Optimizing automated detection of high frequency oscillations using visual markings does not improve SOZ localization.

OBJECTIVE: High frequency oscillations (HFOs) are a biomarker of the seizure onset zone (SOZ) and can be visually or automatically detected. In theory, one can optimize an automated algorithm's parameters to maximize SOZ localization accuracy; however, there is no consensus on whether or how this should be done. Therefore, we optimized an automated detector using visually identified HFOs and evaluated the impact on SOZ localization accuracy. METHODS: We detected HFOs in intracranial EEG from 20 patients with refractory epilepsy from two centers using (1) unoptimized automated detection, (2) visual identification, and (3) automated detection optimized to match visually detected HFOs. RESULTS: SOZ localization accuracy based on HFO rate was not significantly different between the three methods. Across patients, visually optimized detector settings varied, and no single set of settings produced universally accurate SOZ localization. Exploratory analysis suggests that, for many patients, detection settings exist that would improve SOZ localization. CONCLUSIONS: SOZ localization accuracy was similar for all three methods, was not improved by visually optimizing detector settings, and may benefit from patient-specific parameter optimization. SIGNIFICANCE: Visual HFO marking is laborious, and optimizing automated detection using visual markings does not improve localization accuracy. New patient-specific detector optimization methods are needed.

Theta mediated dynamics of human hippocampal-neocortical learning systems in memory formation and retrieval.

Episodic memory arises as a function of dynamic interactions between the hippocampus and the neocortex, yet the mechanisms have remained elusive. Here, using human intracranial recordings during a mnemonic discrimination task, we report that 4-5 Hz (theta) power is differentially recruited during discrimination vs. overgeneralization, and its phase supports hippocampal-neocortical when memories are being formed and correctly retrieved. Interactions were largely bidirectional, with small but significant net directional biases; a hippocampus-to-neocortex bias during acquisition of new information that was subsequently correctly discriminated, and a neocortex-to-hippocampus bias during accurate discrimination of new stimuli from similar previously learned stimuli. The 4-5 Hz rhythm may facilitate the initial stages of information acquisition by neocortex during learning and the recall of stored information from cortex during retrieval. Future work should further probe these dynamics across different types of tasks and stimuli and computational models may need to be expanded accordingly to accommodate these findings.

Theta mediated dynamics of human hippocampal-neocortical learning systems in memory formation and retrieval.

Episodic memory arises as a function of dynamic interactions between the hippocampus and the neocortex, yet the mechanisms have remained elusive. Here, using human intracranial recordings during a mnemonic discrimination task, we report that 4-5 Hz (theta) power is differentially recruited during discrimination vs. overgeneralization, and its phase supports hippocampal-neocortical when memories are being formed and correctly retrieved. Interactions were largely bidirectional, with small but significant net directional biases; a hippocampus-to-neocortex bias during acquisition of new information that was subsequently correctly discriminated, and a neocortex-to-hippocampus bias during accurate discrimination of new stimuli from similar previously learned stimuli. The 4-5 Hz rhythm may facilitate the initial stages of information acquisition by neocortex during learning and the recall of stored information from cortex during retrieval. Future work should further probe these dynamics across different types of tasks and stimuli and computational models may need to be expanded accordingly to accommodate these findings.

Beyond rates: time-varying dynamics of high frequency oscillations as a biomarker of the seizure onset zone.

Objective. High frequency oscillations (HFOs) recorded by intracranial electrodes have generated excitement for their potential to help localize epileptic tissue for surgical resection. However, the number of HFOs per minute (i.e. the HFO 'rate') is not stable over the duration of intracranial recordings; for example, the rate of HFOs increases during periods of slow-wave sleep. Moreover, HFOs that are predictive of epileptic tissue may occur in oscillatory patterns due to phase coupling with lower frequencies. Therefore, we sought to further characterize between-seizure (i.e. 'interictal') HFO dynamics both within and outside the seizure onset zone (SOZ).Approach. Using long-term intracranial EEG (mean duration 10.3 h) from 16 patients, we automatically detected HFOs using a new algorithm. We then fit a hierarchical negative binomial model to the HFO counts. To account for differences in HFO dynamics and rates between sleep and wakefulness, we also fit a mixture model to the same data that included the ability to switch between two discrete brain states that were automatically determined during the fitting process. The ability to predict the SOZ by model parameters describing HFO dynamics (i.e. clumping coefficients and coefficients of variation) was assessed using receiver operating characteristic curves.Main results. Parameters that described HFO dynamics were predictive of SOZ. In fact, these parameters were found to be more consistently predictive than HFO rate. Using concurrent scalp EEG in two patients, we show that the model-found brain states corresponded to (1) non-REM sleep and (2) awake and rapid eye movement sleep. However the brain state most likely corresponding to slow-wave sleep in the second model improved SOZ prediction compared to the first model for only some patients.Significance. This work suggests that delineation of SOZ with interictal data can be improved by the inclusion of time-varying HFO dynamics.

