Elsevier

NeuroImage

Volume 101, 1 November 2014, Pages 96-113
NeuroImage

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

https://doi.org/10.1016/j.neuroimage.2014.06.078Get rights and content

Highlights

  • High frequency activity propagation identifies the seizure onset zone.

  • Patterns of propagation during seizures are recapitulated in interictal recordings.

  • Patterns of propagation differ for seizures with focal vs. regional onset

  • Epilepsy is associated with divergent/convergent architecture of cortical networks.

Abstract

Seizures are increasingly understood to arise from epileptogenic networks across which ictal activity is propagated and sustained. In patients undergoing invasive monitoring for epilepsy surgery, high frequency oscillations have been observed within the seizure onset zone during both ictal and interictal intervals. We hypothesized that the patterns by which high frequency activity is propagated would help elucidate epileptogenic networks and thereby identify network nodes relevant for surgical planning. Intracranial EEG recordings were analyzed with a multivariate autoregressive modeling technique (short-time direct directed transfer function—SdDTF), based on the concept of Granger causality, to estimate the directionality and intensity of propagation of high frequency activity (70–175 Hz) during ictal and interictal recordings. These analyses revealed prominent divergence and convergence of high frequency activity propagation at sites identified by epileptologists as part of the ictal onset zone. In contrast, relatively little propagation of this activity was observed among the other analyzed sites. This pattern was observed in both subdural and depth electrode recordings of patients with focal ictal onset, but not in patients with a widely distributed ictal onset. In patients with focal ictal onsets, the patterns of propagation recorded during pre-ictal (up to 5 min immediately preceding ictal onset) and interictal (more than 24 h before and after seizures) intervals were very similar to those recorded during seizures. The ability to characterize epileptogenic networks from interictal recordings could have important clinical implications for epilepsy surgery planning by reducing the need for prolonged invasive monitoring to record spontaneous seizures.

Introduction

Recent studies provide growing evidence that epileptogenic networks, rather than a single focal source, contribute to the generation of the ictal state (van Diessen et al., 2013), and that epileptic networks are complex and heterogeneous (Bower et al., 2012). It has been suggested that organization of a neural network in which the “epileptogenic zone” would carry higher “connection weights” than other parts of the network, such as the “irritative zone” or the “symptomatogenic zone” may underlie focal epilepsy and that the variability of seizures, may be due to a variation in the location of the seizure onsets within the larger network (Nair et al., 2004). With the concept of an epileptogenic network, an epileptogenic zone may be defined as a strongly connected network node (or hub), and its successful removal may result in degradation of network activity (Frei et al., 2010). Several studies have demonstrated that network nodes may be identified by network connectivity measures, and that these nodes correspond with the location of resected cortical regions in patients who were seizure-free following surgical intervention (Morgan and Soltesz, 2008, Ortega et al., 2008, Wilke et al., 2011). If accurately identified, disruption or inhibition of these epileptogenic network nodes may be used for prevention or termination of seizures without the need for removal of the entire network, which in turn could lead to more effective medical treatment and better post-treatment outcomes.

Connectivity characteristics of epileptic networks have been found to be frequency-dependent, with high frequency activity most closely correlated with improved postsurgical outcome (Wilke et al., 2011). The role of high frequency activity—HFA (Jiruska and Bragin, 2011, Jiruska et al., 2010, Jouny et al., 2007b, Rodin et al., 2009) or high frequency oscillations—HFOs (Worrell et al., 2004, Worrell et al., 2008) in epilepsy has been extensively investigated recently, and has been reported to be temporally and spatially correlated to the seizure onset zone. During ictal recordings, HFOs were recently observed mostly in the region of seizure onset, and less frequently in areas of secondary spread (Jirsch et al., 2006). The rates and durations of HFOs were significantly higher in the seizure onset zone than outside of it. Moreover, resection of brain regions sampled by intracranial electrodes that recorded ictal HFOs was associated with postsurgical seizure-free outcomes (Fujiwara et al., 2012, Jacobs et al., 2010, Jacobs et al., 2012, Modur et al., 2011, Nariai et al., 2011b, Ochi et al., 2007, Zijlmans et al., 2012).

