 5. 3T-MRIs were performed at 30weeks PMA and at term. Specific features were extracted to assess EEG maturation: (1) the spectral content, (2) the continuity [percentage of spontaneous activity transients (SAT%) and the interburst interval (IBI)], and (3) the complexity. Automatic MRI segmentation to assess volumes and MRI score was performed. The relationship between the maturational EEG features and MRI measures was investigated.

Results

Both SAT% and EEG complexity were correlated with PMA. IBI was inversely associated with PMA. Complexity features had a positive correlation with the cerebellar size at 30weeks, while event-based measures were related to the cerebellar size at term. Cerebellar width, cortical grey matter, and total brain volume at term were inversely correlated with the relative power in the higher frequency bands.

Conclusions

The continuity and complexity of the EEG steadily increase with increasing postnatal age. Increasing complexity and event-based features are associated with cerebellar size, a structure with enormous development during preterm life. Brain activity is important for later structural brain development.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12311-021-01232-z.

Normal EEG during the neonatal period: maturational aspects from premature to full-term newborns

Electroencephalography (EEG) is the reference tool for the analysis of brain function, reflecting normal and pathological neuronal network activity. During the neonatal period, EEG patterns evolve weekly, according to gestational age. The first analytical criteria for the various maturational stages and standardized neonatal EEG terminology were published by a group of French neurophysiologists training in Paris (France) in 1999. These criteria, defined from analog EEG, were completed in 2010 with digital EEG analysis. Since then, this work has continued, aided by the technical progress in EEG acquisition, the improvement of knowledge on the maturating processes of neuronal networks, and the evolution of critical care. In this review, we present an exhaustive and didactic overview of EEG characteristics from extremely premature to full-term infants. This update is based on the scientific literature, enhanced by the study of normal EEGs of extremely premature infants by our group of neurophysiologists. For educational purposes, particular attention has been paid to illustrations using new digital tools.

Back to basics: the neuronal substrates and mechanisms that underlie the electroencephalogram in premature neonates

Electroencephalography is the only clinically available technique that can address the premature neonate normal and pathological functional development week after week. The changes in the electroencephalogram (EEG) result from gradual structural and functional modifications that arise during the last trimester of pregnancy. Here, we review the structural changes over time that underlie the establishment of functional immature neural networks, the impact of certain anatomical specificities (fontanelles, connectivity, etc.) on the EEG, limitations in EEG interpretation, and the utility of high-resolution EEG (HR-EEG) in premature newborns (a promising technique with a high degree of spatiotemporal resolution). In particular, we classify EEG features according to whether they are manifestations of endogenous generators (i.e. theta activities that coalesce with a slow wave or delta brushes) or come from a broader network. Furthermore, we review publications on EEG in premature animals because the data provide a better understanding of what is happening in premature newborns. We then discuss the results and limitations of functional connectivity analyses in premature newborns. Lastly, we report on the magnetoelectroencephalographic studies of brain activity in the fetus. A better understanding of complex interactions at various structural and functional levels during normal neurodevelopment (as assessed using electroencephalography as a benchmark method) might lead to better clinical care and monitoring for premature neonates.

The intimate relationship between coalescent generators in very premature human newborn brains: Quantifying the coupling of nested endogenous oscillations

Temporal theta slow-wave activity (TTA-SW) in premature infants is a specific neurobiomarker of the early neurodevelopment of perisylvian networks observed as early as 24 weeks of gestational age (wGA). It is present at the turning point between non-sensory driven spontaneous networks and cortical network functioning. Despite its clinical importance, the underlying mechanisms responsible for this spontaneous nested activity and its functional role have not yet been determined. The coupling between neural oscillations at different timescales is a key feature of ongoing neural activity, the characteristics of which are determined by the network structure and dynamics. The underlying mechanisms of cross-frequency coupling (CFC) are associated with several putative functions in adults. In order to show that this generic mechanism is already in place early in the course of development, we analyzed electroencephalography recordings from sleeping preterm newborns (24-27 wGA). Employing cross-frequency phase-amplitude coupling analyses, we found that TTAs were orchestrated by the SWs defined by a precise temporal relationship. Notably, TTAs were synchronized to the SW trough, and were suppressed during the SW peak. Spontaneous endogenous TTA-SWs constitute one of the very early signatures of the developing temporal neural networks with key functions, such as language and communication. The presence of a fine-tuned relationship between the slow activity and the TTA in premature neonates emphasizes the complexity and relative maturity of the intimate mechanisms that shape the CFC, the disruption of which can have severe neurodevelopmental consequences.

Predictive Value of Early Amplitude Integrated EEG in Extremely Premature Infants

Amplitude integrated EEG (aEEG) is increasingly utilized in preterm infants. The aim of the study was to evaluate whether semiquantitative visual assessment of aEEG background during the first 72 hours of life is associated with long-term outcome in a group of premature infants born less than 28 weeks' gestation. Infants were prospectively enrolled and monitored in the first 72 hours after birth. aEEG was classified daily according to background activity, appearance of cyclical activity and presence of seizures activity. Log-rank and multivariable cox analysis were used to explore associations of background aEEG activity with short and long-term outcome. Overall, 51 infants were enrolled into the study. Depressed aEEG background on the third day of life was associated with poor outcome (P = .028). Similarly, absence of cycling on the third day of life was associated with death or poor outcome (P = .004 and .012, respectively). In different multivariable models adjusted for gestational age, severe intraventricular hemorrhage or use of sedative medication, neither background nor cycling activities were associated with outcome. Depressed aEEG background and absence of aEEG cycling on the third day of life are associated with poor outcome in univariable analysis. Although continuous aEEG monitoring of premature infants can provide real-time assessment of cerebral function, its use as a predictive tool for long-term outcome using visual analysis requires caution as its predictive power is not greater than that of gestational age or intraventricular hemorrhage.

