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AYOP: At Your Own Pace

AYOP: At your own pace

AYOP: At your own pace
Would we react to relevant events more efficiently? Would we learn new things more easily? We aim at answering these questions based on principle knowledge on neural dynamics. ‘At Your Own Pace’ (AYOP) proposes to stream neural oscillations,...

Would we react to relevant events more efficiently? Would we learn new things more easily? We aim at answering these questions based on principle knowledge on neural dynamics. ‘At Your Own Pace’ (AYOP) proposes to stream neural oscillations, on-line decode power and phase parameters, and use them to pace the presentation of sensory stimuli on the fly, at relevant moments for each human subject. We aim at favouring (or discouraging) performance at time t+1 from knowing the relation brain activity - behaviour at time t. AYOP offers an original and unique opportunity of translating neuroscience into technology: it pretends to reliably decipher brain activity and foresee it in time in order to favour or discourage behaviour. AYOP will provide proactive and person-centred solutions in learning applications; it will generate new testable hypotheses toward a better understanding of the mind-brain relationship. No studies to date have capitalized on non-invasive neural recordings to naturally pace the in-flow of information in order to favour (or discourage) behavioural outcome online. No studies have used a control signal in BCI, based on oscillatory phase. Scientifically, this approach becomes a strong ‘reality check’ for the functional role of brain oscillations in shaping cognition. Technologically, the project takes a radical definitive step into the challenge of forecasting non-invasively the power and phase of ongoing human brain activity through EEG signal, in order to anticipate favourable/disadvantageous moments for concrete cognitive outcomes (perceptual detection, memory encoding). 

Key words: Perception, Attention, Working Memory, Brain Oscillations, EEG, Alpha, Theta, Phase, BCI

Illustrative picture

Principal researchers

Manuela Ruzzoli
Ministerio de Economia y Competitividad, Explora PSI2016-75558-P