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.

翻译：经典猜想认为，大脑会为刺激序列分配概率模型。与该猜想相关的一个重要问题是，识别大脑用于完成这一任务的模型类别。我们通过一种新的聚类方法来解决这个问题，该方法针对的是参与者暴露于随机链生成的听觉刺激序列时记录的一组脑电图数据。该聚类方法表明，大脑利用听觉刺激随机序列中的更新点来构建模型。