Placental contribution to neonatal encephalopathy.

Placental assessment, although currently underused, can inform our understanding of the etiology and timing of Neonatal Encephalopathy (NE). We review our current understanding of the links between placental dysfunction and NE and how this information may inform clinical decisions, now and in the future, emphasizing the four major placental lesions associated with NE. In addition, we discuss maternal and fetal factors that are hypothesized to contribute to specific placental pathologies, especially innate or acquired thrombophilias. We outline the importance of assessing placenta across trimesters and after delivery. As this field continues to evolve, currently available placental histopathological examination methods may need to be combined with advanced prenatal molecular and imaging assessments of placenta and be applied in well-designed studies in large representative populations to better define the links between placental dysfunction and NE.

Nonlinear dynamical analysis of the neonatal EEG time series: the relationship between sleep state and complexity.

OBJECTIVE: The complexity of the EEG time series during stages of neonatal sleep states is investigated. The relationship between these sleep states, birth status (i.e. preterm and full-term), and the complexity of the EEG is assessed. METHODS: Dimensional complexity, an estimate of the correlation dimension (D(2)) of the EEG time series, is used as a novel index for quantifying the complexity of the EEG time series during different neonatal sleep states. The dimensional complexity is estimated by using both the Grassberger-Procaccia algorithm and Theiler's modified algorithm. Also, the hypothesis that the neonatal EEG time series contains nonlinear features is investigated and verified in certain sleep states using surrogate data testing. RESULTS: Dimensional complexity of the neonatal EEG time series during active (REM) sleep tends to be higher than during quiet (NREM) sleep; while dimensional complexity of the neonatal EEG time series during indeterminate sleep is virtually at the midpoint of the dimensional complexity range between the active and quiet sleep states. Consequently, there are statistically significant differences between the neonatal EEG time series during different sleep states as measured by dimensional complexity. Also, the birth status (preterm or full-term) of the neonate has an influence on dimensional complexity of the neonatal EEG time series. Further, the surrogate data testing null hypothesis for dimensional complexity cannot be rejected during active sleep. CONCLUSIONS: The neonatal EEG time series tends to have statistically different complexities corresponding to different sleep states. Given that the neonatal EEG time series during active sleep is more complex than during quiet sleep, one can suggest that there is greater activity among cortical circuit elements during active as compared to quiet sleep. Further, active sleep neuronal dynamics are best modeled by a linear stochastic process, while in quiet sleep a nonlinear deterministic model may be more appropriate. SIGNIFICANCE: There has been considerable controversy associated with measures of complexity, such as dimensional analysis, as applied to neonatal EEG data. This paper confirms that there are statistically significant differences in dimensional complexity associated with different states of sleep and that the origin of this complexity shifts from linear stochastic to nonlinear deterministic with transitions from active to quiet sleep, and is further influenced by maturation. This may provide important insight into the organization and structure of neuronal networks during sleep and with brain maturation in the neonatal period.

Nonlinear dynamical analysis of the neonatal EEG time series: the relationship between neurodevelopment and complexity.

OBJECTIVE: To investigate the relationship between the complexity of sleep EEG time series and neurodevelopment for premature or full-term neonates. METHODS: Nonlinear dynamical analysis of neonatal sleep EEG time series is used to compute the correlation dimension D2 which is an index of the complexity of the dynamics of the developing brain. The dimensional complexity is estimated using Theiler's modification of the Grassberger-Procaccia algorithm for two different values of Theiler's w parameter. The hypothesis that neonatal EEG data during sleep contains nonlinear features is verified by means of surrogate data testing. RESULTS: The dimensional complexity of the neonatal EEG increases with neurodevelopment and brain maturation. There is furthermore a statistically significant difference between the dimensional complexity of the EEG for neonates born prematurely when compared to full-term neonates at the same postmenstrual age (PMA). The neonatal EEG time series data used in this study proved to contain nonlinear features where the 'null hypothesis' of surrogate data testing is rejected with p<<0.0001. CONCLUSIONS: A relationship between neurodevelopment and brain maturation and the complexity of the dynamics of the brain as measured by the dimensional complexity of the sleep EEG time series has been established. In particular, the dimensional complexity tends to increase with neurodevelopment and maturation as indicated by their PMA and birth status (premature or full-term). In particular, the brain dynamics of neonates born prematurely is less complex than the brain dynamics of neonates born full-term even at the same PMA. We attribute this to differences in the neurodevelopment between these two cohorts. We propose that the dimensional complexity can be used as an index for quantifying neurodevelopment. SIGNIFICANCE: The dimensional complexity as measured by the correlation dimension of the sleep EEG time series may potentially be a useful measure for quantifying neurodevelopment in neonates. Future work is directed at the analysis of other EEG channels to understand the relationship between complexity in different regions of the brain and maturation and neurodevelopment, along with the utility of complexity to relate to neurodevelopment at older ages as measured by the Bayley score.

