Distributed representations in memory: insights from functional brain imaging.
Distributed representations in memory: insights from functional brain imaging.
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DOI：
10.1146/annurev-psych-120710-100344
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发表时间：
2012
影响因子：
24.8
通讯作者：
Wagner AD
中科院分区：
文献类型：
--
作者：
Rissman J;Wagner AD
对事实和事件形成新的记忆，每时每刻记住关键的细节，以及为当前目标检索知识，都依赖于整个大脑神经系统之间复杂的相互作用。在过去的十年中，研究人员越来越多地利用强大的分析工具（例如，多体素模式分析）以解码分布式fMRI活动模式内表示的信息。在这篇综述中，我们讨论了这些方法如何敏感地索引感知和语义内容的神经表征，以及如何利用分布式表征的参与为记忆引导行为的不同方面提供独特的见解。我们强调，除了表征记忆的内容，分布式模式的分析揭示了影响信息如何编码，维护或检索的过程，从而为记忆理论提供信息。最后，我们强调开放的问题，可以通过分布式模式分析解决的内存。
Forging new memories for facts and events, holding critical details in mind on a moment-to-moment basis, and retrieving knowledge in the service of current goals all depend on a complex interplay between neural ensembles throughout the brain. Over the past decade, researchers have increasingly leveraged powerful analytical tools (e.g., multi-voxel pattern analysis) to decode the information represented within distributed fMRI activity patterns. In this review, we discuss how these methods can sensitively index neural representations of perceptual and semantic content, and how leverage on the engagement of distributed representations provides unique insights into distinct aspects of memory-guided behavior. We emphasize that, in addition to characterizing the contents of memories, analyses of distributed patterns shed light on the processes that influence how information is encoded, maintained, or retrieved, and thus inform memory theory. We conclude by highlighting open questions about memory that can be addressed through distributed pattern analyses.