Characterization of the hemodynamic modes associated with interictal epileptic activity using a deformable model‐based analysis of combined EEG and functional MRI recordings

Abstract

Simultaneous electroencephalography and functional magnetic resonance imaging (EEG/fMRI) have been proposed to contribute to the definition of the epileptic seizure onset zone. Following interictal epileptiform discharges, one usually assumes a canonical hemodynamic response function (HRF), which has been derived from fMRI studies in healthy subjects. However, recent findings suggest that the hemodynamic properties of the epileptic brain are likely to differ significantly from physiological responses. Here, we propose a simple and robust approach that provides HRFs, defined as a limited set of gamma functions, optimized so as to elicit strong activations after standard model-driven statistical analysis at the single subject level. The method is first validated on healthy subjects using experimental data acquired during motor, visual and memory encoding tasks. Second, interictal EEG/fMRI data measured in 10 patients suffering from epilepsy are analyzed. Results show dramatic changes of activation patterns, depending on whether physiological or pathological assumptions are made on the hemodynamics of the epileptic brain. Our study suggests that one cannot assume a priori that HRFs in epilepsy are similar to the canonical model. This may explain why a significant fraction of EEG/fMRI exams in epileptic patients are inconclusive after standard data processing. The heterogeneous perfusion in epileptic regions indicates that the properties of brain vasculature in epilepsy deserve careful attention.

A personalized history of EEG–fMRI integration

“…For example, positive as well as negative signal changes were found , or extensive ones and such remote to regions which were identified as potential seizure origins by other established diagnostic tools (Gotman, 2008). This motivated another wave of principally methodological studies probing different hemodynamic response functions to epileptic discharges Grouiller et al, 2010;Hawco et al, 2007;Jacobs et al, 2008;Jacobs et al, 2007;Kang et al, 2003;Lemieux et al, 2008;Lu et al, 2006; Evolution of EEG-fMRI acquisition and concepts applied to epilepsy. EEG-fMRI in epilepsy was initially applied to map the area of cortical tissue that generates interictal epileptic discharges (a-d), later this was extended by group studies revealing processes common to epilepsy syndromes (e, f), and recently, an area commonly involved across a variety of focal epilepsies was proposed (g).…”

Modeling of the Neurovascular Coupling in Epileptic Discharges

“…Likewise, in case of epilepsy, some authors reported a linear relationship between discharges and hemodynamic responses (Mirsattari et al 2006), while others showed departures from linearity ). In addition, several puzzling observations of negative BOLD deflections with respect to generalized or focal spikes have been made Salek-Haddadi et al 2006;Gotman et al 2006;Grouiller et al 2010). The spike shape, in particular its late slow wave part, has been proposed to have an impact on the sign of the hemodynamic response .…”

Simultaneous intracranial EEG and fMRI of interictal epileptic discharges in humans

“…IED-related multifocal positive and negative haemodynamic changes have been commonly revealed both distant and local to the presumed epileptic focus Salek-Haddadi, Diehl et al 2006). These findings have raised questions about the behaviour of the networks associated with epileptiform discharges, and in particular how haemodynamic responses are coupled to these events (Logothetis 2008) as the neurovascular coupling could be altered in pathological states such as epilepsy (Hamandi, Laufs et al 2008;Lemieux, Laufs et al 2008;Grouiller, Vercueil et al 2010;Masterton, Harvey et al 2010). Moreover, scalp EEG-fMRI fails to reveal convincing haemodynamic changes in a significant proportion of cases, possibly due to the limited sensitivity of scalp EEG and consequent poor characterisation of the baseline and inefficient modelling of the fMRI signal (Al-Asmi, Benar et al 2003;Salek-Haddadi, Diehl et al 2006).…”