Effect of electrocardiogram interference on cortico-cortical connectivity analysis and a possible solution

Association of brain functional connectivity with neurodevelopmental outcomes in healthy full-term newborns

OBJECTIVE

To study the association between neurodevelopmental outcomes and functional brain connectivity (FBC) in healthy term infants.

METHODS

This is a retrospective study of prospectively collected High-density electroencephalography (HD-EEG) from newborns within 72 hours from birth. Developmental assessments were performed at two years of age using the Bayley Scales of Infant Development-III (BSID-III) measuring cognitive, language, motor, and socio-emotional scores. The FBC was calculated using phase synchronization analysis of source signals in delta, theta, alpha, beta, and gamma frequency bands and its association with neurodevelopmental score was assessed with stepwise regression.

RESULTS

47/163 had both HD-EEG and BSID-III scores. The FBC of frontal region was associated with cognitive score in the theta band (corrected p, regression coefficients range: p < 0.01, 1.66-1.735). Language scores were significantly associated with connectivity in all frequency bands, predominantly in the left hemisphere (p < 0.01, -2.74-2.40). The FBC of frontal and occipital brain regions of both hemispheres was related to motor score and socio-emotional development in theta, alpha, and gamma frequency bands (p < 0.01, -2.16-2.97).

CONCLUSIONS

Functional connectivity of higher-order processing is already present at term age.

SIGNIFICANCE

The FBC might be used to guide interventions for optimizing subsequent neurodevelopment even in low-risk newborns.

Functional brain network properties of healthy full-term newborns quantified by scalp and source-reconstructed EEG

OBJECTIVE

Identifying the functional brain network properties of term low-risk newborns using high-density EEG (HD-EEG) and comparing these properties with those of established functional magnetic resonance image (fMRI) - based networks.

METHODS

HD-EEG was collected from 113 low-risk term newborns before delivery hospital discharge and within 72 hours of birth. Functional brain networks were reconstructed using coherence at the scalp and source levels in delta, theta, alpha, beta, and gamma frequency bands. These networks were characterized for the global and local network architecture.

RESULTS

Source-level networks in all the frequency bands identified the presence of the efficient small world (small-world propensity (SWP) > 0.6) architecture with four distinct modules linked by hub regions and rich-club (coefficient > 1) topology. The modular regions included primary, association, limbic, paralimbic, and subcortical regions, which have been demonstrated in fMRI studies. In contrast, scalp-level networks did not display consistent small world architecture (SWP < 0.6), and also identified only 2-3 modules in each frequency band.The modular regions of the scalp-network primarily included frontal and occipital regions.

CONCLUSIONS

Our findings show that EEG sources in low-risk newborns corroborate fMRI-based connectivity results.

SIGNIFICANCE

EEG source analysis characterizes functional connectivity at the bedside of low-risk newborn infants soon after birth.

Frequency-Based Maternal Electrocardiogram Attenuation for Fetal Electrocardiogram Analysis

Fetal electrocardiogram (ECG) waveform analysis along with cardiac time intervals (CTIs) measurements are critical for the management of high-risk pregnancies. Currently, there is no system that can consistently and accurately measure fetal ECG. In this work, we present a new automatic approach to attenuate the maternal ECG in the frequency domain and enhance it with measurable CTIs. First, the coherent components between the maternal ECG and abdominal ECG were identified and subtracted from the latter in the frequency domain. The residual was then converted into the time domain using the inverse Fourier transform to yield the fetal ECG. This process was improved by averaging multiple beats. Two fetal cardiologists, blinded to the method, assessed the quality of fetal ECG based on a grading system and measured the CTIs. We evaluated the fetal ECG quality of our method and time-based methods using one synthetic dataset, one human dataset available in the public domain, and 37 clinical datasets. Among the 37 datasets analyzed, the mean average (± standard deviation) grade was 3.49 ± 1.22 for our method vs. 2.64 ± 1.26 for adaptive interference cancellation (p-value < 0.001), thus showing the frequency-based fetal ECG extraction was the superior method, as assessed from our clinicians' perspectives. This method has the potential for use in clinical settings.

Expert consensus on minimum technical standards for neonatal electroencephalography operation and report writing

Electroencephalography (EEG) monitoring is an important examination method in the management of critically ill neonates, which can be used to evaluate brain function and developmental status, severity of encephalopathy, and seizures and predict the long-term neurodevelopmental outcome of high-risk neonates with brain injury. EEG monitoring for neonates is different from that for adults and children, and its operation and interpretation are easily affected by the number of recording electrodes, electrode montage, and monitoring quality. Therefore, standard operation must be followed to ensure the quality of signal acquisition and correct interpretation, thereby ensuring proper management of critically ill neonates. The Subspecialty Group of Neonatology, Society of Pediatrics, Chinese Medical Association established an expert group composed of professionals in neonatology and brain electrophysiology to perform a literature review, summarize the minimum technical standards for neonatal EEG monitoring, and develop the expert consensus on minimum technical standards for neonatal EEG operation and report writing. This consensus will provide guidance for neonatal EEG operation, including technical parameters of EEG monitoring device, operation procedures of EEG monitoring, and specifications for report writing.