Amplitude of high frequency oscillations as a biomarker of the seizure onset zone.

OBJECTIVE: Studies of high frequency oscillations (HFOs) in epilepsy have primarily tested the HFO rate as a biomarker of the seizure onset zone (SOZ), but the rate varies over time and is not robust for all individual subjects. As an alternative, we tested the performance of HFO amplitude as a potential SOZ biomarker using two automated detection algorithms. METHOD: HFOs were detected in intracranial electroencephalogram (iEEG) from 11 patients using a machine learning algorithm and a standard amplitude-based algorithm. For each detector, SOZ and non-SOZ channels were classified using the rate and amplitude of high frequency events, and performance was compared using receiver operating characteristic curves. RESULTS: The amplitude of detected events was significantly higher in SOZ. Across subjects, amplitude more accurately classified SOZ/non-SOZ than rate (higher values of area under the ROC curve and sensitivity, and lower false positive rates). Moreover, amplitude was more consistent across segments of data, indicated by lower coefficient of variation. CONCLUSION: As an SOZ biomarker, HFO amplitude offers advantages over HFO rate: it exhibits higher classification accuracy, more consistency over time, and robustness to parameter changes. SIGNIFICANCE: This biomarker has the potential to increase the generalizability of HFOs and facilitate clinical implementation as a tool for SOZ localization.

Detection of anomalous high-frequency events in human intracranial EEG.

OBJECTIVE: High-frequency oscillations (HFOs) are a promising biomarker for the epileptogenic zone. However, no physiological definition of an HFO has been established, so detection relies on the empirical definition of an HFO derived from visual observation. This can bias estimates of HFO features such as amplitude and duration, thereby hindering their utility as biomarkers. Therefore, we set out to develop an algorithm that detects high-frequency events in the intracranial EEG that are morphologically distinct from background without requiring assumptions about event amplitude or shape. METHOD: We propose the anomaly detection algorithm (ADA), which uses unsupervised machine learning to identify segments of data that are distinct from the background. We apply ADA and a standard HFO detector using a root mean square amplitude threshold to intracranial EEG from 11 patients undergoing evaluation for epilepsy surgery. The rate, amplitude, and duration of the detected events and the percent overlap between the two detectors are compared. RESULT: In the seizure onset zone (SOZ), ADA detected a subset of conventional HFOs. In non-SOZ channels, ADA detected at least twice as many events as the standard approach, including some conventional HFOs; however, ADA also identified many low and intermediate amplitude events missed by the standard amplitude-based method. The rate of ADA events was similar across all channels; however, the amplitude of ADA events was significantly higher in SOZ channels (P < .0045), and the amplitude measurement was more stable over time than the HFO rate, as indicated by a lower coefficient of variation (P < .0125). SIGNIFICANCE: ADA does not require human supervision, parameter optimization, or prior assumptions about event shape, amplitude, or duration. Our results suggest that the algorithm's estimate of event amplitude may differentiate SOZ and non-SOZ channels. Further studies will examine the utility of HFO amplitude as a biomarker for epilepsy surgical outcome.

A Novel Robotic-Assisted Technique to Implant the Responsive Neurostimulation System.

BACKGROUND: The responsive neurostimulation system (RNS) (NeuroPace Inc, Mountain View, California) was approved as an adjunctive therapy for medically refractory focal epilepsy. RNS detects epileptiform patterns and delivers electrical stimulation to abort seizures. OBJECTIVE: To describe a novel technique of RNS lead implantation using robotic-assisted targeting of ictal-onset zones based on stereoelectroencephalography (sEEG) localization. Secondary objectives are to report the accuracy of robotic-assisted lead implantation using the ROSA robot as well as to report the clinical outcome achieved after RNS implantation by this method. METHODS: A total of 16 patients with medically refractory focal epilepsy underwent sEEG implantation for ictal-onset localization followed by robotic RNS implantation. The electrode most correlative with ictal onset on sEEG was chosen as the target for the RNS electrode. Seizure control was measured at 6-mo and 1-yr follow-up. Ictal-onset electrocorticography (ECoG) data from RNS were compared with ictal onset from sEEG leads based on calculations of lead target to actual lead location from the ROSA robot. RESULTS: At 6-mo follow-up, the average percent seizure reduction was 82% based upon self-reported seizure diaries. At 1-yr follow-up, 8 patients had an average of 90% seizure reduction. The location of seizure onset from ECoG data show similar onset from sEEG leads within 0.165-mm discrepancy. CONCLUSION: The ROSA robot provides an ideal method for targeting subcortical ictal-onset zones. This method of RNS lead implantation achieves high accuracy and is associated with favorable clinical outcomes.

