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Adaptive Design Protocols for real-time functional Magnetic Resonance Imaging (rtfMRI) experiments
Real-time fMRI has become a valuable tool in neuroscience. RtfMRI creates "added value" as compared with offline analysis in several ways: we can see something happen in real time (BCI), we can manipulate cognitive states online (neurofeedback and brain-state dependent stimulation). We could also run tests in real-time (like localizer), test hypotheses about cognitive states or subject's parameters (perceptual threshold or bias). That could give us an advantage in time: in one session we could have results that would otherwise require multiple sessions. The key feature that would allow us to benefit from analysis in real-time is the possibility to adapt stimulation protocols online. However, if we turn to the state of the art in current rtfMRI experiments, we can see that there is a notable gap in this area. In my presentation, I would like to discuss the implementation of an adaptive protocol for our ATTEND real-time experiment with Adaptive Design Optimization framework (Daunizeau et al. ) and how this setup could be generalized to run other types of experiments with rtfMRI.