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A Neuronal Light Show

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Credit: Chen X, Cell, 2019

These colorful lights might look like a video vignette from one of the spectacular evening light shows taking place this holiday season. But they actually aren’t. These lights are illuminating the way to a much fuller understanding of the mammalian brain.

The video features a new research method called BARseq (Barcoded Anatomy Resolved by Sequencing). Created by a team of NIH-funded researchers led by Anthony Zador, Cold Spring Harbor Laboratory, NY, BARseq enables scientists to map in a matter of weeks the location of thousands of neurons in the mouse brain with greater precision than has ever been possible before.

How does it work? With BARseq, researchers generate uniquely identifying RNA barcodes and then tag one to each individual neuron within brain tissue. As reported recently in the journal Cell, those barcodes allow them to keep track of the location of an individual cell amid millions of neurons [1]. This also enables researchers to map the tangled paths of individual neurons from one region of the mouse brain to the next.

The video shows how the researchers read the barcodes. Each twinkling light is a barcoded neuron within a thin slice of mouse brain tissue. The changing colors from frame to frame correspond to one of the four letters, or chemical bases, in RNA (A=purple, G=blue, U=yellow, and C=white). A neuron that flashes blue, purple, yellow, white is tagged with a barcode that reads GAUC, while yellow, white, white, white is UCCC.

By sequencing and reading the barcodes to distinguish among seemingly identical cells, the researchers mapped the connections of more than 3,500 neurons in a mouse’s auditory cortex, a part of the brain involved in hearing. In fact, they report they’re now able to map tens of thousands of individual neurons in a mouse in a matter of weeks.

What makes BARseq even better than the team’s previous mapping approach, called MAPseq, is its ability to read the barcodes at their original location in the brain tissue [2]. As a result, they can produce maps with much finer resolution. It’s also possible to maintain other important information about each mapped neuron’s identity and function, including the expression of its genes.

Zador reports that they’re continuing to use BARseq to produce maps of other essential areas of the mouse brain with more detail than had previously been possible. Ultimately, these maps will provide a firm foundation for better understanding of human thought, consciousness, and decision-making, along with how such mental processes get altered in conditions such as autism spectrum disorder, schizophrenia, and depression.

Here’s wishing everyone a safe and happy holiday season. It’s been a fantastic year in science, and I look forward to bringing you more cool NIH-supported research in 2020!


[1] High-Throughput Mapping of Long-Range Neuronal Projection Using In Situ Sequencing. Chen X, Sun YC, Zhan H, Kebschull JM, Fischer S, Matho K, Huang ZJ, Gillis J, Zador AM. Cell. 2019 Oct 17;179(3):772-786.e19.

[2] High-Throughput Mapping of Single-Neuron Projections by Sequencing of Barcoded RNA. Kebschull JM, Garcia da Silva P, Reid AP, Peikon ID, Albeanu DF, Zador AM. Neuron. 2016 Sep 7;91(5):975-987.


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

Zador Lab (Cold Spring Harbor Laboratory, Cold Spring Harbor, NY)

NIH Support: National Institute of Neurological Disorders and Stroke; National Institute on Drug Abuse; National Cancer Institute

What a Memory Looks Like

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Engram Image
Credit: Stephanie Grella, Ramirez Group, Boston University

Your brain has the capacity to store a lifetime of memories, covering everything from the name of your first pet to your latest computer password. But what does a memory actually look like? Thanks to some very cool neuroscience, you are looking at one.

The physical manifestation of a memory, or engram, consists of clusters of brain cells active when a specific memory was formed. Your brain’s hippocampus plays an important role in storing and retrieving these memories. In this cross-section of a mouse hippocampus, imaged by the lab of NIH-supported neuroscientist Steve Ramirez, at Boston University, cells belonging to an engram are green, while blue indicates those not involved in forming the memory.

When a memory is recalled, the cells within an engram reactivate and turn on, to varying degrees, other neural circuits (e.g., sight, sound, smell, emotions) that were active when that memory was recorded. It’s not clear how these brain-wide connections are made. But it appears that engrams are the gatekeepers that mediate memory.

The story of this research dates back several years, when Ramirez helped develop a system that made it possible to image engrams by tagging cells in the mouse brain with fluorescent dyes. Using an innovative technology developed by other researchers, called optogenetics, Ramirez’s team then discovered it could shine light onto a collection of hippocampal neurons storing a specific memory and reactivate the sensation associated with the memory [1].

