Electrical stimulation for cortical mapping reduces the density of high frequency oscillations

Anticonvulsant Effect of Carbenoxolone on Chronic Epileptic Rats and Its Mechanism Related to Connexin and High-Frequency Oscillations

Objective

This study was designed to investigate the influence and mechanism of gap junction carbenoxolone (CBX) on dynamic changes in the spectral power of ripples and fast ripples (FRs) in the hippocampus of chronic epileptic rats.

Methods

The lithium-pilocarpine (PILO) status epilepticus (SE) model (PILO group) and the CBX pretreatment model (CBX + PILO group) were established to analyze dynamic changes in the spectral power of ripples and FRs, and the dynamic expression of connexin (CX)26, CX32, CX36, and CX43 in the hippocampus of chronic epileptic rats.

Results

Within 28 days after SE, the number of spontaneous recurrent seizures (SRSs) in the PILO group was significantly higher than that in the CBX + PILO group. The average spectral power of FRs in the PILO group was significantly higher than the baseline level at 1 and 7 days after SE. The average spectral power of FRs in the PILO group was significantly higher than that in the CBX + PILO group at 1, 7, and 14 days after SE. Seizures induced an increase in CX43 expression at 1 and 7 days after SE, but had no significant effect on CX26, CX36, or CX32. CBX pretreatment did not affect the expression of CXs in the hippocampus of normal rats, but it inhibited the expression of CX43 in epileptic rats. The number of SRSs at 2 and 4 weeks after SE had the highest correlation with the average spectral power of FRs; the average spectral power of FRs was moderately correlated with the expression of CX43.

Conclusion

The results of this study indicate that the energy of FRs may be regulated by its interference with the expression of CX43, and thus, affect seizures. Blocking the expression of CX43 thereby reduces the formation of pathological high-frequency oscillations (HFOs), making it a promising strategy for the treatment of chronic epilepsy.

Distinction of Physiologic and Epileptic Ripples: An Electrical Stimulation Study

Ripple oscillations (80-250 Hz) are a promising biomarker of epileptic activity, but are also involved in memory consolidation, which impairs their value as a diagnostic tool. Distinguishing physiologic from epileptic ripples has been particularly challenging because usually, invasive recordings are only performed in patients with refractory epilepsy. Here, we identified 'healthy' brain areas based on electrical stimulation and hypothesized that these regions specifically generate 'pure' ripples not coupled to spikes. Intracranial electroencephalography (EEG) recorded with subdural grid electrodes was retrospectively analyzed in 19 patients with drug-resistant focal epilepsy. Interictal spikes and ripples were automatically detected in slow-wave sleep using the publicly available Delphos software. We found that rates of spikes, ripples and ripples coupled to spikes ('spike-ripples') were higher inside the seizure-onset zone (p < 0.001). A comparison of receiver operating characteristic curves revealed that spike-ripples slightly delineated the seizure-onset zone channels, but did this significantly better than spikes (p < 0.001). Ripples were more frequent in the eloquent neocortex than in the remaining non-seizure onset zone areas (p < 0.001). This was due to the higher rates of 'pure' ripples (p < 0.001; median rates 3.3/min vs. 1.4/min), whereas spike-ripple rates were not significantly different (p = 0.87). 'Pure' ripples identified 'healthy' channels significantly better than chance (p < 0.001). Our findings suggest that, in contrast to epileptic spike-ripples, 'pure' ripples are mainly physiological. They may be considered, in addition to electrical stimulation, to delineate eloquent cortex in pre-surgical patients. Since we applied open source software for detection, our approach may be generally suited to tackle a variety of research questions in epilepsy and cognitive science.

Electrical cortical stimulations modulate spike and post-spike slow-related high-frequency activities in human epileptic foci

OBJECTIVE

Using interictal epileptiform discharges (IEDs), consisting of spikes and post-spike slow waves (PSSs), and IED-related high-frequency activities (HFAs), we elucidated inhibitory effects of electrical cortical stimulation (ECS) on human epileptic foci.

