• MTLE;
  • Hippocampus;
  • Theta;
  • Background EEG;
  • Quantitative EEG

Summary:  Purpose: Two subtypes of temporal lobe epilepsy (TLE) can be defined through clinical observations and analysis of hippocampal tissue resected during surgical procedures for intractable TLE: (a) mesial temporal sclerosis (MTS), which is characterized by extensive changes to the hippocampus and good surgical outcome; and (b) paradoxical temporal lobe epilepsy (PTLE), which is characterized by minimal cell loss and comparatively poorer surgical outcome. Patients in both subtypes have seizures that appear to begin in the medial temporal lobe, but documented differences in substrate and outcome between these subtypes has defined a need to distinguish MTS and PTLE patients before surgery. This report describes a retrospective study to investigate the feasibility of doing so during intracranial monitoring.

Methods: Background EEG epochs, 5 min in duration, were recorded from the anterior hippocampus in 14 (10 MTS and four PTLE) patients with consistent localization of seizure onset to medial temporal structures. The power spectral density (PSD) of the EEG epochs was calculated by a Fourier spectral estimator, and the total signal power and power of the delta, theta, alpha, beta, and gamma frequency bands were submitted to group-to-group comparison.

Results: Spectral peaks were observed in the delta band in all PSD estimates and in the theta band in nine of 14 (seven MTS, two PTLE) estimates. The MTS and PTLE subtypes could be distinguished by the total signal power and delta band power. These power measurements were greater in the PTLE subtype.

Conclusions: Both delta and theta spectral components are present in hippocampal background EEGs recorded from patients with TLE. The results indicate that group differences exist in spectral measures of background hippocampal signals recorded from MTS and PTLE subtypes. This suggests both that substrate differences in cellular composition and connectivity are reflected in hippocampal background EEGs and that spectral measurements of these signals may hold promise for tests to identify the group membership of individual patients.