Octavian V. Lie

Electromyography-based seizure detector: Preliminary results comparing a generalized tonic-clonic seizure detection algorithm to video-EEG recordings

Automatic detection of generalized tonic–clonic seizures (GTCS) will facilitate patient monitoring and early intervention to prevent comorbidities, recurrent seizures, or death. Brain Sentinel (San Antonio, Texas, USA) developed a seizure‐detection algorithm evaluating surface electromyography (sEMG) signals during GTCS. This study aims to validate the seizure‐detection algorithm using inpatient video–electroencephalography (EEG) monitoring.

Detection of generalized tonic–clonic seizures using surface electromyographic monitoring

A prospective multicenter phase III trial was undertaken to evaluate the performance and tolerability in the epilepsy monitoring unit (EMU) of an investigational wearable surface electromyographic (sEMG) monitoring system for the detection of generalized tonic–clonic seizures (GTCSs).

The N-methyl-d-aspartate receptor in heart development: A gene knockdown model using siRNA

Antagonists of the N-methyl-d-aspartate receptor (NMDAR) may disrupt the development of the cardiac neural crest (CNC) and contribute to conotruncal heart defects. To test this interaction, a loss-of-function model was generated using small interfering RNAs (siRNA) directed against the critical NR1-subunit of this receptor in avian embryos. The coding sequence of the chicken NR1 gene and predicted protein sequences were characterized and found to be homologous with other vertebrate species. Analysis of its spatiotemporal expression demonstrated its expression within the neural tube at pre-migratory CNC sites. siRNA targeted to the NR1-mRNA in pre-migratory CNC lead to a significant decrease in NR1 protein expression. However, embryo survival and heart development were not adversely affected. These results indicate that the CNC may function normally in the absence of functional NMDAR, and that NMDAR antagonists may have a complex impact upon the CNC that transcends impairment of a single receptor type.

Seizure-Onset Mapping Based on Time-Variant Multivariate Functional Connectivity Analysis of High-Dimensional Intracranial EEG: A Kalman Filter Approach

The visual interpretation of intracranial EEG (iEEG) is the standard method used in complex epilepsy surgery cases to map the regions of seizure onset targeted for resection. Still, visual iEEG analysis is labor-intensive and biased due to interpreter dependency. Multivariate parametric functional connectivity measures using adaptive autoregressive (AR) modeling of the iEEG signals based on the Kalman filter algorithm have been used successfully to localize the electrographic seizure onsets. Due to their high computational cost, these methods have been applied to a limited number of iEEG time-series (<60). The aim of this study was to test two Kalman filter implementations, a well-known multivariate adaptive AR model (Arnold et al. 1998) and a simplified, computationally efficient derivation of it, for their potential application to connectivity analysis of high-dimensional (up to 192 channels) iEEG data. When used on simulated seizures together with a multivariate connectivity estimator, the partial directed coherence, the two AR models were compared for their ability to reconstitute the designed seizure signal connections from noisy data. Next, focal seizures from iEEG recordings (73–113 channels) in three patients rendered seizure-free after surgery were mapped with the outdegree, a graph-theory index of outward directed connectivity. Simulation results indicated high levels of mapping accuracy for the two models in the presence of low-to-moderate noise cross-correlation. Accordingly, both AR models correctly mapped the real seizure onset to the resection volume. This study supports the possibility of conducting fully data-driven multivariate connectivity estimations on high-dimensional iEEG datasets using the Kalman filter approach.

Ictal Asystole: An Indication for Pacemaker Implantation and Emerging Cause of Sudden Death

Ictal asystole is being recognized as a potential mechanism of sudden unexplained death in epilepsy (SUDEP). We report a case of a patient without known cardiac disease presenting with ictal asystole resulting in syncope, trauma, and need for pacemaker implantation. The management of ictal asystole is also briefly reviewed. This case is notable for the asystolic episode wholly captured on video‐electroencephalogram/electrocardiogram, the serious risk of trauma and death posed to the patient, and its implications for the mechanism of ictal asystole. This report will alert physicians to the possibility of ictal arrhythmias as a cause of syncope and SUDEP in vulnerable patients. (PACE 2011; 1–4)

Subdural electrode recording of generalized photoepileptic responses

We evaluated the spatiotemporal distribution of photic driving (PDR), photoparoxysmal (PPR), and photoconvulsive (PCR) responses recorded by intracranial electrodes (ic-EEG) in a patient with generalized photosensitivity and right frontal lobe cortical dysplasia. Intermittent light stimulation (ILS) was performed thirteen times in nine days. Cortical responses to ILS recorded by ic-EEG were reviewed and classified as PDRs, PPRs, and PCRs. Photic driving responses were restricted to the occipital lobe at ILS frequencies below 9 Hz, spreading to the parietal and central regions at > 9 Hz. Photoparoxysmal responses commonly presented as focal, medial occipital, and parietal interictal epileptic discharges (IEDs), the latter propagating to the sensorimotor cortices. Generalized IEDs were also generated in the setting of PPRs. Photoconvulsive responses, characterized by repetitive bilateral upper extremity myoclonus sustained until the end of the stimulus, were associated with propagation of the medial parieto-occipital discharge to the primary sensorimotor and supplementary area cortices, while generalized myoclonic seizures were associated with a generalized spike-and-wave discharge with an interhemispheric posterior cingulate onset sparing the sensorimotor cortices. Both types of PCR could occur during the same stimulus. Regardless of the pathway, PCRs only occurred when PDRs involved the parietal cortices. While there may be more than one pathway underlying PCRs, parietal lobe association cortices appear to be critical to their generation.

