Novelty and imitation within the brain: a Darwinian neurodynamic approach to combinatorial problems

Czégel, Dániel, Giaffar, Hamza, Csillag, Márton, Futó, Bálint, Szathmáry, Eörs (June 2021) Novelty and imitation within the brain: a Darwinian neurodynamic approach to combinatorial problems. Scientific reports, 11 (1). p. 12513. ISSN 2045-2322

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DOI: 10.1038/s41598-021-91489-5


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.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > computational biology
CSHL Authors:
Communities: School of Biological Sciences > Publications
Depositing User: Sasha Luks-Morgan
Date: 15 June 2021
Date Deposited: 23 Jun 2021 13:29
Last Modified: 29 Feb 2024 19:52
PMCID: PMC8206098

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