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Flexible reuse of cortico-hippocampal representations during encoding and recall of naturalistic events.


ABSTRACT: Although every life event is unique, there are considerable commonalities across events. However, little is known about whether or how the brain flexibly represents information about different event components at encoding and during remembering. Here, we show that different cortico-hippocampal networks systematically represent specific components of events depicted in videos, both during online experience and during episodic memory retrieval. Regions of an Anterior Temporal Network represented information about people, generalizing across contexts, whereas regions of a Posterior Medial Network represented context information, generalizing across people. Medial prefrontal cortex generalized across videos depicting the same event schema, whereas the hippocampus maintained event-specific representations. Similar effects were seen in real-time and recall, suggesting reuse of event components across overlapping episodic memories. These representational profiles together provide a computationally optimal strategy to scaffold memory for different high-level event components, allowing efficient reuse for event comprehension, recollection, and imagination.

SUBMITTER: Reagh ZM 

PROVIDER: S-EPMC9995562 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Flexible reuse of cortico-hippocampal representations during encoding and recall of naturalistic events.

Reagh Zachariah M ZM   Ranganath Charan C  

Nature communications 20230308 1


Although every life event is unique, there are considerable commonalities across events. However, little is known about whether or how the brain flexibly represents information about different event components at encoding and during remembering. Here, we show that different cortico-hippocampal networks systematically represent specific components of events depicted in videos, both during online experience and during episodic memory retrieval. Regions of an Anterior Temporal Network represented i  ...[more]

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