Trends in the use of automated algorithms for the detection of high-frequency oscillations associated with human epilepsy.

High-frequency oscillations (HFOs) in intracranial electroencephalography (EEG) are a promising biomarker of the epileptogenic zone and tool for surgical planning. Many studies have shown that a high rate of HFOs (number per minute) is correlated with the seizure-onset zone, and complete removal of HFO-generating brain regions has been associated with seizure-free outcome after surgery. In order to use HFOs as a biomarker, these transient events must first be detected in electrophysiological data. Because visual detection of HFOs is time-consuming and subject to low interrater reliability, many automated algorithms have been developed, and they are being used increasingly for such studies. However, there is little guidance on how to select an algorithm, implement it in a clinical setting, and validate the performance. Therefore, we aim to review automated HFO detection algorithms, focusing on conceptual similarities and differences between them. We summarize the standard steps for data pre-processing, as well as post-processing strategies for rejection of false-positive detections. We also detail four methods for algorithm testing and validation, and we describe the specific goal achieved by each one. We briefly review direct comparisons of automated algorithms applied to the same data set, emphasizing the importance of optimizing detection parameters. Then, to assess trends in the use of automated algorithms and their potential for use in clinical studies, we review evidence for the relationship between automatically detected HFOs and surgical outcome. We conclude with practical recommendations and propose standards for the selection, implementation, and validation of automated HFO-detection algorithms.

Beyond implantation effect? Long-term seizure reduction and freedom following intracranial monitoring without additional surgical interventions.

The term 'implantation effect' is used to describe an immediate and transient improvement in seizure frequency following an intracranial study for seizure onset localization. We conducted a retrospective analysis of 190 consecutive patients undergoing intracranial electroencephalogram (EEG) monitoring, of whom 41 had no subsequent resection/ablation/stimulation; 33 had adequate data and follow-up time available for analysis. Analysis of seizure frequency following an intracranial study showed 36% (12/33) responder rate (>50% seizure reduction) at one year, decreasing and stabilizing at 20% from year 4 onwards. In addition, we describe three patients (9%) who had long term seizure freedom of more than five years following electrode implantation alone, two of whom had thalamic depth electrodes. Electrode implantation perhaps leads to a neuromodulatory effect sufficient enough to disrupt epileptogenic networks. Rarely, this may be significant enough to even result in long term seizure freedom, as seen in our three patients.

Sensor Modalities for Brain-Computer Interface Technology: A Comprehensive Literature Review.

Brain-computer interface (BCI) technology is rapidly developing and changing the paradigm of neurorestoration by linking cortical activity with control of an external effector to provide patients with tangible improvements in their ability to interact with the environment. The sensor component of a BCI circuit dictates the resolution of brain pattern recognition and therefore plays an integral role in the technology. Several sensor modalities are currently in use for BCI applications and are broadly either electrode-based or functional neuroimaging-based. Sensors vary in their inherent spatial and temporal resolutions, as well as in practical aspects such as invasiveness, portability, and maintenance. Hybrid BCI systems with multimodal sensory inputs represent a promising development in the field allowing for complimentary function. Artificial intelligence and deep learning algorithms have been applied to BCI systems to achieve faster and more accurate classifications of sensory input and improve user performance in various tasks. Neurofeedback is an important advancement in the field that has been implemented in several types of BCI systems by showing users a real-time display of their recorded brain activity during a task to facilitate their control over their own cortical activity. In this way, neurofeedback has improved BCI classification and enhanced user control over BCI output. Taken together, BCI systems have progressed significantly in recent years in terms of accuracy, speed, and communication. Understanding the sensory components of a BCI is essential for neurosurgeons and clinicians as they help advance this technology in the clinical setting.

Stability of a chronic implanted brain-computer interface in late-stage amyotrophic lateral sclerosis.

OBJECTIVE: We investigated the long-term functional stability and home use of a fully implanted electrocorticography (ECoG)-based brain-computer interface (BCI) for communication by an individual with late-stage Amyotrophic Lateral Sclerosis (ALS). METHODS: Data recorded from the cortical surface of the motor and prefrontal cortex with an implanted brain-computer interface device was evaluated for 36 months after implantation of the system in an individual with late-stage ALS. In addition, electrode impedance and BCI control accuracy were assessed. Key measures included frequency of use of the system for communication, user and system performance, and electrical signal characteristics. RESULTS: User performance was high consistently over the three years. Power in the high frequency band, used for the control signal, declined slowly in the motor cortex, but control over the signal remained unaffected by time. Impedance increased until month 5, and then remained constant. Frequency of home use increased steadily, indicating adoption of the system by the user. CONCLUSIONS: The implanted brain-computer interface proves to be robust in an individual with late-stage ALS, given stable performance and control signal for over 36 months. SIGNIFICANCE: These findings are relevant for the future of implantable brain-computer interfaces along with other brain-sensing technologies, such as responsive neurostimulation.

Simultaneously recorded intracranial and scalp high frequency oscillations help identify patients with poor postsurgical seizure outcome.

