Summary: Epileptogenic networks are defined by the brain regions involved in the production and propagation of epileptic activities. In this review we describe the historical, methodologic, and conceptual bases of this model in the analysis of electrophysiologic intracerebral recordings. In the context of epilepsy surgery, the determination of cerebral regions producing seizures (i.e., the “epileptogenic zone”) is a crucial objective. In contrast with a traditional focal vision of focal drug‐resistant epilepsies, the concept of epileptogenic networks has been progressively introduced as a model better able to describe the complexity of seizure dynamics and realistically describe the distribution of epileptogenic anomalies in the brain. The concept of epileptogenic networks is historically linked to the development of the stereoelectroencephalography (SEEG) method and subsequent introduction of means of quantifying the recorded signals. Seizures, and preictal and interictal discharges produce clear patterns on SEEG. These patterns can be analyzed utilizing signal analysis methods that quantify high‐frequency oscillations or changes in functional connectivity. Dramatic changes in SEEG brain connectivity can be described during seizure genesis and propagation within cortical and subcortical regions, associated with the production of different patterns of seizure semiology. The interictal state is characterized by networks generating abnormal activities (interictal spikes) and also by modified functional properties. The introduction of novel approaches to large‐scale modeling of these networks offers new methods in the goal of better predicting the effects of epilepsy surgery. The epileptogenic network concept is a key factor in identifying the anatomic distribution of the epileptogenic process, which is particularly important in the context of epilepsy surgery.

The identification of brain regions generating seizures (‘epileptogenic zone’, EZ) in patients with refractory partial epilepsy is crucial prior to surgery. During pre-surgical evaluation, this identification can be performed from the analysis of intracerebral EEG. In particular, the presence of high-frequency oscillations, often referred to as ‘rapid discharges’, has long been recognized as a characteristic electrophysiological pattern of the EZ. However, to date, there has been no attempt to make use of this specific pattern to quantitatively evaluate the degree of epileptogenicity in recorded structures. A novel quantitative measure that characterizes the epileptogenicity of brain structures recorded with depth electrodes is presented. This measure, called ‘Epileptogenicity Index’ (EI), is based on both spectral (appearance of fast oscillations replacing the background activity) and temporal (delay of appearance with respect to seizure onset) properties of intracerebral EEG signals. EI values were computed in mesial and lateral structures of the temporal lobe in a group of 17 patients with mesial temporal lobe epilepsy (MTLE). Statistically high EI values corresponded to structures involved early in the ictal process and producing rapid discharges at seizure onset. In all patients, these high values were obtained in more than one structure of the temporal lobe region. In the majority of patients, highest EI values were computed from signals recorded in mesial structures. In addition, when averaged over patients, EI values gradually decreased from structure to structure. For lateral neocortex, higher EI values were found in patients with normal MRI, in contrast with patients with hippocampal sclerosis. In this former sub-group of patients, a greater number of epileptogenic structures was also found. A statistically significant correlation was found between the duration of epilepsy and the number of structures disclosing high epileptogenicity suggesting that MTLE is a gradually evolving process in which the epileptogenicity of the temporal lobe tends to increase with time.

The EEG activity of the thalamus and temporal lobe structures (hippocampus, entorhinal cortex and neocortex) was obtained using intracerebral recordings (stereoelectroencephalography, SEEG) performed in patients with TLE seizures undergoing pre-surgical evaluation. Synchrony was studied using a statistical measure of SEEG signal interdependencies (non-linear correlation). The results demonstrated an overall increase of synchrony between the thalamus and temporal lobe structures during seizures. Moreover, although there was great inter-individual variability, we found that values from seizure onset period were significantly higher than values from the background period (P = 0.001). Values at the end of seizure were significantly higher than values from the seizure onset (P < 0.0001). Several indices were also defined in order to correlate some clinical features to the degree of coupling between cortical structures and the thalamus. In patients with mesial TLE seizures, a correlation was found between the degree of thalamocortical synchrony and the presence of an early loss of consciousness but not with other clinical parameters. In addition, surgical prognosis seemed better in patients with low values of thalamocortical couplings at the seizure onset. This report demonstrates that the thalamus and remote cortical structures synchronize their activity during TLE seizures and suggest that the extension of the epileptogenic network to the thalamus is a potential important factor determining surgical prognosis.