Altered adult neurogenesis and gliogenesis in patients with mesial temporal lobe epilepsy.

The hippocampus is the most common seizure focus in people. In the hippocampus, aberrant neurogenesis plays a critical role in the initiation and progression of epilepsy in rodent models, but it is unknown whether this also holds true in humans. To address this question, we used immunofluorescence on control healthy hippocampus and surgical resections from mesial temporal lobe epilepsy (MTLE), plus neural stem-cell cultures and multi-electrode recordings of ex vivo hippocampal slices. We found that a longer duration of epilepsy is associated with a sharp decline in neuronal production and persistent numbers in astrogenesis. Further, immature neurons in MTLE are mostly inactive, and are not observed in cases with local epileptiform-like activity. However, immature astroglia are present in every MTLE case and their location and activity are dependent on epileptiform-like activity. Immature astroglia, rather than newborn neurons, therefore represent a potential target to continually modulate adult human neuronal hyperactivity.

A sparse multiscale nonlinear autoregressive model for seizure prediction.

Objectives.Accurate seizure prediction is highly desirable for medical interventions such as responsive electrical stimulation. We aim to develop a classification model that can predict seizures by identifying preictal states, i.e. the precursor of a seizure, based on multi-channel intracranial electroencephalography (iEEG) signals.Approach.A two-level sparse multiscale classification model was developed to classify interictal and preictal states from iEEG data. In the first level, short time-scale linear dynamical features were extracted as autoregressive (AR) model coefficients; arbitrary (usually long) time-scale linear and nonlinear dynamical features were extracted as Laguerre-Volterra AR model coefficients; root-mean-square error of model prediction was used as a feature representing model unpredictability. In the second level, all features were fed into a sparse classifier to discriminate the iEEG data between interictal and preictal states.Main results. The two-level model can accurately classify seizure states using iEEG data recorded from ten canine and human subjects. Adding arbitrary (usually long) time-scale and nonlinear features significantly improves model performance compared with the conventional AR modeling approach. There is a high degree of variability in the types of features contributing to seizure prediction across different subjects.Significance. This study suggests that seizure generation may involve distinct linear/nonlinear dynamical processes caused by different underlying neurobiological mechanisms. It is necessary to build patient-specific classification models with a wide range of dynamical features.

An in vitro seizure model from human hippocampal slices using multi-electrode arrays.

Temporal lobe epilepsy is a neurological condition marked by seizures, typically accompanied by large amplitude synchronous electrophysiological discharges, affecting a variety of mental and physical functions. The neurobiological mechanisms responsible for the onset and termination of seizures are still unclear. While pharmacological therapies can suppress the symptoms of seizures, typically 30% of patients do not respond well to drug control. Unilateral temporal lobectomy, a procedure in which a substantial part of the hippocampal formation and surrounding tissue is removed, is a common surgical treatment for medically refractory epilepsy. In this study, we have developed an in vitro model of epilepsy using human hippocampal slices resected from patients suffering from intractable mesial temporal lobe epilepsy. We show that using a planar multi-electrode array system, spatio-temporal inter-ictal like activity can be consistently recorded in high-potassium (8 mM), low-magnesium (0.25 mM) artificial cerebral spinal fluid with 4-aminopyridine (100 µM) added. The induced epileptiform discharges can be recorded in different subregions of the hippocampus, including dentate, CA1 and subiculum. This new paradigm will allow the study of seizure generation in different subregions of hippocampus simultaneously, as well as propagation of seizure activity throughout the intrinsic circuitry of hippocampus. This experimental model also should provide insights into seizure control and prevention, while providing a platform to develop novel, anti-seizure therapeutics.

Spatio-temporal inter-ictal activity recorded from human epileptic hippocampal slices.

Epilepsy is a medical syndrome that produces seizures affecting a variety of mental and physical functions. The actual mechanisms of the onset and termination of the seizure are still unclear. While medical therapies can suppress the symptoms of seizures, 30% of patients do not respond well. Temporal lobectomy is a common surgical treatment for medically refractory epilepsy. Part of the hippocampus is removed from the patient. In this study, we have developed an in vitro epileptic model in human hippocampal slices resected from patients suffering from intractable mesial temporal lobe epilepsy. Using a planar multielectrode array system, spatio-temporal inter-ictal activity can be consistently recorded in high-potassium (8 mM), low-magnesium (0.25 mM) aCSF with additional 100 µM 4-aminopyridine. The induced inter-ictal activity can be recorded in different regions including dentate, CA1 and Subiculum. We hope the experimental model built in this study will help us understand more about seizure generation, as well as providing insights into prevention and novel therapeutics.