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The Synchronicity of Memory

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Credit: Zhou Y, et al. FASEB J, 2020

You may think that you’re looking at a telescopic heat-map of a distant planet, with clickable thumbnail images to the right featuring its unique topography. In fact, what you’re looking at is a small region of the brain that’s measured in micrometers and stands out as a fascinating frontier of discovery into the very origins of thought and cognition.

It’s a section of a mouse hippocampus, a multi-tasking region of the brain that’s central to memory formation. What makes the image on the left so interesting is it shows four individual neurons (numbered circles) helping to form a memory.

The table of images on the right shows in greater detail how the memory is formed. You see those same four neurons, their activity logged individually. Cooler colors—indigo to turquoise—indicate background or low neuronal activity; warmer colors—yellow to red—indicate high neuronal activity.

Now, take a closer look at the rows of the table that are labeled “Initial.” The four neurons have responded to an initial two-part training session: the sounding of a tone (gray-shaded columns) followed by a stimulus (red-shaded columns) less than a minute later. The neurons, while active (multi-colored pattern), don’t fire in unison or at the same activity levels. A memory has not yet been formed.

That’s not the case just below in the rows labeled “Trained.” After several rounds of reinforcing the one-two sequence, neurons fire together at comparable activity levels in response to the tone (gray) followed by the now-predictable stimulus (red). This process of firing in unison, called neuronal synchronization, encodes the memory. In fact, the four neurons even deactivate in unison after each prompt (unshaded columns).

These fascinating images are the first to show an association between neuronal burst synchronization and hippocampus-dependent memory formation. This discovery has broad implications, from improving memory to reconditioning the mental associations that underlie post-traumatic stress disorder (PTSD).

This research comes from a team led by the NIH-supported investigator Xuanmao Chen, University of New Hampshire, Durham. In the study, published in the FASEB Journal, Chen and colleagues used deep-brain imaging technology to shed new light on some old-fashioned classical conditioning: Pavlovian training [1].

Over a century ago, Ivan Pavlov conducted experiments that conditioned dogs to salivate at the sound of a bell that signaled their feeding time. This concept of “classical conditioning” is central to our understanding of how we humans form certain types of memories. A baby smiles at the sound of her mother’s voice. Stores play holiday music at the end of the year, hoping the positive childhood association puts shoppers in the mood to buy more gifts. Our phone plays a distinctive tone, and we immediately check our text messages. In each example, the association with an otherwise neutral stimulus is learned—and stored in the brain as a “declarative,” or explicit, memory.

The researchers wanted to see what happened in neural cells when mice learned a new association. They applied Pavlov’s learning paradigm, training mice over repeated sessions by pairing an audible tone and, about 30 seconds later, a brief, mild foot stimulus. Mice instinctively halt their activities, or freeze, in response to the foot stimulus. After a few tone-stimulus training sessions, the mice also began freezing after the tone was sounded. They had formed a conditioned response.

During these training sessions, Chen and his colleagues were able to take high-resolution, real-time images of the hippocampus. This allowed them to track the same four neurons over the course of the day—and watch as memory creation, in the form of neuronal synchronization, took place. Later, during recall experiments, the tone itself elicited both the behavioral change and the coordinated neuronal response—if with a bit less regularity. It’s something we humans experience whenever we forget a computer password!

The researchers went on to capture even more evidence. They showed that these neurons, which became part of the stored “engram,” or physical location of the memory, were already active even before they were synchronized. This finding contributes to recent work challenging the long-held paradigm that memory-eligible neurons “switch on” from a silent state to form a memory [2]. The researchers offered a new name for these active neurons: “primed,” as opposed to “silent.”

Chen and his colleagues continue studying the priming process and working out more of the underlying molecular details. They’re attempting to determine how the process is regulated and primed neurons become synchronized. And, of course, the big question: how does this translate into an actual memory in other living creatures? The next round of results should be memorable!


[1] Induction of activity synchronization among primed hippocampal neurons out of random dynamics is key for trace memory formation and retrieval. Zhou Y, Qiu L, Wang H, Chen X. FASEB J. 2020 Mar;34(3):3658–3676.

[2] Memory engrams: Recalling the past and imagining the future. Josselyn S, Tonegawa S. Science 2020 Jan 3;367(6473):eaaw4325.


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

Neuroanatomy, Hippocampus Fogwe LA, Reddy V, Mesfin FB. StatPearls Publishing (National Library of Medicine/NIH)

Xuanmao Chen (University of New Hampshire, Durham)

NIH Support: National Institute of Mental Health; National Institute on Aging; National Institute of General Medical Sciences

On-the-Spot Gene Readouts Offer Clues to How Cells Work

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Credit: MIT and Harvard Medical School, Cambridge, MA

Just as two companies can merge to expand their capabilities, two technologies can become more powerful when integrated into one. That’s why researchers recently merged two breakthrough technologies into one super powerful new method called ExSeq. The two-in-one technology enables researchers for the first time to study an intact tissue sample and track genetic activity on the spot within a cell’s tiniest recesses, or microenvironments—areas that have been largely out of reach until now.

