project017
Idiopathic Generalized Epilepsy (IGE) accounts for approximately 15–20% of all epilepsy cases. It is considered a network disorder involving widespread cortical networks without consistent focal onset across different seizure types. Epileptiform activity arises in bilateral and distributed networks with rapid interhemispheric synchronization (usually <100 ms). IGE comprises four main epilepsy syndrome with onset in childhood or adolescence: childhood absence epilepsy (CAE), juvenile absence epilepsy (JAE), juvenile myoclonic epilepsy (JME), and epilepsy with generalized tonic–clonic seizures alone (EGTCSA).
Seizures in IGE involve abnormal interactions between the cortex and thalamus (thalamocortical loop) that facilitate generalized synchronization, expressed on scalp EEG as generalized spike–wave or polyspike–wave discharges. Connectivity studies using EEG-fMRI, DTI, and MEG have revealed thalamo–frontocortical hyperconnectivity and reorganization of attentional control networks.
Effective connectivity models describe bidirectional thalamo–cortical interactions, with variable predominance depending on the syndrome subtype (e.g., cortex→thalamus in JME).
Beyond the thalamocortical circuit, functional MRI studies have identified alterations in the precuneus/posterior cingulate cortex, the frontoparietal executive network, and the salience network, along with abnormal resting-state attentional networks. These findings align with interictal deficits in cognitive control and alertness. Excessive thalamo–cortical hyperconnectivity has been linked to poorer initial response to antiseizure medications (ASMs) and greater cognitive impairment. Cognitive deficits—particularly in planning, response inhibition, and cognitive flexibility—are increasingly recognized, especially in JME. Even between seizures, attentional, processing speed, and executive function deficits are common, potentially contributing to long-term cognitive morbidity.
This study aims to characterize interictal cortical connectivity (both static and dynamic) in IGE using scalp EEG, and to correlate these findings with epilepsy severity and neuropsychological performance. It will also assess the influence of syndrome subtype, ASM treatment, and interictal epileptiform activity load.
Important Notice: All clinical and neuroimaging data are highly sensitive and subject to strict confidentiality and intellectual property protocols. Any
manipulation of the data outside the scope of the initial study protocol must be communicated to the project supervisor and will be individually evaluated.
Project Goals
The student will join a collaborative project between UPF and the Epilepsy Unit, working with a multidisciplinary team combining clinical neurology,
neuropsychology, and computational neuroscience. The specific goals are:
- Primary goal: Characterize static and dynamic interictal cortical connectivity in IGE and correlate it with (a) epilepsy severity and (b) neuropsychological performance.
- Secondary goals:
- Compare IGE syndrome subtypes (JME, CAE/JAE, EGTCSA).
- Evaluate the impact of ASM treatment and interictal epileptiform activity load.
- Explore directed connectivity and graph theory metrics as potential biomarkers.
Required Computational Skills:
The student will have close support and supervision from the clinical-technical team for data analysis and biomedical reasoning. Preferred experience or interest in:
- Programming Languages: MATLAB (required), Python (desirable).
- Image Processing / EEG Analysis: Familiarity with EEG preprocessing pipelines, functional connectivity analysis, and graph theory metrics.
- Data Analysis: Use of statistical packages, correlation and regression models, supervised machine learning for classification (optional).
- Other Skills: Development or adaptation of signal processing algorithms, interest in clinical neurophysiology and computational neuroscience.
Supervisors: Alba Sierra-Marcos, Victoria Ros Castelló