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cc-by-nc-nd (c) Wu, Xiongbo et al., 2023
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/200881

Contextual incongruency triggers memory reinstatement and the disruption of neural stability

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Schemas, or internal representation models of the environment, are thought to be central in organising our ev-eryday life behaviour by giving stability and predictiveness to the structure of the world. However, when an element from an unfolding event mismatches the schema-derived expectations, the coherent narrative is inter-rupted and an update to the current event model representation is required. Here, we asked whether the perceived incongruence of an item from an unfolding event and its impact on memory relied on the disruption of neural stability patterns preceded by the neural reactivation of the memory representations of the just-encoded event. Our study includes data from two different experiments whereby human participants ( N = 33, 26 females and N = 18, 16 females, respectively) encoded images of objects preceded by trial-unique sequences of events depict-ing daily routine. We found that neural stability patterns gradually increased throughout the ongoing exposure to a schema-consistent episode, which was corroborated by the re-analysis of data from two other experiments, and that the brain stability pattern was interrupted when the encoding of an object of the event was incongru-ent with the ongoing schema. We found that the decrease in neural stability for low-congruence items was seen at similar to 1000 ms from object encoding onset and that it was preceded by an enhanced N400 ERP and an increased degree of neural reactivation of the just-encoded episode. Current results offer new insights into the neural mech-anisms and their temporal orchestration that are engaged during online encoding of schema-consistent episodic narratives and the detection of incongruencies.

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WU, Xiongbo, et al. Contextual incongruency triggers memory reinstatement and the disruption of neural stability. NeuroImage. 2023. Vol. 273. ISSN 1095-9572. [consulted: 10 of August of 2026]. Available at: https://hdl.handle.net/2445/200881

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