Strategic hospital partnerships: improved access to care and increased epilepsy surgical volume.

OBJECTIVE Surgical treatment of patients with medically refractory focal epilepsy is underutilized. Patients may lack access to surgically proficient centers. The University of California, Irvine (UCI) entered strategic partnerships with 2 epilepsy centers with limited surgical capabilities. A formal memorandum of understanding (MOU) was created to provide epilepsy surgery to patients from these centers. METHODS The authors analyzed UCI surgical and financial data associated with patients undergoing epilepsy surgery between September 2012 and June 2016, before and after institution of the MOU. Variables collected included the length of stay, patient age, seizure semiology, use of invasive monitoring, and site of surgery as well as the monthly number of single-surgery cases, complex cases (i.e., staged surgeries), and overall number of surgery cases. RESULTS Over the 46 months of the study, a total of 104 patients underwent a total of 200 operations; 71 operations were performed in 39 patients during the pre-MOU period (28 months) and 129 operations were performed in 200 patients during the post-MOU period (18 months). There was a significant difference in the use of invasive monitoring, the site of surgery, the final therapy, and the type of insurance. The number of single-surgery cases, complex-surgery cases, and the overall number of cases increased significantly. CONCLUSIONS Partnerships with outside epilepsy centers are a means to increase access to surgical care. These partnerships are likely reproducible, can be mutually beneficial to all centers involved, and ultimately improve patient access to care.

Accuracy and Efficacy for Robotic Assistance in Implanting Responsive Neurostimulation Device Electrodes in Bilateral Mesial Temporal Lobe Epilepsy.

BACKGROUND: Responsive neurostimulation (RNS) is a relatively new treatment option that has been shown to be effective for patients with medically refractory focal epilepsy when resection is not possible, especially in bilateral mesial temporal onset. Robotic devices are becoming increasingly popular for use in stereotactic procedures such as stereoelectroencephalography, but have yet to be used when implanting RNS devices. OBJECTIVE: To show that these 2 forms of advanced technology were compatible and could be used effectively in patient care. METHODS: We implanted RNS devices in 3 patients with bilateral mesial temporal lobe epilepsy. Each patient was placed in the prone position, and electrode trajectories were planned via the robotic navigation system via a transoccipital approach. One lead was placed along each amygdalohippocampal complex. A small craniectomy was then created in the parietal region for RNS generator implantation. Actual and expected target locations and distance were calculated for each depth. There were no complications in this group. RESULTS: RNS devices with bilateral leads were successfully implanted in all 3 patients, with bilateral mesial temporal lobe onset. Follow-up ranged from 3 to 6 mo, and there were no complications in this group. The median distance between the estimate and actual targets was 2.18 (range = 1.11-3.27) mm. CONCLUSION: We show that implanting RNS devices with robotic assistance is feasible with excellent precision and accuracy. The advantages of using robotic assistance include higher flexibility, accuracy, precision, and consistency.

Length of stay for patients undergoing invasive electrode monitoring with stereoelectroencephalography and subdural grids correlates positively with increased institutional profitability.

OBJECTIVE: Lowering the length of stay (LOS) is thought to potentially decrease hospital costs and is a metric commonly used to manage capacity. Patients with epilepsy undergoing intracranial electrode monitoring may have longer LOS because the time to seizure is difficult to predict or control. This study investigates the effect of economic implications of increased LOS in patients undergoing invasive electrode monitoring for epilepsy. METHODS: We retrospectively collected and analyzed patient data for 76 patients who underwent invasive monitoring with either subdural grid (SDG) implantation or stereoelectroencephalography (SEEG) over 2 years at our institution. Data points collected included invasive electrode type, LOS, profit margin, contribution margins, insurance type, and complication rates. RESULTS: LOS correlated positively with both profit and contribution margins, meaning that as LOS increased, both the profit and contribution margins rose, and there was a low rate of complications in this patient group. This relationship was seen across a variety of insurance providers. SIGNIFICANCE: These data suggest that LOS may not be the best metric to assess invasive monitoring patients (i.e., SEEG or SDG), and increased LOS does not necessarily equate with lower or negative institutional financial gain. Further research into LOS should focus on specific specialties, as each may differ in terms of financial implications.

"Ictal" lateralized periodic discharges.