ExSeq, which is described in a paper in the journal Science [1], will unleash many new experimental applications. Beyond enabling more precise analysis of the basic building blocks of life, these applications include analyzing tumor biopsies more comprehensively and even unlocking mysteries of how the brain works. The latter use is on display in this colorful cross-section of a mouse’s hippocampus, a region of the brain involved in the memory of facts and events.

Here you can see in precise and unprecedented detail the areas where genes are activated (magenta) in the brain’s neurons (green). In this particular example, the genes are working within subregions of the hippocampus called the CA1 and dentate gyrus regions (white, bottom and top left).

ExSeq is a joint effort from NIH grantees Ed Boyden, Massachusetts Institute of Technology (MIT), Cambridge, and George Church, Harvard Medical School, Boston. The new method combines a technology called tissue expansion with an in situ sequencing approach.

Tissue expansion swells the contents of tissue sections up to 100 times their normal size but retains their same physical structure [2]. It’s sort of like increasing the font size and line spacing on a hard-to-read document. It makes cellular details that were outside the resolution range of the light microscope suddenly accessible.

With the information inside cells now easier to see, the next step involves a technique called FISSEQ (fluorescent in situ sequencing), which generates readouts of thousands of mRNA molecules in cells [3]. FISSEQ works by detecting individual RNA molecules where they are inside cells and amplifying them into “nanoballs,” or rolled-up copies of themselves. Each nanoball can be read using standard sequencing methods and a fluorescence microscope.

Using the combined ExSeq approach, the team can analyze precisely where gene activity changes within tiny cellular microenvironments. Or, it can compile a more-comprehensive readout of gene activity within cells by analyzing as many gene readouts as detectable. When used in the hippocampus, this untargeted, “agnostic” approach led to some surprises—revealing unusual forms of RNA and, by association, genes for proteins not previously linked with communication between neurons.

Like many technology developments, the scientists envision that ExSeq can be used in many ways, including for more precise analysis of tumor biopsies. To illustrate this point, the researchers analyzed breast cancer metastases, which are cells from breast tumors that have spread to other areas in the body. Metastases contain many different cell types, including cancer cells and immune cells.

Using ExSeq, Boyden and Church learned that these distinct cell types can behave differently depending on where they are inside a tumor. They discovered, for example, that immune B cells near tumor cells expressed certain inflammatory genes at a higher level than immune B cells that were further away. Precise information about a tumor’s composition and activity may lead to development of more targeted approaches to attack it.

Many discoveries come on the heels of transformative new technologies. ExSeq shines a much brighter light on the world of the very small. And that should help us better understand how different parts of cells work together, as well as how cells work with each other in the brain, in cancer, and throughout the body.


[1] Expansion sequencing: Spatially precise in situ transcriptomics in intact biological systems. Alon S, Goodwin DR, Sinha A, Wassie AT, et al. Science. 2021 Jan 29;37:eaax2656.

[2] Expansion microscopy. Chen F, Tillberg PW, Boyden ES. Science. 2015;347:543-548.

[3]. Highly multiplexed subcellular RNA sequencing in situ. Lee JH, Daugharthy ER, Scheiman J, Kalhor R, et al. Science. 2014;343:1360-1363.


Ribonucleic Acid (RNA) (National Human Genome Research Institute/NIH)

Synthetic Neurobiology Group (Massachusetts Institute of Technology, Cambridge)

George Church (Harvard Medical School, Boston)

NIH Support: National Human Genome Research Institute; National Cancer Institute; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute of Neurological Disorders and Stroke

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

The Amazing Brain: Shining a Spotlight on Individual Neurons

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A major aim of the NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative is to develop new technologies that allow us to look at the brain in many different ways on many different scales. So, I’m especially pleased to highlight this winner of the initiative’s recent “Show Us Your Brain!” contest.

Here you get a close-up look at pyramidal neurons located in the hippocampus, a region of the mammalian brain involved in memory. While this tiny sample of mouse brain is densely packed with many pyramidal neurons, researchers used new ExLLSM technology to zero in on just three. This super-resolution, 3D view reveals the intricacies of each cell’s structure and branching patterns.

The group that created this award-winning visual includes the labs of X. William Yang at the University of California, Los Angeles, and Kwanghun Chung at the Massachusetts Institute of Technology, Cambridge. Chung’s team also produced another quite different “Show Us Your Brain!” winner, a colorful video featuring hundreds of neural cells and connections in a part of the brain essential to movement.

Pyramidal neurons in the hippocampus come in many different varieties. Some important differences in their functional roles may be related to differences in their physical shapes, in ways that aren’t yet well understood. So, BRAIN-supported researchers are now applying a variety of new tools and approaches in a more detailed effort to identify and characterize these neurons and their subtypes.

The video featured here took advantage of Chung’s new method for preserving brain tissue samples [1]. Another secret to its powerful imagery was a novel suite of mouse models developed in the Yang lab. With some sophisticated genetics, these models make it possible to label, at random, just 1 to 5 percent of a given neuronal cell type, illuminating their full morphology in the brain [2]. The result was this unprecedented view of three pyramidal neurons in exquisite 3D detail.

