Improving the sensitivity of EEG-fMRI studies of epileptic activity by modelling eye blinks, swallowing and other video-EEG detected physiological confounds

Abstract

To improve the sensitivity and specificity of simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) it is prudent to devise modelling strategies explaining the residual variance. The purpose of this study is to investigate the potential value of including additional regressors for physiological activities, derived from video-EEG, in the modelling of haemodynamic patterns linked to interictal epileptiform discharges (IEDs) using simultaneously recorded video-EEG-fMRI. Ten patients with IED (focal epilepsy: 6, idiopathic generalized epilepsy (IGE):4) were studied. BOLD-sensitive fMRI images were acquired on a 3T MRI scanner. 64-channel EEG was recorded using MR-compatible system. A custom made, dual-video-camera system synchronised with EEG was used to record video simultaneously. IEDs and physiological activities were identified and labelled on video-EEG using Brain Analyzer2. fMRI time-series data were pre-processed and analysed using SPM5 software. Two general linear models (GLM) were created; GLM1: IEDs were convolved with the canonical haemodynamic response function and its derivatives. Realignment parameters and pulse regressors were included in the design matrix as confounds, GLM2: GLM1 and additional regressors identified on video-EEG including: eye blinks, hand or foot movement, chewing and swallowing were also included in the design matrix. SPM [F] maps (p<0.05, corrected for family wise error and p<0.001, uncorrected) were generated for both models. We compared the resulting blood oxygen level dependent (BOLD) maps for cluster size, statistical significance and degree of concordance with the irritative zone. BOLD changes relating to physiological activities were generally seen in expected brain areas. In patients with focal epilepsy, the extent and Z-score of the IED-related global maximum BOLD clusters increased in 4/6 patients and additional IED-related BOLD clusters were observed in 3/6 patients for GLM2. Also, the degree of concordance of IED-related maps with irritative zone improved for one patient for GLM2 and was unchanged for the other cases. In patients with IGE, the size and statistical significance for global maximum and other BOLD clusters increased in 2/4 patients. We conclude that the inclusion of additional regressors, derived from video based information, in the design matrix explains a greater amount of variance and can reveal additional IED-related BOLD clusters which may be part of the epileptic networks.