Rapid Cortical Oscillations and Early Motor Activity in Premature Human Neonate

Modeling the Emergence of Circuit Organization and Function during Development

Developing neural circuits show unique patterns of spontaneous activity and structured network connectivity shaped by diverse activity-dependent plasticity mechanisms. Based on extensive experimental work characterizing patterns of spontaneous activity in different brain regions over development, theoretical and computational models have played an important role in delineating the generation and function of individual features of spontaneous activity and their role in the plasticity-driven formation of circuit connectivity. Here, we review recent modeling efforts that explore how the developing cortex and hippocampus generate spontaneous activity, focusing on specific connectivity profiles and the gradual strengthening of inhibition as the key drivers behind the observed developmental changes in spontaneous activity. We then discuss computational models that mechanistically explore how different plasticity mechanisms use this spontaneous activity to instruct the formation and refinement of circuit connectivity, from the formation of single neuron receptive fields to sensory feature maps and recurrent architectures. We end by highlighting several open challenges regarding the functional implications of the discussed circuit changes, wherein models could provide the missing step linking immature developmental and mature adult information processing capabilities.

Automatic detection and characterization of maturational neurobiomarkers identified as nested oscillations in premature newborns using high-density electroencephalography

Neural development leads to the evolution of electroencephalographic (EEG) characteristics during the third trimester of gestation. Theta activity in coalescence with slow waves (TA-SW) and delta brushes (DB) are key clinical neurobiomarkers in the evaluation of neurodevelopment in infants prior to full-term gestation. Both neurobiomarkers exhibit nested oscillations, a key feature of intrinsic spontaneous oscillatory activity, allowing the investigation of neural interaction development in the underlying circuits. In the present study, we propose an automatic approach for the detection and characterization of neurobiomarkers that (1) leverages high-density EEG (HD-EEG), (2) incorporates temporal dynamics and spatial distributions, and (3) evaluates the characteristics of nested oscillations. This method evaluates both slow and rapid neural activity, along with their cross-frequency coupling. Our results are in good agreement with those of clinical experts, achieving ROC performances and overall accuracies of 91 %/84 % and 83 %/75 % for TA-SW/DB events, respectively. Following detection and validation, we characterized and compared these two neurobiomarkers. Correlation-based spatial clustering showed that DB patterns were more symmetric and diffuse, whereas TA-SW patterns were more localized in the right and left temporal areas. Comparisons revealed (1) greater variability in spatial patterns for DB than for TA-SW, and that (2) while slow-wave coupling to fast oscillations showed similar characteristics for both neurobiomarkers, differences emerged in the amplitude and descending slope of the underlying slow waves. These findings suggested potential differences in the mechanisms underlying their generation, particularly in the modulation of slow oscillations. This approach represents a promising avenue for the quantitative evaluation of EEG signatures pertinent to early neural development in premature neonates.

Co-developing sleep-wake and sensory foundations for cognition in the human fetus and newborn

In older children and adults, cognition builds upon waking sensory experience which is consolidated during sleep. In the fetus and newborn, sensory input is instead largely experienced during sleep. The nature of these sensory inputs differs within sleep, between active and quiet sleep, as well as versus wakefulness. Here, sleep-wake organisation in the fetus and newborn is reviewed, and then its interaction with sensory inputs discussed with a focus on somatosensory and auditory modalities. Next, these ideas are applied to how neurological insults affect early development, using fetal growth restriction as a test case. Finally, the argument is made that taking account of sleep-wake state during perinatal functional neuroimaging can better index sensorimotor, language, and cognitive brain activities, potentially improving its diagnostic and prognostic value. To sum up, sensory and sleep-wake functions go hand in hand during early human development. Perturbation of these twinned functions by neurological insults may mediate later neurodevelopmental deficits. Perinatal neuroimaging has the potential to track these trajectories, feasibly identifying opportunities to therapeutically intervene.

Sleep as a driver of pre- and postnatal brain development

In 1966, Howard Roffwarg proposed the ontogenic sleep hypothesis, relating neural plasticity and development to rapid eye movement (REM) sleep, a hypothesis that current fetal and neonatal sleep research is still exploring. Recently, technological advances have enabled researchers to automatically quantify neonatal sleep architecture, which has caused a resurgence of research in this field as attempts are made to further elucidate the important role of sleep in pre- and postnatal brain development. This article will review our current understanding of the role of sleep as a driver of brain development and identify possible areas for future research. IMPACT: The evidence to date suggests that Roffwarg's ontogenesis hypothesis of sleep and brain development is correct. A better understanding of the relationship between sleep and the development of functional connectivity is needed. Reliable, non-invasive tools to assess sleep in the NICU and at home need to be tested in a real-world environment and the best way to promote healthy sleep needs to be understood before clinical trials promoting and optimizing sleep quality in neonates could be undertaken.

Revisiting the functional monitoring of brain development in premature neonates. A new direction in clinical care and research

The first 1000 days of life are of paramount importance for neonatal development. Premature newborns are exposed early to the external environment, modifying the fetal exposome and leading to overexposure in some sensory domains and deprivation in others. The resulting neurodevelopmental effects may persist throughout the individual's lifetime. Several neonatal neuromonitoring techniques can be used to investigate neural mechanisms in early postnatal development. EEG is the most widely used, as it is easy to perform, even at the patient's bedside. It is not expensive and provides information with a high temporal resolution and relatively good spatial resolution when performed in high-density mode. Functional near-infrared spectroscopy (fNIRS), a technique for monitoring vascular network dynamics, can also be used at the patient's bedside. It is not expensive and has a good spatial resolution at the cortical surface. These two techniques can be combined for simultaneous monitoring of the neuronal and vascular networks in premature newborns, providing insight into neurodevelopment before term. However, the extent to which more general conclusions about fetal development can be drawn from findings for premature neonates remains unclear due to considerable differences in environmental and medical situations. Fetal MEG (fMEG, as an alternative to EEG for preterm infants) and fMRI (as an alternative to fNIRS for preterm infants) can also be used to investigate fetal neurodevelopment on a trimester-specific basis. These techniques should be used for validation purposes as they are the only tools available for evaluating neuronal dysfunction in the fetus at the time of the gene-environment interactions influencing transient neuronal progenitor populations in brain structures. But what do these techniques tell us about early neurodevelopment? We address this question here, from two points of view. We first discuss spontaneous neural activity and its electromagnetic and hemodynamic correlates. We then explore the effects of stimulating the immature developing brain with information from exogenous sources, reviewing the available evidence concerning the characteristics of electromagnetic and hemodynamic responses. Once the characteristics of the correlates of neural dynamics have been determined, it will be essential to evaluate their possible modulation in the context of disease and in at-risk populations. Evidence can be collected with various neuroimaging techniques targeting both spontaneous and exogenously driven neural activity. A multimodal approach combining the neuromonitoring of different functional compartments (neuronal and vascular) is required to improve our understanding of the normal functioning and dysfunction of the brain and to identify neurobiomarkers for predicting the neurodevelopmental outcome of premature neonate and fetus. Such an approach would provide a framework for exploring early neurodevelopment, paving the way for the development of tools for earlier diagnosis in these vulnerable populations, thereby facilitating preventive, rescue and reparative neurotherapeutic interventions.