Plasticity and Spontaneous Activity Pulses in Disused Human Brain Circuits

To induce brain plasticity in humans, we casted the dominant upper extremity for 2 weeks and tracked changes in functional connectivity using daily 30-min scans of resting-state functional MRI (rs-fMRI). Casting caused cortical and cerebellar regions controlling the disused extremity to functionally disconnect from the rest of the somatomotor system, while internal connectivity within the disused sub-circuit was maintained. Functional disconnection was evident within 48 h, progressed throughout the cast period, and reversed after cast removal. During the cast period, large, spontaneous pulses of activity propagated through the disused somatomotor sub-circuit. The adult brain seems to rely on regular use to maintain its functional architecture. Disuse-driven spontaneous activity pulses may help preserve functionally disconnected sub-circuits.

Developmental GABA polarity switch and neuronal plasticity in Bioengineered Neuronal Organoids

Brain organoids are promising tools for disease modeling and drug development. For proper neuronal network formation excitatory and inhibitory neurons as well as glia need to co-develop. Here, we report the directed self-organization of human induced pluripotent stem cells in a collagen hydrogel towards a highly interconnected neuronal network at a macroscale tissue format. Bioengineered Neuronal Organoids (BENOs) comprise interconnected excitatory and inhibitory neurons with supportive astrocytes and oligodendrocytes. Giant depolarizing potential (GDP)-like events observed in early BENO cultures mimic early network activity of the fetal brain. The observed GABA polarity switch and reduced GDPs in >40 day BENO indicate progressive neuronal network maturation. BENOs demonstrate expedited complex network burst development after two months and evidence for long-term potentiation. The similarity of structural and functional properties to the fetal brain may allow for the application of BENOs in studies of neuronal plasticity and modeling of disease.

Brain organoids are important tools to study early development and disease but little is known of their network activity and plasticity. Here the authors generate iPSC-derived neuronal organoids that display early network formation and maturation with evidence for a GABA polarity switch and long-term potentiation.

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.

Family nurture intervention alters relationships between preterm infant EEG delta brush characteristics and term age EEG power

OBJECTIVE

Family Nurture Intervention (FNI) facilitates mother/infant emotional connection, improves neurodevelopmental outcomes and increases electroencephalogram (EEG) power at term age. Here we explored whether delta brushes (DB), early EEG bursts that shape brain development, are altered by FNI and mediate later effects of FNI on EEG.

METHODS

We assessed DB characteristics in EEG data from a randomized controlled trial comparing infants with standard care (SC, n = 31) versus SC + FNI (n = 33) at ~35 and ~40 weeks GA.

RESULTS

Compared to SC infants, FNI infant DB amplitude increased more from ~35 to ~40 weeks, and FNI infants had longer duration DBs. DB parameters (rate, amplitude, brush frequency) at ~35 weeks were correlated with power at ~40 weeks, but only in SC infants. FNI effects on DB parameters do not mediate FNI effects on EEG power or coherence at term.

CONCLUSIONS

DBs are related to subsequent brain activity and FNI alters DB parameters. However, FNI's effects on electrocortical activity at term age are not dependent on its earlier effects on DBs.

SIGNIFICANCE

While early DBs can have important effects on later brain activity in preterm infants, facilitating emotional connection with FNI may allow brain maturation to be less dependent on early bursts.

Novel in vitro assay to investigate radiation induced changes in the functionality of human embryonic stem cell-derived neurospheres

Ionizing radiation (IR) is increasingly used for diagnostics and therapy of severe brain diseases. However, IR also has adverse effects on the healthy brain tissue, particularly on the neuronal network. This is true for adults but even more pronounced in the developing brain of unborn and pediatric patients. Epidemiological studies on children receiving radiotherapy showed an increased risk for cognitive decline ranging from mild deficits in academic functioning to severe late effects in intellectual ability and language as a consequence of altered neuronal development and connectivity. To provide a comprehensive approach for the analysis of radiation-induced alterations in human neuronal functionality, we developed an in vitro assay by combining microelectrode array (MEA) analyses and human embryonic stem cell (hESC) derived three-dimensional neurospheres (NS). In our proof of principle study, we irradiated hESC with 1 Gy X-rays and let them spontaneously differentiate into neurons within NS. After the onset of neuronal activity, we recorded and analyzed the activity pattern of the developing neuronal networks. The network activity in NS derived from irradiated hESC was significantly reduced, whereas no differences in molecular endpoints such as cell proliferation and transcript or protein expression analyses were found. Thus, the combination of MEA analysis with a 3D model for neuronal functionality revealed radiation sequela that otherwise would not have been detected. We therefore strongly suggest combining traditional biomolecular methods with the new functional assay presented in this work to improve the risk assessment for IR-induced effects on the developing brain.

