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.

Electroencephalogram in low-risk term newborns predicts neurodevelopmental metrics at age two years.

OBJECTIVE: To determine whether neurodevelopmental biomarkers at 2 years of age are already present in the newborns' EEG at birth. METHODS: Low-risk term newborns were enrolled and studied utilizing EEG prior to discharge from the birth hospital. A 14-channel EEG montage (scalp-level) and source signals were calculated using the EEG. Their spectral power was calculated for each of the five frequency bands. Cognitive, language and motor skills were assessed using the Bayley Scales of Infant Development-III at age 2 years. The relationship between the spectral power in each frequency band and neurodevelopmental scores were quantified using the Spearman's r. The role of gender, gestational age (GA) and delivery mode, if found significant (P < 0.05), were controlled by analyzing partial correlation. RESULTS: We studied 47 newborns and found a significant association between gender, and delivery mode with EEG power. Scalp- and source-level spectral powers were positively associated with cognitive and language scores. At the source level, significant associations were identified in the parietal and occipital regions. CONCLUSIONS: Electrophysiological biomarkers of neurodevelopment at age 2 years are already present at birth in low-risk term infants. SIGNIFICANCE: Low-risk newborns' EEG utility as a screening tool to optimize neurodevelopmental outcome warrants further evaluation.

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.

Change in EEG Activity is Associated with a Decrease in Tinnitus Awareness after rTMS.

OBJECTIVE: To examine how 1Hz and 10Hz rTMS temporarily influence ratings of tinnitus loudness, annoyance, and awareness. The thalamocortical dysrhythmia (TCD) model of tinnitus was tested by examining changes in spectral power and coherence of resting state EEGs from baseline to each phase of treatment and correlating these data with change in tinnitus. METHODS: Nineteen participants completed a double-blind, placebo (sham rTMS) controlled, within-subjects study with crossover between the two active rTMS treatment conditions. An imposed order effect, sham rTMS first, eliminated drift of active treatment into the placebo condition. The primary outcome measures were analogue ratings of tinnitus loudness, annoyance, and awareness, assessed repeatedly at baseline and during treatment, and 64 channel, resting state EEGs collected at baseline and the end of each treatment phase. Active rTMS consisted of 1800 pulses at 110% of motor threshold over temporal cortex delivered at 1Hz and 10Hz over four days. The research design also examined the effect of rTMS immediately following stimulation, regression to the mean in tinnitus ratings made over multiple days, and differences between treatment responders and non-responders. RESULTS: There was no immediate effect of rTMS on tinnitus during a single rTMS session. Regression to the mean in tinnitus ratings occurred over three days of baseline and four days of treatment (both sham and active rTMS). After accounting for regression to the mean in the statistical model, 1Hz rTMS led to a significant decrease in tinnitus awareness from baseline and 10Hz rTMS trended in the same direction, whereas sham rTMS showed little change from baseline other than regression to the mean. Changes from baseline in spectral power of the resting state EEG provided partial support for predictions based on TCD model of tinnitus for active 1 and 10Hz rTMS but not sham rTMS. However, only an increase in beta coherence correlated significantly with a decrease in tinnitus awareness. Changes in the EEG were robust in treatment responders but absent among non-responders and during sham rTMS. CONCLUSIONS: A positive response to rTMS for tinnitus is associated with an rTMS-induced change in beta coherence of the EEG. Increased beta coherence may be a biomarker of the rTMS effect; a "top-down" modulation of the EEG that promotes habituation to tinnitus. Participants whose tinnitus did not improve after rTMS did not show any changes in the EEG.

Detrended fluctuation analysis using orthogonal polynomials.

An alternative analysis approach, namely, orthogonal detrended fluctuation analysis (ODFA), is proposed to quantify the long-range correlation exponent. This method uses an orthogonal polynomial to attenuate any trends and quantify the (auto-) correlations in the data. The method is tested using numerically simulated data with long-range correlation. A matrix formalism of this approach is also proposed. Furthermore, the extension to high-order polynomial detrending is discussed. The proposed approach quantifies the long-range exponent with an error rate of about 8% for short datasets (3000 samples) and an error rate of about 1% for long datasets (100 000 samples). ODFA can find applications that involve processing long datasets as well as in real-time processing.

Identifying an optimal epoch length for spectral analysis of heart rate of critically-ill infants.

