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First Comprehensive Census of Cell Types in Brain Area Controlling Movement

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Credit: SciePro/Shutterstock; BRAIN Initiative Cell Census Network, Nature, 2021

The primary motor cortex is the part of the brain that enables most of our skilled movements, whether it’s walking, texting on our phones, strumming a guitar, or even spiking a volleyball. The region remains a major research focus, and that’s why NIH’s Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative – Cell Census Network (BICCN) has just unveiled two groundbreaking resources: a complete census of cell types present in the mammalian primary motor cortex, along with the first detailed atlas of the region, located along the back of the frontal lobe in humans (purple stripe above).

This remarkably comprehensive work, detailed in a flagship paper and more than a dozen associated articles published in the journal Nature, promises to vastly expand our understanding of the primary motor cortex and how it works to keep us moving [1]. The papers also represent the collaborative efforts of more than 250 BICCN scientists from around the world, teaming up over many years.

Started in 2013, the BRAIN Initiative is an ambitious project with a range of groundbreaking goals, including the creation of an open-access reference atlas that catalogues all of the brain’s many billions of cells. The primary motor cortex was one of the best places to get started on assembling an atlas because it is known to be well conserved across mammalian species, from mouse to human. There’s also a rich body of work to aid understanding of more precise cell-type information.

Taking advantage of recent technological advances in single-cell analysis, the researchers categorized into different types the millions of neurons and other cells in this brain region. They did so on the basis of morphology, or shape, of the cells, as well as their locations and connections to other cells. The researchers went even further to characterize and sort cells based on: their complex patterns of gene expression, the presence or absence of chemical (or epigenetic) marks on their DNA, the way their chromosomes are packaged into chromatin, and their electrical properties.

The new data and analyses offer compelling evidence that neural cells do indeed fall into distinct types, with a high degree of correspondence across their molecular genetic, anatomical, and physiological features. These findings support the notion that neural cells can be classified into molecularly defined types that are also highly conserved or shared across mammalian species.

So, how many cell types are there? While that’s an obvious question, it doesn’t have an easy answer. The number varies depending upon the method used for sorting them. The researchers report that they have identified about 25 classes of cells, including 16 different neuronal classes and nine non-neuronal classes, each composed of multiple subtypes of cells.

These 25 classes were determined by their genetic profiles, their locations, and other characteristics. They also showed up consistently across species and using different experimental approaches, suggesting that they have important roles in the neural circuitry and function of the motor cortex in mammals.

Still, many precise features of the cells don’t fall neatly into these categories. In fact, by focusing on gene expression within single cells of the motor cortex, the researchers identified more potentially important cell subtypes, which fall into roughly 100 different clusters, or distinct groups. As scientists continue to examine this brain region and others using the latest new methods and approaches, it’s likely that the precise number of recognized cell types will continue to grow and evolve a bit.

This resource will now serve as a springboard for future research into the structure and function of the brain, both within and across species. The datasets already have been organized and made publicly available for scientists around the world.

The atlas also now provides a foundation for more in-depth study of cell types in other parts of the mammalian brain. The BICCN is already engaged in an effort to generate a brain-wide cell atlas in the mouse, and is working to expand coverage in the atlas for other parts of the human brain.

The cell census and atlas of the primary motor cortex are important scientific advances with major implications for medicine. Strokes commonly affect this region of the brain, leading to partial or complete paralysis of the opposite side of the body.

By considering how well cell census information aligns across species, scientists also can make more informed choices about the best models to use for deepening our understanding of brain disorders. Ultimately, these efforts and others underway will help to enable precise targeting of specific cell types and to treat a wide range of brain disorders that affect thinking, memory, mood, and movement.


[1] A multimodal cell census and atlas of the mammalian primary motor cortex. BRAIN Initiative Cell Census Network (BICCN). Nature. Oct 6, 2021.


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

BRAIN Initiative – Cell Census Network (BICCN) (NIH)

NIH Support: National Institute of Mental Health; National Institute of Neurological Disorders and Stroke

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.


[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.


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

The Amazing Brain: A Sharper Image of the Pyramidal Tract

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Flip the image above upside down, and the shape may remind you of something. If you think it resembles a pyramid, then you and a lot of great neuroscientists are thinking alike. What you are viewing is a colorized, 3D reconstruction of a pyramidal tract, which are bundles of nerve fibers that originate from the brain’s cerebral cortex and relay signals to the brainstem or the spinal cord. These signals control many important activities, including the voluntary movement of our arms, legs, head, and face.

