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Description: In their recent article ‘Neural differentiation of incorrectly predicted memories’, Kim et al. (2017) investigate how neural representations of items change when they are incorrectly predicted and subsequently restudied. The authors conclude such items undergo representational differentiation, i.e. a decreased overlap in the representations of an item and its context. We suggest the results are equally compatible with the reverse mechanism of integration, i.e. increased learning of new information and present simulations to demonstrate this. More importantly, we show how new experimental conditions could distinguish integration from differentiation and discuss how the results fit with recent suggestions about prediction-error driven learning and transitive inference.