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Analysis of the network\u2019s evolution further reveals that the e-prop-trained input layer evolves to route distinct inputs to different regions of the recurrent layer while suppressing the contribution of noise. This partially resembles signal routing functions attributed to the thalamus in mammalian sensory systems, providing additional support for the biological plausibility of e-prop. These findings offer promising insights for efficiency and advantages of biologically inspired training in RSNNs.<\/jats:p>","DOI":"10.1088\/2634-4386\/ae0826","type":"journal-article","created":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T22:53:01Z","timestamp":1758149581000},"page":"044002","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Efficient connectivity and intrinsic noise separation in recurrent spiking neural networks trained with e-prop"],"prefix":"10.1088","volume":"5","author":[{"given":"Davide","family":"No\u00e8","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3362-5376","authenticated-orcid":true,"given":"Hideaki","family":"Yamamoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2773-0786","authenticated-orcid":true,"given":"Yuichi","family":"Katori","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3912-357X","authenticated-orcid":true,"given":"Shigeo","family":"Sato","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2025,10,6]]},"reference":[{"key":"nceae0826bib1","doi-asserted-by":"publisher","first-page":"5998","DOI":"10.48550\/arXiv.1706.03762","type":"other","article-title":"Attention is all you need","volume":"vol 30","author":"Vaswani","year":"2017"},{"key":"nceae0826bib2","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","type":"journal-article","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"nceae0826bib3","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1186\/s12911-024-02459-6","type":"journal-article","article-title":"Assessing the research landscape and clinical utility of large language models: a scoping review","volume":"24","author":"Park","year":"2024","journal-title":"BMC Med. 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