Intraventricular hemorrhage in the full-term neonate.

Intraventricular hemorrhage (IVH) can occur in full-term newborns with a variety of clinical pictures. We studied five full-term infants who suffered IVH in the neonatal period and survived. No apparent cause for hemorrhage could be found in four. All had normal results of neurologic examinations at birth, and four had no major antecedent perinatal or postnatal difficulties. In 19 previously described full-term infants with IVH, no perinatal problems were noted in 45% of those who survived. Although more common in premature infants, IVH can occur in full-term infants and should be suspected when there is a sudden change in the neurologic status. In subsequent examinations, three of our five infants had mild spasticity and two appeared to be normal. The grading system developed for IVH in premature infants, while indicating severity of the hemorrhage, does not predict clinical outcome in full-term infants. A more definitive statement of outcome will require a longer period of observation.

Destructive brain lesions of presumed fetal onset: antepartum causes of cerebral palsy.

Antepartum events have been associated with fetal brain injury and may contribute to later neurological sequelae. However, children with these injuries may be asymptomatic or exhibit few clinical signs during the neonatal period. Six neonates are presented with destructive brain lesions of fetal onset based on radiological and neurophysiological studies at birth. No intrapartum difficulties were noted in any of the cases. Two maternal histories were significant for either placental bleeding or toxemia during the second or third trimesters of pregnancy. Fetal porencephaly from presumed intraventricular hemorrhage was documented by serial abdominal sonography for these two children. No causes could be assigned for the remaining four patients with destructive brain lesions. All six children had normal results on neurological examinations at birth, although four neonates later presented with isolated seizures at 8 to 30 hours of life which resolved after administration of anti-epileptic medication. In all cases initial neonatal electroencephalographic records showed abnormalities consisting of major background asymmetries or seizures. Initial documentation of cerebral lesions was made by fetal sonography (two patients) and computed tomography scan (four patients) during the initial 30 hours of life, timing the lesions to the antepartum period. Cerebral palsy has been documented in all children; one child had resolution of her deficits by 6 months of age. Better surveillance of events during the antepartum period may help identify specific pathophysiological conditions that contribute to cerebral palsy. Neurophysiological and imaging studies should be used during the immediate new-born period for neonates believed to have cerebral lesions based on maternal sonography or isolated seizures.

Effects of prenatal cocaine/crack and other drug exposure on electroencephalographic sleep studies at birth and one year.

OBJECTIVE: Little is known about the neurophysiologic effects of prenatal cocaine/crack use. The aim of this study, designed to overcome methodologic limitations of previous research, was to investigate the effects of prenatal cocaine use on electroencephalographic (EEG) sleep patterns, a marker of central nervous system development. METHODS: In a longitudinal study of prenatal cocaine/crack exposure, women were interviewed at the end of each trimester about cocaine, crack, alcohol, tobacco, marijuana, and other drug use. Two-hour paper- and computer-generated EEG sleep recordings were obtained on a sample of the full-term infants on the second day of life and at 1 year postpartum. Eligible newborns were full-term, had received no general anesthesia, and had a 5-minute Apgar score >5. All infants whose mothers used one or more lines of cocaine during their first trimester or any crack (n = 37) were selected. A comparison group was chosen randomly from the group of women who did not use cocaine or crack during their pregnancy (n = 34). RESULTS: Women who used cocaine/crack during the first trimester were older, less educated, less likely to be working, and used more tobacco, alcohol, marijuana, and other illicit drugs than women who did not use cocaine/crack during the first trimester. There were no differences in infant birth weight, length, head circumference, or gestational age between the two exposure groups. After controlling for the significant covariates, prenatal cocaine exposure was associated with less well developed spectral correlations between homologous brain regions at birth, and with lower spectral EEG power values at 1 year of age. Prenatal alcohol, marijuana, and tobacco use were found to affect state regulation and cortical activities. CONCLUSIONS: These results indicate that the neurotoxic effects of prenatal cocaine/crack use can be detected with quantitative EEG measures.

