Propagation of epileptic spikes reconstructed from spatiotemporal magnetoencephalographic and electroencephalographic source analysis

Abstract

The purpose of this study is to assess the accuracy of spatiotemporal source analysis of magnetoencephalography (MEG) and scalp electroencephalography (EEG) for representing the propagation of frontotemporal spikes in patients with partial epilepsy. This study focuses on frontotemporal spikes, which are typically characterized by a preceding anterior temporal peak followed by an ipsilateral inferior frontal peak. Ten patients with frontotemporal spikes on MEG/EEG were studied. We analyzed the propagation of temporal to frontal epileptic spikes on both MEG and EEG independently by using a cortically-constrained minimum norm estimate (MNE). Spatiotemporal source distribution of each spike was obtained on the cortical surface derived from the patient’s MRI. All patients underwent an extraoperative intracranial EEG (IEEG) recording covering temporal and frontal lobes after presurgical evaluation. We extracted source waveforms of MEG and EEG from the source distribution of interictal spikes at the sites corresponding to the location of intracranial electrodes. The time differences of the ipsilateral temporal and frontal peaks as obtained by MEG, EEG and IEEG were statistically compared in each patient. In all patients, MEG and IEEG showed similar time differences between temporal and frontal peaks. The time differences of EEG spikes were significantly smaller than those of IEEG in nine of ten patients. Spatiotemporal analysis of MEG spikes models the time course of frontotemporal spikes as observed on IEEG more adequately than EEG in our patients. Spatiotemporal source analysis may be useful for planning epilepsy surgery, by predicting the pattern of IEEG spikes.

Comparison of Brain Networks During Interictal Oscillations and Spikes on Magnetoencephalography and Intracerebral EEG

“…We have confirmed that interictal spikes can involve widespread networks, in line with previous studies showing that interictal epileptic activities can propagate rapidly in IEEG (Alarcon et al 1994) or in non-invasive electrophysiology (Larsson et al 2010;Tanaka et al 2010). Furthermore, we have shown that this is also the case for epileptic oscillations in the beta/low gamma band.…”

Source Connectivity Analysis from MEG and its Application to Epilepsy Source Localization

“…Common source models for interictal discharges include equivalent current dipoles (ECDs) (He et al 1987; Ebersole 1991) and distributed current dipoles (Shiraishi et al 2005). The distributed source model can be used to identify multiple epileptic sources without a priori specification of the number of sources and reveal interictal discharge propagation that is important for understanding the pathophysiology of epilepsy (Lai et al 2007; Tanaka et al 2010). …”

“…Ossadtchi et al used hidden Markov models to infer propagation patterns between several potential epileptogenic regions identified by automatic methods (Ossadtchi et al 2004) and determined the most likely primary epileptogenic source. Tanaka et al (2010) extracted waveforms from the source distribution of interictal spikes at the sites corresponding to the locations of frequently spiking intracranial electrodes and used the time differences between the peaks to represent the propagation. Lin et al (2009) applied bivariate dynamic Granger causality modeling to study the propagation of epileptic interictal spikes.…”

Multimodal investigation of epileptic networks

“…Nonetheless, studies using DSM advocate for its more extensive use in presurgical workups since it outperformed sECD in at least two comparative studies (Shiraishi et al, 2005;Tanaka et al, 2009). It was also shown that patterns of source activity reconstructed with DSM were good predictors (up to 94%) for subsequent surgical resection (Tanaka et al, 2010).…”