Cortical responses to tactile stimuli in preterm infants

The conventional assessment of preterm somatosensory functions using averaged cortical responses to electrical stimulation ignores the characteristic components of preterm somatosensory evoked responses (SERs). Our study aimed to systematically evaluate the occurrence and development of SERs after tactile stimulus in preterm infants. We analysed SERs performed during 45 electroencephalograms (EEGs) from 29 infants at the mean post-menstrual age of 30.7 weeks. Altogether 2,087 SERs were identified visually at single-trial level from unfiltered signals capturing also their slowest components. We observed salient SERs with a high-amplitude slow component at a high success rate after hand (95%) and foot (83%) stimuli. There was a clear developmental change in both the slow wave and the higher-frequency components of the SERs. Infants with intraventricular haemorrhage (IVH; eleven infants) had initially normal SERs, but those with bilateral IVH later showed a developmental decrease in the ipsilateral SER occurrence after 30 weeks of post-menstrual age. Our study shows that tactile stimulus applied at bedside elicits salient SERs with a large slow component and an overriding fast oscillation, which are specific to the preterm period. Prior experimental research indicates that such SERs allow studying both subplate and cortical functions. Our present findings further suggest that they might offer a window to the emergence of neurodevelopmental sequelae after major structural brain lesions and, hence, an additional tool for both research and clinical neurophysiological evaluation of infants before term age.

Complex Oscillatory Waves Emerging from Cortical Organoids Model Early Human Brain Network Development

Structural and transcriptional changes during early brain maturation follow fixed developmental programs defined by genetics. However, whether this is true for functional network activity remains unknown, primarily due to experimental inaccessibility of the initial stages of the living human brain. Here, we developed human cortical organoids that dynamically change cellular populations during maturation and exhibited consistent increases in electrical activity over the span of several months. The spontaneous network formation displayed periodic and regular oscillatory events that were dependent on glutamatergic and GABAergic signaling. The oscillatory activity transitioned to more spatiotemporally irregular patterns, and synchronous network events resembled features similar to those observed in preterm human electroencephalography. These results show that the development of structured network activity in a human neocortex model may follow stable genetic programming. Our approach provides opportunities for investigating and manipulating the role of network activity in the developing human cortex.

Neonatal infant EEG bursts are altered by prenatal maternal depression and serotonin selective reuptake inhibitor use

OBJECTIVE

Increasingly, serotonin selective reuptake inhibitor (SSRI) medications are prescribed in pregnancy. These medications pass freely into the developing fetus but little is known about their effect on brain development in humans. In this study we determine if prenatal maternal depression and SSRI medication change the EEG infant delta brush bursts which are an early marker of normal brain maturation.

METHODS

We measured delta brush bursts from the term infants of three groups of mothers (controls (N = 52), depressed untreated (N = 15), and those taking serotonin SSRI medication (N = 10). High density EEGs were obtained during sleep at an average age of 44 weeks post conceptional age. We measured the rate of occurrence, brush amplitude, oscillation frequency and duration of the bursts.

RESULTS

Compared to infants of control mothers, the parameters of delta brush bursts of the offspring of depressed and SSRI-using mothers are significantly altered: burst amplitude is decreased; the oscillation frequency increased, and the duration increased (SSRI only). These significant differences were found during both sleep states.

CONCLUSIONS

Electrocortical bursting activity (i.e. delta brushes) is known to play an important role in early central nervous system (CNS) synaptic formation and function.

SIGNIFICANCE

Maternal depression or SSRI use may alter brain function in their offspring.

Change detection to tone pairs during the first year of life - Predictive longitudinal relationships for EEG-based source and time-frequency measures

Brain responses related to auditory processing show large changes throughout infancy and childhood with some evidence that the two hemispheres might mature at different rates. Differing rates of hemispheric maturation could be linked to the proposed functional specialization of the hemispheres in which the left auditory cortex engages in analysis of precise timing information whereas the right auditory cortex focuses on analysis of sound frequency. Here the auditory change detection process for rapidly presented tone-pairs was examined in a longitudinal sample of infants at the age of 6 and 12 months using EEG. The ERP response related to change detection of a frequency contrast, its estimated source strength in the auditory areas, as well as time-frequency indices showed developmental effects. ERP amplitudes, source strength, spectral power and inter-trial phase locking decreased across age. A differential lateralization pattern emerged between 6 and 12 months as shown by inter-trial phase locking at 2-3 Hz; specifically, a larger developmental change was observed in the right as compared to the left hemisphere. Predictive relationships for the change in source strength from 6 months to 12 months were found. Six-month predictors were source strength and phase locking values at low frequencies. The results show that the infant change detection response in rapidly presented tone pairs is mainly determined by low frequency power and phase-locking with a larger phase-locking response at 6 months predicting greater change at 12 months. The ability of the auditory system to respond systematically across stimuli is suggested as a marker of maturational change that leads to more automatic and fine-tuned cortical responses.

The Integrative Function of Silent Synapses on Subplate Neurons in Cortical Development and Dysfunction

The thalamocortical circuit is of central importance in relaying information to the cortex. In development, subplate neurons (SPNs) form an integral part of the thalamocortical pathway. These early born cortical neurons are the first neurons to receive thalamic inputs and excite neurons in the cortical plate. This feed-forward circuit topology of SPNs supports the role of SPNs in shaping the formation and plasticity of thalamocortical connections. Recently it has been shown that SPNs also receive inputs from the developing cortical plate and project to the thalamus. The cortical inputs to SPNs in early ages are mediated by N-methyl-D-aspartate (NMDA)-receptor only containing synapses while at later ages α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-receptors are present. Thus, SPNs perform a changing integrative function over development. NMDA-receptor only synapses are crucially influenced by the resting potential and thus insults to the developing brain that causes depolarizations, e.g., hypoxia, can influence the integrative function of SPNs. Since such insults in humans cause symptoms of neurodevelopmental disorders, NMDA-receptor only synapses on SPNs might provide a crucial link between early injuries and later circuit dysfunction. We thus here review subplate associated circuits, their changing functions, and discuss possible roles in development and disease.