The function of Mef2c toward the development of excitatory and inhibitory cortical neurons

Neurodevelopmental disorders (NDDs) are caused by abnormal brain development, leading to altered brain function and affecting cognition, learning, self-control, memory, and emotion. NDDs are often demarcated as discrete entities for diagnosis, but empirical evidence indicates that NDDs share a great deal of overlap, including genetics, core symptoms, and biomarkers. Many NDDs also share a primary sensitive period for disease, specifically the last trimester of pregnancy in humans, which corresponds to the neonatal period in mice. This period is notable for cortical circuit assembly, suggesting that deficits in the establishment of brain connectivity are likely a leading cause of brain dysfunction across different NDDs. Regulators of gene programs that underlie neurodevelopment represent a point of convergence for NDDs. Here, we review how the transcription factor MEF2C, a risk factor for various NDDs, impacts cortical development. Cortical activity requires a precise balance of various types of excitatory and inhibitory neuron types. We use MEF2C loss-of-function as a study case to illustrate how brain dysfunction and altered behavior may derive from the dysfunction of specific cortical circuits at specific developmental times.

Network state transitions during cortical development

Mammalian cortical networks are active before synaptogenesis begins in earnest, before neuronal migration is complete, and well before an animal opens its eyes and begins to actively explore its surroundings. This early activity undergoes several transformations during development. The most important of these is a transition from episodic synchronous network events, which are necessary for patterning the neocortex into functionally related modules, to desynchronized activity that is computationally more powerful and efficient. Network desynchronization is perhaps the most dramatic and abrupt developmental event in an otherwise slow and gradual process of brain maturation. In this Review, we summarize what is known about the phenomenology of developmental synchronous activity in the rodent neocortex and speculate on the mechanisms that drive its eventual desynchronization. We argue that desynchronization of network activity is a fundamental step through which the cortex transitions from passive, bottom-up detection of sensory stimuli to active sensory processing with top-down modulation.

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.

A Thalamocortical Perspective on Sleep Spindle Alterations in Neurodevelopmental Disorders

Purpose of Review

Neurodevelopmental disorders are a group of conditions that affect the development and function of the nervous system, typically arising early in life. These disorders can have various genetic, environmental, and/or neural underpinnings, which can impact the thalamocortical system. Sleep spindles, brief bursts of oscillatory activity that occur during NREM sleep, provide a unique in vivo measure of the thalamocortical system. In this manuscript, we review the development of the thalamocortical system and sleep spindles in rodent models and humans. We then utilize this as a foundation to discuss alterations in sleep spindle activity in four of the most pervasive neurodevelopmental disorders-intellectual disability, attention deficit hyperactivity disorder, autism, and schizophrenia.

Recent Findings

Recent work in humans has shown alterations in sleep spindles across several neurodevelopmental disorders. Simultaneously, rodent models have elucidated the mechanisms which may underlie these deficits in spindle activity. This review merges recent findings from these two separate lines of research to draw conclusions about the pathogenesis of neurodevelopmental disorders.

Summary

We speculate that deficits in the thalamocortical system associated with neurodevelopmental disorders are exquisitely reflected in sleep spindle activity. We propose that sleep spindles may represent a promising biomarker for drug discovery, risk stratification, and treatment monitoring.

Machine Learning-Derived Active Sleep as an Early Predictor of White Matter Development in Preterm Infants

White matter dysmaturation is commonly seen in preterm infants admitted to the neonatal intensive care unit (NICU). Animal research has shown that active sleep is essential for early brain plasticity. This study aimed to determine the potential of active sleep as an early predictor for subsequent white matter development in preterm infants. Using heart and respiratory rates routinely monitored in the NICU, we developed a machine learning-based automated sleep stage classifier in a cohort of 25 preterm infants (12 females). The automated classifier was subsequently applied to a study cohort of 58 preterm infants (31 females) to extract active sleep percentage over 5-7 consecutive days during 29-32 weeks of postmenstrual age. Each of the 58 infants underwent high-quality T2-weighted magnetic resonance brain imaging at term-equivalent age, which was used to measure the total white matter volume. The association between active sleep percentage and white matter volume was examined using a multiple linear regression model adjusted for potential confounders. Using the automated classifier with a superior sleep classification performance [mean area under the receiver operating characteristic curve (AUROC) = 0.87, 95% CI 0.83-0.92], we found that a higher active sleep percentage during the preterm period was significantly associated with an increased white matter volume at term-equivalent age [β = 0.31, 95% CI 0.09-0.53, false discovery rate (FDR)-adjusted p-value = 0.021]. Our results extend the positive association between active sleep and early brain development found in animal research to human preterm infants and emphasize the potential benefit of sleep preservation in the NICU setting.

Sensory event-related potential morphology predicts age in premature infants

OBJECTIVE

We investigated whether sensory-evoked cortical potentials could be used to estimate the age of an infant. Such a model could be used to identify infants who deviate from normal neurodevelopment.

METHODS

Infants aged between 28- and 40-weeks post-menstrual age (PMA) (166 recording sessions in 96 infants) received trains of visual and tactile stimuli. Neurodynamic response functions for each stimulus were derived using principal component analysis and a machine learning model trained and validated to predict infant age.

