First published: November 24, 2025
EEG functional connectivity as a marker of evolution from infantile epileptic spasms syndrome to Lennox–Gastaut Syndrome
Early diagnosis and effective treatment significantly improve LGS outcomes and reduce costs. However, LGS diagnosis is difficult, relies on a combination of EEG features that can vary across patients and time, and can be altered by treatment and overlap with other epilepsy syndromes. Since 20%–40% of children with LGS have a history of infantile epileptic spasms syndrome (IESS), robust biomarkers are needed to monitor IESS progression to LGS and guide treatment.
The Why:
- Patients that evolve from IESS to LGS are less likely to respond favorably to medication compared to those with LGS and no history of IESS
- There is an urgent need to identify robust biomarkers, or predictors to monitor the progression from IESS to LGS and guide treatment decisions
The How:
- The researchers focused on using EEG functional connectivity as a predictive biomarker for IESS to LGS
- EEG functional connectivity uses EEG signals to map functional relationships between different parts of the brain. It analyzes how brain areas synchronize their electrical activity. By analyzing the EEG signals from multiple scalp locations, researchers can determine how these different brain areas are statistically linked.
The What – Key Findings:
- Connectivity Strength: EEG connectivity strength decreased after favorable treatment responses but remained high in cases of poor response.
- Clinical Markers: High connectivity strength correlated with clinical markers of LGS connectivity strength was significantly higher for EEG studies with hypsarrhythmia, SSW, spasms, and GPFA than EEG studies without those markers. However, no single marker reliably predicted connectivity strength.
- Prediction of LGS: Increased connectivity strength often preceded LGS diagnosis, suggesting its potential as an early warning predictor for LGS in IESS patients.
- Treatment Response: Connectivity strength decreased in patients who responded to treatment, providing a possible metric of success for monitoring treatment efficacy.
The Importance:
- This is the first study to explore computational EEG biomarkers during the transition from IESS to LGS.
- This could facilitate the prevention of LGS via early, effective intervention, thus leading to improved outcomes and quality of life for children at high risk of developing LGS.
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Updated 01/21/26 (AM)