How Early Can a Seizure Happen? Pathophysiological Considerations of Extremely Premature Infant Brain Development

Seizures in neonates represent a neurologic emergency requiring prompt recognition, determination of etiology, and treatment. Yet, the definition and identification of neonatal seizures remain challenging and controversial, in part due to the unique physiology of brain development at this life stage. These issues are compounded when considering seizures in premature infants, in whom the complexities of brain development may engender different clinical and electrographic seizure features at different points in neuronal maturation. In extremely premature infants (< 28 weeks gestational age), seizure pathophysiology has not been explored in detail. This review discusses the physiological and structural development of the brain in this developmental window, focusing on factors that may lead to seizures and their consequences at this early time point. We hypothesize that the clinical and electrographic phenomenology of seizures in extremely preterm infants reflects the specific pathophysiology of brain development in that age window.

Outcome in preterm infants with seizures

Most neonatal seizures in preterm newborns are of acute symptomatic origin with a prevalence higher than in full-term infants. To date, recommendations for management of seizures in preterm newborns are scarce and do not differ from those in full-term newborns. Mortality in preterm newborns with seizures has significantly declined over the last decades, from figures of 84%-94% in the 1970s and 1980s to 22%-45% in the last years. However, mortality is significantly higher in those with a birth weight<1000g and a gestational age<28 weeks. Seizures are a strong predictor of unfavorable outcomes, including not only cerebral palsy, epilepsy, and intellectual disability, but also vision, hearing impairment, and microcephaly. The majority of patients with developmental delay are severely affected and this is usually associated with cerebral palsy. Furthermore, the incidence of epilepsy after neonatal seizures seems to be lower in preterm than in full-term infants but the risk is approximately 40 times greater than in the general population. Clinical studies cannot disentangle the specific and independent contributions of seizure-induced functional changes and the role of etiology and brain damage severity in determining the long-term outcomes in these newborns.

Developmental trajectory of movement-related cortical oscillations during active sleep in a cross-sectional cohort of pre-term and full-term human infants

In neonatal animal models, isolated limb movements during active sleep provide input to immature somatomotor cortex necessary for its development and are somatotopically encoded by alpha-beta oscillations as late as the equivalent of human full-term. Limb movements elicit similar neural patterns in very pre-term human infants (average 30 corrected gestational weeks), suggesting an analogous role in humans, but it is unknown until when they subserve this function. In a cohort of 19 neonates (31-42 corrected gestational weeks) we showed that isolated hand movements during active sleep continue to induce these same somatotopically distributed oscillations well into the perinatal period, but that these oscillations decline towards full-term and fully disappear at 41 corrected gestational weeks (equivalent to the end of gestation). We also showed that these highly localised alpha-beta oscillations are associated with an increase in delta oscillations which extends to the frontal area and does not decline with age. These results suggest that isolated limb movements during active sleep could have an important role in experience-dependent somatomotor development up until normal birth in humans.

The Superior Function of the Subplate in Early Neocortical Development

During early development the structure and function of the cerebral cortex is critically organized by subplate neurons (SPNs), a mostly transient population of glutamatergic and GABAergic neurons located below the cortical plate. At the molecular and morphological level SPNs represent a rather diverse population of cells expressing a variety of genetic markers and revealing different axonal-dendritic morphologies. Electrophysiologically SPNs are characterized by their rather mature intrinsic membrane properties and firing patterns. They are connected via electrical and chemical synapses to local and remote neurons, e.g., thalamic relay neurons forming the first thalamocortical input to the cerebral cortex. Therefore SPNs are robustly activated at pre- and perinatal stages by the sensory periphery. Although SPNs play pivotal roles in early neocortical activity, development and plasticity, they mostly disappear by programmed cell death during further maturation. On the one hand, SPNs may be selectively vulnerable to hypoxia-ischemia contributing to brain damage, on the other hand there is some evidence that enhanced survival rates or alterations in SPN distribution may contribute to the etiology of neurological or psychiatric disorders. This review aims to give a comprehensive and up-to-date overview on the many functions of SPNs during early physiological and pathophysiological development of the cerebral cortex.

The distribution of pain activity across the human neonatal brain is sex dependent

In adults, there are differences between male and female structural and functional brain connectivity, specifically for those regions involved in pain processing. This may partly explain the observed sex differences in pain sensitivity, tolerance, and inhibitory control, and in the development of chronic pain. However, it is not known if these differences exist from birth. Cortical activity in response to a painful stimulus can be observed in the human neonatal brain, but this nociceptive activity continues to develop in the postnatal period and is qualitatively different from that of adults, partly due to the considerable cortical maturation during this time. This research aimed to investigate the effects of sex and prematurity on the magnitude and spatial distribution pattern of the long-latency nociceptive event-related potential (nERP) using electroencephalography (EEG). We measured the cortical response time-locked to a clinically required heel lance in 81 neonates born between 29 and 42 weeks gestational age (median postnatal age 4 days). The results show that heel lance results in a spatially widespread nERP response in the majority of newborns. Importantly, a widespread pattern is significantly more likely to occur in females, irrespective of gestational age at birth. This effect is not observed for the short latency somatosensory waveform in the same infants, indicating that it is selective for the nociceptive component of the response. These results suggest the early onset of a greater anatomical and functional connectivity reported in the adult female brain, and indicate the presence of pain-related sex differences from birth.