RESULTS

PMA could be predicted accurately from the magnitude of the evoked responses (training set mean absolute error and 95% confidence intervals: 1.41 [1.14; 1.74] weeks,p = 0.0001; test set mean absolute error: 1.55 [1.21; 1.95] weeks,p = 0.0002). Moreover, we show that their predicted age (their brain age) is correlated with a measure known to relate to maturity of the nervous system and is linked to long-term neurodevelopment.

CONCLUSIONS

Sensory-evoked potentials are predictive of age in premature infants and brain age deviations are related to biologically and clinically meaningful individual differences in nervous system maturation.

SIGNIFICANCE

This model could be used to detect abnormal development of infants' response to sensory stimuli in their environment and may be predictive of neurodevelopmental outcome.

Continuity and change in neural plasticity through embryonic morphogenesis, fetal activity-dependent synaptogenesis, and infant memory consolidation

There is an apparent continuity in human neural development that can be traced to venerable themes of vertebrate morphogenesis that have shaped the evolution of the reptilian telencephalon (including both primitive three-layered cortex and basal ganglia) and then the subsequent evolution of the mammalian six-layered neocortex. In this theoretical analysis, we propose that an evolutionary-developmental analysis of these general morphogenetic themes can help to explain the embryonic development of the dual divisions of the limbic system that control the dorsal and ventral networks of the human neocortex. These include the archicortical (dorsal limbic) Papez circuits regulated by the hippocampus that organize spatial, contextual memory, as well as the paleocortical (ventral limbic) circuits that organize object memory. We review evidence that these dorsal and ventral limbic divisions are controlled by the differential actions of brainstem lemnothalamic and midbrain collothalamic arousal control systems, respectively, thereby traversing the vertebrate subcortical neuraxis. These dual control systems are first seen shaping the phyletic morphogenesis of the archicortical and paleocortical foundations of the forebrain in embryogenesis. They then provide dual modes of activity-dependent synaptic organization in the active (lemnothalamic) and quiet (collothalamic) stages of fetal sleep. Finally, these regulatory systems mature to form the major systems of memory consolidation of postnatal development, including the rapid eye movement (lemnothalamic) consolidation of implicit memory and social attachment in the first year, and then-in a subsequent stage-the non-REM (collothalamic) consolidation of explicit memory that is integral to the autonomy and individuation of the second year of life.

Generation and propagation of bursts of activity in the developing basal ganglia

The neonatal brain is characterized by intermittent bursts of oscillatory activity interspersed by relative silence. Although well-characterized for many cortical areas, to what extent these propagate and interact with subcortical brain areas is largely unknown. Here, early network activity was recorded from the developing basal ganglia, including motor/somatosensory cortex, dorsal striatum, and intralaminar thalamus, during the first postnatal weeks in mice. An unsupervised detection and classification method revealed two main classes of bursting activity, namely spindle bursts and nested gamma spindle bursts, characterized by oscillatory activity at ~ 10 and ~ 30 Hz frequencies, respectively. These were reliably identified across all three brain regions and exhibited region-specific differences in their structural, spectral, and developmental characteristics. Bursts of the same type often co-occurred in different brain regions and coherence and cross-correlation analyses reveal dynamic developmental changes in their interactions. The strongest interactions were seen for cortex and striatum, from the first postnatal week onwards, and cortex appeared to drive burst events in subcortical regions. Together, these results provide the first detailed description of early network activity within the developing basal ganglia and suggest that cortex is one of the main drivers of activity in downstream nuclei during this postnatal period.

Cortical signatures of visual body representation develop in human infancy

Human infants cannot report their experiences, limiting what we can learn about their bodily awareness. However, visual cortical responses to the body, linked to visual awareness and selective attention in adults, can be easily measured in infants and provide a promising marker of bodily awareness in early life. We presented 4- and 8-month-old infants with a flickering (7.5 Hz) video of a hand being stroked and recorded steady-state visual evoked potentials (SSVEPs). In half of the trials, the infants also received tactile stroking synchronously with visual stroking. The 8-month-old, but not the 4-month-old infants, showed a significant enhancement of SSVEP responses when they received tactile stimulation concurrent with the visually observed stroking. Follow-up experiments showed that this enhancement did not occur when the visual hand was presented in an incompatible posture with the infant's own body or when the visual stimulus was a body-irrelevant video. Our findings provide a novel insight into the development of bodily self-awareness in the first year of life.

Self-limited childhood epilepsies are disorders of the perisylvian communication system, carrying the risk of progress to epileptic encephalopathies-Critical review

"Sleep plasticity is a double-edged sword: a powerful machinery of neural build-up, with a risk to epileptic derailment." We aimed to review the types of self-limited focal epilepsies..."i.e. keep as two separate paragraphs" We aimed to review the types of self-limited focal epilepsies: (1) self-limited focal childhood epilepsy with centrotemporal spikes, (2) atypical Rolandic epilepsy, and (3) electrical status epilepticus in sleep with mental consequences, including Landau-Kleffner-type acquired aphasia, showing their spectral relationship and discussing the debated topics. Our endeavor is to support the system epilepsy concept in this group of epilepsies, using them as models for epileptogenesis in general. The spectral continuity of the involved conditions is evidenced by several features: language impairment, the overarching presence of centrotemporal spikes and ripples (with changing electromorphology across the spectrum), the essential timely and spatial independence of interictal epileptic discharges from seizures, NREM sleep relatedness, and the existence of the intermediate-severity "atypical" forms. These epilepsies might be the consequences of a genetically determined transitory developmental failure, reflected by widespread neuropsychological symptoms originating from the perisylvian network that have distinct time and space relations from secondary epilepsy itself. The involved epilepsies carry the risk of progression to severe, potentially irreversible encephalopathic forms.

Sensorimotor foundations of speech perception in infancy

The perceptual system for speech is highly organized from early infancy. This organization bootstraps young human learners' ability to acquire their native speech and language from speech input. Here, we review behavioral and neuroimaging evidence that perceptual systems beyond the auditory modality are also specialized for speech in infancy, and that motor and sensorimotor systems can influence speech perception even in infants too young to produce speech-like vocalizations. These investigations complement existing literature on infant vocal development and on the interplay between speech perception and production systems in adults. We conclude that a multimodal speech and language network is present before speech-like vocalizations emerge.