Electrographic seizures in preterm and full-term neonates: clinical correlates, associated brain lesions, and risk for neurologic sequelae.

Electrographically confirmed seizures in preterm and term neonates were compared with respect to clinical correlates, incidence, associated brain lesions, and risk for neurologic sequelae. Over a 4-year period, 92 neonates from a neonatal intensive care unit population of 4020 admissions at a large obstetric hospital with 40,845 livebirths had electrographically confirmed seizures. Sixty-two neonates were preterm and 30 were full-term for gestational age. Chi-square calculations were used to compare the two groups. While the incidence of seizures for all neonates admitted to a neonatal intensive care unit was 2.3%, outborn neonates were more likely to have seizures than inborn neonates. Preterm neonates of < or = 30 weeks gestational age had a seizure frequency of 3.9%, which was significantly higher than that of older preterm neonates and full-term neonates. Clinical criteria contemporaneous with electrographic seizures were noted in only 28 (45%) of 62 preterm, and 16 (53%) of 30 full-term neonates. Subtle seizures coincident with electrographically confirmed seizures were the most predominant clinical type for both term and preterm neonates (71% and 68%, respectively). The distribution of clonic, myoclonic, and tonic seizures was also similar for both groups. Autonomic signs coincident with electrographically confirmed seizures (ie, blood pressure, heart rate, oxygenation, respiration changes) were more frequently observed in preterm than full-term neonates with subtle seizures; 7 (37%) of 19 compared with 1 (6%) of 16. Electrical seizures without clinical correlates were noted more frequently than electroclinical seizures for both populations.(ABSTRACT TRUNCATED AT 250 WORDS)

Right-sided brain lesions in infants following extracorporeal membrane oxygenation.

In retrospective review of survivors of neonatal extracorporeal membrane oxygenation, eight patients with varying degrees of right hemispheric brain injury were identified. The extent of preextracorporeal membrane oxygenation hypoxia and ischemia was documented: five of eight patients had arterial PO2 values of less than 40 mm Hg, seven of eight required dopamine for blood pressure support, and five of eight required cardiopulmonary resuscitation. Two patients had proven neurologic abnormalities before extracorporeal membrane oxygenation. Postextracorporeal membrane oxygenation CT brain scans showed right hemispheric focal abnormalities in three patients. Seven infants had neuromotor abnormalities which were lateralizing in nature; all were left sided, suggesting right-sided brain injury. EEGs showed an increased incidence of slowing and attenuation over the right hemisphere. These findings indicate that right-sided brain abnormalities exist after extracorporeal membrane oxygenation and that carotid artery ligation for extracorporeal membrane oxygenation is not without risk.

Postnatal adaptation of brain function in full-term neonates as assessed by EEG sleep analyses.

Differences in electroencephalographic (EEG) sleep between preterm and full-term neonatal cohorts at matched postconceptional ages have been previously presented by our study group. These differences may have occurred, however, because of postnatal brain adaptation of the full-term infant after a more recent delivery. EEG sleep analyses, therefore, were performed on only the full-term cohort to determine if EEG sleep measures changed over the first three days after birth, which might account for the differences with the preterm group. Twelve full-term infants studied on the first day of life were compared with 17 full-term infants who were studied on days of life 2 and 3. Using multivariate analysis of variance (MANOVA), comparisons were performed among 13 EEG sleep measures. No EEG sleep differences were seen between full-term children born by Cesarean section versus those born by vaginal presentation. No statistical differences were noted between day 1 compared to days 2 and 3 with respect to 10 measures concerning sleep architecture, phasic, continuity, spectral EEG, and autonomic features. In three EEG sleep measures, changes occurred between days 1 and 2-3, but two of the three measures were in a direction that strengthen our claim that differences exist between preterm and full-term cohorts: more body movements and lower percentages of quiet sleep were noted for full-term infants on days 2-3. EEG sleep differences between preterm and full-term infants at matched postconceptional term ages are more likely to be due to conditions associated with prematurity rather than postnatal brain adaptation in the full-term group who experienced a more recent delivery.

Comparison of EEG sleep measures in healthy full-term and preterm infants at matched conceptional ages.

