Tracking the Morphological Evolution of Neuronal Dendrites by First-Passage Analysis

TL;DR

This paper introduces a novel noninvasive method using first-passage analysis of diffusive signals to monitor the morphological evolution of neuronal dendrites, aiding in early detection of neurodegenerative changes.

Contribution

It presents a stochastic coarse-grained model linking dendrite morphology to measurable signals, enabling indirect assessment of neurodegenerative progression.

Findings

Establishes a quantitative relationship between dendrite structure and signal characteristics.

Proposes a feasible experimental setup using mRNA-carrying liposomes for signal detection.

Provides a rapid, noninvasive technique for monitoring dendritic morphological changes.

Abstract

A high degree of structural complexity arises in dynamic neuronal dendrites due to extensive branching patterns and diverse spine morphologies, which enable the nervous system to adjust function, construct complex input pathways and thereby enhance the computational power of the system. Owing to the determinant role of dendrite morphology in the functionality of the nervous system, recognition of pathological changes due to neurodegenerative disorders is of crucial importance. We show that the statistical analysis of a temporary signal generated by cargos that have diffusively passed through the complex dendritic structure yields vital information about dendrite morphology. As a feasible scenario, we propose engineering mRNA-carrying multilamellar liposomes to diffusively reach the soma and release mRNAs, which are translated into a specific protein upon encountering ribosomes. The concentration of this protein over a large population of neurons can be externally measured, as a detectable temporary signal. Using a stochastic coarse-grained approach for first-passage through dendrites, we connect the key morphological properties affected by neurodegenerative diseases -- including the density and size of spines, the extent of the tree, and the segmental increase of dendrite diameter towards soma -- to the characteristics of the evolving signal. Thus, we establish a direct link between the dendrite morphology and the statistical characteristics of the detectable signal. Our approach provides a fast noninvasive measurement technique to indirectly extract vital information about the morphological evolution of dendrites in the course of neurodegenerative disease progression.