Abnormal phase-amplitude coupling characterizes the interictal state in epilepsy

Objective. Diagnosing epilepsy still requires visual interpretation of electroencephalography (EEG) and magnetoencephalography (MEG) by specialists, which prevents quantification and standardization of diagnosis. Previous studies proposed automated diagnosis by combining various features from EEG and MEG, such as relative power (Power) and functional connectivity (FC). However, the usefulness of interictal phase-amplitude coupling (PAC) in diagnosing epilepsy is still unknown. We hypothesized that resting-state PAC would be different for patients with epilepsy in the interictal state and for healthy participants such that it would improve discrimination between the groups. Approach. We obtained resting-state MEG and magnetic resonance imaging (MRI) in 90 patients with epilepsy during their preoperative evaluation and in 90 healthy participants. We used the cortical currents estimated from MEG and MRI to calculate Power in the delta (1-3 Hz), theta (4-7 Hz), alpha (8-13 Hz), beta (13-30 Hz), low gamma (35-55 Hz), and high gamma (65-90 Hz) bands and FC in the theta band. PAC was evaluated using the synchronization index (SI) for eight frequency band pairs: the phases of delta, theta, alpha, and beta and the amplitudes of low and high gamma. First, we compared the mean SI values for the patients with epilepsy and the healthy participants. Then, using features such as PAC, Power, FC, and features extracted by deep learning (DL) individually or combined, we tested whether PAC improves discrimination accuracy for the two groups. Main results. The mean SI values were significantly different for the patients with epilepsy and the healthy participants. The SI value difference was highest for theta/low gamma in the temporal lobe. Discrimination accuracy was the highest, at 90%, using the combination of PAC and DL. Significance. Abnormal PAC characterized the patients with epilepsy in the interictal state compared with the healthy participants, potentially improving the discrimination of epilepsy.