Seizure Forecasting by High-Frequency Activity (80-170 Hz) in Long-term Continuous Intracranial EEG Recordings.

Background And Objectives: Reliable seizure forecasting has important implications in epilepsy treatment and improving the quality of lives for people with epilepsy. High-frequency activity (HFA) is a biomarker that has received significant attention over the past 2 decades, but its predictive value in seizure forecasting remains uncertain. This work aimed to determine the utility of HFA in seizure forecasting.

Ambient air pollution and epileptic seizures: A panel study in Australia.

Objective: Emerging evidence has shown that ambient air pollution affects brain health, but little is known about its effect on epileptic seizures. This work aimed to assess the association between daily exposure to ambient air pollution and the risk of epileptic seizures.

Methods: This study used epileptic seizure data from two independent data sources (NeuroVista and Seer App seizure diary).

Multiday cycles of heart rate are associated with seizure likelihood: An observational cohort study.

Background: Circadian and multiday rhythms are found across many biological systems, including cardiology, endocrinology, neurology, and immunology. In people with epilepsy, epileptic brain activity and seizure occurrence have been found to follow circadian, weekly, and monthly rhythms. Understanding the relationship between these cycles of brain excitability and other physiological systems can provide new insight into the causes of multiday cycles.

Seizure Forecasting Using a Novel Sub-Scalp Ultra-Long Term EEG Monitoring System.

Accurate identification of seizure activity, both clinical and subclinical, has important implications in the management of epilepsy. Accurate recognition of seizure activity is essential for diagnostic, management and forecasting purposes, but patient-reported seizures have been shown to be unreliable. Earlier work has revealed accurate capture of electrographic seizures and forecasting is possible with an implantable intracranial device, but less invasive electroencephalography (EEG) recording systems would be optimal.

Seizure likelihood varies with day-to-day variations in sleep duration in patients with refractory focal epilepsy: A longitudinal electroencephalography investigation.

Background: While the effects of prolonged sleep deprivation (≥24 h) on seizure occurrence has been thoroughly explored, little is known about the effects of day-to-day variations in the duration and quality of sleep on seizure probability. A better understanding of the interaction between sleep and seizures may help to improve seizure management.

Methods: To explore how sleep and epileptic seizures are associated, we analysed continuous intracranial electroencephalography (EEG) recordings collected from 10 patients with refractory focal epilepsy undergoing ordinary life activities between 2010 and 2012 from three clinical centres (Austin Health, The Royal Melbourne Hospital, and St Vincent's Hospital of the Melbourne University Epilepsy Group).

Long-term seizure dynamics are determined by the nature of seizures and the mutual interactions between them.

The seemingly random and unpredictable nature of seizures is a major debilitating factor for people with epilepsy. An increasing body of evidence demonstrates that the epileptic brain exhibits long-term fluctuations in seizure susceptibility, and seizure emergence seems to be a consequence of processes operating over multiple temporal scales. A deeper insight into the mechanisms responsible for long-term seizure fluctuations may provide important information for understanding the complex nature of seizure genesis.

High-Frequency Oscillations in Epilepsy: What Have We Learned and What Needs to be Addressed.

For the past 2 decades, high-frequency oscillations (HFOs) have been enthusiastically studied by the epilepsy community. Emerging evidence shows that HFOs harbor great promise to delineate epileptogenic brain areas and possibly predict the likelihood of seizures. Investigations into HFOs in clinical epilepsy have advanced from small retrospective studies relying on visual identification and correlation analysis to larger prospective assessments using automatic detection and prediction strategies.

Spatiotemporal Patterns of High-Frequency Activity (80-170 Hz) in Long-Term Intracranial EEG.

Objective: To determine the utility of high-frequency activity (HFA) and epileptiform spikes as biomarkers for epilepsy, we examined the variability in their rates and locations using long-term ambulatory intracranial EEG (iEEG) recordings.

Methods: This study used continuous iEEG recordings obtained over an average of 1.4 years from 15 patients with drug-resistant focal epilepsy.

Critical slowing down as a biomarker for seizure susceptibility.

The human brain has the capacity to rapidly change state, and in epilepsy these state changes can be catastrophic, resulting in loss of consciousness, injury and even death. Theoretical interpretations considering the brain as a dynamical system suggest that prior to a seizure, recorded brain signals may exhibit critical slowing down, a warning signal preceding many critical transitions in dynamical systems. Using long-term intracranial electroencephalography (iEEG) recordings from fourteen patients with focal epilepsy, we monitored key signatures of critical slowing down prior to seizures.

Hybrid diamond/ carbon fiber microelectrodes enable multimodal electrical/chemical neural interfacing.

