Subcortical (thalamic) automated seizure detection: A new option for contingent therapy delivery.

The feasibility of automated detection of cortical-onset epileptic seizures from subcortical structures such as the thalamus was investigated via simultaneous recording of electroencephalography (EEG) and anterior and centromedian thalamic nuclei electrical signals (electrothalamography) in nine subjects with pharmacoresistant seizures admitted to an epilepsy monitoring unit after deep brain stimulating electrode implantation. Thalamic electrical signals were analyzed using a validated seizure detection algorithm, and times of seizure onset and termination were compared to those determined through visual analysis of video-EEG. Ictal activity was recorded from the scalp and thalamic nuclei in three subjects who had seizures during the 3-4-day recording period.

Alterations in skin temperature and sleep in the fear of harm phenotype of pediatric bipolar disorder.

In children diagnosed with pediatric bipolar disorder (PBD), disturbances in the quality of sleep and wakefulness are prominent. A novel phenotype of PBD called Fear of Harm (FOH) associated with separation anxiety and aggressive obsessions is associated with sleep onset insomnia, parasomnias (nightmares, night-terrors, enuresis), REM sleep-related problems, and morning sleep inertia. Children with FOH often experience thermal discomfort (e.

Epileptic seizures: Quakes of the brain?

A dynamical analogy supported by five scale-free statistics (the Gutenberg-Richter distribution of event sizes, the distribution of interevent intervals, the Omori and inverse Omori laws, and the conditional waiting time until the next event) is shown to exist between two classes of seizures ("focal" in humans and generalized in animals) and earthquakes. Increments in excitatory interneuronal coupling in animals expose the system's dependence on this parameter and its dynamical transmutability: moderate increases lead to power-law behavior of seizure energy and interevent times, while marked ones to scale-free (power-law) coextensive with characteristic scales and events. The coextensivity of power law and characteristic size regimes is predicted by models of coupled heterogeneous threshold oscillators of relaxation and underscores the role of coupling strength in shaping the dynamics of these systems.

Patient and caregiver perspectives on seizure prediction.

One of the goals of the Fourth International Workshop on Seizure Prediction was to provide an opportunity for patients with epilepsy and their caregivers to voice their perspectives on seizure prediction and related matters toward the goal of influencing the design of solutions. In an attempt to fulfill this goal, a survey of patients and caregivers, who often make or influence patient choices, was conducted on issues pertaining to living with epilepsy, epilepsy treatments, seizure prediction, and the use of implantable devices for the control of seizures. The results of this survey are reported here.

Controversies in epilepsy: debates held during the Fourth International Workshop on Seizure Prediction.

Debates on six controversial topics were held during the Fourth International Workshop on Seizure Prediction (IWSP4) convened in Kansas City, KS, USA, July 4-7, 2009. The topics were (1) Ictogenesis: Focus versus Network? (2) Spikes and Seizures: Step-relatives or Siblings? (3) Ictogenesis: A Result of Hyposynchrony? (4) Can Focal Seizures Be Caused by Excessive Inhibition? (5) Do High-Frequency Oscillations Provide Relevant Independent Information? (6) Phase Synchronization: Is It Worthwhile as Measured? This article, written by the IWSP4 organizing committee and the debaters, summarizes the arguments presented during the debates.

Seizure prediction: the Fourth International Workshop.

The recently convened Fourth International Workshop on Seizure Prediction (IWSP4) brought together a diverse international group of investigators, from academia and industry, including epileptologists, neurosurgeons, neuroscientists, computer scientists, engineers, physicists, and mathematicians who are conducting interdisciplinary research on the prediction and control of seizures. IWSP4 allowed the presentation and discussion of results, an exchange of ideas, an assessment of the status of seizure prediction, control, and related fields, and the fostering of collaborative projects.

Pharmaco-resistant seizures: self-triggering capacity, scale-free properties and predictability?

Relevant and timely questions such as regarding the predictability of seizures and their capacity to trigger more seizures remain the subject of debate in epileptology. The present study endeavors to gain insight into these dynamic issues by adopting a non-reductionist approach and via the use of mathematical tools. Probability distribution functions of seizure energies and inter-seizure intervals and the probability of seizure occurrence conditional upon the time elapsed from the previous seizure were estimated from prolonged recordings from subjects with pharmaco-resistant seizures, undergoing surgical evaluation, on reduced doses of or on no medications.

Detection of seizure rhythmicity by recurrences.

Epileptic seizures show a certain degree of rhythmicity, a feature of heuristic and practical interest. In this paper, we introduce a simple model of this type of behavior, and suggest a measure for detecting and quantifying it. To evaluate our method, we develop a set of test segments that incorporate rhythmicity features, and present results from the application of this measure to test segments.

Epileptic seizures are temporally interdependent under certain conditions.

Purpose: The possibility that seizures may be intercorrelated has not been sufficiently investigated. A handful of studies, the majority based on patient seizure diaries, provide disparate results: some claim that seizures are serially correlated and others that they are random events. This study investigates the effect that a seizure may have on the time of occurrence and severity of subsequent ones in subjects undergoing invasive surgical evaluation.

