Neurobehavioral deficits and a progressive ictogenesis in the tetrodotoxin model of epileptic spasms.

OBJECTIVE: Our goal was to determine whether animals with a history of epileptic spasms have learning and memory deficits. We also used continuous (24/7) long-term electroencephalographic (EEG) recordings to evaluate the evolution of epileptiform activity in the same animals over time. METHODS: Object recognition memory and object location memory tests were undertaken, as well as a matching to place water maze test that evaluated working memory. A retrospective analysis was undertaken of long-term video/EEG recordings from rats with epileptic spasms. The frequency and duration of the ictal events of spasms were quantified. RESULTS: Rats with a history of epileptic spasms showed impairment on the three behavioral tests, and their scores on the object recognition memory and matching to place water maze tests indicated neocortical involvement in the observed impaired cognition. Analysis of EEG recordings unexpectedly showed that the ictal events of spasms and their accompanying behaviors progressively increased in duration over a 2-week period soon after onset, after which spasm duration plateaued. At the same time, spasm frequency remained unchanged. Soon after spasm onset, ictal events were variable in wave form but became more stereotyped as the syndrome evolved. SIGNIFICANCE: Our EEG findings are the first to demonstrate progressive ictogenesis for epileptic spasms. Furthermore, in demonstrating cognitive deficits in the tetrodotoxin model, we have met a criterion for an animal model of West syndrome. Animal models will allow in-depth studies of spasm progression's potential role in cognitive regression and may elucidate why early treatment is considered essential for improved neurodevelopmental outcomes in children.

A Role for Insulin-like Growth Factor 1 in the Generation of Epileptic Spasms in a murine model.

OBJECTIVE: Infantile spasms are associated with a wide variety of clinical conditions, including perinatal brain injuries. We have created a model in which prolonged infusion of tetrodotoxin (TTX) into the neocortex, beginning in infancy, produces a localized lesion and reproduces the behavioral spasms, electroencephalogram (EEG) abnormalities, and drug responsiveness seen clinically. Here, we undertook experiments to explore the possibility that the growth factor IGF-1 plays a role in generating epileptic spasms. METHODS: We combined long-term video EEG recordings with quantitative immunohistochemical and biochemical analyses to unravel IGF-1's role in spasm generation. Immunohistochemistry was undertaken in surgically resected tissue from infantile spasms patients. We used viral injections in neonatal conditional IGF-1R knock-out mice to show that an IGF-1-derived tripeptide (1-3)IGF-1, acts through the IGF-1 receptor to abolish spasms. RESULTS: Immunohistochemical methods revealed widespread loss of IGF-1 from cortical neurons, but an increase in IGF-1 in the reactive astrocytes in the TTX-induced lesion. Very similar changes were observed in the neocortex from patients with spasms. In animals, we observed reduced signaling through the IGF-1 growth pathways in areas remote from the lesion. To show the reduction in IGF-1 expression plays a role in spasm generation, epileptic rats were treated with (1-3)IGF-1. We provide 3 lines of evidence that (1-3)IGF-1 activates the IGF-1 signaling pathway by acting through the receptor for IGF-1. Treatment with (1-3)IGF-1 abolished spasms and hypsarrhythmia-like activity in the majority of animals. INTERPRETATION: Results implicate IGF-1 in the pathogenesis of infantile spasms and IGF-1 analogues as potential novel therapies for this neurodevelopmental disorder. ANN NEUROL 2022;92:45-60.

Acthar® Gel (repository corticotropin injection) dose-response relationships in an animal model of epileptic spasms.

