A Nonlinear Method to Identify Seizure Dynamic Trajectory Based on Variance of Recurrence Rate in Human Epilepsy Patients Using EEG

Abstract

Background: Surgery is a well-established treatment for drug-resistant epilepsy, but outcomes are often suboptimal, especially when no lesion is visible on preoperative imaging. A major challenge in determining the seizure's origin and spread is interpreting electroencephalogram (EEG) data. Accurately tracing the seizure's signal trajectory, given the brain's complex behavior, remains a crucial hurdle.

Materials and methods: In this study, EEG data from 17 patients were analyzed, using the clinical interpretations of the epileptogenic region as the gold standard. Quantification analysis of recurrence plots primarily based on variance in recurrence rate was used to identify the regions involved during seizures based on investigation of the recurrence phenomena between the regions. This method allowed for a stage-wise analysis across EEG electrodes, highlighting simultaneously involved areas.

Results: The method effectively distinguished involved from noninvolved regions across anterior, posterior, right temporal, and left temporal areas with macro averaged F-score of 95.54. For the anterior region, it achieved an overall accuracy (correct predictions out of total predictions) of 86.96%, sensitivity (ability to correctly identify seizure-involved regions) of 82.79%, and specificity (ability to correctly identify non-involved regions) of 86.96%. For the other regions, accuracy, sensitivity, and specificity values ranged from 66.0% to 89.13%.

Conclusions: This approach could pinpoint brain regions involved in seizures at any stage and could be useful for clinical monitoring and surgical planning. The method's simplicity and strong performance suggest it is promising for the real-time application during epilepsy treatment.

Keywords: Dynamic trajectory; electroencephalogram; recurrence plot; seizure.

Figure 1

Graphical illustration of general block diagram of the nonlinear approach of extraction of trajectory map between epileptic regions

Figure 2

Results of recurrence plot of electroencephalogram (EEG). From left to right at pre-ictal, ictal and post-ictal for PO8 and P10, respectively

Figure 3

Quantification analysis of recurrence plots. (a) Recurrence rate (RR) coefficients of all channels, (b) Variance of RR coefficients. Vertical lines define pre-ictal, ictal and post-ictal stages in turn

Figure 4

Trajectory and areas involved in epilepsy based on specific trajectory lag index. The image depicts the distribution of electroencephalogram (EEG) channels on the scalp, with each channel represented by a dot, accompanied by its respective label

Figure 5

Results of specific trajectory lag index method for detecting regions involved in seizure