Stimulation based assessment of risk of epileptic transitions in neuronal systems

It has been shown that the analysis of electroencephalographic (EEG) signals submitted to an appropriate external stimulation (active paradigm) is efficient with respect to anticipating epileptic seizures [Kalitzin et al., Electrical brain-stimulation paradigm for estimating the seizure onset site and the time to ictal transition in temporal lobe epilepsy. Clin. Neurophysiol. 116, 718 (2005)]. To better understand how an active paradigm is able to detect proictal states, we performed a simulation study using a computational model of seizure generation in a hippocampal network. Applying the active stimulation methodology we investigated: (1) how changes in model parameters that lead to a transition to a seizure are reflected on the properties of the simulated EEG signals and (2) how the evolution of neuronal excitability towards seizures can be reconstructed from EEG data using an active paradigm. The simulations indicate that a stimulation paradigm combined with appropriate analytical tools may yield information about the change in excitability that precedes a transition to a seizure. Such information is not fully reflected on the on-going EEG activity. These findings give support to the development of active paradigms with the aim of predicting the occurrence of a an epileptic seizure.