Feedback-Driven Dynamical Model for Axonal Extension on Parallel Micropatterns
Year: 2025
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: Cheng, Kyle, Kumarasinghe, Udathari, Staii, Cristian
Institution: Tufts University
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W6891906740
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