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The Amazing Brain: Capturing Neurons in Action

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Credit: Andreas Tolias, Baylor College of Medicine, Houston

With today’s powerful imaging tools, neuroscientists can monitor the firing and function of many distinct neurons in our brains, even while we move freely about. They also possess another set of tools to capture remarkable, high-resolution images of the brain’s many thousands of individual neurons, tracing the form of each intricate branch of their tree-like structures.

Most brain imaging approaches don’t capture neural form and function at once. Yet that’s precisely what you’re seeing in this knockout of a movie, another winner in the Show Us Your BRAINs! Photo and Video Contest, supported by NIH’s Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative.

This first-of-its kind look into the mammalian brain produced by Andreas Tolias, Baylor College of Medicine, Houston, and colleagues features about 200 neurons in the visual cortex, which receives and processes visual information. First, you see a colorful, tightly packed network of neurons. Then, those neurons, which were colorized by the researchers in vibrant pinks, reds, blues, and greens, pull apart to reveal their finely detailed patterns and shapes. Throughout the video, you can see neural activity, which appears as flashes of white that resemble lightning bolts.

Making this movie was a multi-step process. First, the Tolias group presented laboratory mice with a series of visual cues, using a functional imaging approach called two-photon calcium imaging to record the electrical activity of individual neurons. While this technique allowed the researchers to pinpoint the precise locations and activity of each individual neuron in the visual cortex, they couldn’t zoom in to see their precise structures.

So, the Baylor team sent the mice to colleagues Nuno da Costa and Clay Reid, Allen Institute for Brain Science, Seattle, who had the needed electron microscopes and technical expertise to zoom in on these structures. Their data allowed collaborator Sebastian Seung’s team, Princeton University, Princeton, NJ, to trace individual neurons in the visual cortex along their circuitous paths. Finally, they used sophisticated machine learning algorithms to carefully align the two imaging datasets and produce this amazing movie.

This research was supported by Intelligence Advanced Research Projects Activity (IARPA), part of the Office of the Director of National Intelligence. The IARPA is one of NIH’s governmental collaborators in the BRAIN Initiative.

Tolias and team already are making use of their imaging data to learn more about the precise ways in which individual neurons and groups of neurons in the mouse visual cortex integrate visual inputs to produce a coherent view of the animals’ surroundings. They’ve also collected an even-larger data set, scaling their approach up to tens of thousands of neurons. Those data are now freely available to other neuroscientists to help advance their work. As researchers make use of these and similar data, this union of neural form and function will surely yield new high-resolution discoveries about the mammalian brain.

Links:

Tolias Lab (Baylor College of Medicine, Houston)

Nuno da Costa (Allen Institute for Brain Science, Seattle)

R. Clay Reid (Allen Institute)

H. Sebastian Seung (Princeton University, Princeton, NJ)

Machine Intelligence from Cortical Networks (MICrONS) Explorer

Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)

Show Us Your BRAINs Photo & Video Contest (BRAIN Initiative)

NIH Support: BRAIN Initiative; Common Fund


Human Brain Compresses Working Memories into Low-Res ‘Summaries’

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Stimulus images are disks of angled lines. A thought bubble shows similar angles in her thoughts
Credit: Adapted from Kwak Y., Neuron (2022)

You have probably done it already a few times today. Paused to remember a password, a shopping list, a phone number, or maybe the score to last night’s ballgame. The ability to store and recall needed information, called working memory, is essential for most of the human brain’s higher cognitive processes.

Researchers are still just beginning to piece together how working memory functions. But recently, NIH-funded researchers added an intriguing new piece to this neurobiological puzzle: how visual working memories are “formatted” and stored in the brain.

The findings, published in the journal Neuron, show that the visual cortex—the brain’s primary region for receiving, integrating, and processing visual information from the eye’s retina—acts more like a blackboard than a camera. That is, the visual cortex doesn’t photograph all the complex details of a visual image, such as the color of paper on which your password is written or the precise series of lines that make up the letters. Instead, it recodes visual information into something more like simple chalkboard sketches.

The discovery suggests that those pared down, low-res representations serve as a kind of abstract summary, capturing the relevant information while discarding features that aren’t relevant to the task at hand. It also shows that different visual inputs, such as spatial orientation and motion, may be stored in virtually identical, shared memory formats.

