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Estimation of intracranial sources, using inverse solutions methods, has been proposed as a mean to improve performance in non-invasive brain-computer interfaces. These methods estimate the activity of a large number of neural sources from a smaller number of scalp electroencephalography (EEG) channels. This is a highly undetermined problem and regularisation constraints need to be applied. In this...
Error-related potentials (ErrP) have been increasingly studied in psychophysical experiments as well as for brain-machine interfacing. In the latter case, the generalisation capabilities of ErrP decoders is a crucial element to avoid frequent recalibration processes, thus increasing their usability. Previous studies have suggested that ErrP signals are rather stable across recording sessions. Also,...
Movement Related Cortical Potentials (MRCP) have been the subject of numerous studies. They accompany many self-initiated movements and this makes them a good candidate for incorporation in BCI paradigms. In this work we propose a novel experimental protocol involving natural controlling of a computer mouse and based on EEG recordings from 5 subjects, show that it elicits MRCP. We also show the feasibility...
Psychophysical studies have reported correlation between neural activity in frontal and parietal areas and subject's reaction time in simple tasks. Here we study whether similar correlates can also be identified in driver's electroencephalography (EEG) activity when they perform steering actions triggered by exogenous stimuli (e.g. Obstacles along the road). We report analysis of the EEG signals of...
Successful operation of motor imagery (MI)-based brain-computer interfaces (BCI) requires mutual adaptation between the human subject and the BCI. Traditional training methods, as well as more recent ones based on co-adaptation, have mainly focused on the machine-learning aspects of BCI training. This work presents a novel co-adaptive training protocol shifting the focus on subject-related performances...
For people with severe physical disabilities, low resolution input devices, such as buttons, sip and puff switches and brain-computer interfaces provide an opportunity to interact with the world. However, it can be difficult to control assistive technology, such as wheelchairs, tele-presence robots and robotic arms, when you have only a limited number of commands available and/or a lack of temporal...
This study aims to characterize the electroencephalography (EEG) correlates of exploratory behavior. Decision making in an uncertain environment raises a conflict between two opposing needs: gathering information about the environment and exploiting this knowledge in order to optimize the decision. Exploratory behavior has already been studied using functional magnetic resonance imaging (fMRI). Based...
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