OBJECTIVE: High frequency oscillations (HFO) between 80-500 Hz are markers of epileptic areas in intracranial and maybe also scalp EEG. We investigate simultaneous recordings of scalp and intracranial EEG and hypothesize that scalp HFOs provide important additional clinical information in the presurgical setting. METHODS: Spikes and HFOs were visually identified in all intracranial scalp EEG channels. Analysis of correlation of event location between intracranial and scalp EEG as well as relationship between events and the SOZ and zone of surgical removal was performed. RESULTS: 24 patients could be included, 23 showed spikes and 19 HFOs on scalp recordings. In 15/19 patients highest scalp HFO rate was located over the implantation side, with 13 patients having the highest scalp and intracranial HFO rate over the same region. 17 patients underwent surgery, 7 became seizure free. Patients with poor post-operative outcome showed significantly more regions with HFO than those with seizure free outcome. CONCLUSIONS: Scalp HFOs are mostly located over the SOZ. Widespread scalp HFOs are indicative of a larger epileptic network and associated with poor postsurgical outcome. SIGNIFICANCE: Analysis of scalp HFO add clinically important information about the extent of epileptic areas during presurgical simultaneous scalp and intracranial EEG recordings.

Clinical and electrocorticographic response to antiepileptic drugs in patients treated with responsive stimulation.

OBJECTIVE: The objective of this study was to explore whether chronic electrocorticographic (ECoG) data recorded by a responsive neurostimulation system could be used to assess clinical responses to antiepileptic drugs (AEDs). METHODS: Antiepileptic drugs initiated and maintained for ≥3 months by patients participating in clinical trials of the RNS® System were identified. Such "AED Starts" that produced an additional ≥50% reduction in patient-reported clinical seizure frequency were categorized as clinically beneficial, and the remaining as not beneficial. Electrocorticographic features recorded by the RNS® Neurostimulator were analyzed during three periods: 3 months before the AED Start, first month after the AED Start, and the first 3 months after the AED Start. RESULTS: The most commonly added medications were clobazam (n = 41), lacosamide (n = 96), levetiracetam (n = 31), and pregabalin (n = 25). Across all four medications, there were sufficient clinical data for 193 AED Starts to be included in the analyses, and 59 AED Starts were considered clinically beneficial. The proportion of AED Starts that qualified as clinically beneficial was higher for clobazam (53.7%) and levetiracetam (51.6%) than for lacosamide (18.8%) and pregabalin (12%). Across all AED Starts for which RNS ECoG detection settings were held constant, the clinically beneficial AED Starts were associated with a significantly greater reduction in the detection of epileptiform activity (p < 0.001) at 1 (n = 33) and 3 months (n = 30) compared with AED Starts that were not beneficial at 1 (n = 71) and 3 months (n = 60). Furthermore, there was a significant reduction in interictal spike rate and spectral power (1-125 Hz) associated with a clinically beneficial response to an AED Start at 1 (n = 32) and 3 months (n = 35) (p < 0.001). These reductions were not observed at either 1 (n = 59) or 3 months (n = 60) for AED Starts that were not clinically beneficial. CONCLUSIONS: Significant quantitative changes in ECoG data recorded by the RNS System were observed in patients who experienced an additional clinical response to a new AED. While there was variability across patients in the changes observed, the results suggest that quantitative ECoG data may provide useful information when assessing whether a patient may have a favorable clinical response to an AED.

Sudden unexpected death in epilepsy in patients treated with brain-responsive neurostimulation.

OBJECTIVE: To study the incidence and clinical features of sudden unexpected death in epilepsy (SUDEP) in patients treated with direct brain-responsive stimulation with the RNS System. METHODS: All deaths in patients treated in clinical trials (N = 256) or following U.S. Food and Drug Administration (FDA) approval (N = 451) through May 5, 2016, were adjudicated for SUDEP. RESULTS: There were 14 deaths among 707 patients (2208 postimplantation years), including 2 possible, 1 probable, and 4 definite SUDEP events. The rate of probable or definite SUDEP was 2.0/1000 (95% confidence interval [CI] 0.7-5.2) over 2036 patient stimulation years and 2.3/1000 (95% CI 0.9-5.4) over 2208 patient implant years. Stored electrocorticograms around the time of death were available for 4 patients with probable/definite SUDEP and revealed the following: frequent epileptiform activity ending abruptly (n = 2), no epileptiform activity or seizures (n = 1), and an electrographic and witnessed seizure with cessation of postictal electrocorticography (ECoG) activity associated with apnea and pulselessness (n = 1). SIGNIFICANCE: The SUDEP rate of 2.0/1000 patient stimulation years among patients treated with the RNS System is favorable relative to treatment-resistant epilepsy patients randomized to the placebo arm of add-on drug studies or with seizures after resective surgery. Our findings support that treatments that reduce seizures reduce SUDEP risk and that not all SUDEPs follow seizures.

Intracranial EEG fluctuates over months after implanting electrodes in human brain.

