Common dynamics in temporal lobe seizures and absence seizures.

Similarities among the clinical features of complex partial temporal lobe seizures and absence (petit mal) seizures suggest shared underlying mechanisms, but dissimilar electrographic features of the two seizure types have cast doubt on common neuronal substrates. However, visual inspection and traditional approaches to quantitative analysis of the electroencephalogram and electrocorticogram, such as Fourier analysis, may not be appropriate to identify and characterize the highly non-linear mechanisms likely to underlie ictal events. We previously introduced a technique, non-linear autoregressive analysis, that is designed to identify non-linear dynamics in the electroencephalogram [Schiff N. D. et al. (1991) Society of Neuroscience 21st Annual Meeting, 638.6; Schiff N. D. et al. (1995) Biol. Cybern. 72, 519-526, 527-533]. The non-linear autoregressive analysis technique is aimed at describing seizure discharges as a disturbance of synchrony at the level of neuronal circuits. In absence seizures, we showed that non-linear autoregressive analysis revealed a consistent "fingerprint" of these non-linearities in 3/s discharges within and across patients. Here, we investigate the possibility that non-linear autoregressive modeling of seizure records from patients with temporal lobe epilepsy might reveal common circuit mechanisms when compared with the non-linear autoregressive analysis fingerprint of absence seizures. Electrocorticographic records of seizure activity were obtained in four patients who had received subdural grids or strips implanted in preparation for epilepsy surgery. Decomposition of the multichannel data recorded from these patients by principal component analysis revealed that at least three to five independent "generators" were required to model the data from each patient. Non-linear autoregressive analysis of these extracted generators revealed non-linear dynamics in two patients. In both patients, the temporal aspects of these non-linearities were similar to the characteristic non-linearities identified in the non-linear autoregressive analysis fingerprint of absence seizures. In particular, both patients showed a non-linear interaction of signals 90 ms in the past with signals 150 ms in the past. This was the most prominent interaction seen in all patients with absence seizures (typical and atypical). These results suggest that seizures from some patients with temporal lobe epilepsy may share common underlying circuit mechanisms with those of absence seizures. Physiological interpretations of these results are considered and proposed mechanisms are placed into the context of the alterations of consciousness seen in both epilepsies.