Predictive coding, precision and synchrony

Abstract Gotts, Chow and Martin provide a very nice review of repetition priming and suppression that reaches a compelling conclusion—we need to look more closely at synchronization in learning and priming. Indeed, current modeling work focuses on this issue—namely, the dynamic causal modeling of electrophysiological responses to address the role of synchrony in Bayesian explaining away. This commentary revisits the nature and relationships among the four theories in Gotts et al. and nuances some of their empirical predictions. In particular, I emphasize precision or uncertainty in predictive coding as a unifying consideration.