 PC accounts of attention have also been championed. For example, Hohwy (2012) notes that realistic PC models, which must tolerate noisy inputs, need to include parameters that track the desired precision to be used in reporting error. So PC models need to make predictions of the error precision relevant for a given situation. Hohwy explores the idea that mechanisms for optimizing precision expectations map onto those that account for attention, and argues that attentional phenomena such as change blindness can be explained within the PC paradigm. 