Semi-Supervised Anomaly Detection Pipeline for SOZ Localization Using Ictal-Related Chirp

TL;DR

This paper introduces a semi-supervised pipeline combining outlier detection and spatial correlation analysis of ictal chirp events to improve seizure onset zone localization in epilepsy patients.

Contribution

It proposes a novel two-step framework utilizing LOF-based anomaly detection and weighted spatial metrics for better SOZ identification from chirp features.

Findings

LOF with 20 neighbors effectively detects anomalous channels.

Weighted spatial matching outperforms exact matching in SOZ localization.

Higher localization accuracy in seizure-free and successful surgical outcome patients.

Abstract

This study presents a quantitative framework for evaluating the spatial concordance between clinically defined seizure onset zones (SOZs) and statistically anomalous channels identified through time-frequency analysis of chirp events. The proposed pipeline employs a two-step methodology: (1) Unsupervised Outlier Detection, where Local Outlier Factor (LOF) analysis with adaptive neighborhood selection identifies anomalous channels based on spectro-temporal features of chirp (Onset frequency, offset frequency, and temporal duration); and (2) Spatial Correlation Analysis, which computes both exact co-occurrence metrics and weighted index similarity, incorporating hemispheric congruence and electrode proximity. Key findings demonstrate that the LOF-based approach (N neighbors=20, contamination=0.2) effectively detects outliers, with index matching (weighted by channel proximity) outperforming exact matching in SOZ localization. Performance metrics (precision, recall, F1) were highest for seizure-free patients (Index Precision mean: 0.903) and those with successful surgical outcomes (Index Precision mean: 0.865), whereas failure cases exhibited lower concordance (Index Precision mean: 0.460). The key takeaway is that chirp-based outlier detection, combined with weighted spatial metrics, provides a complementary method for SOZ localization, particularly in patients with successful surgical outcomes.