Furthermore, recent studies suggest that epileptogenic networks exhibit aberrant dynamics not only at the time of seizure onset, but also during interictal seizure-free periods (Bragin et al., 2010, Monto et al., 2007, Zijlmans et al., 2011), and that interictal high frequency activity can also be used to identify the ictal onset zone (Brazdil et al., 2010, Jacobs et al., 2009, Zijlmans et al., 2009). Interictal activity has been shown to have pathologically strong intrinsic correlations (Monto et al., 2007), and strong coupling in high frequencies (Wilke et al., 2011) among signals recorded near the epileptogenic zone. It has also been shown that despite the apparent discrete localization of the ictal onset zone, epileptic brain networks differ in their global characteristics from non-epileptic brain networks (Horstmann et al., 2010).

Although, high frequency activity appears to be linked to epileptogenesis (Firpi et al., 2007, Jacobs et al., 2008, Rampp and Stefan, 2006, Worrell et al., 2008), its role in seizure generation may depend to a large extent on how it is propagated among sites in cortical networks. Effective connectivity is a particularly promising conceptual framework for understanding this propagation. 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., 2009b, Wilke et al., 2010).

Mapping the propagation of high frequency ictal and interictal activity may provide an important means of defining epileptic networks, in turn contributing crucial information for the selection of brain regions for resective surgery. In particular, understanding of the functional architecture of epileptogenic networks may allow for selective disruption or modulation of key components (nodes or hubs) of these networks to halt seizures without removing the entire network. This approach could potentially improve post-operative seizure control and help prevent post-operative functional deficits. Moreover, if this approach consistently shows a high correspondence between interictal and ictal patterns of effective connectivity, it may be possible to use interictal recordings alone to estimate the epileptogenic zone in patients that would otherwise not be surgery candidates because ictal recordings could not be captured during intracranial monitoring. Finally, this could also reduce the length of stay and the risk of surgical morbidity.

Section snippets

Participants

Data were obtained from six epilepsy patients (3 M, 3 F, ages 14–50 years, two admissions for Patient #1) with medically resistant partial onset seizures who required implantation of intracranial electrodes for epilepsy surgery planning. The exact placement of electrodes was dictated by clinical necessity alone. The study was approved by the Johns Hopkins Medicine Institutional Review Board, conforming to relevant regulatory standards. Patients were selected with a broad spectrum of seizure

High and lower frequency ictal activity vs. seizure onset zone

High frequency ictal activity (70–175 Hz) was observed within the ictal onset zone and its vicinity, while the lower frequency ictal activity (0–40 Hz) occurred more broadly (as identified by matching pursuit (MP) analysis, and statistically compared to the preictal interval). In some cases, e.g. Patient #1 and Patient #2, prominent increases in energy of the lower frequency ictal activity were observed at all recorded sites, while increases in energy of the high frequency component of ictal

High frequency connectivity among epileptogenic networks

In acquired epilepsies, structural or metabolic disturbances are believed to reorganize neuronal circuitry in a manner that enhances synchronization (Engel, 2012). The intrinsic organization of local cortical circuits likely determines their excitability and synchronization, and thus their unique predisposition to generate ictal activity, which may also be mediated by broader networks. It has been recently reported that the activity of epileptogenic networks, rather than a single focal source,

Conclusions

SdDTF analysis of effective connectivity for high frequency activity (70–175 Hz) in ictal, pre-ictal and interictal recordings may help estimate the epileptogenic zone during invasive monitoring in patients with focal ictal onsets. The nodes of epileptogenic networks may be identified by assessing the combined divergence and convergence of propagated high frequency activity, and the relative importance of these nodes to ictogenesis may be reflected by the intensity and stability of propagation.

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