Dynamical systems model of development of the action differentiation in early infancy: a requisite of physical agency

Young infants are sensitive to whether their body movements cause subsequent events or not during the interaction with the environment. This ability has been revealed by empirical studies on the reinforcement of limb movements when a string is attached between an infant limb and a mobile toy suspended overhead. A previous study reproduced the experimental observation by modeling both the infant's limb and a mobile toy as a system of coupled oscillators. The authors then argued that emergence of agency could be explained by a phase transition in the dynamical system: from a weakly coupled state to a state where the both movements of the limb and the toy are highly coordinated. However, what remains unexplained is the following experimental observation: When the limb is connected to the mobile toy by a string, the infant increases the average velocity of the arm's movement. On the other hand, when the toy is controlled externally, the average arm's velocity is greatly reduced. Since young infants produce exuberant spontaneous movements even with no external stimuli, the inhibition of motor action to suppress the formation of spurious action-perception coupling should be also a crucial sign for the emergence of agency. Thus, we present a dynamical system model for the development of action differentiation, to move or not to move, in the mobile task. In addition to the pair of limb and mobile oscillators for providing positive feedback for reinforcement in the previous model, bifurcation dynamics are incorporated to enhance or inhibit self-movements in response to detecting contingencies between the limb and mobile movements. The results from computer simulations reproduce experimental observations on the developmental emergence of action differentiation between 2 and 3 months of age in the form of a bifurcation diagram. We infer that the emergence of physical agency entails young infants' ability not only to enhance a specific action-perception coupling, but also to decouple it and create a new mode of action-perception coupling based on the internal state dynamics with contingency detection between self-generated actions and environmental events.

Infant motor development predicts the dynamics of movement during sleep

The characteristics of infant sleep change over the first year. Generally, infants wake and move less at night as they grow older. However, acquisition of new motor skills leads to temporary increases in night waking and movement at night. Indeed, sleep-dependent movement at night is important for sensorimotor development. Nevertheless, little is known about how movement during sleep changes as infants accrue locomotor experience. The current study investigated whether infant sleep and movement during sleep were predicted by infants' walking experience. Seventy-eight infants wore an actigraph to measure physical activity during sleep. Parents reported when their infants first walked across a room >10 feet without stopping or falling. Infants in the midst of walking skill acquisition had worse sleep than an age-group estimate. Infants with more walk experience had more temporally sporadic movement during sleep and a steeper hourly increase in physical activity over the course of the night. Ongoing motor skill consolidation changes the characteristics of movement during sleep and may alter sleep state-dependent memory consolidation. We propose a model whereby changes in gross motor activity during night sleep reflect movement-dependent consolidation.

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.

Changing subplate circuits: Early activity dependent circuit plasticity

Early neural activity in the developing sensory system comprises spontaneous bursts of patterned activity, which is fundamental for sculpting and refinement of immature cortical connections. The crude early connections that are initially refined by spontaneous activity, are further elaborated by sensory-driven activity from the periphery such that orderly and mature connections are established for the proper functioning of the cortices. Subplate neurons (SPNs) are one of the first-born mature neurons that are transiently present during early development, the period of heightened activity-dependent plasticity. SPNs are well integrated within the developing sensory cortices. Their structural and functional properties such as relative mature intrinsic membrane properties, heightened connectivity via chemical and electrical synapses, robust activation by neuromodulatory inputs-place them in an ideal position to serve as crucial elements in monitoring and regulating spontaneous endogenous network activity. Moreover, SPNs are the earliest substrates to receive early sensory-driven activity from the periphery and are involved in its modulation, amplification, and transmission before the maturation of the direct adult-like thalamocortical connectivity. Consequently, SPNs are vulnerable to sensory manipulations in the periphery. A broad range of early sensory deprivations alters SPN circuit organization and functions that might be associated with long term neurodevelopmental and psychiatric disorders. Here we provide a comprehensive overview of SPN function in activity-dependent development during early life and integrate recent findings on the impact of early sensory deprivation on SPNs that could eventually lead to neurodevelopmental disorders.

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.

Neuronal oscillations: early biomarkers of psychiatric disease?

Our understanding of the environmental and genetic factors contributing to the wide spectrum of neuropsychiatric disorders has significantly increased in recent years. Impairment of neuronal network activity during early development has been suggested as a contributor to the emergence of neuropsychiatric pathologies later in life. Still, the neurobiological substrates underlying these disorders remain yet to be fully understood and the lack of biomarkers for early diagnosis has impeded research into curative treatment options. Here, we briefly review current knowledge on potential biomarkers for emerging neuropsychiatric disease. Moreover, we summarize recent findings on aberrant activity patterns in the context of psychiatric disease, with a particular focus on their potential as early biomarkers of neuropathologies, an essential step towards pre-symptomatic diagnosis and, thus, early intervention.

Sleep, plasticity, and sensory neurodevelopment

A defining feature of early infancy is the immense neural plasticity that enables animals to develop a brain that is functionally integrated with a growing body. Early infancy is also defined as a period dominated by sleep. Here, we describe three conceptual frameworks that vary in terms of whether and how they incorporate sleep as a factor in the activity-dependent development of sensory and sensorimotor systems. The most widely accepted framework is exemplified by the visual system where retinal waves seemingly occur independent of sleep-wake states. An alternative framework is exemplified by the sensorimotor system where sensory feedback from sleep-specific movements activates the brain. We prefer a third framework that encompasses the first two but also captures the diverse ways in which sleep modulates activity-dependent development throughout the nervous system. Appreciation of the third framework will spur progress toward a more comprehensive and cohesive understanding of both typical and atypical neurodevelopment.

