A Review of Short-Term, Long-Term, and Memory Consolidation Mechanisms in the Hippocampus and Cerebral Cortex

Learning and memory have long been a focal point of research across neuroscience and artificial intelligence. A deep understanding of the neural mechanisms underlying learning and memory is necessary to advance artificial intelligence capabilities. Considering this, we review neuroscience principles...

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Main Authors: Zuomin Yang, Anis Salwa Binti Mohd Khairuddin, Joon Huang Chuah, Wei Ru Wong, Hafiz Muhammad Fahad Noman, Tri Wahyu Oktaviana Putri, Xin Xu, Md Minhazul Haq
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
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Online Access:https://ieeexplore.ieee.org/document/10942600/
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Summary:Learning and memory have long been a focal point of research across neuroscience and artificial intelligence. A deep understanding of the neural mechanisms underlying learning and memory is necessary to advance artificial intelligence capabilities. Considering this, we review neuroscience principles about learning and memory in the hippocampus and cerebral cortex (neocortex). Specifically, we present the different stages of learning and memory, including short-term memory (STM), long-term memory (LTM), and memory consolidation. Moreover, this work aims to translate neuroscience’s mechanisms of learning and memory to intelligent agents, enabling machines with human-like learning, memory, cognitive, and decision-making functions. We discuss a foundational overview of cutting-edge research on continuous learning and memory in artificial intelligence. In addition, we analyze the limitations and research prospects in long-term and short-term memory for continuous learning, providing a solid theoretical groundwork for future advancements.
ISSN:2169-3536