Modelling interactions between blood pressure and brain activity in preterm neonates

Hypotension or low blood pressure (BP) is a common problem in preterm neonates and has been associated with adverse short and long-term outcomes. Deciding when and whether to treat hypotension relies on an understanding of the relations between blood pressure and brain function. This study aims to investigate the interaction between BP and multichannel EEG in preterm infants less than 32 weeks gestational age. The mutual information is chosen to model interaction. This measure is independent of absolute values of BP and electroencephalography (EEG) power and quantifies the level of coupling between the short-term dynamics in both signals. It is shown that while adverse health conditions as measured by higher clinical risk indices for babies (CRIB II) are accompanied by consistently lower blood pressure (r=0.43), no significant correlation was observed between CRIB scores and EEG spectral power. More importantly, the chosen measure of interaction between dynamics of EEG and BP was found to be more closely related to CRIB scores (r=0.49, p-value=0.012), with higher CRIB score associated with lower levels of interaction.

Emergence of mature cortical activity in wakefulness and sleep in healthy preterm and full-term infants

Study Objectives

Cortical activity patterns develop rapidly over the equivalent of the last trimester of gestation, in parallel with the establishment of sleep architecture. However, the emergence of mature cortical activity in wakefulness compared with sleep states in healthy preterm infants is poorly understood.

Methods

To investigate whether the cortical activity has a different developmental profile in each sleep-wake state, we recorded 11-channels electroencephalography (EEG), electrooculography (EOG), and respiratory movement for 1 hr from 115 infants 34 to 43 weeks-corrected age, with 0.5-17 days of postnatal age. We characterized the trajectory of δ, θ, and α-β oscillations in wakefulness, rapid eye movement (REM) sleep, and non-REM sleep by calculating the power spectrum of the EEG, averaged across artifact-free epochs.

Results

δ-Oscillations in wakefulness and REM sleep decrease with corrected age, particularly in the temporal region, but not in non-REM sleep. θ-Oscillations increase with corrected age in sleep, especially non-REM sleep, but not in wakefulness. On the other hand, α-β oscillations decrease predominantly with postnatal age, independently of sleep-wake state, particularly in the occipital region.

Conclusions

The developmental trajectory of δ and θ rhythms is state-dependent and results in changed cortical activity patterns between states with corrected age, which suggests that these frequency bands may have particular functional roles in each state. Interestingly, postnatal age is associated with a decrease in α-β oscillations overlying primary visual cortex in every sleep-wake state, suggesting that postnatal experience (including the first visual input through open eyes during periods of wakefulness) is associated with resting-state visual cortical activity changes.

Coupling between mean blood pressure and EEG in preterm neonates is associated with reduced illness severity scores

Hypotension or low blood pressure (BP) is a common problem in preterm neonates and has been associated with adverse short and long-term neurological outcomes. Deciding when and whether to treat hypotension relies on an understanding of the relationship between BP and brain functioning. This study aims to investigate the interaction (coupling) between BP and continuous multichannel unedited EEG recordings in preterm infants less than 32 weeks of gestational age. The EEG was represented by spectral power in four frequency sub-bands: 0.3-3 Hz, 3-8 Hz, 8-15 Hz and 15-30 Hz. BP was represented as mean arterial pressure (MAP). The level of coupling between the two physiological systems was estimated using linear and nonlinear methods such as correlation, coherence and mutual information. Causality of interaction was measured using transfer entropy. The illness severity was represented by the clinical risk index for babies (CRIB II score) and contrasted to the computed level of interaction. It is shown here that correlation and coherence, which are linear measures of the coupling between EEG and MAP, do not correlate with CRIB values, whereas adjusted mutual information, a nonlinear measure, is associated with CRIB scores (r = -0.57, p = 0.003). Mutual information is independent of the absolute values of MAP and EEG powers and quantifies the level of coupling between the short-term dynamics in both signals. The analysis indicated that the dominant causality is from changes in EEG producing changes in MAP. Transfer entropy (EEG to MAP) is associated with the CRIB score (0.3-3 Hz: r = 0.428, p = 0.033, 3-8 Hz: r = 0.44, p = 0.028, 8-15 Hz: r = 0.416, p = 0.038) and indicates that a higher level of directed coupling from brain activity to blood pressure is associated with increased illness in preterm infants. This is the first study to present the nonlinear measure of interaction between brain activity and blood pressure and to demonstrate its relation to the initial illness severity in the preterm infant. The obtained results allow us to hypothesise that the normal wellbeing of a preterm neonate can be characterised by a nonlinear coupling between brain activity and MAP, whereas the presence of weak coupling with distinctive directionality of information flow is associated with an increased mortality rate in preterms.

Waking up too early - the consequences of preterm birth on sleep development

Good quality sleep of sufficient duration is vital for optimal physiological function and our health. Sleep deprivation is associated with impaired neurocognitive function and emotional control, and increases the risk for cardiometabolic diseases, obesity and cancer. Sleep develops during fetal life with the emergence of a recognisable pattern of sleep states in the preterm fetus associated with the development, maturation and connectivity within neural networks in the brain. Despite the physiological importance of sleep, surprisingly little is known about how sleep develops in individuals born preterm. Globally, an estimated 15 million babies are born preterm (<37 weeks gestation) each year, and these babies are at significant risk of neural injury and impaired brain development. This review discusses how sleep develops during fetal and neonatal life, how preterm birth impacts on sleep development to adulthood, and the factors which may contribute to impaired brain and sleep development, leading to altered neurocognitive, behavioural and motor capabilities in the infant and child. Going forward, the challenge is to identify specific risk factors for impaired sleep development in preterm babies to allow for the design of interventions that will improve the quality and quantity of sleep throughout life.