An integrative perspective on the role of touch in the development of intersubjectivity

Touch concerns a fundamental component of sociality. In this review, we examine the hypothesis that somatomotor development constitutes a crucial psychophysiological element in the ontogeny of intersubjectivity. An interdisciplinary perspective is provided on how the communication channel of touch contributes to the sense of self and extends to the social self. During gestation, the transformation of random movements into organized sequences of actions with sensory consequences parallels the development of the brain's functional architecture. Brain subsystems shaped by the coordinated activity of somatomotor circuits to support these first body-environment interactions are the first brain functional arrangements to develop. We propose that tactile self-referring behaviour during gestation constitutes a prototypic mode of interpersonal exchange that supports the subsequent development of intersubjective exchange. The reviewed research suggests that touch constitutes a pivotal bodily experience that in early stages builds and later filters self-other interactions. This view is corroborated by the fact that aberrant social-affective touch experiences appear fundamentally associated with attachment anomalies, interpersonal trauma, and personality disorders. Given the centrality of touch for the development of intersubjectivity and for psychopathological conditions in the social domain, dedicated research is urged to elucidate the role of touch in the evolution of subjective self-other coding.

Learning limb-specific contingencies in early infancy

Most research with the mobile paradigm has the underlying assumption that young infants can selectively move the limb causing the contingent feedback from the mobile while avoiding irrelevant motor responses. Contrary to this long-held belief, others have argued that such differentiation ability is not fully developed early in life. In the current study, we revisited the traditional mobile paradigm with a contemporary research approach (using high-precision motion capture techniques, a yoked-control design, and a large sample size) to investigate whether response differentiation ability emerges before 5 months of age. The data collected from 76 infants (aged between 115 and 159 days) revealed that infants can learn sensorimotor contingencies by increasing the movement of the connected leg relative to their baseline level. However, they did not differentially increase the movement of the leg causing an effect in the environment compared with that of other limbs. Our results illustrate that response differentiation ability emerges later than previously suggested.

The Newborn's Reaction to Light as the Determinant of the Brain's Activation at Human Birth

Developmental neuroscience research has not yet fully unveiled the dynamics involved in human birth. The trigger of the first breath, often assumed to be the marker of human life, has not been characterized nor has the process entailing brain modification and activation at birth been clarified yet. To date, few researchers only have investigated the impact of the extrauterine environment, with its strong stimuli, on birth. This ‘hypothesis and theory' article assumes the role of a specific stimulus activating the central nervous system (CNS) at human birth. This stimulus must have specific features though, such as novelty, efficacy, ubiquity, and immediacy. We propose light as a robust candidate for the CNS activation via the retina. Available data on fetal and neonatal neurodevelopment, in particular with reference to retinal light-responsive pathways, will be examined together with the GABA functional switch, and the subplate disappearance, which, at an experimental level, differentiate the neonatal brain from the fetal brain. In this study, we assume how a very rapid activation of retinal photoreceptors at birth initiates a sudden brain shift from the prenatal pattern of functions to the neonatal setup. Our assumption implies the presence of a photoreceptor capable of capturing and transducing light/photon stimulus, transforming it into an effective signal for the activation of new brain functions at birth. Opsin photoreception or, more specifically, melanopsin-dependent photoreception, which is provided by intrinsically photosensitive retinal ganglion cells (ipRGCs), is considered as a valid candidate. Although what is assumed herein cannot be verified in humans based on knowledge available so far, proposing an important and novel function can trigger a broad range of diversified research in different domains, from neurophysiology to neurology and psychiatry.

The rapid developmental rise of somatic inhibition disengages hippocampal dynamics from self-motion

Early electrophysiological brain oscillations recorded in preterm babies and newborn rodents are initially mostly driven by bottom-up sensorimotor activity and only later can detach from external inputs. This is a hallmark of most developing brain areas, including the hippocampus, which, in the adult brain, functions in integrating external inputs onto internal dynamics. Such developmental disengagement from external inputs is likely a fundamental step for the proper development of cognitive internal models. Despite its importance, the developmental timeline and circuit basis for this disengagement remain unknown. To address this issue, we have investigated the daily evolution of CA1 dynamics and underlying circuits during the first two postnatal weeks of mouse development using two-photon calcium imaging in non-anesthetized pups. We show that the first postnatal week ends with an abrupt shift in the representation of self-motion in CA1. Indeed, most CA1 pyramidal cells switch from activated to inhibited by self-generated movements at the end of the first postnatal week, whereas the majority of GABAergic neurons remain positively modulated throughout this period. This rapid switch occurs within 2 days and follows the rapid anatomical and functional surge of local somatic GABAergic innervation. The observed change in dynamics is consistent with a two-population model undergoing a strengthening of inhibition. We propose that this abrupt developmental transition inaugurates the emergence of internal hippocampal dynamics.

Early brain activity: Translations between bedside and laboratory

Neural activity is both a driver of brain development and a readout of developmental processes. Changes in neuronal activity are therefore both the cause and consequence of neurodevelopmental compromises. Here, we review the assessment of neuronal activities in both preclinical models and clinical situations. We focus on issues that require urgent translational research, the challenges and bottlenecks preventing translation of biomedical research into new clinical diagnostics or treatments, and possibilities to overcome these barriers. The key questions are (i) what can be measured in clinical settings versus animal experiments, (ii) how do measurements relate to particular stages of development, and (iii) how can we balance practical and ethical realities with methodological compromises in measurements and treatments.

Sleep as a window on the sensorimotor foundations of the developing hippocampus

The hippocampal formation plays established roles in learning, memory, and related cognitive functions. Recent findings also suggest that the hippocampus integrates sensory feedback from self-generated movements to modulate ongoing motor responses in a changing environment. Such findings support the view of Bland and Oddie (Behavioural Brain Research, 2001, 127, 119-136) that the hippocampus is a site of sensorimotor integration. In further support of this view, we review neurophysiological evidence in developing rats that hippocampal function is built on a sensorimotor foundation and that this foundation is especially evident early in development. Moreover, at those ages when the hippocampus is first establishing functional connectivity with distant sensory and motor structures, that connectivity is preferentially expressed during periods of active (or REM) sleep. These findings reinforce the notion that sleep, as the predominant state of early infancy, provides a critical context for sensorimotor development, including development of the hippocampus and its associated network.