Studies were undertaken to evaluate the effectiveness of Acthar® Gel (repository corticotropin injection [RCI]) in the tetrodotoxin (TTX) model of early-life-induced epileptic spasms. Repository corticotropin injection (RCI) is widely used in the United States to treat infantile spasms. A major component of RCI is N25 deamidated ACTH. Additionally, we hoped to provide some insight into the possible role circulating corticosteroids play in spasm cessation by comparing the RCI dose-response relationships for spasm suppression to RCI-induced corticosterone release from the adrenal gland. Spasms were induced by chronic TTX infusion into the neocortex beginning on postnatal day 11. Repository corticotropin injection (RCI) dosages were between 8 and 32 IU/kg/day. Drug titration protocols were used, and comparisons were made to injections of a vehicle gel. Video/EEG recordings (24/7) monitored the drug's effects continuously for up to 2 months. Tetrodotoxin (TTX)-infused control rats were monitored for the same period of time. In separate experiments, the same dosages of RCI were given to rats and 1 h later plasma was collected and assayed for corticosterone. A parallel study compared the effects of 1-day and 10-day RCI treatments on circulating corticosterone. Results showed that RCI was ineffective at dosages of 8, 12, and 16 IU/kg/day but eliminated spasms in 66% of animals treated with 24 or 32 IU/kg/day. Treating animals with 32 IU/kg/day alone produced the same degree of spasms suppression as observed during the titration protocols. In rats that had hypsarrhythmia-like activity, RCI eliminated this abnormal interictal EEG pattern in all rats that became seizure-free. In terms of plasma corticosterone, 1- and 10-day treatments with RCI produced similar increases in this hormone and the levels increased linearly with increasing dosages of RCI. This stood in sharp contrast to the sigmoid-like dose-response curve for decreases in spasm counts. Our results further validate the TTX model as relevant for the study of infantile spasms. The model should be useful for investigating how RCI acts to eliminate seizures and hypsarrhythmia. Dose-response results suggest that either very high concentrations of circulating corticosteroids are required to abolish spasms or RCI acts through a different mechanism.

Vigabatrin therapy implicates neocortical high frequency oscillations in an animal model of infantile spasms.

Abnormal high frequency oscillations (HFOs) in EEG recordings are thought to be reflections of mechanisms responsible for focal seizure generation in the temporal lobe and neocortex. HFOs have also been recorded in patients and animal models of infantile spasms. If HFOs are important contributors to infantile spasms then anticonvulsant drugs that suppress these seizures should decrease the occurrence of HFOs. In experiments reported here, we used long-term video/EEG recordings with digital sampling rates capable of capturing HFOs. We tested the effectiveness of vigabatrin (VGB) in the TTX animal model of infantile spasms. VGB was found to be quite effective in suppressing spasms. In 3 of 5 animals, spasms ceased after a daily two week treatment. In the other 2 rats, spasm frequency dramatically decreased but gradually increased following treatment cessation. In all animals, hypsarrhythmia was abolished by the last treatment day. As VGB suppressed the frequency of spasms, there was a decrease in the intensity of the behavioral spasms and the duration of the ictal EEG event. Analysis showed that there was a burst of high frequency activity at ictal onset, followed by a later burst of HFOs. VGB was found to selectively suppress the late HFOs of ictal complexes. VGB also suppressed abnormal HFOs recorded during the interictal periods. Thus VGB was found to be effective in suppressing both the generation of spasms and hypsarrhythmia in the TTX model. Vigabatrin also appears to preferentially suppress the generation of abnormal HFOs, thus implicating neocortical HFOs in the infantile spasms disease state.

Infantile spasms.

Infantile spasms are a unique disorder of infancy and early childhood. The average age at onset of infantile spasms is 6 months and the average incidence of the disorder is approximately 0.31 per 1000 live births. Approximately one-quarter of patients will spontaneously stop having spasms within 1 year of onset. There are three main types of epileptic spasms: flexor, extensor, and mixed flexor-extensor. Spasms frequently occur in clusters and commonly occur upon arousal from sleep. The motor spasms are frequently confused with other normal and abnormal infant behaviors. Typically, the interictal EEG reveals hypsarrhythmia or one of its variants. A variety of ictal EEG patterns may be seen, the most common of which is a generalized slow-wave transient followed by an attenuation of the background activity in all regions. The primary treatment objective is to improve the EEG and stop the spasms as soon as possible and to avoid prolonged treatment durations with any form of therapy. Currently, there is no conclusive evidence that medical or surgical treatment of infantile spasms significantly alters long-term outcome. Although the pathophysiological mechanism underlying infantile spasms is unknown, several animal models of infantile spasms have been developed in recent years.