Influence of Intracranial Electrode Density and Spatial Configuration on Interictal Spike Localization: A Case Study.

Purpose: Poor seizure outcomes after epilepsy surgery often reflect an incorrect localization of the epileptic sources by standard intracranial EEG interpretation because of limited electrode coverage of the epileptogenic zone. This study investigates whether, in such conditions, source modeling is able to provide more accurate source localization than the standard clinical method that can be used prospectively to improve surgical resection planning. Methods: Suboptimal epileptogenic zone sampling is simulated by subsets of the electrode configuration used to record intracranial EEG in a patient rendered seizure free after surgery. sLORETA and the clinical method solutions are applied to interictal spikes sampled with these electrode subsets and are compared for colocalization with the resection volume and displacement due to electrode downsampling. Results: sLORETA provides often congruent and at times more accurate source localization when compared with the standard clinical method. However, with electrode downsampling, individual sLORETA solution locations can vary considerably and shift consistently toward the remaining electrodes. Conclusions: sLORETA application can improve source localization based on the clinical method but does not reliably compensate for suboptimal electrode placement. Incorporating sLORETA solutions based on intracranial EEG in surgical planning should proceed cautiously in cases where electrode repositioning is planned on clinical grounds.

Late-onset temporal lobe epilepsy in a patient with juvenile myoclonic epilepsy

We report a patient with longstanding, severe juvenile myoclonic epilepsy who subsequently developed features of temporal lobe epilepsy, which gradually became clinically dominant. Over the years, there was an electrographic evolution from the typical generalised epileptiform patterns, characteristic of juvenilemyoclonic epilepsy, to the novel appearance of interictal temporal spikes immediately preceding bisynchronous discharges, and subsequently to temporal intermittent rhythmic delta activity and temporal lobe-onset seizures. In this rare case of coexistent primary generalised epilepsy and focal epilepsy, the epileptic networks of the two forms of epilepsy appear to overlap.

Influence of Time-Series Normalization, Number of Nodes, Connectivity and Graph Measure Selection on Seizure-Onset Zone Localization from Intracranial EEG

We investigated the influence of processing steps in the estimation of multivariate directed functional connectivity during seizures recorded with intracranial EEG (iEEG) on seizure-onset zone (SOZ) localization. We studied the effect of (i) the number of nodes, (ii) time-series normalization, (iii) the choice of multivariate time-varying connectivity measure: Adaptive Directed Transfer Function (ADTF) or Adaptive Partial Directed Coherence (APDC) and (iv) graph theory measure: outdegree or shortest path length. First, simulations were performed to quantify the influence of the various processing steps on the accuracy to localize the SOZ. Afterwards, the SOZ was estimated from a 113-electrodes iEEG seizure recording and compared with the resection that rendered the patient seizure-free. The simulations revealed that ADTF is preferred over APDC to localize the SOZ from ictal iEEG recordings. Normalizing the time series before analysis resulted in an increase of 25–35% of correctly localized SOZ, while adding more nodes to the connectivity analysis led to a moderate decrease of 10%, when comparing 128 with 32 input nodes. The real-seizure connectivity estimates localized the SOZ inside the resection area using the ADTF coupled to outdegree or shortest path length. Our study showed that normalizing the time-series is an important pre-processing step, while adding nodes to the analysis did only marginally affect the SOZ localization. The study shows that directed multivariate Granger-based connectivity analysis is feasible with many input nodes (> 100) and that normalization of the time-series before connectivity analysis is preferred.

Seizure onset zone localization from many invasive EEG channels using directed functional connectivity

In this study we investigated how directed functional connectivity can be used to localize the seizure onset zone (SOZ) from ictal intracranial EEG (iEEG) recordings. First, simulations were conducted to investigate the performance of two directed functional connectivity measures, the Adaptive Directed Transfer Function (ADTF) and the Adaptive Partial Directed Coherence (APDC), in combinations with two graph measures, the out-degree and the shortest path, to localize the SOZ. Afterwards the method was applied to the seizure of an epileptic patient, recorded with 113-channel iEEG and localization was compared with the subsequent resection that rendered the patient seizure free. We found both in simulations and in the patient data that the ADTF combined with the out-degree and shortest path resulted in correct SOZ localization. We can conclude that ADTF combined with out-degree or shortest path are most optimal to localize the SOZ from a high number of iEEG channels.