For a while now, it’s been possible to combine a specialized form of magnetic resonance imaging (MRI) with computer modeling tools to produce 3D reconstructions of complicated networks of nerve fibers, such as the pyramidal tract. Still, for technical reasons, the quality of these reconstructions has remained poor in parts of the brain where nerve fibers cross at angles of 40 degrees or less.

The video above demonstrates how adding a sophisticated algorithm, called Orientation Distribution Function (ODF)-Fingerprinting, to such modeling can help overcome this problem when reconstructing a pyramidal tract. It has potential to enhance the reliability of these 3D reconstructions as neurosurgeons begin to use them to plan out their surgeries to help ensure they are carried out with the utmost safety and precision.

In the first second of the video, you see gray, fuzzy images from a diffusion MRI of the pyramidal tract. But, very quickly, a more colorful, detailed 3D reconstruction begins to appear, swiftly filling in from the top down. Colors are used to indicate the primary orientations of the nerve fibers: left to right (red), back to front (green), and top to bottom (blue). The orange, magenta, and other colors represent combinations of these primary directional orientations.

About three seconds into the video, a rough draft of the 3D reconstruction is complete. The top of the pyramidal tract looks pretty good. However, looking lower down, you can see distortions in color and relatively poor resolution of the nerve fibers in the middle of the tract—exactly where the fibers cross each other at angles of less than 40 degrees. So, researchers tapped into the power of their new ODF-Fingerprinting software to improve the image—and, starting about nine seconds into the video, you can see an impressive final result.

The researchers who produced this amazing video are Patryk Filipiak and colleagues in the NIH-supported lab of Steven Baete, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York. The work paired diffusion MRI data from the NIH Human Connectome Project with the ODF-Fingerprinting algorithm, which was created by Baete to incorporate additional MRI imaging data on the shape of nerve fibers to infer their directionality [1].

This innovative approach to imaging recently earned Baete’s team second place in the 2021 “Show Us Your BRAINs” Photo and Video contest, sponsored by the NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative. But researchers aren’t stopping there! They are continuing to refine ODF-Fingerprinting, with the aim of modeling the pyramidal tract in even higher resolution for use in devising new and better ways of helping people undergoing neurosurgery.


[1] Fingerprinting Orientation Distribution Functions in diffusion MRI detects smaller crossing angles. Baete SH, Cloos MA, Lin YC, Placantonakis DG, Shepherd T, Boada FE. Neuroimage. 2019 Sep;198:231-241.


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

Human Connectome Project (University of Southern California, Los Angeles)

Steven Baete (Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York)

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

NIH Support: National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Cancer Institute

The Amazing Brain: Visualizing Data to Understand Brain Networks

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The NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative continues to teach us about the world’s most sophisticated computer: the human brain. This striking image offers a spectacular case in point, thanks to a new tool called Visual Neuronal Dynamics (VND).

VND is not a camera. It is a powerful software program that can display, animate, and analyze models of neurons and their connections, or networks, using 3D graphics. What you’re seeing in this colorful image is a strip of mouse primary visual cortex, the area in the brain where incoming sensory information gets processed into vision.

This strip contains more than 230,000 neurons of 17 different cell types. Long and spindly excitatory neurons that point upward (purple, blue, red, orange) are intermingled with short and stubby inhibitory neurons (green, cyan, magenta). Slicing through the neuronal landscape is a neuropixels probe (silver): a tiny flexible silicon detector that can record brain activity in awake animals [1].

Developed by Emad Tajkhorshid and his team at University of Illinois at Urbana-Champaign, along with Anton Arkhipov of the Allen Institute, Seattle, VND represents a scientific milestone for neuroscience: using an adept software tool to see and analyze massive neuronal datasets on a computer. What’s also nice is the computer doesn’t have to be a fancy one, and VND’s instructions, or code, are publicly available for anyone to use.

VND is the neuroscience-adapted cousin of Visual Molecular Dynamics (VMD), a popular molecular biology visualization tool to see life up close in 3D, also developed by Tajkhorshid’s group [2]. By modeling and visualizing neurons and their connections, VND helps neuroscientists understand at their desktops how neural networks are organized and what happens when they are manipulated. Those visualizations then lay the groundwork for follow-up lab studies to validate the data and build upon them.

Through the Allen Institute, the NIH BRAIN Initiative is compiling a comprehensive whole-brain atlas of cell types in the mouse, and Arkhipov’s work integrates these data into computer models. In May 2020, his group published comprehensive models of the mouse primary visual cortex [3].

