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Pruning of memories by context-based prediction error.

ABSTRACT: The capacity of long-term memory is thought to be virtually unlimited. However, our memory bank may need to be pruned regularly to ensure that the information most important for behavior can be stored and accessed efficiently. Using functional magnetic resonance imaging of the human brain, we report the discovery of a context-based mechanism for determining which memories to prune. Specifically, when a previously experienced context is reencountered, the brain automatically generates predictions about which items should appear in that context. If an item fails to appear when strongly expected, its representation in memory is weakened, and it is more likely to be forgotten. We find robust support for this mechanism using multivariate pattern classification and pattern similarity analyses. The results are explained by a model in which context-based predictions activate item representations just enough for them to be weakened during a misprediction. These findings reveal an ongoing and adaptive process for pruning unreliable memories.

SUBMITTER: Kim G

PROVIDER: S-EPMC4066528 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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Pruning of memories by context-based prediction error.

Kim Ghootae G Lewis-Peacock Jarrod A JA Norman Kenneth A KA Turk-Browne Nicholas B NB

Proceedings of the National Academy of Sciences of the United States of America 20140602 24

The capacity of long-term memory is thought to be virtually unlimited. However, our memory bank may need to be pruned regularly to ensure that the information most important for behavior can be stored and accessed efficiently. Using functional magnetic resonance imaging of the human brain, we report the discovery of a context-based mechanism for determining which memories to prune. Specifically, when a previously experienced context is reencountered, the brain automatically generates predictions ...[more]

PMID: 24889631

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Project description:Reactivation of consolidated memories can induce a labile period, in which these reactivated memories might be susceptible to change and need reconsolidation. Prediction error (PE) has been recognized as a necessary boundary condition for memory destabilization. Moreover, memory strength is also widely accepted as an essential boundary condition to destabilize fear memory. This study investigated whether different strengths of conditioned fear memories require different degrees of PE during memory reactivation in order for the memories to become destabilized. Here, we assessed the fear-potentiated startle and skin conductance response, using the post-retrieval extinction procedure. A violation of expectancy (PE) was induced during retrieval to reactivate enhanced (unpredictable-shock) or ordinary (predictable-shock) fear memories that were established the day before. Results showed that a PE retrieval before extinction can prevent the return of predictable-shock fear memory but cannot prevent the return of unpredictable-shock fear memory, indicating that a single PE is insufficient to destabilize enhanced fear memory. Therefore, we further investigated whether increasing the degree of PE could destabilize enhanced fear memory using different retrieval strategies (multiple PE retrieval and unreinforced CS retrieval). We found that spontaneous recovery of enhanced fear memory was prevented in both retrieval strategies, but reinstatement was only prevented in the multiple PE retrieval group, suggesting that a larger amount of PE is needed to destabilize enhanced fear memory. The findings suggest that behavioral updating during destabilization requires PE, and the degree of PE needed to induce memory destabilization during memory retrieval depends on the strength of fear memory. The study indicates that memory reconsolidation inference can be used to destabilize stronger memories, and the findings shed lights on the treatment of posttraumatic stress disorders and anxiety disorders.

Dataset Information

Pruning of memories by context-based prediction error.

Publications

Pruning of memories by context-based prediction error.

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