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PERSPECTIVE article

Front. Comput. Neurosci.
Volume 18 - 2024 | doi: 10.3389/fncom.2024.1538741
This article is part of the Research Topic Hippocampal Function and Reinforcement Learning View all 5 articles

Memory consolidation from a reinforcement learning perspective

Provisionally accepted
  • 1 Institute for Basic Science (IBS), Daejeon, Daejeon, Republic of Korea
  • 2 Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea

The final, formatted version of the article will be published soon.

    Memory consolidation refers to the process of converting temporary memories into longlasting ones. It is widely accepted that new experiences are initially stored in the hippocampus as rapid associative memories, which then undergo a consolidation process to establish more permanent traces in other regions of the brain. Over the past two decades, studies in humans and animals have demonstrated that the hippocampus is crucial not only for memory but also for imagination and future planning, with the CA3 region playing a pivotal role in generating novel activity patterns. Additionally, a growing body of evidence indicates the involvement of the hippocampus, especially the CA1 region, in valuation processes. Based on these findings, we propose that the CA3 region of the hippocampus generates diverse activity patterns, while the CA1 region evaluates and reinforces those patterns most likely to maximize rewards. This framework closely parallels Dyna, a reinforcement learning algorithm introduced by Sutton in 1991. In Dyna, an agent performs offline simulations to supplement trial-and-error value learning, greatly accelerating the learning process. We suggest that memory consolidation might be viewed as a process of deriving optimal strategies based on simulations derived from limited experiences, rather than merely strengthening incidental memories. From this perspective, memory consolidation functions as a form of offline reinforcement learning, aimed at enhancing adaptive decision-making.

    Keywords: Simulation-selection model, offline learning, value, DYNA, Imagination, CA3, CA1

    Received: 03 Dec 2024; Accepted: 24 Dec 2024.

    Copyright: © 2024 Lee and Jung. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Jong W Lee, Institute for Basic Science (IBS), Daejeon, 34126, Daejeon, Republic of Korea
    Min W Jung, Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 305-701, Republic of Korea

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