Clinical

Two-photon microscope provides unprecedented brain-imaging ability

Neuronal circuitry in mammals, including laboratory mice, must be studied in order to gain a better understanding of the human brain. Using a microscope with high enough resolution to see individual neurons and their neighbors is necessary for these studies. Spencer LaVere Smith, an associate professor in the Department of Electrical and Computer Engineering at UC Santa Barbara, is a leading researcher in the field of two-photon fluorescence microscopy, and his lab is a hotbed of innovation. President Obama’s BRAIN Initiative spawned the Next Generation Multiphoton Neuroimaging Consortium (Nemonic), a five-year, $9 million NSF-funded initiative based at UCSB that aims to “push the frontiers of multi-photon microscopy for neuroscience research.” Smith is the Nemonic hub’s principal investigator. “Dual Independent Enhanced Scan Engines for Large Field of View Two-Photon Imaging (Diesel2p)” is the name given to a novel microscope by Smith and his co-authors in the Nov. 17 issue of Nature Communications. Brain imaging has never been easier because to their two-photon microscope. If you’re looking for a gadget that can deliver subcellular resolution in various brain regions, this is the one for you.

According to Smith, “we’re aiming for three things: resolution to see individual neurons, range of view to record many regions of the brain simultaneously and imaging speed to detect changes in neuron activity throughout behavior.” Smith explained. There isn’t enough time to move the microscope to capture the events we’re interested in, therefore we must ensure that our optics can focus ultrafast laser light pulses in order to capture everything in one shot. With a price tag of around $250,000, the two-photon imaging systems use high-power lasers that can produce pulses of light that are more than a billion times brighter and last 0.0001 nanoseconds. A single beam of 80 million pulses per second is split into two separate scan engine arms, allowing the microscope to simultaneously scan two different locations, each with its own set of imaging characteristics. The two lasers were previously yoked and set to the same parameters in prior incarnations of the instrument, which severely restricted the amount of data that could be sampled. It is possible to employ a distinct set of scanning settings for the two beams thanks to the new equipment, which enables for various scanning parameters to be utilized for each beam. High-speed imaging of neural activity in widely scattered brain regions is already being widely used thanks to the new device’s custom-designed and custom-manufactured components, including the optical relays, the scan lens, the tube lens, and the objective lens.

Smith is dedicated to ensuring that the instrument is freely available. He and his co-authors posted a preprint with the engineering information needed to reproduce this new paper long before it was published. Also, they shared the technology with their colleagues at Boston University, where researchers in Jerry Chen’s group have already made modifications to fit their own investigations with the technology. It’s an exciting time, Smith agreed. In contrast to us, they didn’t have to start from scratch. They could take advantage of our efforts and expand on them. Both Jerry’s and our papers were published back-to-back, and two firms, INSS and CoSys, have commercialized systems based on our concepts. This technology can be used and modified by anybody, since it is not protected by a patent and never will be.

It is a sort of fluorescence microscopy that uses two light sources instead of one. A fluorescent neuron activity indicator is integrated into the neurons of mice in Smith’s lab in order to carry out this type of research. A fluorescent protein from jellyfish and a calcium-binding protein from nature were combined to create the indicator. The method takes use of the transient, orders-of-magnitude surge in calcium that a neuron experiences when firing.. Fluorescence occurs when calcium enters a neuron and the protein fluoresces as a result of this interaction. By utilizing the quantum nature of photons, two-photon imaging improves fluorescence microscopy by reducing the quantity of out-of-focus fluorescence light created. If you’re familiar with optical microscopy, you’ll know how light from an excitation source enters the material and narrows down to the goal focus area, and then an inverted cone is formed below that point. It is impossible to focus on anything that isn’t at the smallest possible angle. An imaging lens is unable to see any out-of-focus light because the two-photon microscope produces a single, focused point of light instead of a series of cones of light. There’s very little light from planes above or below, so the photograph just shows light from the planes we’re looking at. There are a lot of lipids and water-based solutions in the brain, which makes it difficult to look through. Only the top of the brain can be seen with standard optical imaging. Using two-photon imaging, we are able to get sub-cellular resolution while going deeper into the tissue.”

Another benefit of two-photon excitation light is that it employs lower-energy, longer-wavelength light (in the near-infrared range). When passing through tissue, such light scatters less, allowing it to be focused more precisely. The sample is less damaged by the longer wavelengths of lower energy light than shorter wavelengths of higher energy, such as ultraviolet light.

The device was put to the test on mice in Smith’s lab, who used it to track their brain activity while they watched films or navigated virtual reality surroundings. Using a microscope, researchers can peer into the brains of individual mice through a glass implant implanted in their skulls. According to him, he is interested in learning about the computational principles of neural circuits, which allow us to perform intriguing things that we can’t currently reproduce in machines. In many cases, we can create a machine that is superior to us in performance. We’re able to do some things, but not others. As a society, we teach kids how to drive vehicles, but self-driving cars fail in a wide range of scenarios where humans succeed. Only a few insights from the brain are included into the algorithms we use for deep learning. They do the job, but they’re prone to breaking. In contrast, if I introduce a mouse to a room it has never visited before, it will flee to a location beyond my grasp. It is impervious to obstacles. It’s incredibly dependable, and it only consumes approximately a watt of electricity while doing so. Starting in the brains of mice, Smith said, “I want to begin to unearth interesting computational concepts that we cannot yet mimic in human-made computers.”. “That’s why I built this microscope,” I explained.

Citation: Che-Hang Yu, Jeffrey N. Stirman, Yiyi Yu, Riichiro Hira, Spencer L. Smith. Diesel2p mesoscope with dual independent scan engines for flexible capture of dynamics in distributed neural circuitryNature Communications, 2021; 12 (1) DOI: 10.1038/s41467-021-26736-4

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