Neuronal Coupling Modes Show Differential Development in the Early Cortical Activity Networks of Human Newborns.

The third trimester is a critical period for the development of functional networks that support the lifelong neurocognitive performance, yet the emergence of neuronal coupling in these networks is poorly understood. Here, we used longitudinal high-density electroencephalographic recordings from preterm infants during the period from 33 to 45 weeks of conceptional age (CA) to characterize early spatiotemporal patterns in the development of local cortical function and the intrinsic coupling modes [ICMs; phase-phase (PPCs), amplitude-amplitude (AACs), and phase-amplitude correlations (PACs)]. Absolute local power showed a robust increase with CA across the full frequency spectrum, while local PACs showed sleep state-specific, biphasic development that peaked a few weeks before normal birth. AACs and distant PACs decreased globally at nearly all frequencies. In contrast, the PPCs showed frequency- and region-selective development, with an increase of coupling strength with CA between frontal, central, and occipital regions at low-delta and alpha frequencies together with a wider-spread decrease at other frequencies. Our findings together present the spectrally and spatially differential development of the distinct ICMs during the neonatal period and provide their developmental templates for future basic and clinical research.

Quantitative EEG features during the first day correlate to clinical outcome in perinatal asphyxia.

OBJECTIVE: To assess whether computational electroencephalogram (EEG) measures during the first day of life correlate to clinical outcomes in infants with perinatal asphyxia with or without hypoxic-ischemic encephalopathy (HIE). METHODS: We analyzed four-channel EEG monitoring data from 91 newborn infants after perinatal asphyxia. Altogether 42 automatically computed amplitude- and synchrony-related EEG features were extracted as 2-hourly average at very early (6 h) and early (24 h) postnatal age; they were correlated to the severity of HIE in all infants, and to four clinical outcomes available in a subcohort of 40 newborns: time to full oral feeding (nasogastric tube NGT), neonatal brain MRI, Hammersmith Infant Neurological Examination (HINE) at three months, and Griffiths Scales at two years. RESULTS: At 6 h, altogether 14 (33%) EEG features correlated significantly to the HIE grade ([r]= 0.39-0.61, p < 0.05), and one feature correlated to NGT ([r]= 0.50). At 24 h, altogether 13 (31%) EEG features correlated significantly to the HIE grade ([r]= 0.39-0.56), six features correlated to NGT ([r]= 0.36-0.49) and HINE ([r]= 0.39-0.61), while no features correlated to MRI or Griffiths Scales. CONCLUSIONS: Our results show that the automatically computed measures of early cortical activity may provide outcome biomarkers for clinical and research purposes. IMPACT: The early EEG background and its recovery after perinatal asphyxia reflect initial severity of encephalopathy and its clinical recovery, respectively. Computational EEG features from the early hours of life show robust correlations to HIE grades and to early clinical outcomes. Computational EEG features may have potential to be used as cortical activity biomarkers in early hours after perinatal asphyxia.

Multiplex dynamic networks in the newborn brain disclose latent links with neurobehavioral phenotypes.

The higher brain functions arise from coordinated neural activity between distinct brain regions, but the spatial, temporal, and spectral complexity of these functional connectivity networks (FCNs) has challenged the identification of correlates with neurobehavioral phenotypes. Characterizing behavioral correlates of early life FCNs is important to understand the activity dependent emergence of neurodevelopmental performance and for improving health outcomes. Here, we develop an analysis pipeline for identifying multiplex dynamic FCNs that combine spectral and spatiotemporal characteristics of the newborn cortical activity. This data-driven approach automatically uncovers latent networks that show robust neurobehavioral correlations and consistent effects by in utero drug exposure. Altogether, the proposed pipeline provides a robust end-to-end solution for an objective assessment and quantitation of neurobehaviorally meaningful network constellations in the highly dynamic cortical functions.

Networks of cortical activity show graded responses to perinatal asphyxia.