Electroencephalography and quantitative electroencephalography in mild traumatic brain injury.

Mild traumatic brain injury (mTBI) causes brain injury resulting in electrophysiologic abnormalities visible in electroencephalography (EEG) recordings. Quantitative EEG (qEEG) makes use of quantitative techniques to analyze EEG characteristics such as frequency, amplitude, coherence, power, phase, and symmetry over time independently or in combination. QEEG has been evaluated for its use in making a diagnosis of mTBI and assessing prognosis, including the likelihood of progressing to the postconcussive syndrome (PCS) phase. We review the EEG and qEEG changes of mTBI described in the literature. An attempt is made to separate the findings seen during the acute, subacute, and chronic phases after mTBI. Brief mention is also made of the neurobiological correlates of qEEG using neuroimaging techniques or in histopathology. Although the literature indicates the promise of qEEG in making a diagnosis and indicating prognosis of mTBI, further study is needed to corroborate and refine these methods.

Interictal high frequency oscillations in an animal model of infantile spasms.

While infantile spasms is the most common catastrophic epilepsy of infancy and early-childhood, very little is known about the basic mechanisms responsible for this devastating disorder. In experiments reported here, spasms were induced in rats by the chronic infusion of TTX into the neocortex beginning on postnatal days 10-12. Studies of focal epilepsy suggest that high frequency EEG oscillations (HFOs) occur interictally at sites that are most likely responsible for seizure generation. Thus, our goal was to determine if HFOs occurred and where they occurred in cortex in the TTX model. We also undertook multiunit recordings to begin to analyze the basic mechanisms responsible for HFOs. Our results show that HFOs occur most frequently during hypsarrhythmia and NREM sleep and are most prominent contralateral to the TTX infusion site in the homotopic cortex and anterior to this region in frontal cortex. While HFOs were largest and most frequent in these contralateral regions, they were also commonly recorded synchronously across multiple and widely-spaced recordings sites. The amplitude and spatial distribution of interictal HFOs were found to be very similar to the high frequency bursts seen at seizure onset. However, the latter differed from the interictal events in that the high frequency activity was more intense at seizure onset. Microwire recordings showed that neuronal unit firing increased abruptly with the generation of HFOs. A similar increase in neuronal firing occurred at the onset of the ictal events. Taken together, results suggest that neocortical networks are abnormally excitable, particularly contralateral to TTX infusion, and that these abnormalities are not restricted to small areas of cortex. Multiunit firing coincident with HFOs is fully consistent with a neocortical hyperexcitability hypothesis particularly since they both occur at seizure onset.

High frequency EEG activity associated with ictal events in an animal model of infantile spasms.

PURPOSE: To describe high frequency (HF) electrographic activity accompanying ictal discharges in the tetrodotoxin (TTX) model of infantile spasms. Previous studies of HF oscillations in humans and animals suggest that they arise at sites of seizure onset. We compared HF oscillations at several cortical sites to determine regional differences. METHODS: TTX was infused for 4 weeks into the neocortex of rats beginning on postnatal days 11 or 12. Electroencephalography (EEG) electrodes were implanted 2 weeks later and video-EEG recordings were analyzed between postnatal days 31 and 47. EEG recordings were digitally sampled at 2,048 Hz. HF EEG activity (20-900 Hz) was quantified using compressed spectral arrays and band-pass filtering. KEY FINDINGS: Multiple seizures were analyzed in 10 rats. Ictal onset was associated with multiple bands of rhythmic HF activity that could extend to 700 Hz. The earliest and most intense discharging typically occurred contralaterally to where TTX was infused. HF activity continued to occur throughout the seizure (even during the electrodecrement that is recorded with more traditional filter settings), although there was a gradual decrease of the intensity of the highest frequency components as the amplitude of lower frequency oscillations increased. Higher frequencies sometimes reappeared in association with spike/sharp-waves at seizure termination. SIGNIFICANCE: The findings show that HF EEG activity accompanies ictal events in the TTX model. Results also suggest that the seizures in this model do not originate from the TTX infusion site. Instead HF discharges are usually most intense and occur earliest contralaterally, suggesting that these homologous regions may be involved in seizure generation.

