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Novelty and imitation within the brain: a Darwinian neurodynamic approach to combinatorial problems
Efficient search in vast combinatorial spaces, such as those of possible action sequences, linguistic structures, or causal explanations, is an essential component of intelligence. Is there any computational domain that is flexible enough to provide solutions to such diverse problems and can be robu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8206098/ https://www.ncbi.nlm.nih.gov/pubmed/34131159 http://dx.doi.org/10.1038/s41598-021-91489-5 |
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author | Czégel, Dániel Giaffar, Hamza Csillag, Márton Futó, Bálint Szathmáry, Eörs |
author_facet | Czégel, Dániel Giaffar, Hamza Csillag, Márton Futó, Bálint Szathmáry, Eörs |
author_sort | Czégel, Dániel |
collection | PubMed |
description | Efficient search in vast combinatorial spaces, such as those of possible action sequences, linguistic structures, or causal explanations, is an essential component of intelligence. Is there any computational domain that is flexible enough to provide solutions to such diverse problems and can be robustly implemented over neural substrates? Based on previous accounts, we propose that a Darwinian process, operating over sequential cycles of imperfect copying and selection of neural informational patterns, is a promising candidate. Here we implement imperfect information copying through one reservoir computing unit teaching another. Teacher and learner roles are assigned dynamically based on evaluation of the readout signal. We demonstrate that the emerging Darwinian population of readout activity patterns is capable of maintaining and continually improving upon existing solutions over rugged combinatorial reward landscapes. We also demonstrate the existence of a sharp error threshold, a neural noise level beyond which information accumulated by an evolutionary process cannot be maintained. We introduce a novel analysis method, neural phylogenies, that displays the unfolding of the neural-evolutionary process. |
format | Online Article Text |
id | pubmed-8206098 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-82060982021-06-16 Novelty and imitation within the brain: a Darwinian neurodynamic approach to combinatorial problems Czégel, Dániel Giaffar, Hamza Csillag, Márton Futó, Bálint Szathmáry, Eörs Sci Rep Article Efficient search in vast combinatorial spaces, such as those of possible action sequences, linguistic structures, or causal explanations, is an essential component of intelligence. Is there any computational domain that is flexible enough to provide solutions to such diverse problems and can be robustly implemented over neural substrates? Based on previous accounts, we propose that a Darwinian process, operating over sequential cycles of imperfect copying and selection of neural informational patterns, is a promising candidate. Here we implement imperfect information copying through one reservoir computing unit teaching another. Teacher and learner roles are assigned dynamically based on evaluation of the readout signal. We demonstrate that the emerging Darwinian population of readout activity patterns is capable of maintaining and continually improving upon existing solutions over rugged combinatorial reward landscapes. We also demonstrate the existence of a sharp error threshold, a neural noise level beyond which information accumulated by an evolutionary process cannot be maintained. We introduce a novel analysis method, neural phylogenies, that displays the unfolding of the neural-evolutionary process. Nature Publishing Group UK 2021-06-15 /pmc/articles/PMC8206098/ /pubmed/34131159 http://dx.doi.org/10.1038/s41598-021-91489-5 Text en © The Author(s) 2021 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 | Article Czégel, Dániel Giaffar, Hamza Csillag, Márton Futó, Bálint Szathmáry, Eörs Novelty and imitation within the brain: a Darwinian neurodynamic approach to combinatorial problems |
title | Novelty and imitation within the brain: a Darwinian neurodynamic approach to combinatorial problems |
title_full | Novelty and imitation within the brain: a Darwinian neurodynamic approach to combinatorial problems |
title_fullStr | Novelty and imitation within the brain: a Darwinian neurodynamic approach to combinatorial problems |
title_full_unstemmed | Novelty and imitation within the brain: a Darwinian neurodynamic approach to combinatorial problems |
title_short | Novelty and imitation within the brain: a Darwinian neurodynamic approach to combinatorial problems |
title_sort | novelty and imitation within the brain: a darwinian neurodynamic approach to combinatorial problems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8206098/ https://www.ncbi.nlm.nih.gov/pubmed/34131159 http://dx.doi.org/10.1038/s41598-021-91489-5 |
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