Analysis of epileptogenic network properties during ictal activity

Abstract

In the present study, we utilize methods from graph theory to analyze epileptogenic network properties during periods of ictal activity. Using these methods, we analyzed the DTF-based causal information flow in nine seizures recorded from two patients undergoing presurgical monitoring for the treatment of medically intractable epilepsy. From the results, we observed a high degree of correlation between the regions with a high amount of information outflow (termed the outdegree) and the cortical areas identified clinically as the generators of the ictal activity. We furthermore observe a frequency-dependent correlation between the co-localization of these "activated regions" and the clinical foci. These findings suggest that application of network analysis tools to ictal activity could provide clinically useful information concerning these epileptogenic networks.

Clinical correlates of graph theory findings in temporal lobe epilepsy

“…10 In a similar study, it was found that the electrode contact with the highest outdegree during effective connectivity analysis of the first twenty seconds of ictal rhythmic icEEG activity in focal epilepsy was consistently among the contacts identified by epileptologists as the ictal onset, and always lay within the resected brain region. 18 …”

“…9 By reducing the complex network structure of the brain into a set of parameters which characterize specific topological properties of the network, it enables the study of individual nodes as well as the network as a whole. 10 Early encouraging findings suggest that conversion of modality specific data to topologic measures by graph theory analysis may improve clinical interpretability. 11 These metrics constitute ideal potential biomarkers due to their easily accessible clinical interpretability in addition to ability in capturing topological aspects of both the brain network and individual regions.…”

Ictal propagation of high frequency activity is recapitulated in interictal recordings: Effective connectivity of epileptogenic networks recorded with intracranial EEG

“…It has been previously shown that the direction of ictal activity propagation is able to provide information regarding localization of the epileptogenic zone, by the simultaneous analysis of multiple EEG channels (Baccala et al, 2004; Franaszczuk and Bergey, 1998; Franaszczuk et al, 1994; Ge et al, 2007; Jung et al, 2011; Lu et al, 2012; Medvedev and Willoughby, 1999; Mullen et al, 2011; van Mierlo et al, 2013; van Mierlo et al, 2011; Varotto et al, 2012b; Wilke et al, 2008; Wilke et al, 2009a, 2010; Wilke et al, 2009b). It was also recently shown that propagation of high frequency activity (>80 Hz) can be observed in the preictal interval (3 sec before the clinically recognized ictal onset) (Adhikari et al, 2013).…”

“…This concept refers to the pattern of causal interactions between the elements of a network (Friston, 1994; Sporns, 2007). Effective connectivity has been investigated using multivariate measures related to Granger causality (Baccala and Sameshima, 2001; Kaminski and Blinowska, 1991; Sameshima and Baccala, 1999) to study the sources of seizure onset, as well as the neural circuitry of epileptogenic brain tissue (Ding et al, 2007; Franaszczuk and Bergey, 1998; Franaszczuk et al, 1994; Ge et al, 2007; Korzeniewska et al, 2012b; Medvedev and Willoughby, 1999; Takahashi et al, 2007; Wilke et al, 2008; Wilke et al, 2010; Wilke et al, 2009b). …”

Neural Synchronization in Seizures

“…Further network characterization of classic MTLE may enable us to better distinguish it from its variants (secondary MTLE or dual pathology [64,65] and other types of epilepsy. In addition, 4 patients and 25 seizures, compared to similar validation studies [49,50,54,66,67], is a relatively comprehensive sample for these types of explorations.…”