A triplet repeat expansion genetic mouse model of infantile spasms syndrome, Arx(GCG)10+7, with interneuronopathy, spasms in infancy, persistent seizures, and adult cognitive and behavioral impairment.

Infantile spasms syndrome (ISS) is a catastrophic pediatric epilepsy with motor spasms, persistent seizures, mental retardation, and in some cases, autism. One of its monogenic causes is an insertion mutation [c.304ins (GCG)(7)] on the X chromosome, expanding the first polyalanine tract of the interneuron-specific transcription factor Aristaless-related homeobox (ARX) from 16 to 23 alanine codons. Null mutation of the Arx gene impairs GABA and cholinergic interneuronal migration but results in a neonatal lethal phenotype. We developed the first viable genetic mouse model of ISS that spontaneously recapitulates salient phenotypic features of the human triplet repeat expansion mutation. Arx((GCG)10+7) ("Arx plus 7") pups display abnormal spasm-like myoclonus and other key EEG features, including multifocal spikes, electrodecremental episodes, and spontaneous seizures persisting into maturity. The neurobehavioral profile of Arx mutants was remarkable for lowered anxiety, impaired associative learning, and abnormal social interaction. Laminar decreases of Arx+ cortical interneurons and a selective reduction of calbindin-, but not parvalbumin- or calretinin-expressing interneurons in neocortical layers and hippocampus indicate that specific classes of synaptic inhibition are missing from the adult forebrain, providing a basis for the seizures and cognitive disorder. A significant reduction of calbindin-, NPY (neuropeptide Y)-expressing, and cholinergic interneurons in the mutant striatum suggest that dysinhibition within this network may contribute to the dyskinetic motor spasms. This mouse model narrows the range of critical pathogenic elements within brain inhibitory networks essential to recreate this complex neurodevelopmental syndrome.

A multistage system for the automated detection of epileptic seizures in neonatal electroencephalography.

This paper describes the design and test results of a three-stage automated system for neonatal EEG seizure detection. Stage I of the system is the initial detection stage and identifies overlapping 5-second segments of suspected seizure activity in each EEG channel. In stage II, the detected segments from stage I are spatiotemporally clustered to produce multichannel candidate seizures. In stage III, the candidate seizures are processed further using measures of quality and context-based rules to eliminate false candidates. False candidates because of artifacts and commonly occurring EEG background patterns such as bifrontal delta activity are also rejected. Seizures at least 10 seconds in duration are considered for reporting results. The testing data consisted of recordings of 28 seizure subjects (34 hours of data) and 48 nonseizure subjects (87 hours of data) obtained in the neonatal intensive care unit. The data were not edited to remove artifacts and were identical in every way to data normally processed visually. The system was able to detect seizures of widely varying morphology with an average detection sensitivity of almost 80% and a subject sensitivity of 96%, in comparison with a team of clinical neurophysiologists who had scored the same recordings. The average false detection rate obtained in nonseizure subjects was 0.74 per hour.

A new animal model of infantile spasms with unprovoked persistent seizures.