BACKGROUND AND OBJECTIVE: To identify the optimal epoch length for power spectral analysis of cardiac beat-to-beat intervals (BBi) in critically ill newborns. MATERIALS AND METHOD: BBi of 49 term newborns undergoing therapeutic hypothermia for hypoxic-ischemic encephalopathy with well-defined outcomes (good outcome (n = 28): no or mild brain injury and adverse outcome (n = 21): moderate or severe brain injury or death) served as test population. A power spectrum of BBi was calculated with an autoregressive model in three different epoch lengths: 2 min, 5 min, and 10 min. Spectral power was quantified in three different frequency bands: very low-frequency (0.016-0.04 Hz), low-frequency (0.05-0.25 Hz), and high-frequency (0.3-1 Hz). In each frequency band, the absolute power and the normalized power were calculated. Furthermore, standard deviation (SDNN) of BBi was calculated. These metrics were compared between the outcome groups with a receiver operator characteristic (ROC) analysis in 3-h windows. The ROC curve area >0.7 was regarded as a significant separation. RESULTS: The absolute spectral powers in all three epoch lengths in all three frequency bands and SDNN distinguished the two outcome groups consistently for most time points. The spectral metrics calculated with a 2-min epoch length performed as well as the five- and 10-min epoch lengths (paired t-test P < 0.05). CONCLUSION: Spectral analysis of BBi in 2-min epoch shows a similar discriminatory power as longer epoch lengths. A shorter epoch also has clinical advantages for translation into a continuous real-time bedside monitor of heart rate variability in the intensive care unit.

Effect of EKG Sampling Rate on Heart Rate Variability Analysis.

We studied the effect of EKG sampling rate on heart rate variability (HRV) analysis. We acquired EKG from four term hypoxic-ischemic encephalopathic infants undergoing therapeutic hypothermia. The EKG signal was acquired continuously for 4 days from the cardiorespiratory monitor through the analog port. The following HRV metrics were calculated: normalized low-frequency (nLF), normalized high-frequency (nHF), low-frequency (LF), high-frequency (HF), short-term detrended fluctuation analysis (DFA) exponent (αs), long-term DFA exponent (αL), root mean square (RMS) short (RMSS), and RMS long (RMSL). In addition, heart rate was used. These metrics were calculated for EKG acquired at 1 KHz (served as reference, EKGref) as well as from EKGs downsampled at 500 Hz (EKG500), 250 Hz (EKG250), and 125 Hz (EKG125). The bedside monitors were simultaneously sending the EKG to a data warehouse, storing the EKG (EKGDWH) at 250 Hz. All HRV metrics were also calculated for the EKGDWH. The comparison between HRV metrics calculated from EKGref and downsampled EKG (EKG500, EKG250, EKG125) was made with intraclass correlation coefficient (r). The comparisons of HRV metrics between EKG250 and EKGDWH were also made with ICC. Our results show that HRV calculated with EKGref and from downsampled EKG were highly correlated (r>0.8 for all comparisons, P<; 0.001). HRV metrics from EKG250 and EKGDWH were also significantly correlated (r=0.7, P<; 0.001) for all metrics except for HF (r=0.276). These data show that HF power is compromised in the EKGDWH signal and caution must be exercised in interpreting the HF power calculated from this EKG.

Ensuring signal quality of cerebral near infrared spectroscopy during continuous longterm monitoring.

BACKGROUND: Near infrared spectroscopy (NIRS) derived hemoglobin difference (HbD: oxygenated [HbO2] - reduced hemoglobin [Hb]) and total hemoglobin (HbT: HbO2+Hb) have been used as surrogate measures of cerebral blood flow and volume, respectively. Statistically, a lack of HbD-blood pressure (BP) or negative HbT-BP association is regarded as a state of intact cerebral pressure autoregulation (CPA). In contrast, a co-variation of HbD/HbT and systemic blood pressure (BP) in the same direction is thought of as a failure of CPA. If the quality of one (NIRS/BP) or both signals is compromised, the reliability of the results may be adversely affected. In this work, we develop an analytic approach to assess the quality of the NIRS signals. NEW METHOD: Given that cardiac pulses cause hemodynamic changes that are transmitted through the peripheral vasculature, cerebral NIRS signals should exhibit cyclical changes at the pulse frequency. Therefore, we propose that an association between HbD/HbT and electrocardiogram (EKG) signals would be an indicator of NIRS quality. We demonstrate the application of this approach with data collected from six newborns undergoing therapeutic hypothermia for neonatal encephalopathy. RESULTS: We observed an intermittent lack of association between NIRS signals and EKG data over the course of several hours of continuous records, indicating a loss in the strength in NIRS signals. COMPARISON WITH EXISTING METHOD: Existing CPA characterization suffers from Type-II error which the current preprocessing approach can mitigate. CONCLUSIONS: The proposed approach will allow for real-time assessment of NIRS signal quality that is essential for accurate CPA monitoring.

