And a team of scientists has now found a way to create a clear image of the scattered infrared radiation emitted by the laser, even after it passes through a thick layer of bone.
“Our microscope allows us to examine delicate internal structures in the depths of living tissues that cannot be resolved by any other means,” said physicists Seokshan Yun and Hujun Lee, from Korea University.
While a technique called three-photon microscopy has previously captured images of nerve cells under a mouse’s skull, most attempts to obtain crystal-clear images of animal heads covered with bones require cutting openings through the skull.
Three-photon microscopy uses longer wavelengths and special gels to help see beyond the bones, but this method can only penetrate deeper and combine the light frequencies in a way that risks damaging tiny biological particles.
By combining imaging techniques with the power of computational adaptive optics previously used to correct visual distortion in terrestrial astronomy, Yoon and his colleagues were able to create the first-ever high-resolution images of a mouse’s neural networks, behind its intact skull.
They call their new imaging technology Laser Reflection Matrix Scanning Microscopy (LS-RMM). It relies on conventional confocal laser scanning microscopy, however, it detects light scattering not only at the depth imaged, but also obtains a complete input and output response to the interaction between light and medium – the reflection matrix.
When light passes (in this case, from a laser) through an object, some photons travel directly through it, while others are deflected.
The farther the light has to travel, the more ballistic photons are scattered out of the image. Most microscopy techniques rely on direct imaging light waves to build a clear and bright image. The LS-RRM uses a proprietary matrix to make the most of any anomalous light rays.
After recording the reflection matrix, the team used adaptive optics programming to sort the light particles. And they were able to generate an image of the mouse’s neural networks from the data.
In their paper, the team explained: “The determination of wavefront deviations depends on the intrinsic reflection variance of the targets. As such, it does not require fluorescent labeling and high excitation strength.
“This will greatly assist us in early diagnosis of disease and speed up neuroscience research,” said Yoon and Lee.
The LS-RMM is limited in computing power, as it is highly computational and time-consuming to process complex deviations from small, detailed areas. But the team suggests that the aberration correction algorithm could also be applied to other imaging techniques, to allow resolution of deeper images as well. The research was published in Nature Communications, according to ScienceAlert.