Synaptic Spine Head Morphodynamics from Graph Grammar Rules for Actin Dynamics DOI Creative Commons
Matthew Hur, Thomas M. Bartol, Padmini Rangamani

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: April 21, 2025

There is a morphodynamic component to synaptic learning by which changes in dendritic spine head size are associated with the strengthening or weakening of connection between two neurons, response temporal correlation local presynaptic and postsynaptic signals. Morphological factors turn sculpted dynamics actin cytoskeleton. We use Dynamical Graph Grammars (DGGs) implemented within computer algebra system model how networks filaments can dynamically grow shrink, reshaping head. DGGs provide well-defined way accommodate changing structure such as active cytoskeleton represented using dynamic graphs, nonequilibrium statistical physics under master equation. show that also incorporate biophysical forces graph-connected objects at finer time scale, specialized DGG kinetic rules obeying constraints Galilean invariance, conservation momentum, dissipation conserved global energy. graph-local energy functions for interacting membranes, derive from specialization dissipative stochastic mutually exclusive exhaustive collection neighborhood types rule left hand sides. Dissipative comprise version gradient descent dynamics. Thermal noise Gaussian approximation each position coordinate sample jitter-like displacements. designed grammar sub-models including network growth, non-equilibrium mechanics, filament-membrane mechanical interaction regulate re-writing graph objects. From biological perspective, we observe regulatory effects three actin-binding proteins on membrane find evidence supporting mechanisms growth.

Language: Английский

Synaptic Spine Head Morphodynamics from Graph Grammar Rules for Actin Dynamics DOI Creative Commons
Matthew Hur, Thomas M. Bartol, Padmini Rangamani

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: April 21, 2025

There is a morphodynamic component to synaptic learning by which changes in dendritic spine head size are associated with the strengthening or weakening of connection between two neurons, response temporal correlation local presynaptic and postsynaptic signals. Morphological factors turn sculpted dynamics actin cytoskeleton. We use Dynamical Graph Grammars (DGGs) implemented within computer algebra system model how networks filaments can dynamically grow shrink, reshaping head. DGGs provide well-defined way accommodate changing structure such as active cytoskeleton represented using dynamic graphs, nonequilibrium statistical physics under master equation. show that also incorporate biophysical forces graph-connected objects at finer time scale, specialized DGG kinetic rules obeying constraints Galilean invariance, conservation momentum, dissipation conserved global energy. graph-local energy functions for interacting membranes, derive from specialization dissipative stochastic mutually exclusive exhaustive collection neighborhood types rule left hand sides. Dissipative comprise version gradient descent dynamics. Thermal noise Gaussian approximation each position coordinate sample jitter-like displacements. designed grammar sub-models including network growth, non-equilibrium mechanics, filament-membrane mechanical interaction regulate re-writing graph objects. From biological perspective, we observe regulatory effects three actin-binding proteins on membrane find evidence supporting mechanisms growth.

Language: Английский

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