Ramirez has since gone on to show that, at least in mice, optogenetics can be used to trick the brain into creating a false memory [2]. From this work, he has also come to the interesting and somewhat troubling conclusion that the most accurate memories appear to be the ones that are never recalled. The reason: the mammalian brain edits—and slightly changes—memories whenever they are accessed.

All of the above suggested to Ramirez that, given its tremendous plasticity, the brain may possess the power to downplay a traumatic memory or to boost a pleasant recollection. Toward that end, Ramirez’s team is now using its mouse system to explore ways of suppressing one engram while enhancing another [3].

For Ramirez, though, the ultimate goal is to develop brain-wide maps that chart all of the neural networks involved in recording, storing, and retrieving memories. He recently was awarded an NIH Director’s Transformative Research Award to begin the process. Such maps will be invaluable in determining how stress affects memory, as well as what goes wrong in dementia and other devastating memory disorders.


[1] Optogenetic stimulation of a hippocampal engram activates fear memory recall. Liu X, Ramirez S, Pang PT, Puryear CB, Govindarajan A, Deisseroth K, Tonegawa S. Nature. 2012 Mar 22;484(7394):381-385.

[2] Creating a false memory in the hippocampus. Ramirez S, Liu X, Lin PA, Suh J, Pignatelli M, Redondo RL, Ryan TJ, Tonegawa S. Science. 2013 Jul 26;341(6144):387-391.

[3] Artificially Enhancing and Suppressing Hippocampus-Mediated Memories. Chen BK, Murawski NJ, Cincotta C, McKissick O, Finkelstein A, Hamidi AB, Merfeld E, Doucette E, Grella SL, Shpokayte M, Zaki Y, Fortin A, Ramirez S. Curr Biol. 2019 Jun 3;29(11):1885-1894.


The Ramirez Group (Boston University, MA)

Ramirez Project Information (Common Fund/NIH)

NIH Director’s Early Independence Award (Common Fund)

NIH Director’s Transformative Research Award (Common Fund)

NIH Support: Common Fund

Defining Neurons in Technicolor

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Brain Architecture
Credit: Allen Institute for Brain Science, Seattle

Can you identify a familiar pattern in this image’s square grid? Yes, it’s the outline of the periodic table! But instead of organizing chemical elements, this periodic table sorts 46 different types of neurons present in the visual cortex of a mouse brain.

Scientists, led by Hongkui Zeng at the Allen Institute for Brain Science, Seattle, constructed this periodic table by assigning colors to their neuronal discoveries based upon their main cell functions [1]. Cells in pinks, violets, reds, and oranges have inhibitory electrical activity, while those in greens and blues have excitatory electrical activity.

For any given cell, the darker colors indicate dendrites, which receive signals from other neurons. The lighter colors indicate axons, which transmit signals. Examples of electrical properties—the number and intensity of their “spikes”—appear along the edges of the table near the bottom.

To create this visually arresting image, Zeng’s NIH-supported team injected dye-containing probes into neurons. The probes are engineered to carry genes that make certain types of neurons glow bright colors under the microscope.

This allowed the researchers to examine a tiny slice of brain tissue and view each colored neuron’s shape, as well as measure its electrical response. They followed up with computational tools to combine these two characteristics and classify cell types based on their shape and electrical activity. Zeng’s team could then sort the cells into clusters using a computer algorithm to avoid potential human bias from visually interpreting the data.

Why compile such a detailed atlas of neuronal subtypes? Although scientists have been surveying cells since the invention of the microscope centuries ago, there is still no consensus on what a “cell type” is. Large, rich datasets like this atlas contain massive amounts of information to characterize individual cells well beyond their appearance under a microscope, helping to explain factors that make cells similar or dissimilar. Those differences may not be apparent to the naked eye.

Just last year, Allen Institute researchers conducted similar work by categorizing nearly 24,000 cells from the brain’s visual and motor cortex into different types based upon their gene activity [2]. The latest research lines up well with the cell subclasses and types categorized in the previous gene-activity work. As a result, the scientists have more evidence that each of the 46 cell types is actually distinct from the others and likely drives a particular function within the visual cortex.

Publicly available resources, like this database of cell types, fuel much more discovery. Scientists all over the world can look at this table (and soon, more atlases from other parts of the brain) to see where a cell type fits into a region of interest and how it might behave in a range of brain conditions.


[1] Classification of electrophysiological and morphological neuron types in the mouse visual cortex. N Gouwens NW, et al. Neurosci. 2019 Jul;22(7):1182-1195.

[2] Shared and distinct transcriptomic cell types across neocortical areas. Tasic B, et al. Nature. 2018 Nov;563(7729):72-78.