Changes in Autonomic Tone in Premature Infants Developing Necrotizing Enterocolitis.

BACKGROUND: Necrotizing enterocolitis (NEC) is a complication of prematurity with a high mortality rate. Currently, there are no reliable biomarkers capable of identifying infants at risk for developing NEC. We sought to determine the autonomic nervous system antecedents of NEC in premature infants, using heart rate variability (HRV). MATERIALS AND METHODS: HRV was quantified by retrieving archived electrocardiogram (EKG) data from 30 premature infants from 4 days prior, through 4 days after, the clinical NEC diagnosis. HRV metrics were compared with those on the diagnosis day using the receiver operating characteristic (ROC) analysis. RESULTS: HRV metrics showed a depression of autonomic tone that preceded the clinical NEC diagnosis by 2 days, and which recovered to baseline by 2 days after diagnosis (area under the curve [AUC] < 0.7). The pattern of HRV change was significantly associated with the clinical severity of NEC (stage II vs. stage III). CONCLUSION: Our studies suggest that readily accessible metrics of autonomic depression might expedite the diagnosis of NEC and its severity in a clinically meaningful manner. Clearly, these studies need to be extended prospectively to determine the diagnostic utility of this approach.

Identification of QRS complex in non-stationary electrocardiogram of sick infants.

BACKGROUND: Due to the high-frequency of routine interventions in an intensive care setting, electrocardiogram (ECG) recordings from sick infants are highly non-stationary, with recurrent changes in the baseline, alterations in the morphology of the waveform, and attenuations of the signal strength. Current methods lack reliability in identifying QRS complexes (a marker of individual cardiac cycles) in the non-stationary ECG. In the current study we address this problem by proposing a novel approach to QRS complex identification. METHOD: Our approach employs lowpass filtering, half-wave rectification, and the use of instantaneous Hilbert phase to identify QRS complexes in the ECG. We demonstrate the application of this method using ECG recordings from eight preterm infants undergoing intensive care, as well as from 18 normal adult volunteers available via a public database. We compared our approach to the commonly used approaches including Pan and Tompkins (PT), gqrs, wavedet, and wqrs for identifying QRS complexes and then compared each with manually identified QRS complexes. RESULTS: For preterm infants, a comparison between the QRS complexes identified by our approach and those identified through manual annotations yielded sensitivity and positive predictive values of 99% and 99.91%, respectively. The comparison metrics for each method are as follows: PT (sensitivity: 84.49%, positive predictive value: 99.88%), gqrs (85.25%, 99.49%), wavedet (95.24%, 99.86%), and wqrs (96.99%, 96.55%). Thus, the sensitivity values of the four methods previously described, are lower than the sensitivity of the method we propose; however, the positive predictive values of these other approaches is comparable to those of our method, with the exception of the wqrs approach, which yielded a slightly lower value. For adult ECG, our approach yielded a sensitivity of 99.78%, whereas PT yielded 99.79%. The positive predictive value was 99.42% for both our approach as well as for PT. CONCLUSIONS: We propose a novel method for identifying QRS complexes that outperforms common currently available tools for non-stationary ECG data in infants. For stationary ECG our proposed approach and the PT approach perform equally well. The ECG acquired in a clinical environment may be prone to issues related to non-stationarity, especially in critically ill patients. The approach proposed in this report offers superior reliability in these scenarios.

Neural activity during attentional conflict predicts reduction in tinnitus perception following rTMS.