PURPOSE: Infantile spasms is one of the most severe epileptic syndromes of infancy and early childhood. Progress toward understanding the pathophysiology of this disorder and the development of effective therapies has been hindered by the lack of a relevant animal model. We report here the creation of such a model. METHODS: The sodium channel blocker, tetrodotoxin (TTX), was chronically infused into the developing neocortex or hippocampus of infant rats by way of an osmotic minipump starting on postnatal day 10-12. RESULTS: After a minimum of 10 days of infusion, approximately one-third of these rats began to display very brief (1-2 s) spasms, which consisted of symmetric or asymmetric flexion or extension of the trunk and sometimes involvement of one or both forelimbs. The typical ictal EEG pattern associated with the behavioral spasms consisted of an initial generalized, high amplitude, slow wave followed by an electrodecrement with superimposed fast activity. The interictal EEG revealed multifocal spikes and sharp waves, and in most animals that had spasms a hypsarrhythmic pattern was seen, at least intermittently, during NREM sleep. Like in humans, the spasms in the rat often occurred in clusters especially during sleep-wake transitions. Comparison of the ictal and interictal EEGs recorded in this model and those from humans with infantile spasms revealed that the patterns and the frequency components of both the ictal events and hypsarrhythmia were very similar. DISCUSSION: The TTX model of infantile spasms should be of value in furthering an understanding of the pathophysiology of this seizure disorder.

Time interval from a brain insult to the onset of infantile spasms.

The temporal latency between an encephalopathic event and the onset of infantile spasms cannot be determined in the majority of symptomatic cases (e.g. genetic conditions, cerebral malformations). However, we can measure this interval when a previously normal infant sustains brain injury followed by infantile spasms. This information has implications for understanding the underlying pathophysiologic basis for infantile spasms and, also, is germane to allegations that a close temporal relationship between vaccination and the onset of this seizure disorder establishes causation. We identified 19 published cases with sufficient information. The interval between brain injury and the onset of infantile spasms ranged from 6 weeks to 11 months (mean = 5.1 months). A similar temporal latency occurs in children with perinatal cerebral infarction and infantile spasms. We conclude that infantile spasms do not occur acutely following an encephalopathic event. This interval of weeks to months is consistent with prior studies indicating temporal latency between brain injury and the onset of other types of epilepsy, as well as with the previously proposed developmental desynchronization hypothesis. The findings refute claims that a close temporal association between an immunization and the onset of infantile spasms establishes causation.

Automated detection of videotaped neonatal seizures based on motion tracking methods.

This study was carried out during the second phase of the project "Video Technologies for Neonatal Seizures" and aimed at the development of a seizure detection system by training neural networks, using quantitative motion information extracted by motion tracking methods from short video segments of infants monitored for seizures. The motion of the infants' body parts was quantified by temporal motion trajectory signals extracted from video recordings by robust motion trackers, based on block motion models. These motion trackers were developed to autonomously adjust to illumination and contrast changes that may occur during the video frame sequence. The computational tools and procedures developed for automated seizure detection were evaluated on short video segments selected and labeled by physicians from a set of 240 video recordings of 54 patients exhibiting myoclonic seizures (80 segments), focal clonic seizures (80 segments), and random infant movements (80 segments). This evaluation provided the basis for selecting the most effective strategy for training neural networks to detect neonatal seizures as well as the decision scheme used for interpreting the responses of the trained neural networks. The best neural networks exhibited sensitivity and specificity above 90%. The best among the motion trackers developed in this study produced quantitative features that constitute a reliable basis for detecting myoclonic and focal clonic neonatal seizures. The performance targets of the second phase of the project may be achieved by combining the quantitative features described in this paper with those obtained by analyzing motion strength signals produced by motion segmentation methods.

The EEG in selected generalized seizures.

This article reviews the ictal and interictal EEG findings associated with a select group of generalized seizures. These include absence seizures, myoclonic seizures seen in juvenile myoclonic epilepsy, idiopathic generalized tonic clonic seizures, infantile spasms, and atypical absence, tonic, and atonic seizures associated with the Lennox Gastaut syndrome.

Automated detection of videotaped neonatal seizures of epileptic origin.