Brain Basics: The Life and Death of a Neuron (National Institute of Neurological Disorders and Stroke/NIH)

Cell Types: Overview of the Data (Allen Brain Atlas/Allen Institute for Brain Science, Seattle)

Hongkui Zeng (Allen Institute)

NIH Support: National Institute of Mental Health; Eunice Kennedy Shriver National Institute of Child Health & Human Development

Multiplex Rainbow Technology Offers New View of the Brain

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Proteins imaged with this new approach
Caption: Confocal LNA-PRISM imaging of neuronal synapses. Conventional images of cell nuclei and two proteins (top row, three images on the left), along with 11 PRISM images of proteins and one composite, multiplexed image (bottom row, right). Credit: Adapted from Guo SM, Nature Communications, 2019

The NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative is revolutionizing our understanding of how the brain works through its creation of new imaging tools. One of the latest advances—used to produce this rainbow of images—makes it possible to view dozens of proteins in rapid succession in a single tissue sample containing thousands of neural connections, or synapses.

Apart from their colors, most of these images look nearly identical at first glance. But, upon closer inspection, you’ll see some subtle differences among them in both intensity and pattern. That’s because the images capture different proteins within the complex network of synapses—and those proteins may be present in that network in different amounts and locations. Such findings may shed light on key differences among synapses, as well as provide new clues into the roles that synaptic proteins may play in schizophrenia and various other neurological disorders.

Synapses contain hundreds of proteins that regulate the release of chemicals called neurotransmitters, which allow neurons to communicate. Each synaptic protein has its own specific job in the process. But there have been longstanding technical difficulties in observing synaptic proteins at work. Conventional fluorescence microscopy can visualize at most four proteins in a synapse.

As described in Nature Communications [1], researchers led by Mark Bathe, Massachusetts Institute of Technology (MIT), Cambridge, and Jeffrey Cottrell, Broad Institute of MIT and Harvard, Cambridge, have just upped this number considerably while delivering high quality images. They did it by adapting an existing imaging method called DNA PAINT [2]. The researchers call their adapted method PRISM. It is short for: Probe-based Imaging for Sequential Multiplexing.

Here’s how it works: First, researchers label proteins or other molecules of interest using antibodies that recognize those proteins. Those antibodies include a unique DNA probe that helps with the next important step: making the proteins visible under a microscope.

To do it, they deliver short snippets of complementary fluorescent DNA, which bind the DNA-antibody probes. While each protein of interest is imaged separately, researchers can easily wash the probes from a sample to allow a series of images to be generated, each capturing a different protein of interest.

In the original DNA PAINT, the DNA strands bind and unbind periodically to create a blinking fluorescence that can be captured using super-resolution microscopy. But that makes the process slow, requiring about half an hour for each protein.

To speed things up with PRISM, Bathe and his colleagues altered the fluorescent DNA probes. They used synthetic DNA that’s specially designed to bind more tightly or “lock” to the DNA-antibody. This gives a much brighter signal without the blinking effect. As a result, the imaging can be done faster, though at slightly lower resolution.

Though the team now captures images of 12 proteins within a sample in about an hour, this is just a start. As more DNA-antibody probes are developed for synaptic proteins, the team can readily ramp up this number to 30 protein targets.

Thanks to the BRAIN Initiative, researchers now possess a powerful new tool to study neurons. PRISM will help them learn more mechanistically about the inner workings of synapses and how they contribute to a range of neurological conditions.


[1] Multiplexed and high-throughput neuronal fluorescence imaging with diffusible probes. Guo SM, Veneziano R, Gordonov S, Li L, Danielson E, Perez de Arce K, Park D, Kulesa AB, Wamhoff EC, Blainey PC, Boyden ES, Cottrell JR, Bathe M. Nat Commun. 2019 Sep 26;10(1):4377.

[2] Super-resolution microscopy with DNA-PAINT. Schnitzbauer J, Strauss MT, Schlichthaerle T, Schueder F, Jungmann R. Nat Protoc. 2017 Jun;12(6):1198-1228.


Schizophrenia (National Institute of Mental Health)

Mark Bathe (Massachusetts Institute of Technology, Cambridge)

Jeffrey Cottrell (Broad Institute of MIT and Harvard, Cambridge)

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

NIH Support: National Institute of Mental Health; National Human Genome Research Institute; National Institute of Neurological Disorders and Stroke; National Institute of Environmental Health Sciences

Gene Therapy Shows Promise Repairing Brain Tissue Damaged by Stroke

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Glial Gene Therapy
Caption: Neurons (red) converted from glial cells using a new NeuroD1-based gene therapy in mice. Credit: Chen Laboratory, Penn State, University Park

It’s a race against time when someone suffers a stroke caused by a blockage of a blood vessel supplying the brain. Unless clot-busting treatment is given within a few hours after symptoms appear, vast numbers of the brain’s neurons die, often leading to paralysis or other disabilities. It would be great to have a way to replace those lost neurons. Thanks to gene therapy, some encouraging strides are now being made.

