Simulating optical coherence tomography for observing nerve activity: a finite difference time domain bi-dimensional model

TL;DR

This paper introduces a finite difference time domain (FDTD) model for simulating optical coherence tomography (OCT) signals, enabling non-invasive nerve activity monitoring through efficient and scalable computational methods.

Contribution

The authors develop a novel FDTD bi-dimensional model that reduces computational time and allows simulation of larger environments and successive A lines for OCT nerve imaging.

Findings

Successfully simulated nerve tissue and glass samples using the model.

Demonstrated feasibility of OCT for non-invasive nerve activity monitoring.

Reduced computational requirements compared to traditional methods.

Abstract

We present a finite difference time domain (FDTD) model for computation of A line scans in time domain optical coherence tomography (OCT). By simulating only the end of the two arms of the interferometer and computing the interference signal in post processing, it is possible to reduce the computational time required by the simulations and, thus, to simulate much bigger environments. Moreover, it is possible to simulate successive A lines and thus obtaining a cross section of the sample considered. In this paper we present the model applied to two different samples: a glass rod filled with water-sucrose solution at different concentrations and a peripheral nerve. This work demonstrates the feasibility of using OCT for non-invasive, direct optical monitoring of peripheral nerve activity, which is a long-sought goal of neuroscience.