The new study, from Clayton Curtis and Yuna Kwak, New York University, New York, builds upon a known fundamental aspect of working memory. Many years ago, it was determined that the human brain tends to recode visual information. For instance, if passed a 10-digit phone number on a card, the visual information gets recoded and stored in the brain as the sounds of the numbers being read aloud.

Curtis and Kwak wanted to learn more about how the brain formats representations of working memory in patterns of brain activity. To find out, they measured brain activity with functional magnetic resonance imaging (fMRI) while participants used their visual working memory.

In each test, study participants were asked to remember a visual stimulus presented to them for 12 seconds and then make a memory-based judgment on what they’d just seen. In some trials, as shown in the image above, participants were shown a tilted grating, a series of black and white lines oriented at a particular angle. In others, they observed a cloud of dots, all moving in a direction to represent those same angles. After a short break, participants were asked to recall and precisely indicate the angle of the grating’s tilt or the dot cloud’s motion as accurately as possible.

It turned out that either visual stimulus—the grating or moving dots—resulted in the same patterns of neural activity in the visual cortex and parietal cortex. The parietal cortex is a part of the brain used in memory processing and storage.

These two distinct visual memories carrying the same relevant information seemed to have been recoded into a shared abstract memory format. As a result, the pattern of brain activity trained to recall motion direction was indistinguishable from that trained to recall the grating orientation.

This result indicated that only the task-relevant features of the visual stimuli had been extracted and recoded into a shared memory format. But Curtis and Kwak wondered whether there might be more to this finding.

To take a closer look, they used a sophisticated model that allowed them to project the three-dimensional patterns of brain activity into a more-informative, two-dimensional representation of visual space. And, indeed, their analysis of the data revealed a line-like pattern, similar to a chalkboard sketch that’s oriented at the relevant angles.

The findings suggest that participants weren’t actually remembering the grating or a complex cloud of moving dots at all. Instead, they’d compressed the images into a line representing the angle that they’d been asked to remember.

Many questions remain about how remembering a simple angle, a relatively straightforward memory formation, will translate to the more-complex sets of information stored in our working memory. On a technical level, though, the findings show that working memory can now be accessed and captured in ways that hadn’t been possible before. This will help to delineate the commonalities in working memory formation and the possible differences, whether it’s remembering a password, a shopping list, or the score of your team’s big victory last night.

Reference:

[1] Unveiling the abstract format of mnemonic representations. Kwak Y, Curtis CE. Neuron. 2022, April 7; 110(1-7).

Links:

Working Memory (National Institute of Mental Health/NIH)

The Curtis Lab (New York University, New York)

NIH Support: National Eye Institute


Capturing the Extracellular Matrix in 3D Color

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Credit: Sarah Lipp, Purdue University, and Sarah Calve, University of Colorado, Boulder

For experienced and aspiring shutterbugs alike, sometimes the best photo in the bunch turns out to be a practice shot. That’s also occasionally true in the lab when imaging cells and tissues, and it’s the story behind this spectacular image showing the interface of skin and muscle during mammalian development.

Here you see an area of the mouse forelimb located near a bone called the humerus. This particular sample was labeled for laminin, a protein found in the extracellular matrix (ECM) that undergirds cells and tissues to give them mechanical and biochemical support. Computer algorithms were used to convert the original 2D confocal scan into a 3D image, and colorization was added to bring the different layers of tissue into sharper relief.

Skin tissue (bright red and yellow) is located near the top of the image; blood vessels (paler red, orange, and yellow) are in the middle and branching downward; and muscle (green, blue, and purple) makes up the bottom layer.

The image was created by Sarah Lipp, a graduate student in the NIH-supported tissue engineering lab of Sarah Calve. The team focuses on tissue interfaces to better understand the ECM and help devise strategies to engineer musculoskeletal tissues, such as tendon and cartilage.

In February 2020, Lipp was playing around with some new software tools for tissue imaging. Before zeroing in on her main target—the mouse’s myotendinous junction, where muscle transfers its force to tendon, Lipp snapped this practice shot of skin meeting muscle. After processing the practice shot with a color-projecting macro in an image processing tool called Fiji, she immediately liked what she saw.

