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EPINET

Detection of brain patterns for the characterisation of epileptic networks

Total Cost €

EC-Contrib. €

Partnership

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Outcomes and
results

EPINET project word cloud

Explore the words cloud of the EPINET project. It provides you a very rough idea of what is the project "EPINET" about.

epinet spike she maturity professional brain computer complementing tools programming epileptogenic intracranial neurophysiological ez fmri benefit drug epilepsy public clinical mapping fold collaborations localise validating invasively team world invasive teams innovative complementary extend epileptic expertise group biological meg interface classification training patients bci seizures resolution tests zone candidate quitadamo made function responsible area bioelectrical skills presurgical generation hr multimodal eeg lq fellow host characterise magnetoencephalography signal domain activated resistant functional electromagnetic neuroimaging expert repository position independence

Project "EPINET" data sheet

The following table provides information about the project.

Coordinator	ASTON UNIVERSITY Organization address address: ASTON TRIANGLE city: BIRMINGHAM postcode: B4 7ET website: www.aston.ac.uk contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.
Coordinator Country	United Kingdom [UK]
Project website	https://github.com/quitadal/EPINETLAB
Total cost	195˙454 €
EC max contribution	195˙454 € (100%)
Programme	1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
Code Call	H2020-MSCA-IF-2014
Funding Scheme	MSCA-IF-EF-ST
Starting year	2015
Duration (year-month-day)	from 2015-10-05 to 2017-10-04

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	ASTON UNIVERSITY ASTON UNIVERSITY Organization address address: ASTON TRIANGLE city: BIRMINGHAM postcode: B4 7ET website: www.aston.ac.uk contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	UK (BIRMINGHAM)	coordinator	195˙454.00

Map

Project objective

This project will bring in a research fellow with significant experience in the development and application of signal processing tools applied to electromagnetic brain signal, to work with a group carrying out leading research in epilepsy and in the development of non-invasive tests to localise brain function in patients with drug-resistant epilepsy. EPINET research aims at developing and validating innovative methods to localise and characterise non-invasively functional properties of the epileptogenic zone (EZ), i.e. the area responsible for the generation of epileptic seizures. The candidate, L. Quitadamo (LQ), will bring to the team expertise in the classification of biological signal and computer programming developed through collaborations with world-leading teams involved in brain-computer interface (BCI) research, complementing the expertise of the host research group in non-invasive mapping of brain function. Furthermore, she will benefit from expert training in the analysis of neuroimaging and neurophysiological tests (Magnetoencephalography (MEG), High Resolution EEG (HR-EEG), spike-activated fMRI and Intracranial EEG). The benefit will be two-fold: The candidate will extend her expertise in signal processing to the clinical assessment of patients with drug-resistant epilepsy, developing new and complementary skills applied to specific clinical applications, which will enable her to reach a position of maturity and professional independence. The host group will have access to new methods of classification of bioelectrical signal and develop analysis tools that will be made available in the public domain together with a repository of multimodal electromagnetic signal obtained in the presurgical assessment of patients with epilepsy.

Publications

List of publications.
year	authors and title	journal	last update
2017	L R Quitadamo, F Cavrini, L Sbernini, F Riillo, L Bianchi, S Seri, G Saggio Support vector machines to detect physiological patterns for EEG and EMG-based humanâ€“computer interaction: a review published pages: 11001, ISSN: 1741-2560, DOI: 10.1088/1741-2552/14/1/011001	Journal of Neural Engineering 14/1	2019-06-13
2017	LUCIA RITA QUITADAMO, ROBERTO MAI, FRANCESCA GOZZO, VERONICA PELLICCIA, FRANCESCO CARDINALE, STEFANO SERI KURTOSIS-BASED DETECTION OF INTRACRANIAL HIGH-FREQUENCY OSCILLATIONS FOR THE IDENTIFICATION OF THE SEIZURE ONSET ZONE published pages: , ISSN: 0129-0657, DOI:	International Journal of Neural Systems	2019-06-13

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The information about "EPINET" are provided by the European Opendata Portal: CORDIS opendata.