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Related Experiment Video

Updated: May 9, 2026

Whole Cell Patch Clamp for Investigating the Mechanisms of Infrared Neural Stimulation
08:58

Whole Cell Patch Clamp for Investigating the Mechanisms of Infrared Neural Stimulation

Published on: July 31, 2013

Heating during infrared neural stimulation.

Rickard Liljemalm1, Tobias Nyberg, Hans von Holst

  • 1Royal Institute of Technology, School of Technology and Health, Alfred Nobels Allé 10, 14152, Huddinge, Sweden.

Lasers in Surgery and Medicine
|July 9, 2013
PubMed
Summary

A new model accurately predicts temperature changes during infrared neural stimulation (INS). This research enables controlled INS of neural networks, observing both single-cell activation and network inhibition.

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Area of Science:

  • Biophysics
  • Neuroscience
  • Biomedical Engineering

Background:

  • Infrared neural stimulation (INS) is an emerging alternative to electrical stimulation.
  • INS mechanism involves water heating, potentially affecting cell membranes and heat-sensitive receptors.
  • Precise temperature control is crucial to prevent cellular damage during INS.

Purpose of the Study:

  • To develop and validate a detailed model for temperature distribution during INS.
  • To investigate the application of this model for in vitro neural networks.
  • To ensure safe and effective temperature management during INS.

Main Methods:

  • A multiphysics software model was created to simulate heating in cell cultures.
  • Experimental parameters included temperature, laser properties, and distance.
Keywords:
INScortical neuronsheat transferlasermodelingoptical stimulationsimulation

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Last Updated: May 9, 2026

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  • Model validation was performed using temperature measurements and direct neural stimulation experiments.

    • Main Results:

    • The model provided detailed spatial and temporal temperature distribution data.
    • Temperature measurements confirmed the model's accuracy, with peak cell temperatures reaching 48°C.
    • Successful INS of rat cortical neurons was achieved, demonstrating single-cell activation and network inhibition.

    Conclusions:

    • The developed model accurately predicts temperature profiles during INS.
    • This model is a valuable tool for optimizing INS parameters and understanding its effects.
    • The study successfully demonstrated INS of neural networks with controlled heating.