---
title: "Selectivity Dilution in Three-Factor Learning: Implications for Motor Development and Post-Stroke"
id: "biorxiv-6-selectivity-dilution-in-three-factor-learning-a-finite-population-model-with"
canonical_url: "https://medichelpline.com/clinical-feed/biorxiv-6-selectivity-dilution-in-three-factor-learning-a-finite-population-model-with"
content_type: "clinical_feed_article"
specialty: "Neurology"
source_name: "bioRxiv (Biomedical Preprints)"
source_url: "https://www.biorxiv.org/content/10.64898/2026.10.14.759072v1?rss=1"
published_at: "2026-10-20T12:00:00.000Z"
evidence_level: "Verified Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Selectivity Dilution in Three-Factor Learning: Implications for Motor Development and Post-Stroke
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/biorxiv-6-selectivity-dilution-in-three-factor-learning-a-finite-population-model-with
- **Specialty:** [Neurology](https://medichelpline.com/clinical-feed/neurology.md)
- **Primary Source:** bioRxiv (Biomedical Preprints)
- **Source URL:** [Original Journal Publication](https://www.biorxiv.org/content/10.64898/2026.10.14.759072v1?rss=1)
- **Published At:** 2026-10-20T12:00:00.000Z
- **Evidence Rating:** Verified Feed
## Executive GIST (TL;DR)
- The authors propose a finite-population model addressing **selectivity dilution** within **three-factor learning** rules; the framework links synaptic reinforcement dynamics to early motor experience and rehabilitation. - Three-factor rules convert short-lived eligibility traces into lasting synaptic change via a broadcast neuromodulatory reinforcement signal, the paper explained. - Because the reinforcement signal is broadcast, it can strengthen all eligible synapses active at reinforcement time, not exclusively those causally responsible for a successful action; the model frames this as 'selectivity dilution.' - The manuscript contrasts two mechanical environments: fetal movement in buoyant, low-resistance amniotic fluid versus post-stroke motor recovery in normal-gravity conditions without a fluid phase. - The authors posed the central testable question: does the absence of a low-resistance, fluid phase after stroke impair selective synaptic reinforcement and thereby hinder functional motor recovery? - The paper suggests this framework could inform biologically plausible learning algorithms for artificial systems, but it did not report experimental protocols, parameter values, nor direct empirical tests in clinical populations. - Investigators noted potential relevance to both early motor development—where buoyancy reduces gravitational load and enables spontaneous low-resistance movement—and to neurorehabilitation strategies after stroke. - The preprint did not provide peer-reviewed validation; authors listed funding sources and declared no competing interests. The study remains theoretical and hypothesis-generating pending empirical work.
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Zheng Liu 1 The First Affiliated Hospital of University of Science and Technology of China; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Zheng%2BLiu%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Liu%20Z&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AZheng%2BLiu%2B) * [ORCID record for Zheng Liu](http://orcid.org/0000-0002-5273-3826 "Open in new tab") Chunyu Wu 1 The First Affiliated Hospital of University of Science and Technology of China; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Chunyu%2BWu%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Wu%20C&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AChunyu%2BWu%2B) * [ORCID record for Chunyu Wu](http://orcid.org/0009-0004-1736-3382 "Open in new tab") Zhenhao Liu 2 Hefei University of Technology; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Zhenhao%2BLiu%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Liu%20Z&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AZhenhao%2BLiu%2B) * [ORCID record for Zhenhao Liu](http://orcid.org/0009-0001-8840-9307 "Open in new tab") Baohua Hu 3 Hefei University * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Baohua%2BHu%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Hu%20B&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3ABaohua%2BHu%2B) * [ORCID record for Baohua Hu](http://orcid.org/0000-0002-0408-4550 "Open in new tab") Jingsong Mu 1 The First Affiliated Hospital of University of Science and Technology of China; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Jingsong%2BMu%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Mu%20J&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AJingsong%2BMu%2B) * [ORCID record for Jingsong Mu](http://orcid.org/0000-0001-8282-8175 "Open in new tab") * For correspondence: jsmu@ustc.edu.cn * [Abstract](https://www.biorxiv.org/content/10.64898/2026.10.14.759072v1)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_art/node:5885456/1) * [Info/History](https://www.biorxiv.org/content/10.64898/2026.10.14.759072v1.article-info)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_info/node:5885456/1) * [Metrics](https://www.biorxiv.org/content/10.64898/2026.10.14.759072v1.article-metrics)[](https://www.biorxiv.org/panels_ajax_tab/article_tab_metrics/node:5885456/1) * [Supplementary material](https://www.biorxiv.org/content/10.64898/2026.10.14.759072v1.supplementary-material)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_data/node:5885456/1) * [Data/Code](https://www.biorxiv.org/content/10.64898/2026.10.14.759072v1.external-links)[](https://www.biorxiv.org/panels_ajax_tab/article_tab_data_code/node:5885456/1) * [ Preview PDF](https://www.biorxiv.org/content/10.64898/2026.10.14.759072v1.full.pdf+html)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_pdf/node:5885456/1) ![Loading](https://www.biorxiv.org/sites/all/modules/contrib/panels_ajax_tab/images/loading.gif) ## Abstract Motor development and post-stroke motor recovery may share underlying learning mechanisms, but the early mechanical environments of the two processes differ strikingly. During early development the fetus moves within amniotic fluid, where buoyancy substantially reduces gravitational load and enables spontaneous low-resistance movement; in contrast, post-stroke motor reconstruction occurs without this fluid low-resistance phase. Whether and how the absence of a fluid low-resistance phase influences post-stroke functional recovery is the central testable question raised by the selectivity dilution framework. Three-factor learning rules use broadcast neuromodulatory signals to convert eligibility traces into lasting synaptic changes. Because the signal is broadcast, it may reinforce all eligible synapses that are active during reinforcement without obvious deviation, not only those that caused the successful outcome. This framework offers a testable mechanistic principle for early motor learning and neurorehabilitation, and may inform the design of biologically plausible, non-backpropagation learning algorithms in artificial systems. ### Competing Interest Statement The authors have declared no competing interest. ## Footnotes * ## Funder Information Declared the National Natural Science Foundation of China, 52575276 the Scientific Research Project of Education Department of Anhui Province, 2025AHGXZK40769 Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a [CC-BY-NC 4.0 International license](http://creativecommons.org/licenses/by-nc/4.0/). bioRxiv and medRxiv thank the following for their generous financial support: > The Chan Zuckerberg Initiative, Cold Spring Harbor Laboratory, the Sergey Brin Family Foundation, California Institute of Technology, Centre National de la Recherche Scientifique, Fred Hutchinson Cancer Center, Imperial College London, Massachusetts Institute of Technology, Stanford University, The University of Edinburgh, University of Washington, and Vrije Universiteit Amsterdam. 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[ Download PDF](https://www.biorxiv.org/content/10.64898/2026.10.14.759072v1.full.pdf) Print/Save Options [Download PDF](https://www.biorxiv.org/content/biorxiv/early/2026/10/20/2026.10.14.759072.full.pdf)Full Text & In-line FiguresXML [More Info](https://www.biorxiv.org/about/FAQ#PrintOptions "More Information on Print/Save Options") [Supplementary Material ](https://www.biorxiv.org/content/10.64898/2026.10.14.759072v1.supplementary-material) [ Data/Code](https://www.biorxiv.org/content/early/2026/10/20/2026.10.14.759072.external-links) [ Email](https://www.biorxiv.org/ "Email this Article") [ Share](https://www.biorxiv.org/) Selectivity Dilution in Three-Factor Learning: A Finite-Population Model with Potential Implications for Motor Development and Post-Stroke Motor Rehabilitation Zheng Liu, Chunyu Wu, Zhenhao Liu, Baohua Hu, Jingsong Mu bioRxiv 2026.10.14.759072; doi: https://doi.org/10.64898/2026.10.14.759072 This article is a preprint and has not been certified by peer review [[what does this mean?](https://www.biorxiv.org/about/FAQ#unrefereed)]. 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