So, Lipp tweaked the color a bit more and entered the image in the 2020 BioArt Scientific Image & Video Competition, sponsored by the Federation of American Societies for Experimental Biology, Bethesda, MD. Last December, the grad student received the good news that her practice shot had snagged one of the prestigious contest’s top awards.

But she’s not stopping there. Lipp is continuing to pursue her research interests at the University of Colorado, Boulder, where the Calve lab recently moved from Purdue University, West Lafayette, IN. Here’s wishing her a career filled with more great images—and great science!

Links:

Muscle and Bone Diseases (National Institute of Arthritis and Musculoskeletal and Skin Diseases/NIH)

Musculoskeletal Extracellular Matrix Laboratory (University of Colorado, Boulder)

BioArt Scientific Image & Video Competition (Federation of American Societies for Experimental Biology, Bethesda, MD)

NIH Support: National Institute of Arthritis and Musculoskeletal and Skin Diseases


Tapping Into The Brain’s Primary Motor Cortex

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If you’re like me, you might catch yourself during the day in front of a computer screen mindlessly tapping your fingers. (I always check first to be sure my mute button is on!) But all that tapping isn’t as mindless as you might think.

While a research participant performs a simple motor task, tapping her fingers together, this video shows blood flow within the folds of her brain’s primary motor cortex (gray and white), which controls voluntary movement. Areas of high brain activity (yellow and red) emerge in the omega-shaped “hand-knob” region, the part of the brain controlling hand movement (right of center) and then further back within the primary somatic cortex (which borders the motor cortex toward the back of the head).

About 38 seconds in, the right half of the video screen illustrates that the finger tapping activates both superficial and deep layers of the primary motor cortex. In contrast, the sensation of a hand being brushed (a sensory task) mostly activates superficial layers, where the primary sensory cortex is located. This fits with what we know about the superficial and deep layers of the hand-knob region, since they are responsible for receiving sensory input and generating motor output to control finger movements, respectively [1].

The video showcases a new technology called zoomed 7T perfusion functional MRI (fMRI). It was an entry in the recent Show Us Your BRAINs! Photo and Video Contest, supported by NIH’s Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative.

The technology is under development by an NIH-funded team led by Danny J.J. Wang, University of Southern California Mark and Mary Stevens Neuroimaging and Informatics Institute, Los Angeles. Zoomed 7T perfusion fMRI was developed by Xingfeng Shao and brought to life by the group’s medical animator Jim Stanis.

Measuring brain activity using fMRI to track perfusion is not new. The brain needs a lot of oxygen, carried to it by arteries running throughout the head, to carry out its many complex functions. Given the importance of oxygen to the brain, you can think of perfusion levels, measured by fMRI, as a stand-in measure for neural activity.

There are two things that are new about zoomed 7T perfusion fMRI. For one, it uses the first ultrahigh magnetic field imaging scanner approved by the Food and Drug Administration. The technology also has high sensitivity for detecting blood flow changes in tiny arteries and capillaries throughout the many layers of the cortex [2].

Compared to previous MRI methods with weaker magnets, the new technique can measure blood flow on a fine-grained scale, enabling scientists to remove unwanted signals (“noise”) such as those from surface-level arteries and veins. Getting an accurate read-out of activity from region to region across cortical layers can help scientists understand human brain function in greater detail in health and disease.

Having shown that the technology works as expected during relatively mundane hand movements, Wang and his team are now developing the approach for fine-grained 3D mapping of brain activity throughout the many layers of the brain. This type of analysis, known as mesoscale mapping, is key to understanding dynamic activities of neural circuits that connect brain cells across cortical layers and among brain regions.

Decoding circuits, and ultimately rewiring them, is a major goal of NIH’s BRAIN Initiative. Zoomed 7T perfusion fMRI gives us a window into 4D biology, which is the ability to watch 3D objects over time scales in which life happens, whether it’s playing an elaborate drum roll or just tapping your fingers.

References:

[1] Neuroanatomical localization of the ‘precentral knob’ with computed tomography imaging. Park MC, Goldman MA, Park MJ, Friehs GM. Stereotact Funct Neurosurg. 2007;85(4):158-61.

[2]. Laminar perfusion imaging with zoomed arterial spin labeling at 7 Tesla. Shao X, Guo F, Shou Q, Wang K, Jann K, Yan L, Toga AW, Zhang P, Wang D.J.J bioRxiv 2021.04.13.439689.

