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

Troiani et al (1711.05644)

Read on 22 November 2017
#OCT  #imaging  #simulation  #nerves 

I’ve covered OCT imaging in disease before, but this paper demonstrates the physics mechanisms behind the tomography scans by simulating biological tissue — namely, nerves — with glass and saline water.

Light-scattering is already commonly used to record neural activity: When shining light on a small patch of nervous tissue, the amount of light-scattering will change by a small fraction of a percent for about one millisecond. This technique is often used under craniotomy conditions — which is useful for measuring brain activity at a very high level, but doesn’t really help much when recording from tissue any deeper than very topical brain regions.

How do you know if this works in theory (without having to sit through countless OCT scan sessions)? Simulate a nerve! The authors use a glass tube filled with a variable-salinity solution to emulate the refraction of light against an active or inactive nerve.

Using this model, Troiani et al were able to register “activity” in the simulated nerves. This means that OCT with high temporal acuity — a quick refresh rate, and some clever value interpolation — is possibly useful as a nerve-activity sensor.

That is really exciting — measuring from peripheral nerves is conventionally a very invasive procedure (and is, understandably, not often done). This may provide a way to remain minimally invasive while still recording activity from nerves. This has exciting implications in peripheral neurodegenerative disease study, where it’s unclear where exactly damage is taking place along the nerve wire.

The authors have published their code here.