William C. Stacey

Suppression of epileptiform activity by high frequency sinusoidal fields in rat hippocampal slices

1 Sinusoidal high frequency (20‐50 Hz) electric fields induced across rat hippocampal slices were found to suppress zero‐Ca2+, low‐Ca2+, picrotoxin, and high‐K+ epileptiform activity for the duration of the stimulus and for up to several minutes following the stimulus. 2 Suppression of spontaneous activity by high frequency stimulation was found to be frequency (< 500 Hz) but not orientation or waveform dependent. 3 Potassium‐sensitive microelectrodes showed that block of epileptiform activity was always coincident with a stimulus‐induced rise in extracellular potassium concentration during stimulation. Post‐stimulus inhibition was always associated with a decrease in extracellular potassium activity below baseline levels. 4 Intracellular recordings and optical imaging with voltage‐sensitive dyes showed that during suppression neurons were depolarized yet did not fire action potentials. 5 Direct injection of sinusoidal current into individual pyramidal cells did not result in a tonic depolarization. Injection of large direct current (DC) depolarized neurons and suppressed action potential generation. 6 These findings suggest that high frequency stimulation suppresses epileptiform activity by inducing potassium efflux and depolarization block.

Local suppression of epileptiform activity by electrical stimulation in rat hippocampus in vitro

High frequency electrical stimulation of deep brain structures (DBS) has been effective at controlling abnormal neuronal activity in Parkinsons patients and is now being applied for the treatment of pharmacologically intractable epilepsy. The mechanisms underlying the therapeutic effects of DBS are unknown. In particular, the effect of the electrical stimulation on neuronal firing remains poorly understood. Previous reports have showed that uniform electric fields with both AC (continuous sinusoidal) or DC waveforms could suppress epileptiform activity in vitro. In the present study, we tested the effects of monopolar electrode stimulation and low‐duty cycle AC stimulation protocols, which more closely approximate those used clinically, on three in vitro epilepsy models. Continuous sinusoidal stimulation, 50 % duty‐cycle sinusoidal stimulation, and low (1.68 %) duty‐cycle pulsed stimulation (120 μs, 140 Hz) could completely suppress spontaneous low‐Ca2+ epileptiform activity with average thresholds of 71.11 ± 26.16 μA, 93.33 ± 12.58 μA and 300 ± 100 μA, respectively. Continuous sinusoidal stimulation could also completely suppress picrotoxin‐ and high‐K+‐induced epileptiform activity with either uniform or localized fields. The suppression generated by the monopolar electrode was localized to a region surrounding the stimulation electrode. Potassium concentration and transmembrane potential recordings showed that AC stimulation was associated with an increase in extracellular potassium concentration and neuronal depolarization block; AC stimulation efficacy was not orientation‐selective. In contrast, DC stimulation blocked activity by membrane hyperpolarization and was orientation‐selective, but had a lower threshold for suppression.

Technology Insight: neuroengineering and epilepsy—designing devices for seizure control

Despite substantial innovations in antiepileptic drug therapy over the past 15 years, the proportion of patients with uncontrolled epilepsy has not changed, highlighting the need for new treatment strategies. New implantable antiepileptic devices, which are currently under development and in pivotal clinical trials, hold great promise for improving the quality of life of millions of people with epileptic seizures worldwide. A broad range of strategies to stop seizures is currently being investigated, with various modes of control and intervention. The success of novel antiepileptic devices rests upon collaboration between neuroengineers, physicians and industry to adapt new technologies for clinical use. The initial results with these technologies are exciting, but considerable development and controlled clinical trials will be required before these treatments earn a place in our standard of clinical care.

Part 4: Advanced life support

The International Liaison Committee on Resuscitation (ILCOR) Advanced Life Support (ALS) Task Force performed detailed systematic reviews based on the recommendations of the Institute of Medicine of the National Academies1 and using the methodological approach proposed by the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) Working Group.2 Questions to be addressed (using the PICO [population, intervention, comparator, outcome] format)3 were prioritized by ALS Task Force members (by voting). Prioritization criteria included awareness of significant new data and new controversies or questions about practice. Questions about topics no longer relevant to contemporary practice or where little new research has occurred were given lower priority. The ALS Task Force prioritized 42 PICO questions for review. With the assistance of information specialists, a detailed search for relevant articles was performed in each of 3 online databases (PubMed, Embase, and the Cochrane Library). By using detailed inclusion and exclusion criteria, articles were screened for further evaluation. The reviewers for each question created a reconciled risk of bias assessment for each of the included studies, using state-of-the-art tools: Cochrane for randomized controlled trials (RCTs),4 Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 for studies of diagnostic accuracy,5 and GRADE for observational studies that inform both therapy and prognosis questions.6 GRADE evidence profile tables7 were then created to facilitate an evaluation of the evidence in support of each of the critical and important outcomes. The quality of the evidence (or confidence in the estimate of the effect) was categorized as high, moderate, low, or very low,8 based on the study methodologies and the 5 core GRADE domains of risk of bias, inconsistency, indirectness, imprecision, and other considerations (including publication bias).9 These evidence profile tables were then used to create a …