OBJECTIVE: Implanting subdural and penetrating electrodes in the brain causes acute trauma and inflammation that affect intracranial electroencephalographic (iEEG) recordings. This behavior and its potential impact on clinical decision-making and algorithms for implanted devices have not been assessed in detail. In this study we aim to characterize the temporal and spatial variability of continuous, prolonged human iEEG recordings. APPROACH: Intracranial electroencephalography from 15 patients with drug-refractory epilepsy, each implanted with 16 subdural electrodes and continuously monitored for an average of 18 months, was included in this study. Time and spectral domain features were computed each day for each channel for the duration of each patient's recording. Metrics to capture post-implantation feature changes and inflexion points were computed on group and individual levels. A linear mixed model was used to characterize transient group-level changes in feature values post-implantation and independent linear models were used to describe individual variability. MAIN RESULTS: A significant decline in features important to seizure detection and prediction algorithms (mean line length, energy, and half-wave), as well as mean power in the Berger and high gamma bands, was observed in many patients over 100 d following implantation. In addition, spatial variability across electrodes declines post-implantation following a similar timeframe. All selected features decreased by 14-50% in the initial 75 d of recording on the group level, and at least one feature demonstrated this pattern in 13 of the 15 patients. Our findings indicate that iEEG signal features demonstrate increased variability following implantation, most notably in the weeks immediately post-implant. SIGNIFICANCE: These findings suggest that conclusions drawn from iEEG, both clinically and for research, should account for spatiotemporal signal variability and that properly assessing the iEEG in patients, depending upon the application, may require extended monitoring.

Spatial-temporal patterns of electrocorticographic spectral changes during midazolam sedation.

OBJECTIVE: To better understand 'when' and 'where' wideband electrophysiological signals are altered by sedation. METHODS: We generated animation movies showing electrocorticography (ECoG) amplitudes at eight spectral frequency bands across 1.0-116 Hz, every 0.1s, on three-dimensional surface images of 10 children who underwent epilepsy surgery. We measured the onset, intensity, and variance of each band amplitude change at given nonepileptic regions separately from those at affected regions. We also determined the presence of differential ECoG changes depending on the brain anatomy. RESULTS: Within 20s following injection of midazolam, beta (16-31.5 Hz) and sigma (12-15.5 Hz) activities began to be multifocally augmented with increased variance in amplitude at each site. Beta-sigma augmentation was most prominent within the association neocortex. Augmentation of low-delta activity (1.0-1.5 Hz) was relatively modest and confined to the somatosensory-motor region. Conversely, injection of midazolam induced attenuation of theta (4.0-7.5 Hz) and high-gamma (64-116 Hz) activities. CONCLUSIONS: Our observations support the notion that augmentation beta-sigma and delta activities reflects cortical deactivation or inactivation, whereas theta and high-gamma activities contribute to maintenance of consciousness. The effects of midazolam on the dynamics of cortical oscillations differed across regions. SIGNIFICANCE: Sedation, at least partially, reflects a multi-local phenomenon at the cortical level rather than global brain alteration homogeneously driven by the common central control structure.

Proceedings of the Seventh International Workshop on Advances in Electrocorticography.

The Seventh International Workshop on Advances in Electrocorticography (ECoG) convened in Washington, DC, on November 13-14, 2014. Electrocorticography-based research continues to proliferate widely across basic science and clinical disciplines. The 2014 workshop highlighted advances in neurolinguistics, brain-computer interface, functional mapping, and seizure termination facilitated by advances in the recording and analysis of the ECoG signal. The following proceedings document summarizes the content of this successful multidisciplinary gathering.

National trends and complication rates for invasive extraoperative electrocorticography in the USA.

Invasive electrocorticography (ECoG) is used in patients when it is difficult to localize epileptogenic foci for potential surgical resection. As MR neuroimaging has improved over the past decade, we hypothesized the utilization of ECoG diminishing over time. Using the USA Nationwide Inpatient Sample, we collected demographic and complication data on patients receiving ECoG over the years 1988-2008 and compared this to patients with medically refractory epilepsy during the same time period. A total of 695 cases using extraoperative ECoG were identified, corresponding to 3528 cases nationwide and accounting for 1.1% of patients with refractory epilepsy from 1988-2008. African Americans were less likely to receive ECoG than whites, as were patients with government insurance in comparison to those with private insurance. Large, urban, and academic hospitals were significantly more likely to perform ECoG than smaller, rural, and private practice institutions. The most frequent complication was cerebrospinal fluid leak (11.7%) and only one death was reported from the entire cohort, corresponding to an estimated six patients nationally. Invasive ECoG is a relatively safe procedure offered to a growing number of patients with refractory epilepsy each year. However, these data suggest the presence of demographic disparities in those patients receiving ECoG, possibly reflecting barriers due to race and socioeconomic status. Among patients with nonlocalized seizures, ECoG often represents their only hope for surgical treatment. We therefore must further examine the indications and efficacy of ECoG, and more work must be done to understand if and why ECoG is preferentially performed in select socioeconomic groups.