BACKGROUND: Perinatal asphyxia often leads to hypoxic-ischemic encephalopathy (HIE) with a high risk of neurodevelopmental consequences. While moderate and severe HIE link to high morbidity, less is known about brain effects of perinatal asphyxia with no or only mild HIE. Here, we test the hypothesis that cortical activity networks in the newborn infants show a dose-response to asphyxia. METHODS: We performed EEG recordings for infants with perinatal asphyxia/HIE of varying severity (n = 52) and controls (n = 53) and examined well-established computational metrics of cortical network activity. RESULTS: We found graded alterations in cortical activity networks according to severity of asphyxia/HIE. Furthermore, our findings correlated with early clinical recovery measured by the time to attain full oral feeding. CONCLUSION: We show that both local and large-scale correlated cortical activity are affected by increasing severity of HIE after perinatal asphyxia, suggesting that HIE and perinatal asphyxia are better represented as a continuum rather than the currently used discreet categories. These findings imply that automated computational measures of cortical function may be useful in characterizing the dose effects of adversity in the neonatal brain; such metrics hold promise for benchmarking clinical trials via patient stratification or as early outcome measures. IMPACT: Perinatal asphyxia causes every fourth neonatal death worldwide and provides a diagnostic and prognostic challenge for the clinician. We report that infants with perinatal asphyxia show specific graded responses in cortical networks according to severity of asphyxia and ensuing hypoxic-ischaemic encephalopathy. Early EEG recording and automated computational measures of brain function have potential to help in clinical evaluation of infants with perinatal asphyxia.

Neonatal cortical activity organizes into transient network states that are affected by vigilance states and brain injury.

Early neurodevelopment is critically dependent on the structure and dynamics of spontaneous neuronal activity; however, the natural organization of newborn cortical networks is poorly understood. Recent adult studies suggest that spontaneous cortical activity exhibits discrete network states with physiological correlates. Here, we studied newborn cortical activity during sleep using hidden Markov modeling to determine the presence of such discrete neonatal cortical states (NCS) in 107 newborn infants, with 47 of them presenting with a perinatal brain injury. Our results show that neonatal cortical activity organizes into four discrete NCSs that are present in both cardinal sleep states of a newborn infant, active and quiet sleep, respectively. These NCSs exhibit state-specific spectral and functional network characteristics. The sleep states exhibit different NCS dynamics, with quiet sleep presenting higher fronto-temporal activity and a stronger brain-wide neuronal coupling. Brain injury was associated with prolonged lifetimes of the transient NCSs, suggesting lowered dynamics, or flexibility, in the cortical networks. Taken together, the findings suggest that spontaneously occurring transient network states are already present at birth, with significant physiological and pathological correlates; this NCS analysis framework can be fully automatized, and it holds promise for offering an objective, global level measure of early brain function for benchmarking neurodevelopmental or clinical research.

Cortical networks show characteristic recruitment patterns after somatosensory stimulation by pneumatically evoked repetitive hand movements in newborn infants.

Controlled assessment of functional cortical networks is an unmet need in the clinical research of noncooperative subjects, such as infants. We developed an automated, pneumatic stimulation method to actuate naturalistic movements of an infant's hand, as well as an analysis pipeline for assessing the elicited electroencephalography (EEG) responses and related cortical networks. Twenty newborn infants with perinatal asphyxia were recruited, including 7 with mild-to-moderate hypoxic-ischemic encephalopathy (HIE). Statistically significant corticokinematic coherence (CKC) was observed between repetitive hand movements and EEG in all infants, peaking near the contralateral sensorimotor cortex. CKC was robust to common sources of recording artifacts and to changes in vigilance state. A wide recruitment of cortical networks was observed with directed phase transfer entropy, also including areas ipsilateral to the stimulation. The extent of such recruited cortical networks was quantified using a novel metric, Spreading Index, which showed a decrease in 4 (57%) of the infants with HIE. CKC measurement is noninvasive and easy to perform, even in noncooperative subjects. The stimulation and analysis pipeline can be fully automated, including the statistical evaluation of the cortical responses. Therefore, the CKC paradigm holds great promise as a scientific and clinical tool for controlled assessment of functional cortical networks.

Networks of cortical activity in infants with epilepsy.

