Observational studyNeuroImage. Clinical2026
A spectral- topological network signature of drug-resistant epilepsy: a phase 1-2 study on resting-state EEG-based diagnostic biomarkers of drug resistance.
Observational study in NeuroImage. Clinical, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveDrug-resistant epilepsy (DRE) is increasingly recognized as a disorder of large-scale brain networks. Here, we evaluated a candidate resting-state EEG-based biomarker for identifying DRE in a diagnostic context of use.
methodsWe conducted a retrospective observational study (Phase 1-2 biomarker validation) on resting-state EEG recordings on healthy subjects (HS) and people with epilepsy (PwE). In PwE, EEGs were recorded after a second anti-seizure medication trial. The reference standard was longitudinal clinical outcome at 12 months (DRE vs. non-DRE). Index tests included the following quantitative EEG measures: spectral frequency-specific and aperiodic components, along with graph-theory metrics derived from the weighted phase-lag index. Multivariate logistic regression models assessed their discriminative value.
resultsWe enrolled 120 PwE (60 DRE) and 60 HS. DRE showed a distinct spectral profile, with increased δ (1-4 Hz) power, reduced α (8-12 Hz) power, and a steeper aperiodic slope compared with both HS and non-DRE. Network analysis revealed increased δ-band betweenness centrality and small-world index, alongside reduced global efficiency, indicating a shift toward a more regular and less integrative topology. These findings were independent of epilepsy etiology (p-values = 0.001-0.04). Adding EEG features significantly improved DRE classification compared with clinical variables alone (AUC: 0.83 ± 0.03 vs. 0.71 ± 0.02, p < 0.001).
conclusionsWe revealed convergent spectral and network-level alterations that delineate an intrinsic network signature highly associated with DRE. SIGNIFICANCE: Resting-state EEG metrics show promise as candidate diagnostic biomarkers for DRE, addressing an important unmet clinical need, though external validation is required.
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