VARIABILITI · Understanding learning variability to personalise training and boost knowledge-driven, efficient and acceptable neurotechnologies

Lines connect the coordinator with its partners. CORDIS does not always give exact coordinates for projects before 2014. These points are placed at city or country level.

Project objective

Boosted by recBoosted by recent advances in neuroscience, AI and wearable sensors, neurotechnologies, and in particular brain–computer interfaces (BCIs), are increasingly presented as near-future solutions to restore, replace or even enhance movement, communication and cognition. They are envisioned, for example, to support motor rehabilitation after stroke, enable control of assistive technologies, or offer new forms of cognitive enhancement and interaction in virtual environments. Yet, in reality, BCIs remain insufficiently usable and reliable to be adopted in everyday life. Their performance is inconsistent and highly dependent on the individual user, creating a risk of disillusionment, funding loss and stalled innovation if expectations are not met. VARIABILITI addresses this challenge by training 14 DCs with R-COP (responsible, collaborative, open and participatory) principles, placing end-users at the core of the research and innovation (R&I) loop. By moving from a technology-centred to a human-centred approach, VARIABILITI’s overarching ambition is to make BCIs truly usable, acceptable and efficient. The international, interdisciplinary and intersectoral consortium (12 beneficiaries, 18 associated partners including clinicians, SMEs/industrials, and European networks) tackles this through four interconnected objectives: Initiate a paradigm shift toward sustainable, user-centred and responsible R&I in BCI; Model human learning and its variability to enable co-adaptive, personalised BCIs; Design & validate novel BCI protocols and algorithms to enhance the double learning process; Demonstrate the relevance and applicability of the VARIABILITI approach in both clinical and non-clinical real-world contexts. By providing open datasets, models, protocols and prototypes, the network will benefit BCI developers, end-users and decision-makers, strengthen Europe’s innovation capacity and support the emergence of responsible, inclusive and high-impact neurotechnologies.

Original text from CORDIS.

Participants

• UNIVERSITE DE BORDEAUX · BordeauxCoordinatorFrance
• ANT Neuro GmbH · BerlinCity levelGermany
• CARL VON OSSIETZKY UNIVERSITAET OLDENBURG · OldenburgGermany
• CENTRE HOSPITALIER UNIVERSITAIRE VAUDOIS · LausanneSwitzerland
• FUNDACIO UNIVERSITARIA BALMES · VIC BARCELONASpain
• INSTITUT DU CERVEAU ET DE LA MOELLE EPINIERE · ParisFrance
• INSTITUT SUPERIEUR DE L'AERONAUTIQUE ET DE L'ESPACE · TOULOUSEFrance
• INSTITUTO SUPERIOR TECNICO · LisboaPortugal
• KATOLICKI UNIWERSYTET LUBELSKI JANA PAWLA II · LublinPoland
• NATIONAL UNIVERSITY CORPORATION TOKYO UNIVERSITY OF AGRICULTURE AND TECHNOLOGY · Fuchu Shi TokyoJapan
• NEUROX GROUP SA · LausanneSwitzerland
• NeuroCONCISE Ltd · Londonderry DerryCountry levelUnited Kingdom
• OTTO-FRIEDRICH-UNIVERSITAET BAMBERG · BambergGermany
• RIJKSUNIVERSITEIT GRONINGEN · GroningenNetherlands
• SORBONNE UNIVERSITE · ParisFrance
• STICHTING VU · AmsterdamNetherlands
• SYSTEMS RESEARCH INSTITUTE OF THE POLISH ACADEMY OF SCIENCES IBS PAN · WarszawaPoland
• TECHNISCHE UNIVERSITAET GRAZ · GrazAustria
• THE UNIVERSITY OF SHEFFIELD · SHEFFIELDUnited Kingdom
• UNIVERSITA DEGLI STUDI DI PADOVA · PadovaItaly
• UNIVERSITAET GRAZ · GrazAustria
• UNIVERSITAET ULM · UlmGermany
• UNIVERSITE DE LAUSANNE · LAUSANNESwitzerland
• UNIVERSITE DE LILLE · LilleFrance
• UNIVERSITE DE RENNES · RennesFrance
• UNIVERSITE LYON 1 CLAUDE BERNARD · Villeurbanne CedexFrance
• UNIVERSITY OF ESSEX · ColchesterUnited Kingdom
• UNIVERSITY OF GLASGOW · GlasgowUnited Kingdom
• ZURCHER HOCHSCHULE FUR ANGEWANDTE WISSENSCHAFTEN · WinterthurSwitzerland

Links

• View on CORDIS
• DOI: 10.3030/101312302