Epilepsy in infancy links to a significant risk of neurodevelopmental delay, calling for a better understanding of its underlying mechanisms. Here, we studied cortical activity networks in infants with early-onset epilepsy to identify network properties that could pre-empt infants' neurodevelopmental course. We studied high-density (64 channel) electroencephalogram during non-rapid eye movement (N2) sleep in n = 49 infants at 1 year of age after being diagnosed with epilepsy during their first year of life. We computed frequency-specific networks in the cortical source space for two intrinsic brain modes: amplitude-amplitude and phase-phase correlations. Cortical activity networks of all frequency bands and connectivity modes were compared between the syndrome groups as well as between the three categories of neurocognitive development. The group differences were studied at three spatial levels: global, regional, and individual connections. Cortical mechanisms related to infant epilepsy were further compared with physiological networks using an automatic spindle detection algorithm. Our results show that global connectivity does not significantly differ between epilepsy syndromes; however, it co-varies with neurocognitive development. The largest network differences were observed at the lowest (<1 Hz) and mid-range (10-15 Hz) frequency bands. An algorithmic removal of sleep spindles from the data partially reduced the mid-range frequency network's strength. The centrocentral and frontocentral networks at the spindle frequencies were found to be strongest in infants with a persistent age-typical neurocognitive performance, while their low-frequency (< 1 Hz) networks were weaker for both amplitude-amplitude [P = 0.008, effect size = 0.61] and phase-phase correlations (P = 0.02, effect size = 0.54) at low (< 1 Hz). However, subjects with persistent mild neurocognitive delay from 1 to 2 years of age had higher amplitude-amplitude (P = 0.02, effect size = 0.73) and phase-phase (P = 0.06, effect size = 0.59) at low frequencies than those that deteriorated from mild to severely delayed from 1 to 2 years of age. Our findings suggest that cortical activity networks reflect the underlying clinical course of infants' epilepsy, and measures of spectrally and spatially resolved networks might become useful in better understanding infantile epilepsy as a network disease.

Facilitating early parent-infant emotional connection improves cortical networks in preterm infants.

Exposure to environmental adversities during early brain development, such as preterm birth, can affect early brain organization. Here, we studied whether development of cortical activity networks in preterm infants may be improved by a multimodal environmental enrichment via bedside facilitation of mother-infant emotional connection. We examined functional cortico-cortical connectivity at term age using high-density electroencephalography recordings in infants participating in a randomized controlled trial of Family Nurture Intervention (FNI). Our results identify several large-scale, frequency-specific network effects of FNI, most extensively in the alpha frequency in fronto-central cortical regions. The connectivity strength in this network was correlated to later neurocognitive performance, and it was comparable to healthy term-born infants rather than the infants receiving standard care. These findings suggest that preterm neurodevelopmental care can be improved by a biologically driven environmental enrichment, such as early facilitation of direct human connection.

Cortical Cross-Frequency Coupling Is Affected by in utero Exposure to Antidepressant Medication.

Up to five percent of human infants are exposed to maternal antidepressant medication by serotonin reuptake inhibitors (SRI) during pregnancy, yet the SRI effects on infants' early neurodevelopment are not fully understood. Here, we studied how maternal SRI medication affects cortical frequency-specific and cross-frequency interactions estimated, respectively, by phase-phase correlations (PPC) and phase-amplitude coupling (PAC) in electroencephalographic (EEG) recordings. We examined the cortical activity in infants after fetal exposure to SRIs relative to a control group of infants without medical history of any kind. Our findings show that the sleep-related dynamics of PPC networks are selectively affected by in utero SRI exposure, however, those alterations do not correlate to later neurocognitive development as tested by neuropsychological evaluation at two years of age. In turn, phase-amplitude coupling was found to be suppressed in SRI infants across multiple distributed cortical regions and these effects were linked to their neurocognitive outcomes. Our results are compatible with the overall notion that in utero drug exposures may cause subtle, yet measurable changes in the brain structure and function. Our present findings are based on the measures of local and inter-areal neuronal interactions in the cortex which can be readily used across species, as well as between different scales of inspection: from the whole animals to in vitro preparations. Therefore, this work opens a framework to explore the cellular and molecular mechanisms underlying neurodevelopmental SRI effects at all translational levels.

Phase-Based Cortical Synchrony Is Affected by Prematurity.

Inter-areal synchronization by phase-phase correlations (PPCs) of cortical oscillations mediates many higher neurocognitive functions, which are often affected by prematurity, a globally prominent neurodevelopmental risk factor. Here, we used electroencephalography to examine brain-wide cortical PPC networks at term-equivalent age, comparing human infants after early prematurity to a cohort of healthy controls. We found that prematurity affected these networks in a sleep state-specific manner, and the differences between groups were also frequency-selective, involving brain-wide connections. The strength of synchronization in these networks was predictive of clinical outcomes in the preterm infants. These findings show that prematurity affects PPC networks in a clinically significant manner, suggesting early functional biomarkers of later neurodevelopmental compromise that may be used in clinical or translational studies after early neonatal adversity.

Impact of In Utero Exposure to Antiepileptic Drugs on Neonatal Brain Function.