PURPOSE: This study aimed at the development of a seizure-detection system by training neural networks with quantitative motion information extracted from short video segments of neonatal seizures of the myoclonic and focal clonic types and random infant movements. METHODS: The motion of the infants' body parts was quantified by temporal motion-strength signals extracted from video segments by motion-segmentation methods based on optical flow computation. The area of each frame occupied by the infants' moving body parts was segmented by clustering the motion parameters obtained by fitting an affine model to the pixel velocities. The motion of the infants' body parts also was quantified by temporal motion-trajectory signals extracted from video recordings by robust motion trackers based on block-motion models. These motion trackers were developed to adjust autonomously to illumination and contrast changes that may occur during the video-frame sequence. Video segments were represented by quantitative features obtained by analyzing motion-strength and motion-trajectory signals in both the time and frequency domains. Seizure recognition was performed by conventional feed-forward neural networks, quantum neural networks, and cosine radial basis function neural networks, which were trained to detect neonatal seizures of the myoclonic and focal clonic types and to distinguish them from random infant movements. RESULTS: The computational tools and procedures developed for automated seizure detection were evaluated on a set of 240 video segments of 54 patients exhibiting myoclonic seizures (80 segments), focal clonic seizures (80 segments), and random infant movements (80 segments). Regardless of the decision scheme used for interpreting the responses of the trained neural networks, all the neural network models exhibited sensitivity and specificity>90%. For one of the decision schemes proposed for interpreting the responses of the trained neural networks, the majority of the trained neural-network models exhibited sensitivity>90% and specificity>95%. In particular, cosine radial basis function neural networks achieved the performance targets of this phase of the project (i.e., sensitivity>95% and specificity>95%). CONCLUSIONS: The best among the motion segmentation and tracking methods developed in this study produced quantitative features that constitute a reliable basis for detecting neonatal seizures. The performance targets of this phase of the project were achieved by combining the quantitative features obtained by analyzing motion-strength signals with those produced by analyzing motion-trajectory signals. The computational procedures and tools developed in this study to perform off-line analysis of short video segments will be used in the next phase of this project, which involves the integration of these procedures and tools into a system that can process and analyze long video recordings of infants monitored for seizures in real time.

Automated detection of videotaped neonatal seizures based on motion segmentation methods.

OBJECTIVE: This study was aimed at the development of a seizure detection system by training neural networks using quantitative motion information extracted by motion segmentation methods from short video recordings of infants monitored for seizures. METHODS: The motion of the infants' body parts was quantified by temporal motion strength signals extracted from video recordings by motion segmentation methods based on optical flow computation. The area of each frame occupied by the infants' moving body parts was segmented by direct thresholding, by clustering of the pixel velocities, and by clustering the motion parameters obtained by fitting an affine model to the pixel velocities. The computational tools and procedures developed for automated seizure detection were tested and evaluated on 240 short video segments selected and labeled by physicians from a set of video recordings of 54 patients exhibiting myoclonic seizures (80 segments), focal clonic seizures (80 segments), and random infant movements (80 segments). RESULTS: The experimental study described in this paper provided the basis for selecting the most effective strategy for training neural networks to detect neonatal seizures as well as the decision scheme used for interpreting the responses of the trained neural networks. Depending on the decision scheme used for interpreting the responses of the trained neural networks, the best neural networks exhibited sensitivity above 90% or specificity above 90%. CONCLUSIONS: The best among the motion segmentation methods developed in this study produced quantitative features that constitute a reliable basis for detecting myoclonic and focal clonic neonatal seizures. The performance targets of this phase of the project may be achieved by combining the quantitative features described in this paper with those obtained by analyzing motion trajectory signals produced by motion tracking methods. SIGNIFICANCE: A video system based upon automated analysis potentially offers a number of advantages. Infants who are at risk for seizures could be monitored continuously using relatively inexpensive and non-invasive video techniques that supplement direct observation by nursery personnel. This would represent a major advance in seizure surveillance and offers the possibility for earlier identification of potential neurological problems and subsequent intervention.