Continuous electroencephalogram (EEG) sleep studies were obtained on healthy full-term and preterm infants at matched conceptional ages. Studies were recorded under environmentally controlled conditions. Eighteen healthy preterm infants were matched to 18 full-term infants based on conceptional age, sex, race and socioeconomic class. The initial 3 hours of a 12-hour recording were simultaneously recorded on paper and computer. The visually scored data based on the paper recordings for sleep architecture and continuity measures were studied. Differences in each sleep organization for the preterm infants included the following: a longer ultradian sleep cycle (70 minutes vs. 53 minutes, p = 0.02) was noted. More abundant tracé alternant (34% vs. 28%, p = 0.02) and less abundant low-voltage irregular active sleep (13% vs. 17%, p = 0.05) were noted. Although no differences were observed for sleep latency and efficiency, the preterm infants had fewer numbers and shorter durations of arousals, fewer body movements and rapid eye movement (REM) (p < 0.01), particularly during quiet sleep. The extrauterine experience or the earlier birth of the preterm infant may influence specific sleep architecture and continuity measures when compared with the sleep of full-term infants who experienced a complete intrauterine gestation.

Computer classification of state in healthy preterm neonates.

Nineteen electroencephalographic (EEG) sleep measures describing four physiologic aspects of sleep behavior (i.e. sleep continuity, EEG spectra, body and eye movements, and autonomic measures) were derived from visual and computer analyses of 71 24-channel, 3-hour EEG sleep recordings on 52 healthy preterm neonates from 28-36.5 weeks postconceptional age (PCA). Forty-eight subjects were neurodevelopmentally normal up to 2 years of age. Four electrographic states that comprise tracé discontinu of the preterm neonate were defined in terms of increasing seconds of EEG quiescence per minute. A regression analysis was performed after transformations of nonlinear data sets representing the 19 EEG sleep measures, with the four sleep states as outcome variables. Postconceptional age was also included in these analyses as the 20th explanatory variable. Four measures best defined the EEG sleep states, explaining 75% of the variance: decreasing rapid eye movements per minute, decreasing numbers of spontaneous arousals per minute, increasing spectral theta energies, and decreasing facial movements per minute. Other cerebral and noncerebral measures, including total spectral EEG energies, spectral EEG energies in three bandwidths (i.e. delta, alpha, beta), cardiac and respiratory measures, and body movements, did not contribute as significantly to the prediction. Inclusion of PCA into the regression equation with the four EEG measures, selected by the analysis procedure, indicated that its contribution to state prediction was also small; the effect of PCA on state was found to be explained by the four EEG sleep measures.

Sleep architecture and continuity measures of neonates with chronic lung disease.

Electroencephalographic (EEG) sleep studies of 25 preterm neonates with chronic lung disease (CLD) corrected to a fullterm postconceptional age were compared with recordings from two groups of neonates without CLD: a fullterm appropriate for gestational age group (9 patients) and a preterm group studied at a corrected term postconceptional age (15 patients). Electrographic/polygraphic studies were obtained using 21-channel EEG recordings. Scores were tabulated based on minute-by-minute visual analyses of sleep state, number and duration of arousals, body movements and rapid eye movements (REM). A significant reduction in the percentage of active sleep was noted in the CLD group compared to both control groups (31.15% vs. 47.01% and 52.9%, respectively). The mean percentage of indeterminate sleep was significantly increased in the study group as compared to both control groups (31.23% vs. 15.18% and 11.5%). In addition, significant differences were noted between the CLD group and the healthy preterm control group with respect to the number (0.29/minute vs. 0.13/minute) and duration (4.8 seconds vs. 2.94 seconds) of arousals as well as the total number of body movements (1.57/minute vs. 0.74/minute). These data suggest that neurophysiological organization of the immature brain, as reflected in neonatal sleep architecture and continuity measures, is adversely affected in neonates with CLD. EEG sleep architecture and continuity measures may be helpful in predicting the longitudinal outcome of infants with CLD as this group is at risk for adverse neurodevelopmental outcome.

Comparisons of EEG sleep state-specific spectral values between healthy full-term and preterm infants at comparable postconceptional ages.

Differences in state-specific electroencephalographic (EEG) spectral values are described between groups of preterm and full-term neonates at comparable postconceptional term ages. Eighteen healthy preterm neonates of < or = 32 weeks gestation were selected from an inborn population of a neonatal intensive care unit. Twenty-four-channel recordings were obtained at a full-term age and compared with studies of 22 healthy full-term neonates. The initial three hours of each 12-hour study were recorded on paper from which EEG sleep state scores per minute were visually assessed. Six mean spectral values (i.e. total EEG, electromyogram, delta, theta, alpha and beta energies) were calculated from each corresponding minute of digitized data, which was also assigned one of six EEG sleep states. Each neonatal group displayed statistically significant differences among sleep-state segments for all spectral values. The alpha- and beta-range spectral values of the preterm group, compared to the full-term control group, were lower during all sleep state segments. Spectral values for the theta band were lower during both quiet sleep segments only, whereas spectral values for delta were lower during all sleep stages, except tracé-alternant quiet sleep. Significant differences in EEG spectral values were noted among states of sleep for both preterm and full-term infants of similar postconceptional term ages. These data also suggest differences in central nervous system maturation between neonatal populations. These findings strengthen our previously stated contention that there is a functional alteration in brain development of the preterm infant as reflected in sleep organization that results from a prolonged extrauterine experience and/or prematurity.