Thalamocortical function in developing sensory circuits

Thalamocortical activity patterns, both spontaneous and evoked, undergo a dramatic shift in preparation for the onset of rich sensory experience (e.g. birth in humans; eye-opening in rodents). This change is the result of a switch from thalamocortical circuits tuned for transmission of spontaneous bursting in sense organs, to circuits capable of high resolution, active sensory processing. Early 'pre-sensory' tuning uses amplification generated by corticothalamic excitatory feedback and early-born subplate neurons to ensure transmission of bursts, at the expense of stimulus discrimination. The switch to sensory circuits is due, at least in part, to the coordinated remodeling of inhibitory circuits in thalamus and cortex. Appreciation of the distinct rules that govern early circuit function can, and should, inform translational studies of genetic and acquired developmental dysfunction.

Models for Preterm Cortical Development Using Non Invasive Clinical EEG

The objective of this study was to evaluate the piglet and the mouse as model systems for preterm cortical development. According to the clinical context, we used non invasive EEG recordings. As a prerequisite, we developed miniaturized Ag/AgCl electrodes for full band EEG recordings in mice and verified that Urethane had no effect on EEG band power. Since mice are born with a “preterm” brain, we evaluated three age groups: P0/P1, P3/P4 and P13/P14. Our aim was to identify EEG patterns in the somatosensory cortex which are distinguishable between developmental stages and represent a physiologic brain development. In mice, we were able to find clear differences between age groups with a simple power analysis of EEG bands and also for phase locking and power spectral density. Interhemispheric coherence between corresponding regions can only be seen in two week old mice. The canolty maps for piglets as well as for mice show a clear PAC (phase amplitude coupling) pattern during development. From our data it can be concluded that analytic tools relying on network activity, as for example PAC (phase amplitude coupling) are best suited to extract basic EEG patterns of cortical development across species.

Family nurture intervention in preterm infants increases early development of cortical activity and independence of regional power trajectories

AIM

Premature delivery and maternal separation during hospitalisation increase infant neurodevelopmental risk. Previously, a randomised controlled trial of Family Nurture Intervention (FNI) in the neonatal intensive care unit demonstrated improvement across multiple mother and infant domains including increased electroencephalographic (EEG) power in the frontal polar region at term age. New aims were to quantify developmental changes in EEG power in all brain regions and frequencies and correlate developmental changes in EEG power among regions.

METHODS

EEG (128 electrodes) was obtained at 34-44 weeks postmenstrual age from preterm infants born 26-34 weeks. Forty-four infants were treated with Standard Care and 53 with FNI. EEG power was computed in 10 frequency bands (1-48 Hz) in 10 brain regions and in active and quiet sleep.

RESULTS

Percent change/week in EEG power was increased in FNI in 132/200 tests (p < 0.05), 117 tests passed a 5% False Discovery Rate threshold. In addition, FNI demonstrated greater regional independence in those developmental rates of change.

CONCLUSION

This study strengthens the conclusion that FNI promotes cerebral cortical development of preterm infants. The findings indicate that developmental changes in EEG may provide biomarkers for risk in preterm infants as well as proximal markers of effects of FNI.

Modulation of Neocortical Development by Early Neuronal Activity: Physiology and Pathophysiology

Animal and human studies revealed that patterned neuronal activity is an inherent feature of developing nervous systems. This review summarizes our current knowledge about the mechanisms generating early electrical activity patterns and their impact on structural and functional development of the cerebral cortex. All neocortical areas display distinct spontaneous and sensory-driven neuronal activity patterns already at early phases of development. At embryonic stages, intermittent spontaneous activity is synchronized within small neuronal networks, becoming more complex with further development. This transition is accompanied by a gradual shift from electrical to chemical synaptic transmission, with a particular role of non-synaptic tonic currents before the onset of phasic synaptic activity. In this review article we first describe functional impacts of classical neurotransmitters (GABA, glutamate) and modulatory systems (e.g., acetylcholine, ACh) on early neuronal activities in the neocortex with special emphasis on electrical synapses, nonsynaptic and synaptic currents. Early neuronal activity influences probably all developmental processes and is crucial for the proper formation of neuronal circuits. In the second part of our review, we illustrate how specific activity patterns might interfere with distinct neurodevelopmental processes like proliferation, migration, axonal and dendritic sprouting, synapse formation and neurotransmitter specification. Finally, we present evidence that transient alterations in neuronal activity during restricted perinatal periods can lead to persistent changes in functional connectivity and therefore might underlie the manifestation of neurological and neuropsychiatric diseases.

Review of sleep-EEG in preterm and term neonates

Neonatal sleep is a crucial state that involves endogenous driven brain activity, important for neuronal survival and guidance of brain networks. Sequential EEG-sleep analysis in preterm infants provides insights into functional brain integrity and can document deviations of the biologically pre-programmed process of sleep ontogenesis during the neonatal period. Visual assessment of neonatal sleep-EEG, with integration of both cerebral and non-cerebral measures to better define neonatal state, is still considered the gold standard. Electrographic patterns evolve over time and are gradually time locked with behavioural characteristics which allow classification of quiet sleep and active sleep periods during the last 10weeks of gestation. Near term age, the neonate expresses a short ultradian sleep cycle, with two distinct active and quiet sleep, as well as brief periods of transitional or indeterminate sleep. Qualitative assessment of neonatal sleep is however challenged by biological and environmental variables that influence the expression of EEG-sleep patterns and sleep organization. Developing normative EEG-sleep data with the aid of automated analytic methods, can further improve our understanding of extra-uterine brain development and state organization under stressful or pathological conditions. Based on those developmental biomarkers of normal and abnormal brain function, research can be conducted to support and optimise sleep in the NICU, with the ultimate goal to improve therapeutic interventions and neurodevelopmental outcome.

