Real-time detection, quantification, warning, and control of epileptic seizures: the foundations for a scientific epileptology.

Substantive advances in clinical epileptology may be realized through the judicious use of real-time automated seizure detection, quantification, warning, and delivery of therapy in subjects with pharmacoresistant seizures. Materialization of these objectives is likely to elevate epileptology to the level of a mature clinical science.

Seizure abatement with single dc pulses: is phase resetting at play?

Topological approaches for seizure abatement have received scarce attention. The ability to reset the phase of biological oscillations has been widely exploited in cardiology, as evidenced in part by the usefulness of implantable of defibrillators, but not in epileptology. The aim of this work is to investigate the feasibility of seizure blockage using single or brief monophasic (DC) pulse trains. Single DC or brief (0.1 s) pulse trains were delivered manually or automatically to generalized seizures, induced in rats with the convulsant 3-mercaptoprionic acid, a GABA inhibitor. Treatment outcome (blocked vs. not blocked seizures) was ascertained visually and correlated with the "rhythmicity index", an indirect estimate of neuronal synchrony level. Blockage using single or brief (0.1 s) DC pulses was consistently achieved for seizures with a rhythmicity index > 0.6, while seizures with levels <0.6 were not, although transient phase changes in their oscillations were effected. This work reveals that level of neuronal synchronization may be an important factor in determining the probability of seizure blockage. Seizure blockage using single or brief DC pulse trains and its effects on neural tissue merit further investigation. The clinical applicability of this therapeutic modality and means to enhance it are discussed.

Vagal and sciatic nerve stimulation have complex, time-dependent effects on chemically-induced seizures: a controlled study.

Previous studies of the effects of electrical vagus stimulation on experimental seizures were without suitable controls or statistical validation, and ignored the potential role of vagally-induced hemodynamic depression on seizure expression. This study addresses these limitations. The effects of periodic left vagus nerve stimulation (LVNS) on chemically-induced seizures in rats were compared with control groups receiving no stimulation (NoS), left sciatic nerve stimulation (LSNS) and LVNS after pretreatment with methyl atropine (MA-LVNS). Stimulation followed a 30 s on-120 s off cycle over 130 min. Seizures were scored visually and the temporal variation of their probability P(s) across the stimulation cycle was measured statistically. P(s) was significantly different (P<0.01) for all groups: LSNS had the highest and MA-LVNS the lowest seizure probability; LVNS and NoS had intermediate values. While LVNS blocked seizures, it also precipitated them, explaining why its anti-seizure effect was only slightly greater than NoS. Neither LVNS nor MA-LVNS induced changes in cortical rhythms ('activation') associated with decreased P(s), unlike LSNS which increased cortical rhythm synchrony and with it, P(s). LVNS alone induced marked bradycardia and moderate hypoxemia. In conclusion, cranial and peripheral nerve stimulation have complex, time-varying effects on cerebral excitability: low frequency LSNS facilitated seizures, while LVNS both suppressed and facilitated them. The anti-seizure effect of LVNS was small and may have, in part, been due to a hemodynamically-induced deficit in energy substrates. The effects of MA-LVNS on seizure duration and P(s) raise the possibility that, in the absence of hemodynamic depression, stimulation of this nerve does not have a strong anti-seizure effect.

Left vagus nerve stimulation with the neurocybernetic prosthesis has complex effects on heart rate and on its variability in humans.

PURPOSE: The purpose of this study was to determine if stimulation of the left vagus nerve (LVNS) with the neurocybernetic prosthesis (NCP) in humans is, as claimed in the literature, without cardiac chronotropic actions. METHODS: We analyzed 228 h of ECG recorded from five subjects with intractable epilepsy who had not benefited from LVNS, for effects on instantaneous heart rate (IHR) and heart rate variability (HRV). RESULTS: There were two main cardiac responses: (a) bradycardia, and (b) tachycardia during the first half, followed by bradycardia during the second half of stimulation (biphasic response). Multiphasic responses characterized by alternating bradycardia and tachycardia were rarely observed. HRV was either increased or decreased depending on the subject and on the stimulation parameters. HRV as a function of HR also showed high interindividual variability, and interestingly, in one case behaved paradoxically, increasing at higher and decreasing at lower heart rates. CONCLUSIONS: LVNS at high intensities has complex effects on IHR and HRV, which show large interindividual variability. These spectra of cardiac responses reflect the interplay of autonomic, visceral, and somatic sensory afferences and the role of central structures in their integration. These findings also point to the need for more comprehensive studies of cardiac function in humans implanted with the NCP, using sensitive methods for data processing and analysis such as those developed for this study.

Observations on the application of the correlation dimension and correlation integral to the prediction of seizures.

