Prediction errors disrupt hippocampal representations and update episodic memories.
Journal Article (Journal Article)
The brain supports adaptive behavior by generating predictions, learning from errors, and updating memories to incorporate new information. Prediction error, or surprise, triggers learning when reality contradicts expectations. Prior studies have shown that the hippocampus signals prediction errors, but the hypothesized link to memory updating has not been demonstrated. In a human functional MRI study, we elicited mnemonic prediction errors by interrupting familiar narrative videos immediately before the expected endings. We found that prediction errors reversed the relationship between univariate hippocampal activation and memory: greater hippocampal activation predicted memory preservation after expected endings, but memory updating after surprising endings. In contrast to previous studies, we show that univariate activation was insufficient for understanding hippocampal prediction error signals. We explain this surprising finding by tracking both the evolution of hippocampal activation patterns and the connectivity between the hippocampus and neuromodulatory regions. We found that hippocampal activation patterns stabilized as each narrative episode unfolded, suggesting sustained episodic representations. Prediction errors disrupted these sustained representations and the degree of disruption predicted memory updating. The relationship between hippocampal activation and subsequent memory depended on concurrent basal forebrain activation, supporting the idea that cholinergic modulation regulates attention and memory. We conclude that prediction errors create conditions that favor memory updating, prompting the hippocampus to abandon ongoing predictions and make memories malleable.
Full Text
Duke Authors
Cited Authors
- Sinclair, AH; Manalili, GM; Brunec, IK; Adcock, RA; Barense, MD
Published Date
- December 21, 2021
Published In
Volume / Issue
- 118 / 51
PubMed ID
- 34911768
Pubmed Central ID
- PMC8713973
Electronic International Standard Serial Number (EISSN)
- 1091-6490
Digital Object Identifier (DOI)
- 10.1073/pnas.2117625118
Language
- eng
Conference Location
- United States