File:Representation of Prediction Error.png

English: The environment consists of a stationary random process. Here the environment produces a Bernoulli sequence of two stimuli. The organism perceives the sequence, summarizing the recent past by a state of a reduced representation (m), then uses m to produce a prediction for the next stimulus in the sequence. Perception is characterized by P(m|past), mapping a sequence of past observations (N = 4 in this illustration) into states m of the reduced representation. In this example, the reduced representation consists of the number of red stimuli among the last N stimuli. Prediction is characterized by P(future|m), which assigns to each state m a set of subjective expectations for the next (future) stimulus. As the number of red stimuli in the past increases, the probability assigned to a red stimulus increases and that assigned to a blue stimulus decreases. The numbers shown here correspond to the posterior probabilities for the corresponding stimulus given a uniform prior on the probability of a red stimulus.