  The P300 speller is a brain-computer interface that enables people with
neuromuscular disorders to communicate based on eliciting event-related
potentials (ERP) in electroencephalography (EEG) measurements. One challenge to
reliable communication is the presence of refractory effects in the P300 ERP
that induces temporal dependence in the user's EEG responses. We propose a
model for the P300 speller as a communication channel with memory. By studying
the maximum information rate on this channel, we gain insight into the
fundamental constraints imposed by refractory effects. We construct codebooks
based on the optimal input distribution, and compare them to existing codebooks
in literature.
