Selectivity Dilution in Three-Factor Learning: A Finite-Population Model with Potential Implications for Motor Development and Post-Stroke Motor Rehabilitation
- 1The First Affiliated Hospital of University of Science and Technology of China
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.
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BibTeX
@misc{liu2026selectivity,
title = {{Selectivity Dilution in Three-Factor Learning: A Finite-Population Model with Potential Implications for Motor Development and Post-Stroke Motor Rehabilitation}},
author = {Z. Liu and C. Wu and Z. Liu and B. Hu and J. Mu},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.14.759072},
url = {https://www.biorxiv.org/content/10.64898/2026.10.14.759072v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - Selectivity Dilution in Three-Factor Learning: A Finite-Population Model with Potential Implications for Motor Development and Post-Stroke Motor Rehabilitation
AU - Z. Liu
AU - C. Wu
AU - Z. Liu
AU - B. Hu
AU - J. Mu
PY - 2026
DA - 2026/10/14
PB - bioRxiv
DO - 10.64898/2026.10.14.759072
UR - https://www.biorxiv.org/content/10.64898/2026.10.14.759072v1
AB - 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.
ER -