Global and intertuberal epileptic networks in tuberous sclerosis based on stereoelectroencephalographic (sEEG) findings: a quantitative EEG analysis in pediatric subjects and surgical implications

OBJECTIVE

Recent evidence favors a network concept in tuberous sclerosis (TSC) with seizure generation and propagation related to changes in global and regional connectivity between multiple, anatomically distant tubers. Direct exploration of network dynamics in TSC has been made possible through intracranial sampling with stereoelectroencephalography (sEEG). The objective of this study is to define epileptic networks in TSC using quantitative analysis of sEEG recordings. We also discuss the impact of the definition of these epileptic networks on surgical decision-making.

METHODS

Intracranial sEEG recordings were obtained from four pediatric patients who presented with medically refractory epilepsy secondary to TSC and subjected to quantitative signal analysis methods. Cortical connectivity was quantified by calculating pairwise coherence between all contacts and constructing an association matrix. The global coherence, defined as the ratio of the largest eigenvalue to the sum of all the eigenvalues, was calculated for each frequency band (delta, theta, alpha, beta, gamma). Spatial distribution of the connectivity was identified by plotting the leading principal component (product of the largest eigenvalue and its corresponding eigenvector).

RESULTS

Four pediatric subjects with TSC underwent invasive intracranial monitoring with sEEG, comprising 31 depth electrodes and 250 contacts, for localization of the epileptogenic focus and guidance of subsequent surgical intervention. Quantitative connectivity analysis revealed a change in global coherence during the ictal period in the beta/low gamma (14-30 Hz) and high gamma (31-80 Hz) bands. Our results corroborate findings from existing literature, which implicate higher frequencies as a driver of synchrony and desynchrony.

CONCLUSIONS

Coordinated high-frequency activity in the beta/low gamma and high gamma bands among spatially distant sEEG define the ictal period in TSC. This time-dependent change in global coherence demonstrates evidence for intra-tuberal and inter-tuberal connectivity in TSC. This observation has surgical implications. It suggests that targeting multiple tubers has a higher chance of seizure control as there is a higher chance of disrupting the epileptic network. The use of laser interstitial thermal therapy (LITT) allowed us to target multiple disparately located tubers in a minimally invasive manner with good seizure control outcomes.

Automated Detection and Removal of Cardiac and Pulse Interferences from Neonatal EEG Signals

Electrical cardiac and pulsatile interference is very difficult to remove from electroencephalographic (EEG) signals, especially if recorded in neonates, for which a small number of EEG channels is used. Several methods were proposed, including Blind Source Separation (BSS) methods that required the use of artificial cardiac-related signals to improve the separation of artefactual components. To optimize the separation of cardiac-related artefactual components, we propose a method based on Independent Component Analysis (ICA) that exploits specific features of the real electrocardiographic (ECG) signals that were simultaneously recorded with the neonatal EEG. A total of forty EEG segments from 19-channel neonatal EEG recordings with and without seizures were used to test and validate the performance of our method. We observed a significant reduction in the number of independent components (ICs) containing cardiac-related interferences, with a consequent improvement in the automated classification of the separated ICs. The comparison with the expert labeling of the ICs separately containing electrical cardiac and pulsatile interference led to an accuracy = 0.99, a false omission rate = 0.01 and a sensitivity = 0.93, outperforming existing methods. Furthermore, we verified that true brain activity was preserved in neonatal EEG signals reconstructed after the removal of artefactual ICs, demonstrating the effectiveness of our method and its safe applicability in a clinical context.

EEG Spectral Power: A Proposed Physiological Biomarker to Classify the Hypoxic-Ischemic Encephalopathy Severity in Real Time

BACKGROUND

Mild hypoxic-ischemic encephalopathy (HIE) constitutes a large unstudied population with considerable debate on how to define and treat due to the dynamic evolution of the clinical signs of encephalopathy. We propose to address this gap with quantitative physiological biomarkers to aid in stratification of the disease severity. The objectives of this prospective cohort study were to measure the electroencephalographic (EEG) power as an objective biomarker of the evolution of the clinical encephalopathy in newborns with mild to severe HIE.

METHODS

EEG was collected in infants with HIE using four bipolar electrodes analyzed for the first three hours of the recording. Delta power (DP, 0.5 to 4 Hz) and total power (TP, 0.5 to 20 Hz) were compared between groups with different HIE severity using a univariate ordinal logistic regression model and receiver operating characteristic curves.

