Project description
Hypergraphs uncover hidden seizure-triggering brain regions
Epilepsy is one of the EU’s most common neurological disorders, causing unpredictable seizures and brain dysfunction. For drug-resistant cases, surgery to remove the seizure-generating brain area – guided by intracranial recordings – are most effective. However, the recordings are difficult to interpret, resulting in a surgical success rate below 70 %. With the support of the Marie Skłodowska-Curie Actions programme, the HYPHEN project aims to represent the intracranial signals as hypergraphs of interconnected nodes representing the electrodes. HYPHEN will then develop an approach to complete the graph, capturing epileptogenic patterns not sampled by the implanted electrodes and enabling prediction of hidden epileptogenic structures. The work could extend surgical treatment to currently inoperable cases.
Objective
Epilepsy is one of the most common neurological disorders in the European Union (EU) and is characterized by unpredictable interruptions of brain functions, known as epileptic seizures. In drug-resistant epilepsy, the most effective path to seizure freedom is epilepsy surgery, which targets the removal of the Epileptogenic Zone (EZ), the brain area responsible for seizure generation. The localization of the EZ can be aided by Stereo-Electroencephalography (SEEG), a presurgical intervention that records brain activity in cortical and subcortical areas via intracranial electrodes. SEEG signals are highly complex to interpret, and the success rate of epilepsy surgery remains below 70% despite recent technological advancements. The identification of new biomarkers of the EZ is thus an essential priority for the medical community and the European Reference Network for Rare and Complex Epilepsies. With this aim, the HYPHEN project will develop a new framework for analysing SEEG data. The project will be among the first to represent SEEG signals as hypergraphs, in which each SEEG channel is modelled as a node and connections between multiple nodes are captured via high-order interactions. This approach will make it possible to identify epileptogenic channels and infer the presence of epileptogenic structures not sampled by the SEEG implant. In the latter cases, HYPHEN will design a graph-completion strategy to predict hidden epileptogenic nodes, enabling epilepsy surgery in scenarios currently considered too complex for treatment. These activities will be conducted at Aix-Marseille University (France), under the supervision of Prof. Bénar, in close collaboration with Prof. Bartolomei, two world leaders in the field of SEEG analysis. Complementary methodological expertise will be provided through a secondment at Northeastern University London (UK), in the laboratory of Prof. Petri, a leading authority in high-order networks and their application to neuroscience.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences neurobiology
- medical and health sciences basic medicine neurology epilepsy
- medical and health sciences clinical medicine surgery
- natural sciences mathematics pure mathematics discrete mathematics graph theory
- medical and health sciences medical biotechnology implants
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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(opens in new window) HORIZON-MSCA-2025-PF
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13284 Marseille
France
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