METHODS

We recruited 8 patients with intractable focal epilepsy, and 50-Hz ECS was applied to the seizure-onset zone (SOZ) and non-SOZ. Before (5-min) and after (20-min) ECS, we evaluated the number of IED, the amplitudes of spikes and PSSs, spike-related HFA power, and PSS-related low gamma (30-50 Hz) activities.

RESULTS

SOZ stimulation significantly decreased the number of IEDs and amplitude of spikes. Spike-related HFA power values in fast ripple (200-300 Hz) and ripple (80-150 Hz) bands were significantly suppressed only by SOZ stimulation in 4 and 3 patients, respectively. Among 4 patients with discrete PSSs, the amplitude ratio of spike/PSS decreased and the PSS-related low gamma activity power increased significantly in 2 patients and marginally in 1 patient.

CONCLUSIONS

ECS potentially modulates cortical excitability by reducing excitation and increasing inhibition, and monitoring IED-related HFAs may help achieve the optimal effects of ECS.

SIGNIFICANCE

IED and IED-related HFAs are dynamic, potential surrogate markers for epileptic excitability during the interictal period.

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 Simple Statistical Method for the Automatic Detection of Ripples in Human Intracranial EEG

High frequency oscillations (HFOs) are a promising biomarker of epileptic tissue, but detection of these electrographic events remains a challenge. Automatic detectors show encouraging results, but they typically require optimization of multiple parameters, which is a barrier to good performance and broad applicability. We therefore propose a new automatic HFO detection algorithm, focusing on simplicity and ease of implementation. It requires tuning of only an amplitude threshold, which can be determined by an iterative process or directly calculated from statistics of the rectified filtered data (i.e. mean plus standard deviation). The iterative approach uses an estimate of the amplitude probability distribution of the background activity to calculate the optimum threshold for identification of transient high amplitude events. We tested both the iterative and non-iterative approaches using a dataset of visually marked HFOs, and we compared the performance to a commonly used detector based on the root-mean-square. When the threshold was optimized for individual channels via ROC curve, all three methods were comparable. The iterative detector achieved a sensitivity of 99.6%, false positive rate (FPR) of 1.1%, and false detection rate (FDR) of 37.3%. However, in an eight-fold cross-validation test, the iterative method had better sensitivity than the other two methods (80.0% compared to 64.4 and 65.8%), with FPR and FDR of 1.3, and 49.4%, respectively. The simplicity of this algorithm, with only a single parameter, will enable consistent application of automatic detection across research centers and recording modalities, and it may therefore be a powerful tool for the assessment and localization of epileptic activity.

Oscillatory Activities in Neurological Disorders of Elderly: Biomarkers to Target for Neuromodulation

Non-invasive brain stimulation (NIBS) has been under investigation as adjunct treatment of various neurological disorders with variable success. One challenge is the limited knowledge on what would be effective neuronal targets for an intervention, combined with limited knowledge on the neuronal mechanisms of NIBS. Motivated on the one hand by recent evidence that oscillatory activities in neural systems play a role in orchestrating brain functions and dysfunctions, in particular those of neurological disorders specific of elderly patients, and on the other hand that NIBS techniques may be used to interact with these brain oscillations in a controlled way, we here explore the potential of modulating brain oscillations as an effective strategy for clinical NIBS interventions. We first review the evidence for abnormal oscillatory profiles to be associated with a range of neurological disorders of elderly (e.g., Parkinson's disease (PD), Alzheimer's disease (AD), stroke, epilepsy), and for these signals of abnormal network activity to normalize with treatment, and/or to be predictive of disease progression or recovery. We then ask the question to what extent existing NIBS protocols have been tailored to interact with these oscillations and possibly associated dysfunctions. Our review shows that, despite evidence for both reliable neurophysiological markers of specific oscillatory dis-functionalities in neurological disorders and NIBS protocols potentially able to interact with them, there are few applications of NIBS aiming to explore clinical outcomes of this interaction. Our review article aims to point out oscillatory markers of neurological, which are also suitable targets for modification by NIBS, in order to facilitate in future studies the matching of technical application to clinical targets.

