 It must be admitted that there is still no convincing evidence that the essential features of PC models are directly implemented as anatomical structures in the brain. Although it is conjectured that superficial pyramidal cells may transmit prediction error, and deep pyramidal cells predictions, we do not know that that is how they actually function. On the other hand, PC models do appear more neurally plausible than backpropagation architectures, for there is no need for a separate process of training on an externally provided set of training samples. Instead, predictions replace the role of the training set, so that learning and interacting with the environment are two sides of a unified unsupervised process. 