Uncorrelated Neural Firing in Mouse Visual Cortex during Spontaneous Retinal Waves

Synchronous firing among the elements of forming circuits is critical for stabilization of synapses. Understanding the nature of these local network interactions during development can inform models of circuit formation. Within cortex, spontaneous activity changes throughout development. Unlike the adult, early spontaneous activity occurs in discontinuous population bursts separated by long silent periods, suggesting a high degree of local synchrony. However, whether the micro-patterning of activity within early bursts is unique to this early age and specifically tuned for early development is poorly understood, particularly within the column. To study this we used single-shank multi-electrode array recordings of spontaneous activity in the visual cortex of non-anesthetized neonatal mice to quantify single-unit firing rates, and applied multiple measures of network interaction and synchrony throughout the period of map formation and immediately after eye-opening. We find that despite co-modulation of firing rates on a slow time scale (hundreds of ms), the number of coactive neurons, as well as pair-wise neural spike-rate correlations, are both lower before eye-opening. In fact, on post-natal days (P)6–9 correlated activity was lower than expected by chance, suggesting active decorrelation of activity during early bursts. Neurons in lateral geniculate nucleus developed in an opposite manner, becoming less correlated after eye-opening. Population coupling, a measure of integration in the local network, revealed a population of neurons with particularly strong local coupling present at P6–11, but also an adult-like diversity of coupling at all ages, suggesting that a neuron’s identity as locally or distally coupled is determined early. The occurrence probabilities of unique neuronal “words” were largely similar at all ages suggesting that retinal waves drive adult-like patterns of co-activation. These findings suggest that the bursts of spontaneous activity during early visual development do not drive hyper-synchronous activity within columns. Rather, retinal waves provide windows of potential activation during which neurons are active but poorly correlated, adult-like patterns of correlation are achieved soon after eye-opening.

Localization of spontaneous bursting neuronal activity in the preterm human brain with simultaneous EEG-fMRI

Electroencephalographic recordings from the developing human brain are characterized by spontaneous neuronal bursts, the most common of which is the delta brush. Although similar events in animal models are known to occur in areas of immature cortex and drive their development, their origin in humans has not yet been identified. Here, we use simultaneous EEG-fMRI to localise the source of delta brush events in 10 preterm infants aged 32–36 postmenstrual weeks. The most frequent patterns were left and right posterior-temporal delta brushes which were associated in the left hemisphere with ipsilateral BOLD activation in the insula only; and in the right hemisphere in both the insular and temporal cortices. This direct measure of neural and hemodynamic activity shows that the insula, one of the most densely connected hubs in the developing cortex, is a major source of the transient bursting events that are critical for brain maturation.

Development of Activity in the Mouse Visual Cortex

A comprehensive developmental timeline of activity in the mouse cortex in vivo is lacking. Understanding the activity changes that accompany synapse and circuit formation is important to understand the mechanisms by which activity molds circuits and would help to identify critical checkpoints for normal development. To identify key principles of cortical activity maturation, we systematically tracked spontaneous and sensory-evoked activity with extracellular recordings of primary visual cortex (V1) in nonanesthetized mice. During the first postnatal week (postnatal days P4-P7), V1 was not visually responsive and exhibited long (>10 s) periods of network silence. Activation consisted exclusively of "slow-activity transients," 2-10 s periods of 6-10 Hz "spindle-burst' oscillations; the response to spontaneous retinal waves. By tracking daily changes in this activity, two key components of spontaneous activity maturation were revealed: (1) spindle-burst frequency acceleration (eventually becoming the 20-50 Hz broadband activity caused by the asynchronous state) and (2) "filling-in" of silent periods with low-frequency (2-4 Hz) activity (beginning on P10 and complete by P13). These two changes are sufficient to create the adult-like pattern of continuous activity, alternation between fast-asynchronous and slow-synchronous activity, by eye opening. Visual responses emerged on P8 as evoked spindle-bursts and neuronal firing with a signal-to-noise ratio higher than adult. Both were eliminated by eye opening, leaving only the mature, short-latency response. These results identify the developmental origins of mature cortical activity and implicate the period before eye opening as a critical checkpoint. By providing a systematic description of electrical activity development, we establish the murine visual cortex as a model for the electroencephalographic development of fetal humans.

SIGNIFICANCE STATEMENT

Cortical activity is an important indicator of long-term health and survival in preterm infants and molds circuit formation, but gaps remain in our understanding of the origin and normal progression of this activity in the developing cortex. We aimed to rectify this by monitoring daily changes in cortical activity in the nonanesthetized mouse, an important preclinical model of disease and development. At ages approximately equivalent to normal human term birth, mouse cortex exhibits primarily network silence, with spontaneous "spindle bursts" as the only form of activity. In contrast, mature cortex is noisy, alternating between asynchronous/discontinuous and synchronous/continuous states. This work identifies the key processes that produce this maturation and provides a normative reference for murine-based studies of cortical circuit development.

