Schema-driven prediction effects on episodic memory across the lifespan

This is the authors' abstract. We don't add key points for this paper.

The predictive processing framework posits that brain function is essentially predictive. Internal models facilitate mental time travel by predicting future states against which incoming information is compared. The difference between predicted and actual states, the prediction error (PE), signals novel information. However, the constrains of the further use of PE are not fully understood: In particular, with respect to how PE influence episodic memories across the lifespan. We examine the relationship between PE and episodic memory in children, young and older adults. We use a novel paradigm that uses rich visual narratives to build action schemas and enables measuring different mnemonic aspects. Critically, we manipulate the endings to be either expected, neutral, or unexpected based on the unfolded action. We show that 1) expected endings are better encoded than neutral ones and 2) unexpected endings upregulate encoding of the mismatching event but also of other aspects of the narrative. Moreover, these effects are modulated across the lifespan with PE-driven-encoding being more prominent in children and young adults and with schema integration playing a larger role on memory encoding in older adults. These results highlight the role of predictions in mental time travel by enriching past experiences and informing future anticipations.