Implantable medical devices are now in regular use to treat or ameliorate medical conditions, including movement disorders, chronic pain, cardiac arrhythmias, and hearing or vision loss. Aside from offering alternatives to pharmaceuticals, one major advantage of device therapy is the potential to monitor treatment efficacy, disease progression, and perhaps begin to uncover elusive mechanisms of diseases pathology. In an ideal system, neural stimulation, neural recording, and electrochemical sensing would be conducted by the same electrode in the same anatomical region.

Deep Brain Stimulation for Epilepsy: Biomarkers for Optimization.

Purpose Of Review: Two large-scale controlled clinical trials have provided Class I evidence for the benefit of deep brain stimulation (DBS) as a therapy for refractory epilepsy. However, the efficacy has been variable, with some patients not achieving any improvement in their seizure control. This disparity could be the result of suboptimal stimulation parameters/electrodes or alternatively a difference in the type of seizures being treated.

Loss of neuronal network resilience precedes seizures and determines the ictogenic nature of interictal synaptic perturbations.

The mechanism of seizure emergence and the role of brief interictal epileptiform discharges (IEDs) in seizure generation are two of the most important unresolved issues in modern epilepsy research. We found that the transition to seizure is not a sudden phenomenon, but is instead a slow process that is characterized by the progressive loss of neuronal network resilience. From a dynamical perspective, the slow transition is governed by the principles of critical slowing, a robust natural phenomenon that is observable in systems characterized by transitions between dynamical regimes.

Biophysical basis of the linear electrical receptive fields of retinal ganglion cells.

Unlabelled: Responses of retinal ganglion cells to direct electrical stimulation have been shown experimentally to be well described by linear-nonlinear models. These models rely on the simplifying assumption that retinal ganglion cell responses to stimulation with an array of electrodes are driven by a simple linear weighted sum of stimulus current amplitudes from each electrode, known as the 'electrical receptive field'.

Objective: This paper aims to demonstrate the biophysical basis of the linear-nonlinear model and the electrical receptive field to facilitate the development of improved stimulation strategies for retinal implants.

Electrical receptive fields of retinal ganglion cells: Influence of presynaptic neurons.

Implantable retinal stimulators activate surviving neurons to restore a sense of vision in people who have lost their photoreceptors through degenerative diseases. Complex spatial and temporal interactions occur in the retina during multi-electrode stimulation. Due to these complexities, most existing implants activate only a few electrodes at a time, limiting the repertoire of available stimulation patterns.

A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina.

Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants).

The effects of temperature changes on retinal ganglion cell responses to electrical stimulation.

Little is known about how the retina's response to electrical stimulation is modified by temperatures. In vitro experiments are often used to inform in vivo studies, hence it is important to understand what changes occur at physiological temperature. To investigate this, we recorded from eight RGCs in vitro at three temperatures; room temperature (24°C), 30°C and 34°C.

Prosthetic vision: devices, patient outcomes and retinal research.

Retinal disease and its associated retinal degeneration can lead to the loss of photoreceptors and therefore, profound blindness. While retinal degeneration destroys the photoreceptors, the neural circuits that convey information from the eye to the brain are sufficiently preserved to make it possible to restore sight using prosthetic devices. Typically, these devices consist of a digital camera and an implantable neurostimulator.

Ionic channel changes in glaucomatous retinal ganglion cells: multicompartment modeling.

This research takes a step towards discovering underlying ionic channel changes in the glaucomatous ganglion cells. Glaucoma is characterized by a gradual death of retinal ganglion cells. In this paper, we propose a hypothesis that the ionic channel concentrations change during the progression of glaucoma.

Retinal ganglion cells electrophysiology: the effect of cell morphology on impulse waveform.

There are 16 morphologically defined classes of rats retinal ganglion cells (RGCs). Using computer simulation of a realistic anatomically correct A1 mouse RGC, we investigate the effect of the cell's morphology on its impulse waveform, using the first-, and second-order time derivatives as well as the phase plot features. Using whole cell patch clamp recordings, we recorded the impulse waveform for each of the rat RGCs types.

Multicompartment retinal ganglion cells response to high frequency bi-phasic pulse train stimulation: Simulation results.

Retinal ganglion cells (RGCs) are the sole output neurons of the retina that carry information about a visual scene to the brain. By stimulating RGCs with electrical stimulation, it is possible to elicit a sensation of light for people with macular degeneration or retinitis pigmentosa. To investigate the responses of RGCs to high frequency bi-phasic pulse train stimulation, we use previously constrained models of multi-compartment OFF RGCs.

The effect of morphology upon electrophysiological responses of retinal ganglion cells: simulation results.

Retinal ganglion cells (RGCs) display differences in their morphology and intrinsic electrophysiology. The goal of this study is to characterize the ionic currents that explain the behavior of ON and OFF RGCs and to explore if all morphological types of RGCs exhibit the phenomena described in electrophysiological data. We extend our previous single compartment cell models of ON and OFF RGCs to more biophysically realistic multicompartment cell models and investigate the effect of cell morphology on intrinsic electrophysiological properties.