Active Brain & Nervous System Pregnancy, Children & Inherited Conditions

Interictal Epileptiform Discharges as Predictive Markers of Neurodevelopmental Outcomes in Early-Onset Epilepsy

Funder Wellcome Charity-funded
Recipient organisation University of Edinburgh
Funding Not disclosed
Period Oct 2025 — Sept 2028

In plain English

AI plain-English summary

Children diagnosed with epilepsy before age five often face uncertain futures, but their brainwave patterns recorded during routine EEGs may hold early clues to how they will develop. The problem is that doctors currently lack reliable tools to predict which children will experience developmental delays, intellectual disability, or autism. This project will analyse thousands of EEG recordings from the Edinburgh Paediatric Epilepsy Cohort, looking at specific features of interictal epileptiform discharges—brief bursts of abnormal electrical activity between seizures—and linking them to long-term outcomes such as cognitive scores and clinical diagnoses. The researchers will also incorporate video-coded behaviours like vocalisations and facial expressions, and test whether combining these signals improves prediction. In parallel, rat experiments will explore whether similar brain activity and anti-seizure medications alter neural synchrony and protein pathways, offering preliminary mechanistic insights. If successful, this work could enable earlier risk stratification for children with epilepsy, allowing clinicians to tailor interventions—such as therapy or medication adjustments—before developmental problems become entrenched. This is primarily fundamental science aimed at understanding how early network instability shapes the developing brain, but it lays groundwork for future clinical tools that could quietly improve the lives of thousands of families.

View original technical description
This project will investigate whether interictal epileptiform discharges (IEDs), detected on electroencephalography (EEG), can serve as early markers of network instability and predictors of neurodevelopmental outcomes in early- onset epilepsy. Using the Edinburgh Paediatric Epilepsy Cohort (EPEC), a longitudinal dataset of children diagnosed before age five with linked EEG, clinical, video, and outcome data, we will characterise IED features (frequency, morphology, spatial distribution, sleep–wake modulation) and evaluate their association with long-term developmental outcomes. Analyses will integrate clinical moderators (aetiology, seizure onset, anti-seizure medication) and expressive behaviours (vocalisations, affective gestures) coded from videos, to test whether a multimodal approach improves early risk prediction. Outcomes will be modelled both categorically (diagnoses) and dimensionally (psychometric scores) considering the developmental heterogeneity. As an exploratory component, rat models will be used to determine whether IED-like activity and ASM exposure alter network synchrony and protein pathways. This cross-species approach will provide preliminary mechanistic insights into whether molecular changes linked to hyperexcitability point to targetable therapeutic pathways. By combining clinical data with mechanistic experimental work, this project aims to identify early markers of vulnerability and resilience in childhood epilepsy, laying the foundation for earlier risk stratification and targeted interventions. Keywords: Interictal epileptiform discharges, childhood epilepsy, EEG, proteomics, neurodevelopment

View the original record at the funder ↗

Researchers

Uffaq Mastoor (EPMC Awardee)

Related Research

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Unravelling Disease Mechanisms Causing Seizures and Cognitive Dysfunction in Early Infantile Epileptic Encephalopathy (EIEE)
Brain architecture and connectivity at epilepsy diagnosis: markers of cognitive dysfunction and pharmacoresistance
Predicting cognitive recovery and side-effects of treatments for epilepsy
Infant predictors of neurodevelopmental outcomes in early-onset epilepsy: integrating video-based electronic health records
Quantitative brain network biomarkers for patient-specific diagnostics in idiopathic generalized epilepsy

Original classification

PhD Studentship (Basic)

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