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Rapid Memory Encoding in a Spiking Hippocampus Circuit Model.

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Title: Rapid Memory Encoding in a Spiking Hippocampus Circuit Model.
Authors: Wang, Jiashuo (AUTHOR), Yuan, Mengwen (AUTHOR), Shen, Jiangrong (AUTHOR), Chai, Qingao (AUTHOR), Tang, Huajin (AUTHOR)
Source: Neural Computation. Jul2025, Vol. 37 Issue 7, p1320-1352. 33p.
Subjects: Dentate gyrus, Episodic memory, Neural circuitry, Sensory memory, Learning strategies
Abstract: Memory is a complex process in the brain that involves the encoding, consolidation, and retrieval of previously experienced stimuli. The brain is capable of rapidly forming memories of sensory input. However, applying the memory system to real-world data poses challenges in practical implementation. This article demonstrates that through the integration of sparse spike pattern encoding scheme population tempotron, and various spike-timing-dependent plasticity (STDP) learning rules, supported by bounded weights and biological mechanisms, it is possible to rapidly form stable neural assemblies of external sensory inputs in a spiking neural circuit model inspired by the hippocampal structure. The model employs neural ensemble module and competitive learning strategies that mimic the pattern separation mechanism of the hippocampal dentate gyrus (DG) area to achieve nonoverlapping sparse coding. It also uses population tempotron and NMDA-(N-methyl-D-aspartate)mediated STDP to construct associative and episodic memories, analogous to the CA3 and CA1 regions. These memories are represented by strongly connected neural assemblies formed within just a few trials. Overall, this model offers a robust computational framework to accommodate rapid memory throughout the brain-wide memory process. [ABSTRACT FROM AUTHOR]
Copyright of Neural Computation is the property of MIT Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Rapid Memory Encoding in a Spiking Hippocampus Circuit Model.
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  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Jiashuo%22">Wang, Jiashuo</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yuan%2C+Mengwen%22">Yuan, Mengwen</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shen%2C+Jiangrong%22">Shen, Jiangrong</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chai%2C+Qingao%22">Chai, Qingao</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tang%2C+Huajin%22">Tang, Huajin</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Neural+Computation%22">Neural Computation</searchLink>. Jul2025, Vol. 37 Issue 7, p1320-1352. 33p.
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  Data: <searchLink fieldCode="DE" term="%22Dentate+gyrus%22">Dentate gyrus</searchLink><br /><searchLink fieldCode="DE" term="%22Episodic+memory%22">Episodic memory</searchLink><br /><searchLink fieldCode="DE" term="%22Neural+circuitry%22">Neural circuitry</searchLink><br /><searchLink fieldCode="DE" term="%22Sensory+memory%22">Sensory memory</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+strategies%22">Learning strategies</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Memory is a complex process in the brain that involves the encoding, consolidation, and retrieval of previously experienced stimuli. The brain is capable of rapidly forming memories of sensory input. However, applying the memory system to real-world data poses challenges in practical implementation. This article demonstrates that through the integration of sparse spike pattern encoding scheme population tempotron, and various spike-timing-dependent plasticity (STDP) learning rules, supported by bounded weights and biological mechanisms, it is possible to rapidly form stable neural assemblies of external sensory inputs in a spiking neural circuit model inspired by the hippocampal structure. The model employs neural ensemble module and competitive learning strategies that mimic the pattern separation mechanism of the hippocampal dentate gyrus (DG) area to achieve nonoverlapping sparse coding. It also uses population tempotron and NMDA-(N-methyl-D-aspartate)mediated STDP to construct associative and episodic memories, analogous to the CA3 and CA1 regions. These memories are represented by strongly connected neural assemblies formed within just a few trials. Overall, this model offers a robust computational framework to accommodate rapid memory throughout the brain-wide memory process. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Neural Computation is the property of MIT Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1162/neco_a_01762
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      – Code: eng
        Text: English
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      – SubjectFull: Dentate gyrus
        Type: general
      – SubjectFull: Episodic memory
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      – SubjectFull: Neural circuitry
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      – SubjectFull: Sensory memory
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      – SubjectFull: Learning strategies
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      – TitleFull: Rapid Memory Encoding in a Spiking Hippocampus Circuit Model.
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            NameFull: Yuan, Mengwen
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            NameFull: Chai, Qingao
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            – D: 01
              M: 07
              Text: Jul2025
              Type: published
              Y: 2025
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