Ictal source analysis: Localization and imaging of causal interactions in humans

Abstract

We propose a new integrative approach to characterize the structure of seizures in the space, time, and frequency domains. Such characterization leads to a new technical development for ictal source analysis for the presurgical evaluation of epilepsy patients. The present new ictal source analysis method consists of three parts. First, a three-dimensional source scanning procedure is performed by a spatio-temporal FINE source localization method to locate the multiple sources responsible for the time evolving ictal rhythms at their onsets. Next, the dynamic behavior of the sources is modeled by a multivariate autoregressive process (MVAR). Lastly, the causal interaction patterns among the sources as a function of frequency are estimated from the MVAR modeling of the source temporal dynamics. The causal interaction patterns indicate the dynamic communications between sources, which are useful to distinguish the primary sources responsible for the ictal onset from the secondary sources caused by the ictal propagation. The present ictal analysis strategy has been applied to a number of seizures from five epilepsy patients, and their results are consistent with observations from either MRI lesions or SPECT scans, which indicate its effectiveness. Each step of the ictal source analysis is statistically evaluated in order to guarantee the confidence in the results.

How to detect the Granger-causal flow direction in the presence of additive noise?

“…using minimum-norm estimates or minimumvariance beamforming. Source reconstruction can be used for EEG/MEG signals prior to computing connectivity measures (Babiloni et al, 2005;Ding et al, 2007;Hui et al, 2010;Gross, 2009, 2014), although spurious correlations can still be abundant after application of source reconstruction (Schoffelen and Gross, 2009). …”

Localization and propagation analysis of ictal source rhythm by electrocorticography

“…The Directional Transfer Function (DTF) approach was used to analyze ictal source propagation. This function is formulated in the framework of the multivariate autoregressive (MVAR) model, and is well described in the literature (Babiloni et al, 2005;Ding et al, 2007;Kamiński and Blinowska, 1991). Accordingly, to the MVAR model, a multivariate process can be described as a data vector S of M source signals, estimated as described in Spatiotemporal source localization, in time: S(t) = (S 1 (t), S 2 (t), …, S M (t)) T .…”

Source localization of ictal epileptic activity investigated by high resolution EEG and validated by SEEG

“…However, there have been few studies concerning ictal source localization (Lantz et al, 2001;Boon et al, 2002;Holmes et al, 2004;Beniczky et al, 2006;Ding et al, 2007). In addition, the relationship between the "irritative" zone (i.e.…”