Cargando…
Neural kernels for recursive support vector regression as a model for episodic memory
Retrieval of episodic memories requires intrinsic reactivation of neuronal activity patterns. The content of the memories is thereby assumed to be stored in synaptic connections. This paper proposes a theory in which these are the synaptic connections that specifically convey the temporal order info...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170657/ https://www.ncbi.nlm.nih.gov/pubmed/35348879 http://dx.doi.org/10.1007/s00422-022-00926-9 |
_version_ | 1784721483081187328 |
---|---|
author | Leibold, Christian |
author_facet | Leibold, Christian |
author_sort | Leibold, Christian |
collection | PubMed |
description | Retrieval of episodic memories requires intrinsic reactivation of neuronal activity patterns. The content of the memories is thereby assumed to be stored in synaptic connections. This paper proposes a theory in which these are the synaptic connections that specifically convey the temporal order information contained in the sequences of a neuronal reservoir to the sensory-motor cortical areas that give rise to the subjective impression of retrieval of sensory motor events. The theory is based on a novel recursive version of support vector regression that allows for efficient continuous learning that is only limited by the representational capacity of the reservoir. The paper argues that hippocampal theta sequences are a potential neural substrate underlying this reservoir. The theory is consistent with confabulations and post hoc alterations of existing memories. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00422-022-00926-9. |
format | Online Article Text |
id | pubmed-9170657 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-91706572022-06-08 Neural kernels for recursive support vector regression as a model for episodic memory Leibold, Christian Biol Cybern Original Article Retrieval of episodic memories requires intrinsic reactivation of neuronal activity patterns. The content of the memories is thereby assumed to be stored in synaptic connections. This paper proposes a theory in which these are the synaptic connections that specifically convey the temporal order information contained in the sequences of a neuronal reservoir to the sensory-motor cortical areas that give rise to the subjective impression of retrieval of sensory motor events. The theory is based on a novel recursive version of support vector regression that allows for efficient continuous learning that is only limited by the representational capacity of the reservoir. The paper argues that hippocampal theta sequences are a potential neural substrate underlying this reservoir. The theory is consistent with confabulations and post hoc alterations of existing memories. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00422-022-00926-9. Springer Berlin Heidelberg 2022-03-29 2022 /pmc/articles/PMC9170657/ /pubmed/35348879 http://dx.doi.org/10.1007/s00422-022-00926-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Leibold, Christian Neural kernels for recursive support vector regression as a model for episodic memory |
title | Neural kernels for recursive support vector regression as a model for episodic memory |
title_full | Neural kernels for recursive support vector regression as a model for episodic memory |
title_fullStr | Neural kernels for recursive support vector regression as a model for episodic memory |
title_full_unstemmed | Neural kernels for recursive support vector regression as a model for episodic memory |
title_short | Neural kernels for recursive support vector regression as a model for episodic memory |
title_sort | neural kernels for recursive support vector regression as a model for episodic memory |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170657/ https://www.ncbi.nlm.nih.gov/pubmed/35348879 http://dx.doi.org/10.1007/s00422-022-00926-9 |
work_keys_str_mv | AT leiboldchristian neuralkernelsforrecursivesupportvectorregressionasamodelforepisodicmemory |