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 characterize 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 the
development and evaluation of a neurofeedback platform for the self-modulation of HFOs, and its
relevance to the clinical management of MRE.

Project Objectives
The project aims to develop and maintain long-term collaborations between Universities in the
European Union and the USA. The collaboration is centered on advancing a 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 of 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 new software that will ultimately enable patients to modulate HFOs in a
biofeedback system and evaluate the effect of this on MRE.