Inducing brain-like sleep in an artificial spiking neural network helps it to keep learning without “catastrophic forgetting”

Article URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010628

Press-only preview: https://plos.io/3fsE1Tl

Image Caption: Representation of memories in an abstract synaptic space and its evolution with and without sleep.

Image Credit: Golden R, Delanois JE, Sanda P, and Bazhenov M, 2022, PLOS Computational Biology, CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/)

Image URL: https://plos.io/3sVvivP

Article Title: Sleep prevents catastrophic forgetting in spiking neural networks by forming a joint synaptic weight representation

Author Countries: United States, Czech Republic

Funding: This study was supported by ONR (N00014-16-1-2829 to MB), Lifelong Learning Machines program from DARPA/MTO (HR0011-18-2-0021 to MB), NSF (IIS-1724405 to MB), and NIH (1RF1MH117155 to MB; 1R01MH125557 to MB; 1R01NS109553 to MB). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

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