P288 Modelling the temperature profile of the retina in response to nanophotonic neuromodulation
Daniel B Richardson1, James Begeng1, Paul R Stoddart1,Tatiana Kameneva*1,2
1Department of Engineering Technologies, School of Engineering, Swinburne University of Technology, Australia
2Iverson Health Innovation Institute, Swinburne University of Technology, Australia
*Email: tkam@swin.edu.au
Electrical stimulation of neurons has been used as a reliable technique to elicit action potentials in implantable devices. Recently, novel optical stimulation techniques have been developed as alternatives to electrical stimulation. One approach involves applying near infrared wavelengths of light to stimulate neurons. Neurophotonic stimulation may increase the resultant visual acuity compared to electrical stimulation as it does not apply any current and thus has no current spread. As a result of applying nanophotonic stimulation, the retina experiences an increase in temperature. For this reason, modelling the temperature profile within the retina is vital in testing the feasibility of optical stimulation techniques.
Step 1: To model the temperature profile in a retina environment, a Monte Carlo simulation was implemented in MATLAB. The environment consisted of four layers: water, gold nanorods, retinal tissue, and a layer of glass. A 750nm beam was used to simulate near infrared stimulation at varying powers that matched the experimental values of Begeng et al (2023). Each layer had specified coefficients obtained from literature, which included the absorption and scattering coefficients, scattering anisotropy, volumetric heat capacity, and thermal conductivity. The simulation models the temperature profile through finite element modelling of the defined geometry. It determines the temperature through tracking the photon paths of the stimulation beam, monitoring how it progresses through the tissues via their varying scattering coefficients and refractive indexes. It then models the florescence and absorption of the tissues through probabilistic determination. Theamountof photons absorbed, and its associated power, is then used in conjunction with the heat equation to determine the temperature.
Step 2: A single-compartment Hodgkin-Huxley model of a temperature-sensitive rat RGC was constructed in the NEURON simulation environment. The model uses the Gouy-Chapman-Stern theory of temperature-variant bilayer capacitance, and experimentally-derived temperature dependence for key sodium, potassium, calcium and leak ion channels, as well as cytosolic resistance. Thermal profiles for the pulse durations were approximated using the thermal model described in Step 1.
The simulation temperature model demonstrated general agreement with the experimental results, showing comparable peak temperatures and maintaining a consistent trend with the varying pulse durations. Furthermore, the proposed temperature model allows for estimation of the temperature profile on the retinal surface, which is difficult to measure experimentally. Hodgkin-Huxley model replicated the main features of nanophotonic stimulation, including an initial driving subthreshold depolarisation hump, followed by an action potential, inhibition and excitation phenomena, that were dependent on the pulse duration.
Acknowledgements
-
References
Begeng JM, Tong W, Rosal B, Ibbotson M, Kameneva T, Stoddart PR (2023) Activity of retinal neurons can be modulated by tunable near-infrared nanoparticle sensors, ACS Nano 17 (3), 2079 – 2088,doi/10.1021/acsnano.2c07663