Computer classification of sleep in preterm and full-term neonates at similar postconceptional term ages.

A classification strategy of neonatal sleep is being developed by comparing visually scored minutes of 21 channels of electroencephalographic (EEG)/polygraphic recordings with the corresponding values for each physiological signal derived from either visual or computer analyses. Continuous 3-hour sleep studies on 54 preterm and full-term neonates at similar postconceptional term ages were acquired under environmentally controlled conditions using a computerized monitoring system. An on-line event marker program recorded behavioral observations. One of three EEG sleep states was assigned to each of 8,995 minutes by traditional visual analysis criteria. EEG spectral values, spectral and nonspectral cardiorespiratory calculations and behaviorally observed movements, arousals and rapid eye movement counts were submitted for discriminant analysis. Based on the total minutes known for each of three states (i.e. active, quiet and awake), linear combinations of all specified digitized parameters were formed into an arithmetic algorithm by use of discriminant analysis, which served as the basis of a state assignment for each minute. Fifty percent of the data were arbitrarily used as the training set to derive the state classification model. The remaining fifty percent of the data were used as the cross-validation "test sample" to determine the accuracy of the classification when compared to the visually analyzed score for each corresponding minute. Thirteen out of 32 physiological measures best predicted state of both preterm and full-term neonatal groups. For both groups, the correct classification for active sleep was 90.3%, quiet sleep was 97.4%, awake was 97% and the overall accuracy was 93.3%. However, the order of significance for specific variables differed between these two neonatal groups. Differences in the order of variables that predict sleep states between preterm and full-term infants may reflect adaptation of brain function of the preterm infant to prematurity and/or prolonged extrauterine experience.

A longitudinal study of prenatal marijuana use. Effects on sleep and arousal at age 3 years.

OBJECTIVE: To test the hypothesis that sleep disruptions would be evident in 3-year-old children with a history of prenatal marijuana exposure. DESIGN: A prospective study using stratified random sampling beginning in the fourth month of pregnancy. Marijuana and other substance use were assessed by interviews at multiple time points. Offspring were followed up through age 3 years with multidomain assessments at fixed time points, including electroencephalographic sleep studies in the newborn period and at age 3 years. SETTING: Primary care, prenatal clinic at a university hospital. SUBJECTS: The sample included 18 children with prenatal marijuana exposure (mean [+/- SD] age, 39.0 +/- 4.4 months) and 20 control children (mean [+/- SD] age, 39.7 +/- 4.4 months). The two groups were similar in relationship to maternal age, race, income, education, or maternal use of alcohol, nicotine, and other substances in the first trimester. MAIN OUTCOME MEASURE: Sleep variables from polysomnographic recordings at age 3 years. RESULTS: Children with prenatal marijuana exposure showed more nocturnal arousals (mean [+/- SD], 8.2 +/- 5.3 vs 3.2 +/- 4.6; P < .003), more awake time after sleep onset (mean [+/- SD], 27.4 +/- 20.0 vs 13.7 +/- 12.4 min; P < .03), and lower sleep efficiency (mean [+/- SD], 91.0 +/- 3.8 vs 94.4 +/- 2.1; P < .03) than did control children. CONCLUSION: Prenatal marijuana exposure was associated with disturbed nocturnal sleep at age 3 years.

Automated detection of tracé alternant during sleep in healthy full-term neonates using discrete wavelet transform.

OBJECTIVE: To develop an automated procedure for scoring neonatal sleep states using signal processing which are based on visual pattern recognition techniques. METHODS: We are developing an automated computer system to study relationships among multiple non-cerebral physiologic measures and brain activity in newborn infants, and are evaluating the usefulness of a number of different time-frequency domain transforms as potential diagnostic tools. RESULTS: Wavelet transforms yield excellent results in the detection of all twenty tracé alternant quiet sleep segments for 6 full-term healthy infants. CONCLUSIONS: We suggest that this method will be useful for the automated detection of neonatal sleep states, and may help delineate when sleep cycle disturbances occur on either an environmental or disease basis. More accurate physiologic descriptions of neonatal state may improve the clinician's ability to assess functional brain organization for a given post-conceptional age as well as document functional brain maturation at progressively older corrected ages.

