Feedback-Driven Dynamical Model for Axonal Extension on Parallel Micropatterns

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Hauptverfasser: Cheng, Kyle, Kumarasinghe, Udathari, Staii, Cristian
Format: Preprint
Veröffentlicht: 2025
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author Cheng, Kyle
Kumarasinghe, Udathari
Staii, Cristian
author_facet Cheng, Kyle
Kumarasinghe, Udathari
Staii, Cristian
contents Despite significant advances in understanding neuronal development, a fully quantitative framework that integrates intracellular mechanisms with environmental cues during axonal growth remains incomplete. Here, we present a unified biophysical model that captures key mechanochemical processes governing axonal extension on micropatterned substrates. In these environments, axons preferentially align with the pattern direction, form bundles, and advance at constant speed. The model integrates four core components: (i) actin-adhesion traction coupling, (ii) lateral inhibition between neighboring axons, (iii) tubulin transport from soma to the growth cone, and (4) orientation dynamics guided by the substrate anisotropy. Dynamical systems analysis reveals that the saddle-node bifurcation in the actin adhesion subsystem drives a transition to a high-traction motile state, while traction feedback shifts a pitchfork bifurcation in the signaling loop, promoting symmetry breaking and robust alignment. An exact linear solution in the tubulin transport subsystem functions as a built-in speed regulator, ensuring stable elongation rates. Simulations using experimentally inferred parameters accurately reproduce elongation speed, alignment variance, and bundle spacing. The model provides explicit design rules for enhancing axonal alignment through modulation of substrate stiffness and adhesion dynamics. By identifying key control parameters, this work enables rational design of biomaterials for neural repair and engineered tissue systems.
format Preprint
id arxiv_https___arxiv_org_abs_2505_13361
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Feedback-Driven Dynamical Model for Axonal Extension on Parallel Micropatterns
Cheng, Kyle
Kumarasinghe, Udathari
Staii, Cristian
Neurons and Cognition
Adaptation and Self-Organizing Systems
Cell Behavior
Quantitative Methods
Despite significant advances in understanding neuronal development, a fully quantitative framework that integrates intracellular mechanisms with environmental cues during axonal growth remains incomplete. Here, we present a unified biophysical model that captures key mechanochemical processes governing axonal extension on micropatterned substrates. In these environments, axons preferentially align with the pattern direction, form bundles, and advance at constant speed. The model integrates four core components: (i) actin-adhesion traction coupling, (ii) lateral inhibition between neighboring axons, (iii) tubulin transport from soma to the growth cone, and (4) orientation dynamics guided by the substrate anisotropy. Dynamical systems analysis reveals that the saddle-node bifurcation in the actin adhesion subsystem drives a transition to a high-traction motile state, while traction feedback shifts a pitchfork bifurcation in the signaling loop, promoting symmetry breaking and robust alignment. An exact linear solution in the tubulin transport subsystem functions as a built-in speed regulator, ensuring stable elongation rates. Simulations using experimentally inferred parameters accurately reproduce elongation speed, alignment variance, and bundle spacing. The model provides explicit design rules for enhancing axonal alignment through modulation of substrate stiffness and adhesion dynamics. By identifying key control parameters, this work enables rational design of biomaterials for neural repair and engineered tissue systems.
title Feedback-Driven Dynamical Model for Axonal Extension on Parallel Micropatterns
topic Neurons and Cognition
Adaptation and Self-Organizing Systems
Cell Behavior
Quantitative Methods
url https://arxiv.org/abs/2505.13361