An Integrated Computational Framework for the Neurobiology of Memory Based on the ACT-R Declarative Memory System

Memory is a complex process that spans multiple time-scales and stages, and, as expected, involves multiple brain regions. Traditionally, computational models of memory are either too abstract (Shiffrin & Steyvers, 1997 ) to be meaningfully connected to a biological substrate, or, when explicitl...

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Veröffentlicht in:Computational brain & behavior 2024-03, Vol.7 (1), p.129-149
Hauptverfasser: Stocco, Andrea, Rice, Patrick, Thomson, Robert, Smith, Briana, Morrison, Don, Lebiere, Christian
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Sprache:eng
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Zusammenfassung:Memory is a complex process that spans multiple time-scales and stages, and, as expected, involves multiple brain regions. Traditionally, computational models of memory are either too abstract (Shiffrin & Steyvers, 1997 ) to be meaningfully connected to a biological substrate, or, when explicitly connected, are narrowly focused on one specific region and process (Blum & Abbott, 1996 ; Weber et al., 2017 ). By contrast, a comprehensive model of memory with a plausible neural interpretation would be extremely valuable to drive further research in memory function and dysfunction. In this paper, we attempt to fill in this gap by providing a detailed biological analysis of ACT-R’s declarative memory system. This system, developed over four decades, has evolved into a consistent framework that describes how memories are formed, retrieved, forgotten, mistaken, and merged. Building on existing mappings between some components and their biological counterpart, as well as the existing literature, this paper provides a comprehensive view of how the framework’s various computations map onto different brain regions, their network dynamics and functional connectivity, and biological structure. We also show that these mappings provide further insights and explanations for puzzling findings in the memory disorders literature. Finally, we outline the remaining gaps (such as the transition from episodic to semantic memory) and how they could be addressed by future research and modeling efforts.
ISSN:2522-0861
2522-087X
DOI:10.1007/s42113-023-00189-y