EEG and the neuropathology in premature neonates with intraventricular hemorrhage.

Eighty-eight EEGs from 32 premature neonates with autopsy-verified periventricular-intraventricular hemorrhage (PVH-IVH) were compared with associated neuropathological findings. PVH-IVH was rarely an isolated lesion at autopsy. Twenty-seven infants (84%) had additional parenchymal brain lesions, such as periventricular leukomalacia (47%), ischemic neuronal necrosis (22%), pontosubicular necrosis (22%), cerebral infarction (13%), and/or cerebellar hemorrhage (13%). A significant correlation was found between the patient's most abnormal EEG and the severity of morphological changes. Infants with more abnormal EEGs had more extensive brain lesions. On the other hand, IVH grade did not correlate with the degree of parenchymal brain lesions, with the exception of IVH with intraparenchymal involvement. Positive rolandic sharp wave transients (PRS) were observed in eight patients (25%). All infants with PRS had white matter lesions. The sensitivity of PRS for white matter lesions, however, was only 38%. EEG has limited value in the diagnosis of PVH-IVH or specific anatomical changes but provides useful electrographic information that correlates with the severity of brain damage in infants with PVH-IVH.

Neonatal electroencephalography and neuropathology.

One-hundred-eight EEGs from 47 newborn infants were compared with the postmortem neuropathological findings. The degree of EEG background abnormality had good correlation with the severity of the brain lesion; the more severe the EEG background abnormality, the more extensive and intensive the morphological change. Widespread encephalomalacia was demonstrated in six infants who manifested isoelectric tracings. In particular, cerebral cortex, corpus striatum, thalamus, midbrain, and pons were affected in all patients with this abnormal EEG pattern. Burst-suppression patterns, which were seen in seven infants, also correlated with multifocal severe brain damage, but there was no common structure that was consistently affected for all patients with this pattern. Positive rolandic sharp-wave transients (PRS) appeared highly specific for white matter lesions. All eight infants with PRS had white matter lesions. However, the sensitivity of PRS for white matter lesions was not high (32%), and the white matter lesions of PRS-positive patients were not necessarily composed of periventricular leukomalacia. The sensitivity of EEG asymmetry was also low (40%) for the focality of morphological change, although the specificity was relatively high (85%). The origin of seizure discharges, on the other hand, had poor correlation with the site of the brain lesion.

Computer analyses of EEG-sleep in the neonate: methodological considerations.

Neonatal EEG interpretation can aid in the estimation of central nervous system maturation, as well as provide diagnostic and prognostic information of the high-risk infant. However, one cannot easily visualize the complex interrelationships coupling EEG and polysomnographic components of the EEG-sleep rhythm. This is particularly relevant for the preterm neonate, in whom a rudimentary sleep cycle has not yet been clearly delineated. Computer analysis can augment the information derived from the visual interpretation of scalp-generated EEG activity. Automated techniques for EEG-sleep analysis have only recently been applied to a neonatal population. Such studies have been limited to full-term rather than preterm infants and rely on conventional methods that assume stationarity of neurophysiologic signals. We describe a computer system that simultaneously compares behavioral and electrographic components of EEG-sleep in a manner that preserves the integrity of the signals over time, while investigating the time- and frequency-dependent relationships among signals. Strategies for on-line and off-line editing, data storage, and off-line signal processing are described. Computational algorithms regarding analyses of EEG power, motility, and cardiorespiratory data are being used to study the ontogeny of EEG-sleep in asymptomatic preterm and full-term neonates. Computer strategies are based on both principles of stationarity and nonstationarity of physiologic signals and are applied depending on the temporal resolution required for specific signal processing needs.

Applying classifications of sleep disorders to children with neurologic conditions.

Information concerning sleep ontogeny and sleep disorders in children is required by many pediatric specialists. Pediatric neurologists, for instance, frequently are called upon to assist in the evaluation of children with undiagnosed symptoms and signs during sleep, as well as to care for children and adolescents with specific neurologic diseases who also experience sleep disturbances. This review discusses pediatric sleep disturbances with specific reference to sleep in children with neurologic conditions.