Pruning of memories by context-based prediction error

Ghootae Kim; Jarrod A. Lewis-Peacock; Kenneth A. NormanNicholas B. Turk-Browne

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Pruning of memories by context-based prediction error

机译：Pruning of memories by context-based prediction error

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摘要

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.

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《Proceedings of the National Academy of Sciences of the United States of America》 |2014年第24期|8997-9002|共6页
作者
Ghootae Kim; Jarrod A. Lewis-Peacock; Kenneth A. NormanNicholas B. Turk-Browne;
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作者单位

Department of Psychology,Princeton University, Princeton, NJ 08544;

Department of Psychology,University of Texas at Austin, Austin, TX 78712;

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收录信息美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
原文格式 PDF
正文语种英语
中图分类自然科学总论;
关键词
forgetting; learning; multivariate pattern analysis; perception; temporal context;

Pruning of memories by context-based prediction error

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