Arkhipov and team are now working to understand how the primary visual cortex’s physical structure (the cell shapes and connections within its complicated circuits) determines its outputs. For example, how do specific connections determine network activity? Or, how fast do cells fire under different conditions?

Ultimately, such computational research may help us understand how brain injuries or disease affect the structure and function of these neural networks. VND should also propel understanding of many other areas of the brain, for which the data are accumulating rapidly, to answer similar questions that still remain mysterious to scientists.

In the meantime, VND is also creating some award-winning art. The image above was the second-place photo in the 2021 “Show us Your BRAINs!” Photo and Video Contest sponsored by the NIH BRAIN Initiative.


[1] Fully integrated silicon probes for high-density recording of neural activity. Jun JJ, Steinmetz NA, Siegle JH, Denman DJ, Bauza M, Barbarits B, Lee AK, Anastassiou CA, Andrei A, Aydın Ç, Barbic M, Blanche TJ, Bonin V, Couto J, Dutta B, Gratiy SL, Gutnisky DA, Häusser M, Karsh B, Ledochowitsch P, Lopez CM, Mitelut C, Musa S, Okun M, Pachitariu M, Putzeys J, Rich PD, Rossant C, Sun WL, Svoboda K, Carandini M, Harris KD, Koch C, O’Keefe J, Harris TD. Nature. 2017 Nov 8;551(7679):232-236.

[2] VMD: visual molecular dynamics. Humphrey W, Dalke A, Schulten K. J Mol Graph. 1996 Feb;14(1):33-8, 27-8.

[3] Systematic integration of structural and functional data into multi-scale models of mouse primary visual cortex. Billeh YN, Cai B, Gratiy SL, Dai K, Iyer R, Gouwens NW, Abbasi-Asl R, Jia X, Siegle JH, Olsen SR, Koch C, Mihalas S, Arkhipov A. Neuron. 2020 May 6;106(3):388-403.e18


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

Models of the Mouse Primary Visual Cortex (Allen Institute, Seattle)

Visual Neuronal Dynamics (NIH Center for Macromolecular Modeling and Bioinformatics, University of Illinois at Urbana-Champaign)

Tajkhorshid Lab (University of Illinois at Urbana-Champaign)

Arkhipov Lab (Allen Institute)

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

NIH Support: National Institute of Neurological Disorders and Stroke

The Amazing Brain: Toward a Wiring Diagram of Connectivity

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It’s summertime and, thanks to the gift of COVID-19 vaccines, many folks are getting the chance to take a break. So, I think it’s also time that my blog readers finally get a break from what’s been nearly 18 months of non-stop coverage of COVID-19 research. And I can’t think of a more enjoyable way to do that than by taking a look at just a few of the many spectacular images and insights that researchers have derived about the amazing brain.

The Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative, which is an NIH-led project aimed at revolutionizing our understanding of the human brain, happens to have generated some of the coolest—and most informative—imagery now available in neuroscience. So, throughout the month of August, I’ll share some of the entries from the initiative’s latest Show Us Your BRAINs! Photo and Video Contest.

With nearly 100 billion neurons and 100 trillion connections, the human brain remains one of the greatest mysteries in science. Among the many ways in which neuroscientists are using imaging to solve these mysteries is by developing more detailed maps of connectivity within the brain.

For example, the image featured above from the contest shows a dense weave of neurons in the anterior cingulate cortex, which is the part of the brain involved in learning, memory, and some motor control. In this fluorescence micrograph of tissue from a mouse, each neuron has been labeled with green fluorescent protein, enabling you to see how it connects to other neurons through arm-like projections called axons and dendrites.

The various connections, or circuits, within the brain process and relay distinct types of sensory information. In fact, a single neuron can form a thousand or more of these connections. Among the biggest challenges in biomedicine today is deciphering how these circuits work, and how they can misfire to cause potentially debilitating neurological conditions, including Alzheimer’s disease, Parkinson’s disease, autism, epilepsy, schizophrenia, depression, and traumatic brain injury.

This image was produced by Nicholas Foster and Lei Gao in the NIH-supported lab of Hong Wei Dong, University of California, Los Angeles. The Dong Lab is busy cataloging cell types and helping to assemble a wiring diagram of the connectivity in the mammalian brain—just one of the BRAIN Initiative’s many audacious goals. Stay tuned for more throughout the month of August!


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

Dong Lab (University of California, Los Angeles)

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

NIH Support: National Institute of Mental Health

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