Data mining neocortical high-frequency oscillations in epilepsy and controls.

Transient high-frequency (100-500 Hz) oscillations of the local field potential have been studied extensively in human mesial temporal lobe. Previous studies report that both ripple (100-250 Hz) and fast ripple (250-500 Hz) oscillations are increased in the seizure-onset zone of patients with mesial temporal lobe epilepsy. Comparatively little is known, however, about their spatial distribution with respect to seizure-onset zone in neocortical epilepsy, or their prevalence in normal brain. We present a quantitative analysis of high-frequency oscillations and their rates of occurrence in a group of nine patients with neocortical epilepsy and two control patients with no history of seizures. Oscillations were automatically detected and classified using an unsupervised approach in a data set of unprecedented volume in epilepsy research, over 12 terabytes of continuous long-term micro- and macro-electrode intracranial recordings, without human preprocessing, enabling selection-bias-free estimates of oscillation rates. There are three main results: (i) a cluster of ripple frequency oscillations with median spectral centroid = 137 Hz is increased in the seizure-onset zone more frequently than a cluster of fast ripple frequency oscillations (median spectral centroid = 305 Hz); (ii) we found no difference in the rates of high frequency oscillations in control neocortex and the non-seizure-onset zone neocortex of patients with epilepsy, despite the possibility of different underlying mechanisms of generation; and (iii) while previous studies have demonstrated that oscillations recorded by parenchyma-penetrating micro-electrodes have higher peak 100-500 Hz frequencies than penetrating macro-electrodes, this was not found for the epipial electrodes used here to record from the neocortical surface. We conclude that the relative rate of ripple frequency oscillations is a potential biomarker for epileptic neocortex, but that larger prospective studies correlating high-frequency oscillations rates with seizure-onset zone, resected tissue and surgical outcome are required to determine the true predictive value.

What is the present-day EEG evidence for a preictal state?

EEG-based seizure prediction has undergone phases of optimism when analyses based on limited EEG samples suggested high sensitivity and specificity for several algorithms extracting features from raw preictal EEG data. When using long-term recordings, a more realistic view emerged which suggests that statistically significant predictions might be possible from surface and intracranial EEG, but no algorithm has yet demonstrated performance allowing for clinical application. Here, progress in EEG recording techniques, EEG analysis, and requirements for proper statistical validation of results are reported and discussed as they pertain to clinical implementation.

Synaptic Noise and Physiological Coupling Generate High-Frequency Oscillations in a Hippocampal Computational Model

There is great interest in the role of coherent oscillations in the brain. In some cases, high-frequency oscillations (HFOs) are integral to normal brain function, whereas at other times they are implicated as markers of epileptic tissue. Mechanisms underlying HFO generation, especially in abnormal tissue, are not well understood. Using a physiological computer model of hippocampus, we investigate random synaptic activity (noise) as a potential initiator of HFOs. We explore parameters necessary to produce these oscillations and quantify the response using the tools of stochastic resonance (SR) and coherence resonance (CR). As predicted by SR, when noise was added to the network the model was able to detect a subthreshold periodic signal. Addition of basket cell interneurons produced two novel SR effects: 1) improved signal detection at low noise levels and 2) formation of coherent oscillations at high noise that were entrained to harmonics of the signal frequency. The periodic signal was then removed to study oscillations generated only by noise. The combined effects of network coupling and synaptic noise produced coherent, periodic oscillations within the network, an example of CR. Our results show that, under normal coupling conditions, synaptic noise was able to produce gamma (30-100 Hz) frequency oscillations. Synaptic noise generated HFOs in the ripple range (100-200 Hz) when the network had parameters similar to pathological findings in epilepsy: increased gap junctions or recurrent synaptic connections, loss of inhibitory interneurons such as basket cells, and increased synaptic noise. The model parameters that generated these effects are comparable with published experimental data. We propose that increased synaptic noise and physiological coupling mechanisms are sufficient to generate gamma oscillations and that pathologic changes in noise and coupling similar to those in epilepsy can produce abnormal ripples.