Ultimately, the goal of these and other BRAIN Initiative researchers is to produce a dynamic picture of the brain that, for the first time, shows how individual cells and complex neural circuits interact in both time and space. I look forward to their continued progress, which promises to revolutionize our understanding of how the human brain functions in both health and disease.


[1] Protection of tissue physicochemical properties using polyfunctional crosslinkers. Park YG, Sohn CH, Chen R, McCue M, Yun DH, Drummond GT, Ku T, Evans NB, Oak HC, Trieu W, Choi H, Jin X, Lilascharoen V, Wang J, Truttmann MC, Qi HW, Ploegh HL, Golub TR, Chen SC, Frosch MP, Kulik HJ, Lim BK, Chung K. Nat Biotechnol. 2018 Dec 17.

[2] Genetically-directed Sparse Neuronal Labeling in BAC Transgenic Mice through Mononucleotide Repeat Frameshift. Lu XH, Yang XW. Sci Rep. 2017 Mar 8;7:43915.


Chung Lab (Massachusetts Institute of Technology, Cambridge)

Yang Lab (University of California, Los Angeles)

Show Us Your Brain! (BRAIN Initiative/NIH)

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

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

A GPS-like System for Single-Cell Analysis

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Courtesy of the Chen and Macosko labs

A few years ago, I highlighted a really cool technology called Drop-seq for simultaneously analyzing the gene expression activity inside thousands of individual cells. Today, one of its creators, Evan Macosko, reports significant progress in developing even better tools for single-cell analysis—with support from an NIH Director’s New Innovator Award.

In a paper in the journal Science, Macosko, Fei Chen, and colleagues at the Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, recently unveiled another exciting creation called Slide-seq [1]. This technology acts as a GPS-like system for mapping the exact location of each of the thousands of individual cells undergoing genomic analysis in a tissue sample.

This 3D video shows the exquisite precision of this new cellular form of GPS, which was used to generate a high-resolution map of the different cell types found in a tiny cube of mouse brain tissue. Specifically, it provides locations of the cell types and gene expression in the hippocampal regions called CA1 (green), CA2/3 (blue), and dentate gyrus (red).

Because using Slide-seq in the lab requires no specialized imaging equipment or skills, it should prove valuable to researchers across many different biomedical disciplines who want to look at cellular relationships or study gene activity in tissues, organs, or even whole organisms.

How does Slide-seq work? Macosko says one of the main innovations is an inexpensive rubber-coated glass slide nicknamed a puck. About 3 millimeters in diameter, pucks are studded with tens of thousands of 10 micron-sized beads, each one decorated with a random snippet of genetic material—an RNA barcode—that serves as its unique identifier of the bead.

The barcodes are sequenced en masse, and the exact location of each barcoded bead is indexed using innovative software developed by a team led by Chen, who is an NIH Director’s Early Independence awardee.

Then, the researchers place a sample of fresh-frozen tissue (typically, 10 micrometers, or 0.00039 inches, thick) on the puck and dissolve the tissue, lysing the cells and releasing their messenger RNA (mRNA). That leaves only the barcoded beads binding the mRNA transcripts expressed by the cells in the tissue—a biological record of the genes that were turned on at the time the sample was frozen.

The barcoded mRNA is then sequenced. The spatial position of each mRNA molecule can be inferred, using the reference index on the puck. This gives researchers a great deal of biological information about the cells in the tissue, often including their cell type and their gene expression pattern. All the data can then be mapped out in ways similar to those seen in this video, which was created using data from 66 pucks.

Slide-seq has been tested on a range of tissues from both mouse and human, replicating results from similar maps created using existing approaches, but also uncovering new biology. For example, in the mouse cerebellum, Slide-seq allowed the researchers to detect bands of variable gene activity across the tissues. This intriguing finding suggests that there may be subpopulations of cells in this part of the brain that have gene activity influenced by their physical locations.

Such results demonstrate the value of combining cell location with genomic information. In fact, Macosko now hopes to use Slide-seq to study the response of brain cells that are located near the buildup of damaged amyloid protein associated with the early-stage Alzheimer’s disease. Meanwhile, Chen is interested in pursuing cell lineage studies in a variety of tissues to see how and where changes in the molecular dynamics of tissues can lead to disease.

These are just a few examples of how Slide-seq will add to the investigative power of single-cell analysis in the years ahead. In meantime, the Macosko and Chen labs are working hard to develop even more innovative approaches to this rapidly emerging areas of biomedical research, so who knows what “seq” we will be talking about next?


[1] Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Rodriques SG, Stickels RR, Goeva A, Martin CA, Murray E, Vanderburg CR, Welch J, Chen LM, Chen F, Macosko EZ. Science. 2019 Mar 29;363(6434):1463-1467.


Single Cell Analysis (NIH)

Macosko Lab (Broad Institute of Harvard and MIT, Cambridge)

Chen Lab (Broad Institute)

NIH Support: National Institute on Aging; Common Fund

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