In utero brain development underpins brain health across the lifespan but is vulnerable to physiological and pharmacological perturbation. Here, we show that antiepileptic medication during pregnancy impacts on cortical activity during neonatal sleep, a potent indicator of newborn brain health. These effects are evident in frequency-specific functional brain networks and carry prognostic information for later neurodevelopment. Notably, such effects differ between different antiepileptic drugs that suggest neurodevelopmental adversity from exposure to antiepileptic drugs and not maternal epilepsy per se. This work provides translatable bedside metrics of brain health that are sensitive to the effects of antiepileptic drugs on postnatal neurodevelopment and carry direct prognostic value.

A Bedside Method for Measuring Effects of a Sedative Drug on Cerebral Function in Newborn Infants.

BACKGROUND: Data on the cerebral effects of analgesic and sedative drugs are needed for the development of safe and effective treatments during neonatal intensive care. Electroencephalography (EEG) is an objective, but interpreter-dependent method for monitoring cortical activity. Quantitative computerized analyses might reveal EEG changes otherwise not detectable. METHODS: EEG registrations were retrospectively collected from 21 infants (mean 38.7 gestational weeks; range 27-42) who received dexmedetomidine during neonatal care. The registrations were transformed into computational features and analyzed visually, and with two computational measures quantifying relative and absolute changes in power (range EEG; rEEG) and cortico-cortical synchrony (activation synchrony index; ASI), respectively. RESULTS: The visual assessment did not reveal any drug effects. In rEEG analyses, a negative correlation was found between the baseline and the referential frontal (rho = 0.612, p = 0.006) and parietal (rho = -0.489, p = 0.035) derivations. The change in ASI was negatively correlated to baseline values in the interhemispheric (rho = -0.753; p = 0.001) and frontal comparisons (rho = -0.496; p = 0.038). CONCLUSION: Cerebral effects of dexmedetomidine as determined by EEG in newborn infants are related to cortical activity prior to DEX administration, indicating that higher brain activity levels (higher rEEG) during baseline links to a more pronounced reduction by DEX. The computational measurements indicate drug effects on both overall cortical activity and cortico-cortical communication. These effects were not evident in visual analysis.

Recording activity in proximal muscle networks with surface EMG in assessing infant motor development.

OBJECTIVE: To develop methods for recording and analysing infant's proximal muscle activations. METHODS: Surface electromyography (sEMG) of truncal muscles was recorded in three months old infants (N = 18) during spontaneous movement and controlled postural changes. The infants were also divided into two groups according to motor performance. We developed an efficient method for removing dynamic cardiac artefacts to allow i) accurate estimation of individual muscle activations, as well as ii) quantitative characterization of muscle networks. RESULTS: The automated removal of cardiac artefacts allowed quantitation of truncal muscle activity, which showed predictable effects during postural changes, and there were differences between high and low performing infants.The muscle networks showed consistent change in network density during spontaneous movements between supine and prone position. Moreover, activity correlations in individual pairs of back muscles linked to infant́s motor performance. CONCLUSIONS: The hereby developed sEMG analysis methodology is feasible and may disclose differences between high and low performing infants. Analysis of the muscle networks may provide novel insight to central control of motility. SIGNIFICANCE: Quantitative analysis of infant's muscle activity and muscle networks holds promise for an objective neurodevelopmental assessment of motor system.

Characterization of the Functional Dynamics in the Neonatal Brain during REM and NREM Sleep States by means of Microstate Analysis.

Neonates spend most of their life sleeping. During sleep, their brain experiences fast changes in its functional organization. Microstate analysis permits to capture the rapid dynamical changes occurring in the functional organization of the brain by representing the changing spatio-temporal features of the electroencephalogram (EEG) as a sequence of short-lasting scalp topographies-the microstates. In this study, we modeled the ongoing neonatal EEG into sequences of a limited number of microstates and investigated whether the extracted microstate features are altered in REM and NREM sleep (usually known as active and quiet sleep states-AS and QS-in the newborn) and depend on the EEG frequency band. 19-channel EEG recordings from 60 full-term healthy infants were analyzed using a modified version of the k-means clustering algorithm. The results show that ~ 70% of the variance in the datasets can be described using 7 dominant microstate templates. The mean duration and mean occurrence of the dominant microstates were significantly different in the two sleep states. Microstate syntax analysis demonstrated that the microstate sequences characterizing AS and QS had specific non-casual structures that differed in the two sleep states. Microstate analysis of the neonatal EEG in specific frequency bands showed a clear dependence of the explained variance on frequency. Overall, our findings demonstrate that (1) the spatio-temporal dynamics of the neonatal EEG can be described by non-casual sequences of a limited number of microstate templates; (2) the brain dynamics described by these microstate templates depends on frequency; (3) the features of the microstate sequences can well differentiate the physiological conditions characterizing AS and QS.