Neuronal activity patterns in the developing barrel cortex

The developing barrel cortex reveals a rich repertoire of neuronal activity patterns, which have been also found in other sensory neocortical areas and in other species including the somatosensory cortex of preterm human infants. The earliest stage is characterized by asynchronous, sparse single-cell firing at low frequencies. During the second stage neurons show correlated firing, which is initially mediated by electrical synapses and subsequently transforms into network bursts depending on chemical synapses. Activity patterns during this second stage are synchronous plateau assemblies, delta waves, spindle bursts and early gamma oscillations (EGOs). In newborn rodents spindle bursts and EGOs occur spontaneously or can be elicited by sensory stimulation and synchronize the activity in a barrel-related columnar network with topographic organization at the day of birth. Interfering with this early activity causes a disturbance in the development of the cortical architecture, indicating that spindle bursts and EGOs influence the formation of cortical columns. Early neuronal activity also controls the rate of programed cell death in the developing barrel cortex, suggesting that spindle bursts and EGOs are physiological activity patterns particularly suited to suppress apoptosis. It remains to be studied in more detail how these different neocortical activity patterns control early developmental processes such as formation of synapses, microcircuits, topographic maps and large-scale networks.

An Automated Quiet Sleep Detection Approach in Preterm Infants as a Gateway to Assess Brain Maturation

Sleep state development in preterm neonates can provide crucial information regarding functional brain maturation and give insight into neurological well being. However, visual labeling of sleep stages from EEG requires expertise and is very time consuming, prompting the need for an automated procedure. We present a robust method for automated detection of preterm sleep from EEG, over a wide postmenstrual age (PMA = gestational age + postnatal age) range, focusing first on Quiet Sleep (QS) as an initial marker for sleep assessment. Our algorithm, CLuster-based Adaptive Sleep Staging (CLASS), detects QS if it remains relatively more discontinuous than non-QS over PMA. CLASS was optimized on a training set of 34 recordings aged 27–42 weeks PMA, and performance then assessed on a distinct test set of 55 recordings of the same age range. Results were compared to visual QS labeling from two independent raters (with inter-rater agreement Kappa = 0. 93), using Sensitivity, Specificity, Detection Factor (DF = proportion of visual QS periods correctly detected by CLASS) and Misclassification Factor (MF = proportion of CLASS-detected QS periods that are misclassified). CLASS performance proved optimal across recordings at 31–38 weeks (median DF = 1.0, median MF 0–0.25, median Sensitivity 0.93–1.0, and median Specificity 0.80–0.91 across this age range), with minimal misclassifications at 35–36 weeks (median MF = 0). To illustrate the potential of CLASS in facilitating clinical research, normal maturational trends over PMA were derived from CLASS-estimated QS periods, visual QS estimates, and nonstate specific periods (containing QS and non-QS) in the EEG recording. CLASS QS trends agreed with those from visual QS, with both showing stronger correlations than nonstate specific trends. This highlights the benefit of automated QS detection for exploring brain maturation.

Characteristics and clinical significance of delta brushes in the EEG of premature infants

Delta brushes are the hallmark of the EEG of premature infants. They are readily recognisable because of their characteristic appearance and are a key marker of neural maturation. However they are sometimes inconsistently described in the literature making identification of abnormalities challenging. The goal of this review is to provide an overview of research findings on this topic in the last five decades. Firstly, the characteristic features of delta brushes are described, including the developmental trajectory of their incidence and how they are modulated by vigilance state in normal neonates. Secondly, their clinical significance is discussed including how abnormalities in their incidence or appearance indicate particular pathophysiology. We propose that (i) the effect of age and vigilance state on the frequency, amplitude and topography of delta brushes, and (ii) heterogeneity within the cohorts of 'normal' premature infants studied, may explain the very variable descriptions of delta brush characteristics in the literature. By explicitly taking these factors into consideration to explain delta brush variability, the presented summary facilitates the clinical electrodiagnostic and prognostic use of delta brush abnormalities as a biomarker.

Neuronal activity controls the development of interneurons in the somatosensory cortex

BACKGROUND

Neuronal activity in cortical areas regulates neurodevelopment by interacting with defined genetic programs to shape the mature central nervous system. Electrical activity is conveyed to sensory cortical areas via intracortical and thalamocortical neurons, and includes oscillatory patterns that have been measured across cortical regions.

OBJECTIVE

In this work, we review the most recent findings about how electrical activity shapes the developmental assembly of functional circuitry in the somatosensory cortex, with an emphasis on interneuron maturation and integration. We include studies on the effect of various neurotransmitters and on the influence of thalamocortical afferent activity on circuit development. We additionally reviewed studies describing network activity patterns.

METHODS

We conducted an extensive literature search using both the PubMed and Google Scholar search engines. The following keywords were used in various iterations: "interneuron", "somatosensory", "development", "activity", "network patterns", "thalamocortical", "NMDA receptor", "plasticity". We additionally selected papers known to us from past reading, and those recommended to us by reviewers and members of our lab.

RESULTS

We reviewed a total of 132 articles that focused on the role of activity in interneuronal migration, maturation, and circuit development, as well as the source of electrical inputs and patterns of cortical activity in the somatosensory cortex. 79 of these papers included in this timely review were written between 2007 and 2016.

CONCLUSIONS

Neuronal activity shapes the developmental assembly of functional circuitry in the somatosensory cortical interneurons. This activity impacts nearly every aspect of development and acquisition of mature neuronal characteristics, and may contribute to changing phenotypes, altered transmitter expression, and plasticity in the adult. Progressively changing oscillatory network patterns contribute to this activity in the early postnatal period, although a direct requirement for specific patterns and origins of activity remains to be demonstrated.