  It has been classically conjectured that the brain assigns probabilistic
models to sequences of stimuli. An important issue associated with this
conjecture is the identification of the classes of models used by the brain to
perform this task. We address this issue by using a new clustering procedure
for sets of electroencephalographic (EEG) data recorded from participants
exposed to a sequence of auditory stimuli generated by a stochastic chain. This
clustering procedure indicates that the brain uses renewal points in the
stochastic sequence of auditory stimuli in order to build a model.