Detection of pseudosinusoidal epileptic seizure segments in the neonatal EEG by cascading a rule-based algorithm with a neural network.

This paper presents an approach to detect epileptic seizure segments in the neonatal electroencephalogram (EEG) by characterizing the spectral features of the EEG waveform using a rule-based algorithm cascaded with a neural network. A rule-based algorithm screens out short segments of pseudosinusoidal EEG patterns as epileptic based on features in the power spectrum. The output of the rule-based algorithm is used to train and compare the performance of conventional feedforward neural networks and quantum neural networks. The results indicate that the trained neural networks, cascaded with the rule-based algorithm, improved the performance of the rule-based algorithm acting by itself. The evaluation of the proposed cascaded scheme for the detection of pseudosinusoidal seizure segments reveals its potential as a building block of the automated seizure detection system under development.

Quantifying motion in video recordings of neonatal seizures by regularized optical flow methods.

This paper presents the development of regularized optical flow computation methods and an evaluation of their performance in the extraction of quantitative motion information from video recordings of neonatal seizures. A general formulation of optical flow computation is presented and a mathematical framework for the development of practical tools for computing optical flow is outlined. In addition, this paper proposes an alternative formulation of the optical flow problem that relies on a discrete approximation of a family of quadratic functionals. These regularized optical flow computation methods are used to extract motion strength signals from video recordings of neonatal seizures.

Quantifying motion in video recordings of neonatal seizures by robust motion trackers based on block motion models.

This paper introduces a methodology for the development of robust motion trackers for video based on block motion models. According to this methodology, the motion of a site between two successive frames is estimated by minimizing an error function defined in terms of the intensities at these frames. The proposed methodology is used to develop robust motion trackers that rely on fractional block motion models. The motion trackers developed in this paper are utilized to extract motor activity signals from video recordings of neonatal seizures. The experimental results reveal that the proposed motion trackers are more accurate and reliable than existing motion tracking methods relying on pure translation and affine block motion models.

Computerized motion analysis of videotaped neonatal seizures of epileptic origin.

PURPOSE: The main objective of this research is the development of automated video processing and analysis procedures aimed at the recognition and characterization of the types of neonatal seizures. The long-term goal of this research is the integration of these computational procedures into the development of a stand-alone automated system that could be used as a supplement in the neonatal intensive care unit (NICU) to provide 24-h per day noninvasive monitoring of infants at risk for seizures. METHODS: We developed and evaluated a variety of computational tools and procedures that may be used to carry out the three essential tasks involved in the development of a seizure recognition and characterization system: the extraction of quantitative motion information from video recordings of neonatal seizures in the form of motion-strength and motor-activity signals, the selection of quantitative features that convey some unique behavioral characteristics of neonatal seizures, and the training of artificial neural networks to distinguish neonatal seizures from random infant behaviors and to differentiate between myoclonic and focal clonic seizures. RESULTS: The methods were tested on a set of 240 video recordings of 43 patients exhibiting myoclonic seizures (80 cases), focal clonic seizures (80 cases), and random infant movements (80 cases). The outcome of the experiments verified that optical- flow methods are promising computational tools for quantifying neonatal seizures from video recordings in the form of motion-strength signals. The experimental results also verified that the robust motion trackers developed in this study outperformed considerably the motion trackers based on predictive block matching in terms of both reliability and accuracy. The quantitative features selected from motion-strength and motor-activity signals constitute a satisfactory representation of neonatal seizures and random infant movements and seem to be complementary. Such features lead to trained neural networks that exhibit performance levels exceeding the initial goals of this study, the sensitivity goal being >or=80% and the specificity goal being >or=90%. CONCLUSIONS: The outcome of this experimental study provides strong evidence that it is feasible to develop an automated system for the recognition and characterization of the types of neonatal seizures based on video recordings. This will be accomplished by enhancing the accuracy and improving the reliability of the computational tools and methods developed during the course of the study outlined here.