Links:

Brain Basics: Know Your Brain (National Institute of Neurological Disorders and Stroke)

Laboratory of Functional MRI Technology (University of Southern California Mark and Mary Stevens Neuroimaging and Informatics Institute)

The Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)

Show Us Your BRAINs! Photo and Video Contest (BRAIN Initiative)

NIH Support: National Institute of Neurological Disorders and Stroke; National Institute of Biomedical Imaging and Bioengineering; Office of the Director


New Microscope Technique Provides Real-Time 3D Views

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Most of the “cool” videos shared on my blog are borne of countless hours behind a microscope. Researchers must move a biological sample through a microscope’s focus, slowly acquiring hundreds of high-res 2D snapshots, one painstaking snap at a time. Afterwards, sophisticated computer software takes this ordered “stack” of images, calculates how the object would look from different perspectives, and later displays them as 3D views of life that can be streamed as short videos.

But this video is different. It was created by what’s called a multi-angle projection imaging system. This new optical device requires just a few camera snapshots and two mirrors to image a biological sample from multiple angles at once. Because the device eliminates the time-consuming process of acquiring individual image slices, it’s up to 100 times faster than current technologies and doesn’t require computer software to construct the movie. The kicker is that the video can be displayed in real time, which isn’t possible with existing image-stacking methods.

The video here shows two human melanoma cells, rotating several times between overhead and side views. You can see large amounts of the protein PI3K (brighter orange hues indicate higher concentrations), which helps some cancer cells divide and move around. Near the cell’s perimeter are small, dynamic surface protrusions. PI3K in these “blebs” is thought to help tumor cells navigate and survive in foreign tissues as the tumor spreads to other organs, a process known as metastasis.

The new multi-angle projection imaging system optical device was described in a paper published recently in the journal Nature Methods [1]. It was created by Reto Fiolka and Kevin Dean at the University of Texas Southwestern Medical Center, Dallas.

Like most technology, this device is complicated. Rather than the microscope and camera doing all the work, as is customary, two mirrors within the microscope play a starring role. During a camera exposure, these mirrors rotate ever so slightly and warp the acquired image in such a way that successive, unique perspectives of the sample magically come into view. By changing the amount of warp, the sample appears to rotate in real-time. As such, each view shown in the video requires only one camera snapshot, instead of acquiring hundreds of slices in a conventional scheme.

The concept traces to computer science and an algorithm called the shear warp transform method. It’s used to observe 3D objects from different perspectives on a 2D computer monitor. Fiolka, Dean, and team found they could implement a similar algorithm optically for use with a microscope. What’s more, their multi-angle projection imaging system is easy-to-use, inexpensive, and can be converted for use on any camera-based microscope.

The researchers have used the device to view samples spanning a range of sizes: from mitochondria and other tiny organelles inside cells to the beating heart of a young zebrafish. And, as the video shows, it has been applied to study cancer and other human diseases.

In a neat, but also scientifically valuable twist, the new optical method can generate a virtual reality view of a sample. Any microscope user wearing the appropriately colored 3D glasses immediately sees the objects.

While virtual reality viewing of cellular life might sound like a gimmick, Fiolka and Dean believe that it will help researchers use their current microscopes to see any sample in 3D—offering the chance to find rare and potentially important biological events much faster than is possible with even the most advanced microscopes today.

Fiolka, Dean, and team are still just getting started. Because the method analyzes tissue very quickly within a single image frame, they say it will enable scientists to observe the fastest events in biology, such as the movement of calcium throughout a neuron—or even a whole bundle of neurons at once. For neuroscientists trying to understand the brain, that’s a movie they will really want to see.

Reference:

[1] Real-time multi-angle projection imaging of biological dynamics. Chang BJ, Manton JD, Sapoznik E, Pohlkamp T, Terrones TS, Welf ES, Murali VS, Roudot P, Hake K, Whitehead L, York AG, Dean KM, Fiolka R. Nat Methods. 2021 Jul;18(7):829-834.

Links:

Metastatic Cancer: When Cancer Spreads (National Cancer Institute)

Fiolka Lab (University of Texas Southwestern Medical Center, Dallas)

Dean Lab (University of Texas Southwestern)

Microscopy Innovation Lab (University of Texas Southwestern)

NIH Support: National Cancer Institute; National Institute of General Medical Sciences


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