- Poster presentation
- Open Access
Assisted closed-loops for brain-computer interfaces
© Fernandez-Vargas et al; licensee BioMed Central Ltd. 2013
- Published: 8 July 2013
- Auditory Feedback
- Synaptic Conductance
- Flicker Frequency
- Dynamic Clamp
- Steady State Visually Evoke Potential
Our results show that this shared online information leads to an enhanced BCI efficiency, as compared to classic BCI protocols, by helping them to reach the BCI goal in their interaction. The analysis also shows that the ACL protocol takes into account interindividual variabilities. In particular, baseline resting state EEG measures seem to predict subjects' BCI performances, which indicates that the ACL based BCIs might be expanded to innovative new diagnostic/therapeutic tools for clinical contexts and as new paradigms for basic research. Taking all together, these results illustrate that assisted closed-loop protocols can reveal dynamics otherwise hidden under traditional stimulation techniques, provide control of regular and pathological states, induce learning processes, bridge between distinct levels of analysis and lead to automation of experiments. The proposed approach might have a large impact for applied uses, such as computer control and biomedical or prosthetic uses, but also in novel paradigms for neuroscientific and biomedical research.
This work was supported by UAM CEMU 2012-004, MINECO TIN2012-30883 and TIN-2010-19607.
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