In a recent study in Molecular Therapy, researchers reported that, in their mouse and rat models of ischemic stroke, gene therapy could actually convert the brain’s support cells into new, fully functional neurons [1]. Even better, after gaining the new neurons, the animals had improved motor and memory skills.

For the team led by Gong Chen, Penn State, University Park, the quest to replace lost neurons in the brain began about a decade ago. While searching for the right approach, Chen noticed other groups had learned to reprogram fibroblasts into stem cells and make replacement neural cells.

As innovative as this work was at the time, it was performed mostly in lab Petri dishes. Chen and his colleagues thought, why not reprogram cells already in the brain?

They turned their attention to the brain’s billions of supportive glial cells. Unlike neurons, glial cells divide and replicate. They also are known to survive and activate following a brain injury, remaining at the wound and ultimately forming a scar. This same process had also been observed in the brain following many types of injury, including stroke and neurodegenerative conditions such as Alzheimer’s disease.

To Chen’s NIH-supported team, it looked like glial cells might be a perfect target for gene therapies to replace lost neurons. As reported about five years ago, the researchers were on the right track [2].

The Chen team showed it was possible to reprogram glial cells in the brain into functional neurons. They succeeded using a genetically engineered retrovirus that delivered a single protein called NeuroD1. It’s a neural transcription factor that switches genes on and off in neural cells and helps to determine their cell fate. The newly generated neurons were also capable of integrating into brain circuits to repair damaged tissue.

There was one major hitch: the NeuroD1 retroviral vector only reprogrammed actively dividing glial cells. That suggested their strategy likely couldn’t generate the large numbers of new cells needed to repair damaged brain tissue following a stroke.

Fast-forward a couple of years, and improved adeno-associated viral vectors (AAV) have emerged as a major alternative to retroviruses for gene therapy applications. This was exactly the breakthrough that the Chen team needed. The AAVs can reprogram glial cells whether they are dividing or not.

In the new study, Chen’s team, led by post-doc Yu-Chen Chen, put this new gene therapy system to work, and the results are quite remarkable. In a mouse model of ischemic stroke, the researchers showed the treatment could regenerate about a third of the total lost neurons by preferentially targeting reactive, scar-forming glial cells. The conversion of those reactive glial cells into neurons also protected another third of the neurons from injury.

Studies in brain slices showed that the replacement neurons were fully functional and appeared to have made the needed neural connections in the brain. Importantly, their studies also showed that the NeuroD1 gene therapy led to marked improvements in the functional recovery of the mice after a stroke.

In fact, several tests of their ability to make fine movements with their forelimbs showed about a 60 percent improvement within 20 to 60 days of receiving the NeuroD1 therapy. Together with study collaborator and NIH grantee Gregory Quirk, University of Puerto Rico, San Juan, they went on to show similar improvements in the ability of rats to recover from stroke-related deficits in memory.

While further study is needed, the findings in rodents offer encouraging evidence that treatments to repair the brain after a stroke or other injury may be on the horizon. In the meantime, the best strategy for limiting the number of neurons lost due to stroke is to recognize the signs and get to a well-equipped hospital or call 911 right away if you or a loved one experience them. Those signs include: sudden numbness or weakness of one side of the body; confusion; difficulty speaking, seeing, or walking; and a sudden, severe headache with unknown causes. Getting treatment for this kind of “brain attack” within four hours of the onset of symptoms can make all the difference in recovery.


[1] A NeuroD1 AAV-Based gene therapy for functional brain repair after ischemic injury through in vivo astrocyte-to-neuron conversion. Chen Y-C et al. Molecular Therapy. Published online September 6, 2019.

[2] In vivo direct reprogramming of reactive glial cells into functional neurons after brain injury and in an Alzheimer’s disease model. Guo Z, Zhang L, Wu Z, Chen Y, Wang F, Chen G. Cell Stem Cell. 2014 Feb 6;14(2):188-202.


Stroke (National Heart, Lung, and Blood Institute/NIH)

Gene Therapy (National Human Genome Research Institute/NIH)

Chen Lab (Penn State, University Park)

NIH Support: National Institute on Aging; National Institute of Mental Health

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