Evoked versus spontaneous high frequency oscillations in the chronic electrocorticogram in focal epilepsy

OBJECTIVE

Spontaneous high frequency oscillations (HFOs; ripples 80-250Hz, fast ripples (FRs) 250-500Hz) are biomarkers for epileptogenic tissue in focal epilepsy. Single pulse electrical stimulation (SPES) can evoke HFOs. We hypothesized that stimulation distinguishes pathological from physiological ripples and compared the occurrence of evoked and spontaneous HFOs within the seizure onset zone (SOZ) and eloquent functional areas.

METHODS

Ten patients underwent SPES during 2048Hz electrocorticography (ECoG). Evoked HFOs in time-frequency plots and spontaneous HFOs were visually analyzed. We compared electrodes with evoked and spontaneous HFOs for: percentages in the SOZ, sensitivity and specificity for the SOZ, percentages in functional areas outside the SOZ.

RESULTS

Two patients without spontaneous FRs showed evoked FRs in the SOZ. Percentages of evoked and spontaneous HFOs in the SOZ were similar (ripples 32:33%, p=0.77; FRs 43:48%, p=0.63), but evoked HFOs had generally a lower specificity (ripples 45:69%, p=0.02; FRs 83:92%, p=0.04) and higher sensitivity (ripples 85:70%, p=0.27; FRs 52:37%, p=0.05). More electrodes with evoked than spontaneous ripples were found in functional (54:30%, p=0.03) and 'silent' areas (57:27%, p=0.01) outside the SOZ.

CONCLUSIONS

SPES can elicit SOZ-specific FRs in patients without spontaneous FRs, but activates ripples in all areas.

SIGNIFICANCE

SPES is an alternative for waiting for spontaneous HFOs, but does not warrant exclusively pathological ripples.

Optogenetic Approaches for Controlling Seizure Activity

Optogenetics, a technique that utilizes light-sensitive ion channels or pumps to activate or inhibit neurons, has allowed scientists unprecedented precision and control for manipulating neuronal activity. With the clinical need to develop more precise and effective therapies for patients with drug-resistant epilepsy, these tools have recently been explored as a novel treatment for halting seizure activity in various animal models. In this review, we provide a detailed and current summary of these optogenetic approaches and provide a perspective on their future clinical application as a potential neuromodulatory therapy.

The Influence of Vagus Nerve and Spinal Cord Stimulation on the Ictal Fast Ripple Activity in a Spike-and-Wave Rat Model of Seizures

OBJECTIVES

Fast ripple (FR) activity has received increasing attention as a potential epileptic marker. The current knowledge on how neurostimulation affects FRs is, however, very limited. In this study, we assess the influence of the vagus nerve stimulation (VNS) and spinal cord stimulation (SCS) frequency on ictal FRs associated with spike-and-wave (SW) seizures.

METHODS

SW discharges were induced and maintained by an infusion of pentylenetetrazol in rat. During ongoing SW seizures, SCS was conducted at 30, 80, 130, and 180 Hz and VNS at 10, 30, 80, 130, and 180 Hz. The FRs were derived from intracortical recordings and the FR rate was used for quantifying the level of FR activity.

RESULTS

The FR rate was significantly correlated (r = 0.81) with the level of total pentylenetetrazol dose. Compared with no stimulation intervals, SCS conducted at 80, 130, and 180 Hz significantly reduced the normalized FR rate by 24, 38, and 44%, respectively. Similarly, VNS conducted at 30, 80, 130, and 180 Hz significantly reduced the normalized FR rate by 23, 40, 61, and 65%, respectively.

CONCLUSIONS

In the present model of sustained SW seizures, the FR rate was proportional with the severity of the SW seizures. Both SCS and VNS attenuated the FR rate and this attenuation was consistently strongest at the higher stimulation frequencies. Our results suggest that SCS may induce some of the same antiepileptic effects as VNS.