Editorial Feature

Advancing Brain Imaging with Two-Photon Fluorescence Microscopy

Neuroscience relies on imaging that can capture neural circuitry at work in live brains. A microscope that provides a high enough resolution to see individual neurons and the particles surrounding them is necessary for this kind of analysis. This article explores the role of two-photon fluorescence microscopy – one of the most advanced microscopy techniques available right now – in cutting-edge brain imaging.

brain imaging

Image Credit: Gorodenkoff/Shutterstock.com

Research led by Spencer LaVere Smith’s laboratory in the Department of Electrical and Computer Engineering at the University of California (UC) Santa Barbara is working at the forefront of two-photon fluorescence microscopy progress.

Smith’s laboratory is the principal investigator in a new five-year hub fund with $9 million: the Next Generation Multiphoton Neuroimaging Consortium (Nemonic). Nemonic’s strategic vision and funding were part of a US government initiative intended to break boundaries in neuroscience research using multi-photon microscopy.

Smith and his co-authors reported on a new microscope they developed in Nature Communications in 2021. The system was dubbed “Dual Independent Enhanced Scan Engines for Large Field-of-View Two-Photon Imaging (Diesel2p).”

The new microscope has the largest field of view ever achieved in a comparable device (up to 25 mm2) and provides previously unheard-of quality for brain imaging. These features mean the device can provide resolution to below the scale of individual cells in multiple areas of the brain simultaneously.

The researchers made three separate but related improvements to two-photon fluorescence microscopy:

  1. The resolution was improved so that individual neurons could be captured
  2. The field of view was improved so that multiple regions of the brain could be captured simultaneously
  3. Imaging speed was improved so that changes in neuron activity during brain-behavior could be captured

These optimizations would enable them to image events that take less than a second to occur in live brains. This means there is no time to move the microscope and focus on a new area where brain activity is happening. Getting everything in one shot requires high resolution, wide field of view, and fast imaging speed and sensor responsiveness.

Therefore, two-photon fluorescence microscopy has been the preferred tool to explore future brain imaging technologies. It uses a powerful laser costing around $250,000 to send ultrafast, intense pulses of light in 0.0001 nanosecond bursts. Each pulse is more than a billion times brighter than the sun, and the lasers emit them at a rate of 80 million pulses per second.

In traditional two-photon fluorescence microscopy, the laser beam is split but both new beams were yoked together and configured along the same parameters. But the new technique’s beams are configured to different imaging parameters. This enables the new device to scan two regions at once.

Yoking laser beams together strongly constrained sampling in previous two-photon fluorescence microscopy methods. By enabling different scan parameters to be used for the different beams, the new method can provide fast imaging of brain activity in regions scattered all over the brain.

This is enabled by optimizing scan parameters such as frame rate and scan region size for different regions of the brain. This ability is a result of several custom-designed and manufactured elements in the device, including the optical relays, scan lens, tube lens, and objective lens which were all made bespoke.

Researchers said that their new device is already being widely applied for brain imaging over scattered regions with high speed and resolution. They intend to keep the instrument as accessible as possible for future researchers.

This was achieved initially with a preprint released by the paper’s authors some time before the main paper was published. The preprint included all the engineering details needed to reproduce the device.

Researchers also collaborated with Boston University-based colleagues by sharing their designs with them. Boston University scientists in Jerry Chen’s laboratory are already modifying the device to suit their own experimental requirements.

The UC Santa Barbara team responsible for the two-photon fluorescence microscopy breakthrough are happy to see their work flourishing beyond their immediate control. They do not intend to patent the technology, enabling it to be freely used and modified by all.

Advanced microscopy device suppliers INSS and CoSys have already sold systems based on the new two-photon fluorescence microscopy technique.

Brain Imaging for Advanced Neural Networks

One of the key applications for advanced brain imaging, said UC Santa Barbara researchers, would be to inform the development of advanced neural networks.

Smith says that he is motivated to learn how computational principles in neural circuitry allow us to do things that machines cannot. Driving a car, for example, is something that teenagers learn how to do every year, but there is still no wide acceptance of self-driving vehicles.

Current deep learning models using neural networks are based on what we know about how brains work, but we only have a limited understanding of the complex circuitry and computation going on in the grey matter.

Advancing neuroimaging techniques will improve our understanding of brains’ computational powers, and therefore improve our development of cutting-edge computing based on the most powerful computers we know of – our brains.

References and Further Reading

UC Santa Barbara (2021). Two-photon microscope provides unprecedented brain-imaging ability. [Online] ScienceDaily.com. Available at: https://www.sciencedaily.com/releases/2021/12/211202123008.htm.

Wieczorek, S., D. Filipiak, and A. Filipowska (2018). Semantic Image-Based Profiling of Users' Interests with Neural Networks. Studies on the Semantic Web. https://doi.org/10.3233%2F978-1-61499-894-5-179.

Yu, C-H., et al. (2021). Diesel2p mesoscope with dual independent scan engines for flexible capture of dynamics in distributed neural circuitry. Nature Communications. https://doi.org/10.1038/s41467-021-26736-4.

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Ben Pilkington

Written by

Ben Pilkington

Ben Pilkington is a freelance writer who is interested in society and technology. He enjoys learning how the latest scientific developments can affect us and imagining what will be possible in the future. Since completing graduate studies at Oxford University in 2016, Ben has reported on developments in computer software, the UK technology industry, digital rights and privacy, industrial automation, IoT, AI, additive manufacturing, sustainability, and clean technology.


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