BACKGROUND: Subjective idiopathic tinnitus is an intrusive, distracting, and potentially disabling disorder characterized by phantom perception of sounds. Although tinnitus has no approved pharmacologic treatment, recent evidence supports the use of repetitive transcranial magnetic stimulation (rTMS) to alleviate tinnitus symptoms. OBJECTIVE/HYPOTHESIS: Repetitive TMS delivered over the middle superior temporal gyrus (STG) may alter ratings of tinnitus awareness and annoyance more than loudness due to change in attentional processing. STG has reciprocal connections to regions of the prefrontal cortex that mediate attention. To probe the hypothesized influence of STG stimulation on attention, a subset of patients with tinnitus enrolled in an rTMS clinical trial [n = 12, 9 male, mean (sd) age = 49 (15) years] underwent an attentional conflict task before and after rTMS treatment in a repeated-measures functional magnetic resonance imaging (fMRI) study. METHODS: The Multi-Source Interference Task (MSIT), a Stroop-based visual attentional conflict fMRI task, was used to map participants' neural processing of attentional conflict prior to rTMS intervention (Baseline) and after three rTMS intervention arms: Sham, 1 Hz, and 10 Hz (four sessions per arm, 1800 pulses per session, delivered @110% of the motor threshold over the posterior superior temporal gyrus). RESULTS: All measures of tinnitus severity (awareness, loudness, and annoyance) improved with 1 Hz rTMS intervention; however, the greatest and most robust changes were observed for ratings of tinnitus awareness (mean 16% reduction in severity from Baseline, p < 0.01). The MSIT elicited a similar pattern of neural activation among tinnitus participants at Baseline compared to an independent sample of 43 healthy comparison adults (r = 0.801, p = 0.001). Linear regression with bootstrap resampling showed that greater recruitment of bilateral prefrontal and bilateral parietal regions by MSIT at Baseline corresponded with poorer treatment response. Individual regions' activities explained 37-67% variance in participant treatment response, with left dorsolateral prefrontal cortex's MSIT activity at Baseline explaining the greatest reduction in tinnitus awareness following 1 Hz stimulation. Although left dorsolateral prefrontal cortex activity at Baseline also predicted reduction in tinnitus loudness and annoyance (∼50% variance explained), these symptoms were more strongly predicted by right middle occipital cortex (∼70% variance explained) - suggesting that the neural predictors of symptom-specific treatment outcomes may be dissociable. CONCLUSION: These candidate neural reactivity markers of treatment response have potential clinical value in identifying tinnitus sufferers who would or would not therapeutically benefit from rTMS intervention.

The Impact of Surgical Patent Ductus Arteriosus Closure on Autonomic Function in Premature Infants.

Background Patent ductus arteriosus (PDA) is a common complication of prematurity and a risk factor for poor outcome. Infants undergoing surgical PDA ligation are at highest risk for neurodevelopmental injury. Autonomic dysfunction has been described in premature infants with PDA. Aim To interrogate the autonomic nervous system by analysis of advanced heart rate variability (HRV) metrics before and after surgical closure of the PDA. Study Design Prospective, observational study. Subjects Twenty-seven infants born before 28 weeks' gestation were included in this study. Methods Continuous electrocardiogram data were sampled at a rate of 125 Hz for a total of 6 hours before and 6 hours after 30 hours of surgical closure. HRV was determined by detrended fluctuation analysis to calculate the short and long root mean square (RMSL and RMSS) and α components at two time scales (long and short). Results Gestational age (GA) was positively associated with RMSL, RMSS, and αS and was negatively associated with αL. There was no difference between RMSs, RMSL, αS, or αL before and after surgery; however, median heart rate was lower after surgery (p < 0.01). Conclusion Advancing GA is highly associated with increasing HRV; however, surgical ligation does not affect HRV in the postoperative period.

Inflammatory cytokine response and reduced heart rate variability in newborns with hypoxic-ischemic encephalopathy.

OBJECTIVE: To determine whether systemic inflammation-modulating cytokine expression is related to heart rate variability (HRV) in newborns with hypoxic-ischemic encephalopathy (HIE). STUDY DESIGN: The data from 30 newborns with HIE were analyzed. Cytokine levels (IL-2, IL-4, IL-6, IL-8, IL-10, IL-13, IL-1ß, TNF-α, IFN-λ) were measured either at 24 h of cooling (n=5), 72 h of cooling (n=4) or at both timepoints (n=21). The following HRV metrics were quantified in the time domain: alpha_S, alpha_L, root mean square (RMS) at short time scales (RMS_S), RMS at long time scales (RMS_L), while low-frequency power (LF) and high-frequency power (HF) were quantified in the frequency domain. The relationships between HRV metrics and cytokines were evaluated using mixed-models. RESULT: IL-6, IL-8, IL-10, and IL-13 levels were inversely related to selected HRV metrics. CONCLUSION: Inflammation-modulating cytokines may be important mediators in the autonomic dysfunction observed in newborns with HIE.

Cerebral modulation of the autonomic nervous system in term infants.