Characterization of synchrony with applications to epileptic brain signals.

Measurement of synchrony in networks of complex or high-dimensional, nonstationary, and noisy systems such as the mammalian brain is technically difficult. We present a general method to analyze synchrony from multichannel time series. The idea is to calculate the phase-synchronization times and to construct a matrix.

Strategies for adapting automated seizure detection algorithms.

The time-varying dynamics of epileptic seizures and the high inter-individual variability make their detection difficult. Osorio et al. [Osorio, I, Frei, MG, Wilkinson, SB.

Detecting and characterizing phase synchronization in nonstationary dynamical systems.

We propose a general framework for detecting and characterizing phase synchronization from noisy, nonstationary time series. For detection, we propose to use the average phase-synchronization time and show that it is extremely sensitive to parameter changes near the onset of phase synchronization. To characterize the degree of temporal phase synchronization, we suggest to monitor the evolution of phase diffusion from a moving time window and argue that this measure is practically useful as it can be enhanced by increasing the size of the window.

Analog seizure detection and performance evaluation.

Epilepsy is the most prevalent neurological disorder affecting both adults and children. Over two-and-one-half million individuals in the United States have epilepsy and 25% of them do not respond to drugs. A significant focus of current research efforts is the development of a fully implantable device for real-time seizure detection and automated warning and blockage of seizures.

Correlation dimension and integral do not predict epileptic seizures.

Reports in the literature have indicated potential value of the correlation integral and dimension for prediction of epileptic seizures up to several minutes before electrographic onset. We apply these measures to over 2000 total hours of continuous electrocortiogram, taken from 20 patients with epilepsy, examine their sensitivity to quantifiable properties such as the signal amplitude and autocorrelation, and investigate the influence of embedding and filtering strategies on their performance. The results are compared against those obtained from surrogate time series.

Accumulated energy revisited.

Objective: To examine the seizure prediction and detection abilities of the accumulated energy on multi-center data submitted to the First International Collaborative Workshop on Seizure Prediction.

Methods: The accumulated energy (AE), windowed average power, and FHS seizure detection algorithm were applied to a single channel of ECoG data taken from the data sets contributed to the workshop. The FHS seizure detection algorithm was used to perform automated scoring of the data in order to locate subclinical events not picked up by the centers where the data was collected.

Automated seizure abatement in humans using electrical stimulation.

The need for novel, efficacious, antiseizure therapies is widely acknowledged. This study investigates in humans the feasibility, safety, and efficacy of high-frequency electrical stimulation (HFES; 100-500 Hz) triggered by automated seizure detections. Eight patients were enrolled in this study, which consisted of a control and an experimental phase.

Controlled test for predictive power of Lyapunov exponents: their inability to predict epileptic seizures.

Lyapunov exponents are a set of fundamental dynamical invariants characterizing a system's sensitive dependence on initial conditions. For more than a decade, it has been claimed that the exponents computed from electroencephalogram (EEG) or electrocorticogram (ECoG) signals can be used for prediction of epileptic seizures minutes or even tens of minutes in advance. The purpose of this paper is to examine the predictive power of Lyapunov exponents.

Gaussian mixture models of ECoG signal features for improved detection of epileptic seizures.

Purpose: To investigate the potential for improving the performance of the Osorio-Frei seizure detection algorithm (OFA) by incorporating multiple FIR filters operating in parallel and Gaussian mixture models (GMM) for ECoG features distributions, thus creating "hybrid" system.

Methods: The "hybrid" algorithm decomposes the signal into four subbands, using wavelets, after which relevant features are extracted for each subband. Following these steps, multivariate GMM are developed for seizure and non-seizure states, using training segments.

Inability of Lyapunov exponents to predict epileptic seizures.

It has been claimed that Lyapunov exponents computed from electroencephalogram or electrocorticogram (ECoG) time series are useful for early prediction of epileptic seizures. We show, by utilizing a paradigmatic chaotic system, that there are two major obstacles that can fundamentally hinder the predictive power of Lyapunov exponents computed from time series: finite-time statistical fluctuations and noise. A case study with an ECoG signal recorded from a patient with epilepsy is presented.

Performance reassessment of a real-time seizure-detection algorithm on long ECoG series.

Purpose: Automated seizure detection and blockage requires highly sensitive and specific algorithms. This study reassessed the performance of an algorithm by using a more extensive database than that of a previous study and its suitability for safety/efficacy closed-loop studies to block seizures in humans.

Methods: Up to eight electrocorticography (EcoG) channels from 15 subjects were analyzed off-line.

Correlation-dimension and autocorrelation fluctuations in epileptic seizure dynamics.

We focus on an anomalous scaling region in correlation integral [C(epsilon)] analysis of electrocorticogram in epilepsy patients. We find that epileptic seizures typically are accompanied by wide fluctuations in the slope of this scaling region. An explanation, based on analyzing the interplay between the autocorrelation and C(epsilon), is provided for these fluctuations.