Neurophysiology of the Developing Cerebral Cortex: What We Have Learned and What We Need to Know

This review article aims to give a brief summary on the novel technologies, the challenges, our current understanding, and the open questions in the field of the neurophysiology of the developing cerebral cortex in rodents. In the past, in vitro electrophysiological and calcium imaging studies on single neurons provided important insights into the function of cellular and subcellular mechanism during early postnatal development. In the past decade, neuronal activity in large cortical networks was recorded in pre- and neonatal rodents in vivo by the use of novel high-density multi-electrode arrays and genetically encoded calcium indicators. These studies demonstrated a surprisingly rich repertoire of spontaneous cortical and subcortical activity patterns, which are currently not completely understood in their functional roles in early development and their impact on cortical maturation. Technological progress in targeted genetic manipulations, optogenetics, and chemogenetics now allow the experimental manipulation of specific neuronal cell types to elucidate the function of early (transient) cortical circuits and their role in the generation of spontaneous and sensory evoked cortical activity patterns. Large-scale interactions between different cortical areas and subcortical regions, characterization of developmental shifts from synchronized to desynchronized activity patterns, identification of transient circuits and hub neurons, role of electrical activity in the control of glial cell differentiation and function are future key tasks to gain further insights into the neurophysiology of the developing cerebral cortex.

Longitudinal Analysis of Sleep-Wake States in Neonatal Rats Subjected to Hypoxia-Ischemia

OBJECTIVE

Sleep is necessary for brain maturation in infants. Perinatal hypoxic-ischemic encephalopathy (HIE) is a major cause of chronic neurological disease in infants. Although the developmental changes of electroencephalogram (EEG) in human newborns have been described, little is known about the EEG normal maturation characteristics in rodents and the changes in sleep-awake states caused by hypoxia-ischemia (HI). This study aimed to investigate the pathological response of sleep-wake states in neonatal rats with HIE.

METHODS

We constructed HIE and sham models on postnatal day (P) 3 rats and continuously monitored them using electroencephalography and electromyography for up to P12. The distribution of sleep-wake states was analyzed to estimate the effects of HIE.

RESULTS

Compared with the sham group, the HI group showed lower rapid eye movement (REM) sleep percentage, but wake percentage and frequency was higher during P4-P12. The frequency of REM and non-rapid eye movement (NREM) sleep increased and the duration of REM and NREM sleep decreased after HI induction. However, it gradually returned to the normal level with an increase in daytime.

CONCLUSION

HI damage alters the sleep-wake patterns during early neural development. The findings provide a comprehensive assessment of serial sleep-wake state recordings in neonatal rats from P4-P12.

The impact of premature extrauterine exposure on infants' stimulus-evoked brain activity across multiple sensory systems

Prematurity can result in widespread neurodevelopmental impairment, with the impact of premature extrauterine exposure on brain function detectable in infancy. A range of neurodynamic and haemodynamic functional brain measures have previously been employed to study the neurodevelopmental impact of prematurity, with methodological and analytical heterogeneity across studies obscuring how multiple sensory systems are affected. Here, we outline a standardised template analysis approach to measure evoked response magnitudes for visual, tactile, and noxious stimulation in individual infants (n = 15) using EEG. By applying these templates longitudinally to an independent cohort of very preterm infants (n = 10), we observe that the evoked response template magnitudes are significantly associated with age-related maturation. Finally, in a cross-sectional study we show that the visual and tactile response template magnitudes differ between a cohort of infants who are age-matched at the time of study but who differ according to whether they are born during the very preterm or late preterm period (n = 10 and 8 respectively). These findings demonstrate the significant impact of premature extrauterine exposure on brain function and suggest that prematurity can accelerate maturation of the visual and tactile sensory system in infants born very prematurely. This study highlights the value of using a standardised multi-modal evoked-activity analysis approach to assess premature neurodevelopment, and will likely complement resting-state EEG and behavioural assessments in the study of the functional impact of developmental care interventions.

Sensorimotor Integration in Childhood Dystonia and Dystonic Cerebral Palsy-A Developmental Perspective

Dystonia is a disorder of sensorimotor integration, involving dysfunction within the basal ganglia, cortex, cerebellum, or their inter-connections as part of the sensorimotor network. Some forms of dystonia are also characterized by maladaptive or exaggerated plasticity. Development of the neuronal processes underlying sensorimotor integration is incompletely understood but involves activity-dependent modeling and refining of sensorimotor circuits through processes that are already taking place in utero and which continue through infancy, childhood, and into adolescence. Several genetic dystonias have clinical onset in early childhood, but there is evidence that sensorimotor circuit development may already be disrupted prenatally in these conditions. Dystonic cerebral palsy (DCP) is a form of acquired dystonia with perinatal onset during a period of rapid neurodevelopment and activity-dependent refinement of sensorimotor networks. However, physiological studies of children with dystonia are sparse. This discussion paper addresses the role of neuroplasticity in the development of sensorimotor integration with particular focus on the relevance of these mechanisms for understanding childhood dystonia, DCP, and implications for therapy selection, including neuromodulation and timing of intervention.

A transient postnatal quiescent period precedes emergence of mature cortical dynamics

Mature neural networks synchronize and integrate spatiotemporal activity patterns to support cognition. Emergence of these activity patterns and functions is believed to be developmentally regulated, but the postnatal time course for neural networks to perform complex computations remains unknown. We investigate the progression of large-scale synaptic and cellular activity patterns across development using high spatiotemporal resolution in vivo electrophysiology in immature mice. We reveal that mature cortical processes emerge rapidly and simultaneously after a discrete but volatile transition period at the beginning of the second postnatal week of rodent development. The transition is characterized by relative neural quiescence, after which spatially distributed, temporally precise, and internally organized activity occurs. We demonstrate a similar developmental trajectory in humans, suggesting an evolutionarily conserved mechanism that could facilitate a transition in network operation. We hypothesize that this transient quiescent period is a requisite for the subsequent emergence of coordinated cortical networks.

It can take several months, or even years, for the brain of a young animal to develop and refine the complex neural networks which underpin cognitive abilities such as memory, planning, and decision making. While the properties that support these functions have been well-documented, less is known about how they emerge during development.

Domínguez, Ma, Yu et al. therefore set out to determine when exactly these properties began to take shape in mice, using lightweight nets of electrodes to record brain activity in sleeping newborn pups. The nets were designed to avoid disturbing the animals or damaging their fragile brains.