OBJECTIVE: Central topography of autonomic nervous system (ANS) function has yet to be fully deciphered. In adults it has been shown to lateralize sympathetic and parasympathetic influence predominantly to the right and left cerebral hemispheres, respectively. We examined functional topography of central ANS in newborn subjects utilizing spectral analysis of heart rate variability (HRV), an established measure of ANS function. STUDY DESIGN: We studied newborns with hypoxic-ischemic encephalopathy participating in a prospective study undergoing a therapeutic hypothermia protocol.We included subjects with continuous heart rate data over the first 3 h of normothermia (post rewarming) and brain magnetic resonance imaging, which was reviewed and scored according to a 4 region scheme. HRV was evaluated by spectral analysis in the low-frequency (0.05 to 0.25 Hz) and high-frequency (0.3 to 1 Hz) ranges. The relationship between injured brain regions and HRV was studied using multiple regressions. RESULTS: Forty eight newborns were included. When examined in isolation, right hemisphere injury had a significant negative effect on HRV (-0.088; 95% CI: -0.225,-0.008). The combination of posterior fossa region injury with right hemispheric injury or left hemispheric injury demonstrated significant positive (0.299; 95% CI: 0.065, 0.518) and negative (-0.475; 95% CI: -0.852, -0.128) influences on HRV, respectively. The association between brain injury location and HRV in the high-frequency range did not reach significance. CONCLUSION: Our data support the notion that lateralized cerebral modulation of the ANS, specifically of its sympathetic component, is present in the term newborn, and suggest complex modulation of these tracts by components of the posterior fossa.

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

BACKGROUND: Electroencephalogram (EEG) signals are often contaminated by the electrocardiogram (ECG) interference, which affects quantitative characterization of EEG. NEW METHOD: We propose null-coherence, a frequency-based approach, to attenuate the ECG interference in EEG using simultaneously recorded ECG as a reference signal. After validating the proposed approach using numerically simulated data, we apply this approach to EEG recorded from six newborns receiving therapeutic hypothermia for neonatal encephalopathy. We compare our approach with an independent component analysis (ICA), a previously proposed approach to attenuate ECG artifacts in the EEG signal. The power spectrum and the cortico-cortical connectivity of the ECG attenuated EEG was compared against the power spectrum and the cortico-cortical connectivity of the raw EEG. RESULTS: The null-coherence approach attenuated the ECG contamination without leaving any residual of the ECG in the EEG. COMPARISON WITH EXISTING METHOD: We show that the null-coherence approach performs better than ICA in attenuating the ECG contamination without enhancing cortico-cortical connectivity. CONCLUSION: Our analysis suggests that using ICA to remove ECG contamination from the EEG suffers from redistribution problems, whereas the null-coherence approach does not. We show that both the null-coherence and ICA approaches attenuate the ECG contamination. However, the EEG obtained after ICA cleaning displayed higher cortico-cortical connectivity compared with that obtained using the null-coherence approach. This suggests that null-coherence is superior to ICA in attenuating the ECG interference in EEG for cortico-cortical connectivity analysis.

A computer-aided approach to detect the fetal behavioral states using multi-sensor Magnetocardiographic recordings.

We propose a novel computational approach to automatically identify the fetal heart rate patterns (fHRPs), which are reflective of sleep/awake states. By combining these patterns with presence or absence of movements, a fetal behavioral state (fBS) was determined. The expert scores were used as the gold standard and objective thresholds for the detection procedure were obtained using Receiver Operating Characteristics (ROC) analysis. To assess the performance, intraclass correlation was computed between the proposed approach and the mutually agreed expert scores. The detected fHRPs were then associated to their corresponding fBS based on the fetal movement obtained from fetal magnetocardiogaphic (fMCG) signals. This approach may aid clinicians in objectively assessing the fBS and monitoring fetal wellbeing.

A novel technique for quantitative bedside monitoring of neurovascular coupling.

BACKGROUND: There is no current method for continuous quantification of neurovascular coupling (NVC) in spontaneous brain activity. To fill this void, we propose a novel method to quantify NVC using electroencephalogram (EEG) and near-infrared spectroscopy (NIRS) data. NEW METHOD: Since EEG and NIRS measure physiologic changes occurring at different time scales, we bring them into a common dynamical time frame (DTF). To achieve this, we partition both signals into one-second epochs and calculate the standard deviation of the EEG and the average value of the NIRS for each epoch. We then quantify the NVC by calculating spectral coherence between the two signals in the DTF. The resulting NVC will have a low resolution with all of its content localized below 1Hz. RESULTS: After validating this framework on simulated data, we applied this approach to EEG and NIRS signals collected from four term infants undergoing therapeutic hypothermia for neonatal encephalopathy. Two of these infants showed no evidence of structural brain injury, and the other two died during the course of the therapy. The intact survivors showed emergence of NVC during hypothermia and/or after rewarming. In contrast, the two critically ill infants, who subsequently died, lacked this feature. COMPARISON WITH EXISTING METHODS: Existing methods quantify NVC by averaging neurovascular signals based on certain events (for example seizure) in the EEG activity, whereas our approach quantifies coupling between spontaneous background EEG and NIRS. CONCLUSION: Real-time continuous monitoring of NVC may be a promising physiologic signal for cerebral monitoring in future.