RESULTS

A total of 44 term-born infants with mild to severe HIE were identified within six hours of birth. The DP and TP values were significantly higher for the mild group than for the moderate group for all bipolar electrodes. A one-unit increase in DP was associated with significantly lower odds of encephalopathy. DP best distinguished mild from higher encephalopathy grades by area under the curve.

CONCLUSIONS

We conclude that DP and TP are sensitive real-time biomarkers for monitoring the dynamic evolution of the encephalopathy severity in the first day of life. The quantitative EEG power may lead to timely recognition of the worsening of the encephalopathy and guide future therapeutic interventions targeting mild HIE.

Cerebral cortical autonomic connectivity in low-risk term newborns

PURPOSE

The mature central autonomic network includes connectivity between autonomic nervous system brainstem centers and the cerebral cortex. The study objective was to evaluate the regional connectivity between the cerebral cortex and brainstem autonomic centers in term newborns by measuring coherence between high-density electroencephalography and heart rate variability as measured by electrocardiography.

METHODS

Low-risk term newborns with birth gestational age of 39-40 weeks were prospectively enrolled and studied using time-synced electroencephalography and electrocardiography for up to 60 min before discharge from the birth hospital. The ccortical autonomicc nervous system association was analyzed using coherence between electroencephalography-delta power and heart rate variability. Heart rate variability measured the parasympathetic tone (root mean square of successive differences of heart rate) and sympathetic tone (standard deviation of heart rate).

RESULTS

One hundred and twenty-nine low-risk term infants were included. High coherence delta-root mean square of successive differences was found in central, bitemporal, and occipital brain regions, with less robust coherence delta-standard deviation in the central region and bitemporal areas.

CONCLUSIONS

Our findings describe a topography of ccortical autonomicc connectivity present at term in low-risk newborns, which was more robust to parasympathetic than sympathetic brainstem centers and was independent of newborn state.

Prognostic Value of Continuous Electroencephalogram Delta Power in Neonates With Hypoxic-Ischemic Encephalopathy

The objective was to examine the discriminatory ability of electroencephalogram (EEG) delta power in neonates with hypoxic-ischemic encephalopathy (HIE) with well-defined outcomes. Prolonged continuous EEG recordings from term neonates with HIE during therapeutic hypothermia enrolled in a prospective observational study were examined. Adverse outcome was defined as death or severe brain injury by magnetic resonance imaging (MRI); favorable outcome was defined as normal or mild injury by MRI. Neonates were stratified by Sarnat grade of encephalopathy at admission. EEG was partitioned into 10-minute nonoverlapping artifact- and seizure-free epochs. Delta power was calculated and compared between the groups using receiver operating characteristic (ROC) analyses and Wilcoxon rank-sum tests. An area under the ROC curve >0.7 with P <.05 was considered a significant separation between groups. The favorable outcome group (n = 67) had higher delta power than the adverse outcome group (n = 28) across the majority of time periods from 9 to 90 hours of life. Delta power discriminated outcome groups for neonates with moderate encephalopathy (63 favorable and 14 adverse outcome) earlier in cooling (9-42 hours of life) than neonates with severe encephalopathy (21-42 hours of life). Outcome groups were differentiated after 81 hours of life in neonates with moderate and severe encephalopathy. Delta power can distinguish cooled HIE neonates with adverse outcome independently of the encephalopathy grade at presentation. Delta power may be a real-time continuous biomarker of evolving encephalopathy and brain injury/death in neonates with HIE.

The effect of labor and delivery mode on electrocortical and brainstem autonomic function during neonatal transition

Delivery of the newborn occurs either vaginally or via caesarean section. It is not known whether the mode of delivery and exposure to labor affects early autonomic nervous system (ANS) function, as measured by heart rate variability (HRV), or cortical electroencephalogram (EEG) activity. The objective of the study was to determine if autonomic function in newborns differs by mode of delivery. Simultaneous recording of EEG and electrocardiogram were collected in low-risk term newborns at <72 hours of age to measure HRV, the asymmetry index, and EEG power. Newborns were compared by delivery type: vaginal delivery (VD), cesarean section (CS) after labor (L-CS), or elective CS (E-CS). Quantile Regression controlled for gestational age, postnatal age, and percent active states. One hundred and eighteen newborns were studied at 25.2 (11.4) hours of age. Sixty-two (52.5%) were born by VD, 22 by L-CS (18.6%), and 34 by E-CS (28.8%). HRV metrics didn't differ by delivery mode. Asymmetry index was higher in L-CS compared to VD and E-CS (P = 0.03). On EEG, L-CS newborns showed lower relative gamma power compared to VD and E-CS (P = 0.005). The study found that overall ANS tone is not altered by mode of delivery in low-risk term newborns.