OBJECTIVE: Whether lateralized periodic discharges (LPDs) represent ictal or interictal phenomena, and even the circumstances in which they may represent one or the other, remains highly controversial. Lateralized periodic discharges are, however, widely accepted as being ictal when they are time-locked to clinically apparent symptoms. We sought to investigate the characteristics of "ictal" lateralized periodic discharges (ILPDs) defined by time-locked clinical symptoms in order to explore the utility of using this definition to dichotomize LPDs into "ictal" and "nonictal" categories. METHODS: Our archive of all continuous EEG (cEEG) reports of adult inpatients undergoing prolonged EEG monitoring for nonelective indications between 2007 and 2011 was searched to identify all reports describing LPDs. Lateralized periodic discharges were considered ILPDs when they were reported as being consistently time-locked to clinical symptoms; LPDs lacking a clear time-locked correlate were considered to be "nonictal" lateralized periodic discharges (NILPDs). Patient charts and available neuroimaging studies were also reviewed. Neurophysiologic localization of LPDs, imaging findings, presence of seizures, discharge outcomes, and other demographic factors were compared between patients with ILPDs and those with NILPDs. p-Values were adjusted for false discovery rate (FDR). RESULTS: One thousand four hundred fifty-two patients underwent cEEG monitoring at our institution between 2007 and 2011. Lateralized periodic discharges were reported in 90 patients, 10 of whom met criteria for ILPDs. Nine of the patients with ILPDs demonstrated motor symptoms, and the remaining patient experienced stereotyped sensory symptoms. Ictal lateralized periodic discharges had significantly increased odds for involving central head regions (odds ratio [OR]=11; 95% confidence interval [CI]=2.16-62.6; p=0.018, FDR adjusted), with a trend towards higher proportion of lesions involving the primary sensorimotor cortex (p=0.09, FDR adjusted). CONCLUSIONS: When defined by the presence of a time-locked clinical correlate, ILPDs appear to be strongly associated with a central EEG localization. This is likely due to cortical irritability in central head regions having greater propensity to manifest with positive, clinically apparent, and time-locked symptoms. Thus, dichotomization of ILPDs and NILPDs on this basis principally reflects differences in underlying anatomical locations of the periodic discharges rather than providing a clinically salient categorization.

Assessment of a quasi-piezoelectric mattress monitor as a detection system for generalized convulsions.

The risk of sudden unexpected death in epilepsy (SUDEP) is highest with nocturnal, unattended generalized convulsions, and basic resuscitation may be able to prevent SUDEP. This study investigates an under-mattress device (ElectroMechanical Film - Emfit®) which is triggered by rhythmic motor activity of a specifiable duration, frequency, and intensity using a quasi-piezoelectric material sensitive to changes in mattress pressure. The device was tested during inpatient video-EEG monitoring. Eighteen GTCSs were recorded, 10 out of wakefulness and 8 out of sleep. Sixteen of the 18 seizures (89%) resulted in Emfit® activation with both false negative alarms occurring during wakefulness. On average, the device was activated within 9 s of onset of bilateral clonic motor movements (range: -37 to +39 s) and occurred, on average, 45 s before seizure end (range: 19 to 76 s). Only 21 false alarms were encountered, all occurring during wakefulness (PPV: 43%). The data suggest that the Emfit® detection device has a high predictive value for generalized convulsions, offers caregivers a reliable and early warning to assist the patient during convulsions, and may be a novel way to prevent SUDEP.

Ictal sensory periodic lateralized epileptiform discharges.

We describe the case of a 74-year-old man with left parietal arteriovenous malformation (AVM) and cerebral white matter radiation necrosis who developed persistent subjective right-sided groin pulsations. The EEG revealed left parietal periodic lateralized epileptiform discharges (PLEDs) time-locked to these sensations, confirming that the patient's symptoms represented sensory seizures with ictal PLEDs as the electrographic correlate. To our knowledge, this is the first reported case of ictal PLEDs manifesting as sensory seizures.

A new method to determine the electrical transfer function of the human thorax.

Traditional analyses have assumed that cardiac electrical activity is reflected on the surface ECG without distortion as the signal passes through the body tissues. This study aims to explore the frequency dependence of thoracic attenuation of surface-recorded intracardiac electrical activity. Twenty patients (14 men, 55 +/- 15 yr of age) undergoing electrophysiological study were enrolled. Rectangular unipolar stimuli were applied from a catheter positioned in the right ventricular apical area and another in the posteroseptal area without contact with the myocardium. An orthogonal Frank-lead surface ECG and a unipolar intracardiac electrogram near the pacing site were recorded. Frequency domain characteristics of the signal-averaged pacing impulses were analyzed. Linear regression analysis showed significant frequency-dependent attenuation in the magnitude transfer functions (R(2) = 0.84-0.89, P < 0.0001) and good linear fit for the phase transfer characteristics (R(2) = 0.98-1.0, P < 0.0001). Age, physical dimension, and respiratory characteristics had significant effects on the magnitude and phase characteristics of the transfer functions. Application of models of the low- and high-slope transfer functions to signal-averaged ECGs from 33 subjects showed differences in the attenuation of P and T waves relative to the QRS.