Surface charge and lanthanum block of calcium current in bullfrog sympathetic neurons.

The density of surface charge associated with the calcium channel pore was estimated from the effect of extracellular ionic strength on block by La3+. Currents carried by 2 mM Ba2+ were recorded from isolated frog sympathetic neurons by the whole-cell patch-clamp technique. In normal ionic strength (120 mM N-methyl-D-glucamine, NMG), La3+ blocked the current with high affinity (IC50 = 22 nM at 0 mV). La3+ block was relieved by strong depolarization in a time- and voltage-dependent manner. After unblocking, open channels reblocked rapidly at 0 mV, allowing estimation of association and dissociation rates for La3+: k(on) = (7.2 +/- 0.7) x 10(8) M(-1) s(-1), k(off) = 10.0 +/- 0.5 s(-1). To assess surface charge effects, La3+ block was also measured in low ionic strength (12.5 mM NMG) and high ionic strength (250 mM NMG). La3+ block was higher affinity and faster by two- to threefold in 12.5 mM NMG, with little effect of 250 mM NMG. The data could be described by Gouy-Chapman theory with a surface charge density of approximately 1 e-/3000-4000 A2. These results indicate that there is a small but detectable surface charge associated with the pore of voltage-dependent calcium channels.

Temporal changes of neocortical high-frequency oscillations in epilepsy.

High-frequency (100-500 Hz) oscillations (HFOs) recorded from intracranial electrodes are a potential biomarker for epileptogenic brain. HFOs are commonly categorized as ripples (100-250 Hz) or fast ripples (250-500 Hz), and a third class of mixed frequency events has also been identified. We hypothesize that temporal changes in HFOs may identify periods of increased the likelihood of seizure onset. HFOs (86,151) from five patients with neocortical epilepsy implanted with hybrid (micro + macro) intracranial electrodes were detected using a previously validated automated algorithm run over all channels of each patients entire recording. HFOs were characterized by extracting quantitative morphologic features and divided into four time epochs (interictal, preictal, ictal, and postictal) and three HFO clusters (ripples, fast ripples, and mixed events). We used supervised classification and nonparametric statistical tests to explore quantitative changes in HFO features before, during, and after seizures. We also analyzed temporal changes in the rates and proportions of events from each HFO cluster during these periods. We observed patient-specific changes in HFO morphology linked to fluctuation in the relative rates of ripples, fast ripples, and mixed frequency events. These changes in relative rate occurred in pre- and postictal periods up to thirty min before and after seizures. We also found evidence that the distribution of HFOs during these different time periods varied greatly between individual patients. These results suggest that temporal analysis of HFO features has potential for designing custom seizure prediction algorithms and for exploring the relationship between HFOs and seizure generation.

Universal automated high frequency oscillation detector for real-time, long term EEG.

OBJECTIVE Interictal high frequency oscillations (HFOs) in intracranial EEG are a potential biomarker of epilepsy, but current automated HFO detectors require human review to remove artifacts. Our objective is to automatically redact false HFO detections, facilitating clinical use of interictal HFOs. METHODS Intracranial EEG data from 23 patients were processed with automated detectors of HFOs and artifacts. HFOs not concurrent with artifacts were labeled quality HFOs (qHFOs). Methods were validated by human review on a subset of 2000 events. The correlation of qHFO rates with the seizure onset zone (SOZ) was assessed via (1) a retrospective asymmetry measure and (2) a novel quasi-prospective algorithm to identify SOZ. RESULTS Human review estimated that less than 12% of qHFOs are artifacts, whereas 78.5% of redacted HFOs are artifacts. The qHFO rate was more correlated with SOZ (p=0.020, Wilcoxon signed rank test) and resected volume (p=0.0037) than baseline detections. Using qHFOs, our algorithm was able to determine SOZ in 60% of the ILAE Class I patients, with all algorithmically-determined SOZs fully within the resected volumes. CONCLUSIONS The algorithm reduced false-positive HFO detections, improving the precision of the HFO-biomarker. SIGNIFICANCE These methods provide a feasible strategy for HFO detection in real-time, continuous EEG with minimal human monitoring of data quality.