The recordings showed that patterns of brain activity similar to those seen in adults emerged during the first couple of weeks after birth. Just before, however, the brains of the pups went through a brief period of reduced activity: this lull seemed to mark a transition from an immature to a more mature mode of operation. After this pause, neurons in the mouse brains showed coordinated patterns of firing reminiscent of those seen in adults. By monitoring the brains of human babies using scalp sensors, Domínguez, Ma, Yu et al. showed that a similar transition also occurs in infants during their first few months of life, suggesting that brains may mature via a process retained across species.

Overall, the relative lull in activity before transition may mark when neural networks gain mature properties; in the future, it could therefore potentially be used to diagnose and monitor individuals with delayed cognitive development.

Spontaneous activity in developing thalamic and cortical sensory networks

Developing sensory circuits exhibit different patterns of spontaneous activity, patterns that are related to the construction and refinement of functional networks. During the development of different sensory modalities, spontaneous activity originates in the immature peripheral sensory structures and in the higher-order central structures, such as the thalamus and cortex. Certainly, the perinatal thalamus exhibits spontaneous calcium waves, a pattern of activity that is fundamental for the formation of sensory maps and for circuit plasticity. Here, we review our current understanding of the maturation of early (including embryonic) patterns of spontaneous activity and their influence on the assembly of thalamic and cortical sensory networks. Overall, the data currently available suggest similarities between the developmental trajectory of brain activity in experimental models and humans, which in the future may help to improve the early diagnosis of developmental disorders.

Twitches emerge postnatally during quiet sleep in human infants and are synchronized with sleep spindles

In humans and other mammals, the stillness of sleep is punctuated by bursts of rapid eye movements (REMs) and myoclonic twitches of the limbs.¹ Like the spontaneous activity that arises from the sensory periphery in other modalities (e.g., retinal waves),² sensory feedback arising from twitches is well suited to drive activity-dependent development of the sensorimotor system.³ It is partly because of the behavioral activation of REM sleep that this state is also called active sleep (AS), in contrast with the behavioral quiescence that gives quiet sleep (QS)-the second major stage of sleep-its name. In human infants, for which AS occupies 8 h of each day,⁴ twitching helps to identify the state;^5-8 nonetheless, we know little about the structure and functions of twitching across development. Recently, in sleeping infants,⁹ we documented a shift in the temporal expression of twitching beginning around 3 months of age that suggested a qualitative change in how twitches are produced. Here, we combine behavioral analysis with high-density electroencephalography (EEG) to demonstrate that this shift reflects the emergence of limb twitches during QS. Twitches during QS are not only unaccompanied by REMs, but they also occur synchronously with sleep spindles, a hallmark of QS. As QS-related twitching increases with age, sleep spindle rate also increases along the sensorimotor strip. The emerging synchrony between subcortically generated twitches and cortical oscillations suggests the development of functional connectivity among distant sensorimotor structures, with potential implications for detecting and explaining atypical developmental trajectories.

The development of body representations: an associative learning account

Representing one's own body is of fundamental importance to interact with our environment, yet little is known about how body representations develop. One account suggests that the ability to represent one's own body is present from birth and supports infants' ability to detect similarities between their own and others' bodies. However, in recent years evidence has been accumulating for alternative accounts that emphasize the role of multisensory experience obtained through acting and interacting with our own body in the development of body representations. Here, we review this evidence, and propose an integrative account that suggests that through experience, infants form multisensory associations that facilitate the development of body representations. This associative account provides a coherent explanation for previous developmental findings, and generates novel hypotheses for future research.

Sleep-wake regulation in preterm and term infants

Study Objectives

In adults, wakefulness can be markedly prolonged at the expense of sleep, e.g. to stay vigilant in the presence of a stressor. These extra-long wake bouts result in a heavy-tailed distribution (highly right-skewed) of wake but not sleep durations. In infants, the relative importance of wakefulness and sleep are reversed, as sleep is necessary for brain maturation. Here, we tested whether these developmental pressures are associated with the unique regulation of sleep–wake states.

Methods

In 175 infants of 28–40 weeks postmenstrual age (PMA), we monitored sleep–wake states using electroencephalography and behavior. We constructed survival models of sleep–wake bout durations and the effect of PMA and other factors, including stress (salivary cortisol), and examined whether sleep is resilient to nociceptive perturbations (a clinically necessary heel lance).

Results

Wake durations followed a heavy-tailed distribution as in adults and lengthened with PMA and stress. However, differently from adults, active sleep durations also had a heavy-tailed distribution, and with PMA, these shortened and became vulnerable to nociception-associated awakenings.

Conclusions

Sleep bouts are differently regulated in infants, with especially long active sleep durations that could consolidate this state’s maturational functions. Curtailment of sleep by stress and nociception may be disadvantageous, especially for preterm infants given the limited value of wakefulness at this age. This could be addressed by environmental interventions in the future.

Fundamentals of the Development of Connectivity in the Human Fetal Brain in Late Gestation: From 24 Weeks Gestational Age to Term

During the second half of gestation, the human cerebrum undergoes pivotal histogenetic events that underlie functional connectivity. These include the growth, guidance, selection of axonal pathways, and their first engagement in neuronal networks. Here, we characterize the spatiotemporal patterns of cerebral connectivity in extremely preterm (EPT), very preterm (VPT), preterm and term babies, focusing on magnetic resonance imaging (MRI) and histological data. In the EPT and VPT babies, thalamocortical axons enter into the cortical plate creating the electrical synapses. Additionally, the subplate zone gradually resolves in the preterm and term brain in conjunction with the growth of associative pathways leading to the activation of large-scale neural networks. We demonstrate that specific classes of axonal pathways within cerebral compartments are selectively vulnerable to temporally nested pathogenic factors. In particular, the radial distribution of axonal lesions, that is, radial vulnerability, is a robust predictor of clinical outcome. Furthermore, the subplate tangential nexus that we can visualize using MRI could be an additional marker as pivotal in the development of cortical connectivity. We suggest to direct future research toward the identification of sensitive markers of earlier lesions, the elucidation of genetic mechanisms underlying pathogenesis, and better long-term follow-up using structural and functional MRI.

