Mapping the Phenotypic Spectrum of Occipital Lobe Epilepsy: A SEEG-Defined Network Classification

Occipital lobe epilepsy (OLE) often presents with complex clinical symptoms that extend beyond the occipital lobe, posing significant challenges for diagnosis and lesion localization. This study aims to systematically characterize the seizure phenotype spectrum of OLE using stereo-electroencephalography (SEEG) and elucidates its electrophysiological and anatomical basis.

This single-center, retrospective case series included 19 patients who underwent comprehensive SEEG evaluation. Seizure phenotypes were classified based on the initial and evolving clinical manifestations. SEEG recordings coregistered with MRI/CT fusion images were used to identify the seizure onset zone and subsequent propagation pathways. Through systematic analysis of electroclinical correlations in conjunction with the dual-stream model, phenotypic features were mapped to specific propagation networks.

We identified five distinct clinical phenotypes: Pure visual (I), ±visual → automatism (II), visual aura → oculomotor → evolving motor (III), oculomotor onset (IV), and behavioral arrest → motor (V). These mapped to four reproducible SEEG propagation patterns: restricted (I, 10.5%), ventral stream-limbic (II, 26.3%), dorsal-medial/default mode network-limbic (III, 47.4%), and lateral occipital-temporoparietooccipital junction (TPOJ) (IV, 15.8%). Individual patients could exhibit multiple clinical phenotypes across different seizures. The TPOJ and posterior cingulate/precuneus emerged as key hubs for rapid cross-network propagation and symptom evolution. Representative cases showed close temporal concordance between clinical semiology and SEEG-defined propagation sequences.

This study proposes a preliminary anatomical-electrophysiological-clinical classification for OLE. Seizure phenotypes in OLE were associated with structured, pathway-specific network recruitment rather than nonspecific spread within this single-center cohort. A phenotype-driven SEEG approach may offer valuable insights into seizure network organization and could inform presurgical evaluation and individualized surgical planning, though these findings require validation in larger, prospective cohorts.