The authors reexamine the correlation integral and the related correlation dimension in the context of EEG analysis with application to seizure prediction. They identify dependencies of the correlation integral and the correlation dimension on frequency and amplitude of the signal, which may result in a reinterpretation of the dynamic importance of these measures and may cast doubts on their predictive abilities for certain classes of seizures. The relevance, for clinical and research purposes, of the distinction between retrospective and prospective inference (prediction) is addressed briefly. The authors point to the need for further research, consisting of long time series, containing multiple seizures, and for the development of objective prediction criteria.

An introduction to contingent (closed-loop) brain electrical stimulation for seizure blockage, to ultra-short-term clinical trials, and to multidimensional statistical analysis of therapeutic efficacy.

Automated seizure blockage is a top research priority of the American Epilepsy Society. This delivery modality (referred to herein as contingent or closed loop) requires for implementation a seizure detection algorithm for control of delivery of therapy via a suitable device. The authors address the many potential advantages of this modality over conventional alternatives (periodic or continuous), and the challenges it poses in the design and analysis of trials to assess efficacy and safety-in the particular context of direct delivery of electrical stimulation to brain tissue. The experimental designs of closed-loop therapies are currently limited by ethical, technical, medical, and practical considerations. One type of design that has been used successfully in an in-hospital "closed-loop" trial using subjects undergoing epilepsy surgery evaluation as their own controls is discussed in detail. This design performs a two-way comparison of seizure intensity, duration, and extent of spread between the control (surgery evaluation) versus the experimental phase, and, within the experimental phase, between treated versus untreated seizures. The proposed statistical analysis is based on a linear model that accounts for possible circadian effects, changes in treatment protocols, and other important factors such as change in seizure probability. The analysis is illustrated using seizure intensity as one of several possible end points from one of the subjects who participated in this trial. In-hospital ultra-short-term trials to assess safety and efficacy of closed-loop delivery of electrical stimulation for seizure blockage are both feasible and valuable.

Network system for automated seizure detection and contingent delivery of therapy.

The authors describe an integrated bedside system for real-time seizure detection and automated delivery of electrical stimulation directly to the brain of subjects undergoing invasive epilepsy surgery evaluation. These stimulations were triggered by specific detections following a prespecified pattern. The system uses a commercially available EEG unit, two personal computers, two Grass S-12 stimulators, and other custom-built units to enable interfacing between these components. To date, more than 9,500 hours of electrocorticographic data have been acquired, displayed, and analyzed, and more than 900 closed-loop stimulations for seizure blockage have been delivered safely and reliably to eight subjects with intractable epilepsy. This system generates on-line reports containing information about seizures that provide the epileptologist with timely, valuable data while allowing adaptation of the algorithm detection parameters to improve its performance if necessary. Additionally, it can control the output of any therapeutic device and administrate automatically cognitive tests or radioactive tracers for neuroimaging purposes. This network system, which can be replicated at a relatively low cost by others, is proof of concept for a portable or implantable device that could serve identical functions. Widespread availability of this type of system will advance the fields of clinical and basic epilepsy rapidly and considerably.

Least squares acceleration filtering for the estimation of signal derivatives and sharpness at extrema.

A family of finite impulse-response (FIR) filters is derived which estimate the second derivative or "acceleration" of a digitized signal. The acceleration is obtained from parabolas that are continuously fit to the signal using a least squares optimization criterion. A closed-form solution for the filter coefficients is obtained. The general approach is computationally simple, can be performed in real-time, and is robust in the presence of noise. An important application of the method, that of measuring sharpness in biologic signals, is presented using the electroencephalogram (EEG) and electrocardiogram (EKG) signals as examples. Furthermore, the design method is extended to derive FIR filters for estimating derivatives of arbitrary order in digital signals of biologic or other origins.

Real-time automated detection and quantitative analysis of seizures and short-term prediction of clinical onset.

PURPOSE: We describe an algorithm for rapid real-time detection, quantitation, localization of seizures, and prediction of their clinical onset. METHODS: Advanced digital signal processing techniques used in time-frequency localization, image processing, and identification of time-varying stochastic systems were used to develop the algorithm, which operates in generic or adaptable "modes." The "generic mode" was tested on (a) 125 partial seizures (each contained in a 10-min segment) involving the mesial temporal regions and recorded using depth electrodes from 16 subjects, and (b) 205 ten-minute segments of randomly selected interictal (nonseizure) data. The performance of the algorithm was compared with expert visual analysis, the current "gold standard." RESULTS: The generic algorithm achieved perfect sensitivity and specificity (no false-positive and no false-negative detections) over the entire data set. Seizure intensity, a novel measure that seems clinically relevant, ranged between 35.7 and 6129. Detection was sufficiently rapid to allow prediction of clinical onset in 92% of seizures by a mean of 15.5 s. CONCLUSIONS: This algorithm, which was implemented with a personal computer, represents a definitive step toward rapid and accurate detection and prediction of seizures. It may also enable development of intelligent devices for automated seizure warning and treatment and stimulate new study of the dynamics of seizures and of the epileptic brain.