Sleep and human cognitive development

Emerging studies across learning domains have shed light on mechanisms underlying sleep's benefits during numerous developmental periods. In this conceptual review, we survey recent studies of sleep and cognition across infancy, childhood, and adolescence. By summarizing recent findings and integrating across studies with disparate approaches, we provide a novel understanding of sleep's role in human cognitive function. Collectively, these studies point to an interrelation between brain development, sleep, and cognition. Moreover, we point to gaps in our understanding, which inform the agenda for future research in developmental and sleep science.

The relation between sleep and neurocognitive development in infancy and early childhood: A neuroscience perspective

Sleep is essential for human life. It has different characteristics in the early stages of life compared to later periods: during development, qualitative and quantitative changes in sleep features occur such as the onset of REM/NREM sleep at 3 months, the progressive increase of night sleep duration, and the reduction of total sleep time. Sleep seems to be essential in the cognitive functions' development, especially in the first period of life. Indeed, higher rates of night sleep at the age of 12 and 18 months are associated with higher executive functions' performance. Furthermore, memory consolidation occurs during sleep and sleep contributes to children's learning not only in retaining information but also in organizing memories most efficiently. Therefore, sleep problems could cause negative effects on some features of cognitive development like memory, executive functions, and learning process. There is also an intimate relationship between sleep and regulation of emotional brain functions, with a link between sleep disturbance and behavioral problems.

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.

Delta brushes are not just a hallmark of EEG in human preterm infants

The delta brush, a well-known characteristic waveform of the human preterm electroencephalogram, represents spontaneous electrical activity. Recent experimental animal model evidence suggests that delta brushes are not only spontaneous intrinsic activity but are also evoked by external sensory stimulation or spontaneous movement. They are also likely to reflect the activity of subplate neurons, which play an important role in early brain development and network organization. Here, evidence about delta brushes in human preterm electroencephalogram is provided along with future perspectives.

Deep Learning for EEG Seizure Detection in Preterm Infants

EEG is the gold standard for seizure detection in the newborn infant, but EEG interpretation in the preterm group is particularly challenging; trained experts are scarce and the task of interpreting EEG in real-time is arduous. Preterm infants are reported to have a higher incidence of seizures compared to term infants. Preterm EEG morphology differs from that of term infants, which implies that seizure detection algorithms trained on term EEG may not be appropriate. The task of developing preterm specific algorithms becomes extra-challenging given the limited amount of annotated preterm EEG data available. This paper explores novel deep learning (DL) architectures for the task of neonatal seizure detection in preterm infants. The study tests and compares several approaches to address the problem: training on data from full-term infants; training on data from preterm infants; training on age-specific preterm data and transfer learning. The system performance is assessed on a large database of continuous EEG recordings of 575[Formula: see text]h in duration. It is shown that the accuracy of a validated term-trained EEG seizure detection algorithm, based on a support vector machine classifier, when tested on preterm infants falls well short of the performance achieved for full-term infants. An AUC of 88.3% was obtained when tested on preterm EEG as compared to 96.6% obtained when tested on term EEG. When re-trained on preterm EEG, the performance marginally increases to 89.7%. An alternative DL approach shows a more stable trend when tested on the preterm cohort, starting with an AUC of 93.3% for the term-trained algorithm and reaching 95.0% by transfer learning from the term model using available preterm data. The proposed DL approach avoids time-consuming explicit feature engineering and leverages the existence of the term seizure detection model, resulting in accurate predictions with a minimum amount of annotated preterm data.

Dance on the Brain: Enhancing Intra- and Inter-Brain Synchrony

Dance has traditionally been viewed from a Eurocentric perspective as a mode of self-expression that involves the human body moving through space, performed for the purposes of art, and viewed by an audience. In this Hypothesis and Theory article, we synthesize findings from anthropology, sociology, psychology, dance pedagogy, and neuroscience to propose The Synchronicity Hypothesis of Dance, which states that humans dance to enhance both intra- and inter-brain synchrony. We outline a neurocentric definition of dance, which suggests that dance involves neurobehavioral processes in seven distinct areas including sensory, motor, cognitive, social, emotional, rhythmic, and creative. We explore The Synchronicity Hypothesis of Dance through several avenues. First, we examine evolutionary theories of dance, which suggest that dance drives interpersonal coordination. Second, we examine fundamental movement patterns, which emerge throughout development and are omnipresent across cultures of the world. Third, we examine how each of the seven neurobehaviors increases intra- and inter-brain synchrony. Fourth, we examine the neuroimaging literature on dance to identify the brain regions most involved in and affected by dance. The findings presented here support our hypothesis that we engage in dance for the purpose of intrinsic reward, which as a result of dance-induced increases in neural synchrony, leads to enhanced interpersonal coordination. This hypothesis suggests that dance may be helpful to repattern oscillatory activity, leading to clinical improvements in autism spectrum disorder and other disorders with oscillatory activity impairments. Finally, we offer suggestions for future directions and discuss the idea that our consciousness can be redefined not just as an individual process but as a shared experience that we can positively influence by dancing together.

The Role of Affectionate Caregiver Touch in Early Neurodevelopment and Parent-Infant Interactional Synchrony

Though rarely included in studies of parent–infant interactions, affectionate touch plays a unique and vital role in infant development. Previous studies in human and rodent models have established that early and consistent affectionate touch from a caregiver confers wide-ranging and holistic benefits for infant psychosocial and neurophysiological development. We begin with an introduction to the neurophysiological pathways for the positive effects of touch. Then, we provide a brief review of how affectionate touch tunes the development of infant somatosensory, autonomic (stress regulation), and immune systems. Affective touch also plays a foundational role in the establishment of social affiliative bonds and early psychosocial behavior. These touch-related bonding effects are known to be mediated primarily by the oxytocin system, but touch also activates mesocorticolimbic dopamine and endogenous opioid systems which aid the development of social cognitive processes such as social learning and reward processing. We conclude by proposing a unique role for affectionate touch as an essential pathway to establishing and maintaining parent-infant interactional synchrony at behavioral and neural levels. The limitations of the current understanding of affectionate touch in infant development point to fruitful avenues for future research.

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.