Title

Computational Model for Growth Cone Motility Guidance Using Laser-Induced Electromagnetic Gradients

Document Type

Oral Presentation

Campus where you would like to present

Ellensburg

Event Website

https://digitalcommons.cwu.edu/source

Start Date

18-5-2020

Abstract

Many neurodegenerative diseases are caused by the disruption of processes vital to neurons and their surrounding networks, including communication, metabolism, and repair. Damage to nerve axons can result in loss of nerve function and cell death. In order to repair these neurons in vivo, the ability to regenerate the damaged axons and then guide the axons along paths that will result in functional connections is necessary. This requires the development of noninvasive, highly efficient tools to guide the movement of a structure called the growth cone, which facilitates axon growth and guidance. Using purely optical repulsive and attractive guidance techniques with low power and near infrared light provides a noninvasive and efficient tool to repair neurons and restore their vital processes. While the experimental data demonstrates the ability of optical cues to guide growth cone motility, computational models are needed to provide new insights and to suggest which variables are most important in future experiments. Computational models lead to a new and better understanding of the system being investigated. The goal of this project is to create a computational model that complements published experimental data, providing a novel understanding of growth cone motility and how it can be used in the treatment of neurodegenerative diseases. Initial simulations using custom Matlab code demonstrate that an optical guidance cue can induce growth cone turning.

Faculty Mentor(s)

Erin Craig

Department/Program

Physics

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May 18th, 12:00 PM

Computational Model for Growth Cone Motility Guidance Using Laser-Induced Electromagnetic Gradients

Ellensburg

Many neurodegenerative diseases are caused by the disruption of processes vital to neurons and their surrounding networks, including communication, metabolism, and repair. Damage to nerve axons can result in loss of nerve function and cell death. In order to repair these neurons in vivo, the ability to regenerate the damaged axons and then guide the axons along paths that will result in functional connections is necessary. This requires the development of noninvasive, highly efficient tools to guide the movement of a structure called the growth cone, which facilitates axon growth and guidance. Using purely optical repulsive and attractive guidance techniques with low power and near infrared light provides a noninvasive and efficient tool to repair neurons and restore their vital processes. While the experimental data demonstrates the ability of optical cues to guide growth cone motility, computational models are needed to provide new insights and to suggest which variables are most important in future experiments. Computational models lead to a new and better understanding of the system being investigated. The goal of this project is to create a computational model that complements published experimental data, providing a novel understanding of growth cone motility and how it can be used in the treatment of neurodegenerative diseases. Initial simulations using custom Matlab code demonstrate that an optical guidance cue can induce growth cone turning.

https://digitalcommons.cwu.edu/source/2020/COTS/84