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New Research, Cognition and Behavior

Traces of semantization - from episodic to semantic memory in a spiking cortical network model

Nikolaos Chrysanthidis, Florian Fiebig, Anders Lansner and Pawel Herman
eNeuro 8 July 2022, ENEURO.0062-22.2022; https://doi.org/10.1523/ENEURO.0062-22.2022
Nikolaos Chrysanthidis
1Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 10044 Stockholm, Sweden
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Florian Fiebig
1Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 10044 Stockholm, Sweden
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Anders Lansner
1Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 10044 Stockholm, Sweden
2Department of Mathematics, Stockholm University, 10691 Stockholm, Sweden
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Pawel Herman
1Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 10044 Stockholm, Sweden
3Digital Futures, Stockholm, Sweden
4Swedish e-Science Research Centre, Stockholm, Sweden
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Abstract

Episodic memory is a recollection of past personal experiences associated with particular times and places. This kind of memory is commonly subject to loss of contextual information or” semantization”, which gradually decouples the encoded memory items from their associated contexts while transforming them into semantic or gist-like representations. Novel extensions to the classical Remember/Know behavioral paradigm attribute the loss of episodicity to multiple exposures of an item in different contexts. Despite recent advancements explaining semantization at a behavioral level, the underlying neural mechanisms remain poorly understood. In this study, we suggest and evaluate a novel hypothesis proposing that Bayesian-Hebbian synaptic plasticity mechanisms might cause semantization of episodic memory. We implement a cortical spiking neural network model with a Bayesian-Hebbian learning rule called Bayesian Confidence Propagation Neural Network (BCPNN), which captures the semantization phenomenon and offers a mechanistic explanation for it. Encoding items across multiple contexts leads to item-context decoupling akin to semantization. We compare BCPNN plasticity with the more commonly used spike-timing dependent plasticity (STDP) learning rule in the same episodic memory task. Unlike BCPNN, STDP does not explain the decontextualization process. We further examine how selective plasticity modulation of isolated salient events may enhance preferential retention and resistance to semantization. Our model reproduces important features of episodicity on behavioral timescales under various biological constraints whilst also offering a novel neural and synaptic explanation for semantization, thereby casting new light on the interplay between episodic and semantic memory processes.

Significance Statement

Remembering single episodes is a fundamental attribute of cognition. Difficulties recollecting contextual information is a key sign of episodic memory loss or semantization. Behavioral studies demonstrate that semantization of episodic memory can occur rapidly, yet the neural mechanisms underlying this effect are insufficiently investigated. In line with recent behavioral findings, we show that multiple stimulus exposures in different contexts may advance item-context decoupling. We suggest a Bayesian-Hebbian synaptic plasticity hypothesis of memory semantization and further show that a transient modulation of plasticity during salient events may disrupt the decontextualization process by strengthening memory traces, and thus, enhancing preferential retention. The proposed cortical network-of-networks model thus bridges micro and mesoscale synaptic effects with network dynamics and behavior.

  • Bayesian-Hebbian plasticity
  • BCPNN
  • Episodic memory
  • Semantization
  • Spiking cortical memory model
  • STDP

Footnotes

  • The authors declare no competing financial interests.

  • This research was supported by Swedish Research Council 2018-05360. The simulations were enabled by resources provided by Swedish National Infrastructure for Computing (SNIC) at the PDC Center for High Performance Computing, KTH Royal Institute of Technology.

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

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Traces of semantization - from episodic to semantic memory in a spiking cortical network model
Nikolaos Chrysanthidis, Florian Fiebig, Anders Lansner, Pawel Herman
eNeuro 8 July 2022, ENEURO.0062-22.2022; DOI: 10.1523/ENEURO.0062-22.2022

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Traces of semantization - from episodic to semantic memory in a spiking cortical network model
Nikolaos Chrysanthidis, Florian Fiebig, Anders Lansner, Pawel Herman
eNeuro 8 July 2022, ENEURO.0062-22.2022; DOI: 10.1523/ENEURO.0062-22.2022
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Keywords

  • Bayesian-Hebbian plasticity
  • BCPNN
  • episodic memory
  • Semantization
  • Spiking cortical memory model
  • STDP

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