![]() Importantly, the latter enable the optimization of a model selection error rate with respect to experimental control variables, yielding maximally powerful designs. Such complex interpretations of empirical data call for efficient and robust computational approaches that can deal with statistical model comparison, such as approximate Bayesian inference schemes. Recently, psychological theories became more biologically plausible, leading to more realistic generative models of psychophysiological observations. ![]() This is why BCIs are highly dependent upon advances in cognitive neuroscience and neuroimaging research. The main issue that remains, however, is the identification of a reliable mapping between electrophysiological measures and relevant states of mind. Methodological and technical progress has largely solved the challenge of processing these signals online. Brain-computer interfaces (BCIs) mostly rely on electrophysiological brain signals.
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