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). One of the limitations to a more widespread use of this biomarker is the inherent difficulty in its detection using non-invasive methods.
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.
The project aims to develop and maintain long-term collaborations between Universities in the European Union with the USA. The collaboration is centred on advancing technological and computational approach to HFOs identification and its relevance to MRE beyond the current state-of-the-art. This will be achieved through staff exchanges with world-leading researchers in hardware and software development, applied neurosciences and neurofeedback, dynamic signal processing, clinical assessment of patients with MRE, and techno-economic analysis. Our objectives include the improvement in sensitivity of the hardware technology behind diagnostic equipment and the development innovative algorithms for the detection and localization of HFOs. We will also exploit these advancements to design a portal for promoting HOPE algorithms, as well as a new software that will ultimately enable patients to modulate HFOs in a biofeedback system and evaluate the effect of this on MRE.
The technical objectives (TO) of the HOPE project are:
1. To develop MEG SQUID and EEG sensor in order to improve the Signal to Noise Ratio (SNR) of HFOs (WP1 and WP2)
2. To develop a classifier for the automatic detection of HFOs (WP4)
3. To develop an algorithm for the localization of HFOs (WP5)
4. To develop HOPE portal(WP6)
5. To develop a neurofeedback process (software) for the inhibition of HFOs (WP7)
The knowledge transfer objectives (KTO) of the RISE project are:
1. To develop and strengthen research and innovation partnerships (i.e. joint research programme and co-supervision of research students) between the EU and USA through international staff exchanges and networking activities. (WP8)
2. To strengthen EU research and innovation through enhanced training, mobility and career development of experienced and early stage researchers. (WP9)
3. To disseminate widely, and fully exploit the outcomes of the project through published articles, seminars, summer school, workshops, conferences and commercial exploitation opportunities. (WP8)
4. To fully embrace public engagement to communicate the research activities with the public. (WP8)
5. To work towards the sustainability of the collaboration through the development of project proposals for further funding. (WP8)
6. To effectively manage the Research and Innovation Staff Exchange programme for maximum knowledge exchange and career development for all the researchers. (WP9)
