Linear and nonlinear interrelations show fundamentally distinct network structure in preictal intracranial EEG of epilepsy patients

Abstract

Resection of the seizure generating tissue can be highly beneficial in patients with drug-resistant epilepsy. However, only about half of all patients undergoing surgery get permanently and completely seizure free. Investigating the dependences between intracranial EEG signals adds a multivariate perspective largely unavailable to visual EEG analysis, which is the current clinical practice. We examined linear and nonlinear interrelations between intracranial EEG signals regarding their spatial distribution and network characteristics. The analyzed signals were recorded immediately before clinical seizure onset in epilepsy patients who received a standardized electrode implantation targeting the mesiotemporal structures. The linear interrelation networks were predominantly locally connected and highly reproducible between patients. In contrast, the nonlinear networks had a clearly centralized structure, which was specific for the individual pathology. The nonlinear interrelations were overrepresented in the focal hemisphere and in patients with no or only rare seizures after surgery specifically in the resected tissue. Connections to the outside were predominantly nonlinear. In all patients without worthwhile improvement after resective treatment, tissue producing strong nonlinear interrelations was left untouched by surgery. Our findings indicate that linear and nonlinear interrelations play fundamentally different roles in preictal intracranial EEG. Moreover, they suggest nonlinear signal interrelations to be a marker of epileptogenic tissue and not a characteristic of the mesiotemporal structures. Our results corroborate the network-based nature of epilepsy and suggest the application of network analysis to support the planning of resective epilepsy surgery. K E Y W O R D S epilepsy, epilepsy surgery, linear, network structure, nonlinear, quantitative EEG Hum Brain Mapp. 2020;41:467-483. wileyonlinelibrary.com/journal/hbm 467 SUPPORTING INFORMATION Additional supporting information may be found online in the Supporting Information section at the end of this article. How to cite this article: Müller M, Caporro M, Gast H, et al. Linear and nonlinear interrelations show fundamentally distinct network structure in preictal intracranial EEG of epilepsy patients. Hum Brain Mapp. 2020;41:467-483.

More Than Spikes: On the Added Value of Non-linear Intracranial EEG Analysis for Surgery Planning in Temporal Lobe Epilepsy

“… Indicated are the post-surgical seizure control according to the Engel classification scheme, durations of the included epochs, the location of seizure onset, etiological factors, the type of resection, the total number of artifact free channels, and the number of channels recording from RBT. Nineteen of these patients were already included in our preceding study ( 32 ) and are indicated by an asterisk *. One patient (p5) had two implantation schemes before resection, one patient (p29) had two distinct implantation schemes both followed by resection, and one patient (p28) had a second implantation after the surgical removal of brain tissue but no second resection .…”

“…The qEEG measure used in this study was introduced by Rummel et al ( 34 , 41 ) and has been applied in ( 32 , 42 , 43 ). A similar measure was also used in ( 16 , 27 , 30 ).…”

“…This single value per channel is confined to the range [0, 1] and indicates how strongly it is connected with all others. Based on the channels' connection strength, we automatically separated the most strongly connected channels by sorting all channels by their node strengths and identifying the largest difference between two adjacent values on the linear and the logarithmic scale ( 32 , 46 ). We call these epoch-specific channel collections the “core” and based on our previous findings ( 32 , 34 ) hypothesized them to be indicative of pathological epileptic activity.…”

“…In our previous study ( 32 ), we have demonstrated for patients with mesiotemporal implantation of depth electrodes that surrogate corrected non-linear interrelations between iEEG signals were associated with the individual pathology. In addition, the spatial overlap of salient non-linear interrelations with the RBT was associated with post-surgical seizure control.…”

How Would You Like Your Epileptic Network? Linear, Nonlinear, Virtual?

“…The study of Müller et al 4 evaluates the linear relationships measured by coherence and the nonlinear relationships measured by mutual information during a 3-minute preictal period in 20 patients with bilateral temporal electrode implantations. Nonlinear measures usually reflect both linear and nonlinear relationships but in this study the nonlinear relationships represent the excess part of the relationship which cannot be explained by linear relationships.…”