In spite of the continuous development of new drugs that target molecular mechanisms responsible for generating epileptic seizures, approximately 25% of the patients with epilepsy are proven medically resistant. These patients should be evaluated for surgery to remove the area responsible for generating the attacks referred to as the epileptogenic zone (EZ). Surgical outcomes strongly depend on the accuracy of the recognition of the EZ, which is currently identified using a potential range of diagnostic tests. In such cases, long-term intracranial electroencephalogram (iEEG) monitoring is used to correctly characterise the seizures and establish the surgical approach. iEEG monitoring has however its limitations, which are mainly found in its invasiveness, cost and the limited spatial sampling - i.e. the chance to record activity propagated from other close areas and not originated where electrodes are placed. To date, this results in a significant number of patients continuing to experience postsurgical seizures.
During the last few years, high-frequency oscillations (HFOs above 80 Hz) have emerged as a new promising biomarker in pre-surgical diagnosis of epileptogenicity. Indeed, recent studies have shown that the resection of the tissue generating HFOs improves surgical outcome in patients with medically refractory epilepsy (MRE).
HOPE aims to facilitate the interaction between academic, clinical industrial partners to produce a step-change in our ability to detect and quantify HFOs using non-invasive investigations like EEG and MEG, tackling the existing limitations at computational, hardware and software level. As the HFOs are a paradigmatic case for signal detection in low signal/noise condition, the technology will also benefit research in neurofeedback and BCI recordings and allow is to develop and evaluate a neurofeedback platform for the self-modulation of HFOs, and it’s relevance to clinical management of MRE.
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