More Than Spikes: On the Added Value of Non-linear Intracranial EEG Analysis for Surgery Planning in Temporal Lobe Epilepsy

Epilepsy surgery can be a very effective therapy in medication refractory patients. During patient evaluation intracranial EEG is analyzed by clinical experts to identify the brain tissue generating epileptiform events. Quantitative EEG analysis increasingly complements this approach in research settings, but not yet in clinical routine. We investigate the correspondence between epileptiform events and a specific quantitative EEG marker. We analyzed 99 preictal epochs of multichannel intracranial EEG of 40 patients with mixed etiologies. Time and channel of occurrence of epileptiform events (spikes, slow waves, sharp waves, fast oscillations) were annotated by a human expert and non-linear excess interrelations were calculated as a quantitative EEG marker. We assessed whether the visually identified preictal events predicted channels that belonged to the seizure onset zone, that were later resected or that showed strong non-linear interrelations. We also investigated whether the seizure onset zone or the resection were predicted by channels with strong non-linear interrelations. In patients with temporal lobe epilepsy (32 of 40), epileptic spikes and the seizure onset zone predicted the resected brain tissue much better in patients with favorable seizure control after surgery than in unfavorable outcomes. Beyond that, our analysis did not reveal any significant associations with epileptiform EEG events. Specifically, none of the epileptiform event types did predict non-linear interrelations. In contrast, channels with strong non-linear excess EEG interrelations predicted the resected channels better in patients with temporal lobe epilepsy and favorable outcome. Also in the small number of patients with seizure onset in the frontal and parietal lobes, no association between epileptiform events and channels with strong non-linear excess EEG interrelations was detectable. In contrast to patients with temporal seizure onset, EEG channels with strong non-linear excess interrelations did neither predict the seizure onset zone nor the resection of these patients or allow separation between patients with favorable and unfavorable seizure control. Our study indicates that non-linear excess EEG interrelations are not strictly associated with epileptiform events, which are one key concept of current clinical EEG assessment. Rather, they may provide information relevant for surgery planning in temporal lobe epilepsy. Our study suggests to incorporate quantitative EEG analysis in the workup of clinical cases. We make the EEG epochs and expert annotations publicly available in anonymized form to foster similar analyses for other quantitative EEG methods.

An Ensemble Feature Selection Approach to Identify Relevant Features from EEG Signals

Identifying relevant data to support the automatic analysis of electroencephalograms (EEG) has become a challenge. Although there are many proposals to support the diagnosis of neurological pathologies, the current challenge is to improve the reliability of the tools to classify or detect abnormalities. In this study, we used an ensemble feature selection approach to integrate the advantages of several feature selection algorithms to improve the identification of the characteristics with high power of differentiation in the classification of normal and abnormal EEG signals. Discrimination was evaluated using several classifiers, i.e., decision tree, logistic regression, random forest, and Support Vecctor Machine (SVM); furthermore, performance was assessed by accuracy, specificity, and sensitivity metrics. The evaluation results showed that Ensemble Feature Selection (EFS) is a helpful tool to select relevant features from the EEGs. Thus, the stability calculated for the EFS method proposed was almost perfect in most of the cases evaluated. Moreover, the assessed classifiers evidenced that the models improved in performance when trained with the EFS approach’s features. In addition, the classifier of epileptiform events built using the features selected by the EFS method achieved an accuracy, sensitivity, and specificity of 97.64%, 96.78%, and 97.95%, respectively; finally, the stability of the EFS method evidenced a reliable subset of relevant features. Moreover, the accuracy, sensitivity, and specificity of the EEG detector are equal to or greater than the values reported in the literature.

Localized Chemogenetic Silencing of Inhibitory Neurons: A novel Mouse Model of Focal Cortical Seizures

Focal cortical epilepsies are frequently refractory to available anticonvulsant drug therapies. One key factor contributing to this state is the limited availability of animal models that allow to reliably study focal cortical seizures and how they recruit surrounding brain areas in-vivo. In this study, we selectively expressed the inhibitory chemogenetic receptor, hM4D, in GABAergic neurons in focal cortical areas using viral gene transfer. Following focal silencing of GABAergic neurons by administration of Clozapine-N-Oxide (CNO), we demonstrated reliable induction of local epileptiform events in the electroencephalogram (EEG) signal of awake freely moving mice. Experiments in anesthetized mice showed consistent induction of focal seizures in two different brain regions – the barrel cortex (BC) and at the medial prefrontal cortex (mPFC). Seizures were accompanied by high frequency oscillations, a known characteristic of human focal seizures. Seizures propagated, but an analysis of seizure propagation revealed favored propagation pathways. CNO-induced epileptiform events propagated from the BC on one hemisphere to its counterpart and from the BC to the mPFC, but not vice-versa. Lastly, post-CNO epileptiform events in the BC could be triggered by sensory whisker-pad stimulation, indicating that this model, applied to sensory cortices, may be useful to study sensory-evoked seizures. Taken together, our results show that targeted chemogenetic inhibition of GABAergic neurons using hM4D can serve as a novel, versatile and reliable model of focal cortical epilepsy suitable to systematically study cortical ictogenesis in different cortical areas.Significance StatementFocal cortical epilepsies are often hard to alleviate using current anticonvulsant therapies while further drug discovery is impeded by the limited variety of suitable animal models. In this study, we established a novel model of focal cortical seizures induced by spatially-restricted chemogenetic silencing of cortical inhibitory neurons. We have shown this method to be effective at various cortical regions and reliably induce seizures that share key characteristics with known human epilepsy traits, including sensory triggering and seizure propagation. This model may thus be used to advance the discovery of new remedies for focal cortical epilepsies, as well as to improve our understanding of seizure spread along different cortical pathways.

Regulation of epileptiform discharges in rat neocortex by HCN channels

Hyperpolarization-activated, cyclic nucleotide-gated, nonspecific cation (HCN) channels have a well-characterized role in regulation of cellular excitability and network activity. The role of these channels in control of epileptiform discharges is less thoroughly understood. This is especially pertinent given the altered HCN channel expression in epilepsy. We hypothesized that inhibition of HCN channels would enhance bicuculline-induced epileptiform discharges. Whole cell recordings were obtained from layer (L)2/3 and L5 pyramidal neurons and L1 and L5 GABAergic interneurons. In the presence of bicuculline (10 μM), HCN channel inhibition with ZD 7288 (20 μM) significantly increased the magnitude (defined as area) of evoked epileptiform events in both L2/3 and L5 neurons. We recorded activity associated with epileptiform discharges in L1 and L5 interneurons to test the hypothesis that HCN channels regulate excitatory synaptic inputs differently in interneurons versus pyramidal neurons. HCN channel inhibition increased the magnitude of epileptiform events in both L1 and L5 interneurons. The increased magnitude of epileptiform events in both pyramidal cells and interneurons was due to an increase in network activity, since holding cells at depolarized potentials under voltage-clamp conditions to minimize HCN channel opening did not prevent enhancement in the presence of ZD 7288. In neurons recorded with ZD 7288-containing pipettes, bath application of the noninactivating inward cationic current ( Ih) antagonist still produced increases in epileptiform responses. These results show that epileptiform discharges in disinhibited rat neocortex are modulated by HCN channels.