Identification of critical areas in presurgical evaluations of patients with temporal lobe epilepsy is the most important step prior to resection. According to the “epileptic focus model”, localization of seizure onset zones is the main task to be accomplished. Nevertheless, a significant minority of epileptic patients continue to experience seizures after surgery (even when the focus is correctly located), an observation that is difficult to explain under this approach. However, if attention is shifted from a specific cortical location toward the network properties themselves, then the epileptic network model does allow us to explain unsuccessful surgical outcomes. The intraoperative electrocorticography records of 20 patients with temporal lobe epilepsy were analyzed in search of interictal synchronization clusters. Synchronization was analyzed, and the stability of highly synchronized areas was quantified. Surrogate data were constructed and used to statistically validate the results. Our results show the existence of highly localized and stable synchronization areas in both the lateral and the mesial areas of the temporal lobe ipsilateral to the clinical seizures. Synchronization areas seem to play a central role in the capacity of the epileptic network to generate clinical seizures. Resection of stable synchronization areas is associated with elimination of seizures; nonresection of synchronization clusters is associated with the persistence of seizures after surgery. We suggest that synchronization clusters and their stability play a central role in the epileptic network, favoring seizure onset and propagation. We further speculate that the stability distribution of these synchronization areas would differentiate normal from pathologic cases.

The current practice under which patients with refractory epilepsy are surgically treated is based mainly on the identification of specific cortical areas, mainly the epileptogenic zone, which is believed to be responsible for generation of seizures. A better understanding of the whole epileptic network and its components and properties is required before more effective and less invasive therapies can be developed. The aim of the present study was to partially characterize the evolution of the functional network during the preictal-ictal transition in partial seizures in patients with temporal lobe epilepsy (TLE). Scalp and foramen ovale (FOE) recordings from twenty-two TLE patients were analyzed under the complex network perspective. The density of links, average path length, average clustering coefficient, and modularity were calculated during the preictal and the ictal stages. Both linear–Pearson correlation–and non-linear–phase synchronization–measures were used as proxies of functional connectivity between the electrode locations areas. The transition from one stage to the other was evaluated in the whole network and in the mesial sub-networks. The results were compared with a voltage-dependent measure, namely, the spectral entropy. Changes in the global functional network during the transition from the preictal to the ictal stage show, in the linear case, that in sixteen cases (72.7%) the density of the links increased during the seizure, with a decrease in the average path length in fifteen cases (68.1%). There was also a preictal and ictal imbalance in functional connectivity during both stages (77.2% to 86.3%). The SE dropped during the seizure in 95.4% of the cases, but did not show any tendency towards lateralization. When using the nonlinear measure of functional connectivity, the phase synchronization, similar results were obtained. In TLE patients, the transition to the ictal stage is accompanied by increasing global synchronization and a more ordered spectral content of the signals, indicated by lower spectral entropy. The interictal connectivity imbalance (lower ipsilateral connectivity) is sustained during the seizure, irrespective of any appreciable imbalance in the spectral entropy of the mesial recordings.

The postictal period is characterized by several neurological alterations, but its exact limits are clinically or even electroencephalographically hard to determine in most cases. We aim to provide quantitative functions or conditions with a clearly distinguishable behavior during the ictal-postictal transition. Spectral methods were used to analyze foramen ovale electrodes (FOE) recordings during the ictal/postictal transition in 31 seizures of 15 patients with strictly unilateral drug resistant temporal lobe epilepsy. In particular, density of links, spectral entropy, and relative spectral power were analyzed. Partial simple seizures are accompanied by an ipsilateral increase in the relative Delta power and a decrease in synchronization in a 66% and 91% of the cases, respectively, after seizures offset. Complex partial seizures showed a decrease in the spectral entropy in 94% of cases, both ipsilateral and contralateral sides (100% and 73%, respectively) mainly due to an increase of relative Delta activity. Seizure offset is defined as the moment at which the “seizure termination mechanisms” actually end, which is quantified in the spectral entropy value. We propose as a definition for the postictal start the time when the ipsilateral SE reaches the first global minimum.

Objective: Interictal synchronization clusters have recently been described in several publications using diverse techniques, including neurophysiological recordings and fMRI, in patients suffering from epilepsy. However, little is known about the role of these hyper-synchronous areas during seizures. In this work, we report an analysis of synchronization clusters jointly with several network measures during seizure activity; we then discuss our findings in the context of prior literature. Methods: Subdural activity was recorded by electrocorticography (with sixty electrodes placed at temporal and parietal lobe locations) in a patient with temporal lobe epilepsy with partial seizures with and without secondary generalization. Both interictal and ictal activities (during four seizures) were investigated and characterized using local synchronization and complex network methodology. The modularity, density of links, average clustering coefficient and average path lengths were calculated to obtain information about the dynamics of the global network. Functional connectivity changes during the seizures were compared with the time-evolution of highly synchronized areas. Results: Our findings reveal temporal changes in local synchronization areas during seizures and a tight relationship between the cortical locations of these areas and the patterns of their evolution over time. Seizure evolution and secondary generalization appear to be driven by two different underlying mechanisms.