Use of complex visual stimuli allows controlled recruitment of cortical networks in infants.

OBJECTIVE: To characterize cortical networks activated by patterned visual stimuli in infants, and to evaluate their potential for assessment of visual processing and their associations with neurocognitive development. METHODS: Three visual stimuli, orientation reversal (OR), global form (GF), and global motion (GM), were presented to cohort of five-month-old infants (N = 26). Eye tracker was used to guide the stimulation and to choose epochs for analysis. Visual responses were recorded with electroencephalography and analysed in source space using weighted phase lag index as the connectivity measure. The networks were quantified using several metrics that were compared between stimuli and correlated to cognitive outcomes. RESULTS: Responses to OR/GF/GM stimuli were observed in nearly all (96/100/100%) recordings. All stimuli recruited cortical networks that were partly condition-specific in their characteristics. The more complex GF and GM conditions recruited wider global networks than OR. Additionally, strength of the GF network showed positive association with later cognitive performance. CONCLUSIONS: Network analysis suggests that visual stimulation recruits large-scale cortical networks that extend far beyond the conventional visual streams and that differ between stimulation conditions. SIGNIFICANCE: The method allows controlled recruitment of wide cortical networks, which holds promise for the early assessment of visual processing and its related higher-order cognitive processes.

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.

Large-scale brain modes reorganize between infant sleep states and carry prognostic information for preterms.

Sleep architecture carries vital information about brain health across the lifespan. In particular, the ability to express distinct vigilance states is a key physiological marker of neurological wellbeing in the newborn infant although systems-level mechanisms remain elusive. Here, we demonstrate that the transition from quiet to active sleep in newborn infants is marked by a substantial reorganization of large-scale cortical activity and functional brain networks. This reorganization is attenuated in preterm infants and predicts visual performance at two years. We find a striking match between these empirical effects and a computational model of large-scale brain states which uncovers fundamental biophysical mechanisms not evident from inspection of the data. Active sleep is defined by reduced energy in a uniform mode of neural activity and increased energy in two more complex anteroposterior modes. Preterm-born infants show a deficit in this sleep-related reorganization of modal energy that carries novel prognostic information.

Preterm Birth Changes Networks of Newborn Cortical Activity.

Preterm birth is the greatest risk factor for lifelong neurocognitive deficits, globally. The effect of prematurity on early cortical network function has, however, remained poorly understood. Here, we developed a novel methodology that allows reliable assessment of functional connectivity in neonatal brain activity at millisecond and multisecond scales in terms of cortical phase and amplitude correlations, respectively. We measured scalp electroencephalography at term-equivalent age in infants exposed to very early prematurity as well as in healthy controls. We found that newborn cortical activity organizes into multiplex networks that differ significantly between vigilance states. As compared with healthy control infants, prematurity was found to cause frequency-specific patterns of dysconnectivity in cortical network, changes that were distinct for networks of phase and amplitude correlations. Neuroanatomically, the most prominent markers of prematurity were found in connections involving the frontal regions. Phase synchrony in frontally connected networks was correlated with newborn neurological performance, suggesting the first measure of cortical functional coupling that correlates with neurological performance in human infant.

Newborn Brain Function Is Affected by Fetal Exposure to Maternal Serotonin Reuptake Inhibitors.

Recent experimental animal studies have shown that fetal exposure to serotonin reuptake inhibitors (SRIs) affects brain development. Modern recording methods and advanced computational analyses of scalp electroencephalography (EEG) have opened a possibility to study if comparable changes are also observed in the human neonatal brain. We recruited mothers using SRI during pregnancy (n = 22) and controls (n = 62). Mood and anxiety of mothers, newborn neurology, and newborn cortical function (EEG) were assessed. The EEG parameters were compared between newborns exposed to drugs versus controls, followed by comparisons of newborn EEG features with maternal psychiatric assessments. Neurological assessment showed subtle abnormalities in the SRI-exposed newborns. The computational EEG analyses disclosed a reduced interhemispheric connectivity, lower cross-frequency integration, as well as reduced frontal activity at low-frequency oscillations. These effects were not related to maternal depression or anxiety. Our results suggest that antenatal serotonergic treatment might change newborn brain function in a manner compatible with the recent experimental studies. The present EEG findings suggest links at the level of neuronal activity between human studies and animal experiments. These links will also enable bidirectional translation in future studies on the neuronal mechanisms and long-term neurodevelopmental effects of early SRI exposure.