Skip to main content


Celebrating the Fourth with Neuroscience Fireworks

Posted on by

There’s so much to celebrate about our country this Fourth of July. That includes giving thanks to all those healthcare providers who have put themselves in harm’s way to staff the ERs, hospital wards, and ICUs to care for those afflicted with COVID-19, and also for everyone who worked so diligently to develop, test, and distribute COVID-19 vaccines.

These “shots of hope,” created with rigorous science and in record time, are making it possible for a great many Americans to gather safely once again with family and friends. So, if you’re vaccinated (and I really hope you are—because these vaccines have been proven safe and highly effective), fire up the grill, crank up the music, and get ready to show your true red, white, and blue colors. My wife and I—both fully vaccinated—intend to do just that!

To help get the celebration rolling, I’d like to share a couple minutes of some pretty amazing biological fireworks. While the track of a John Philip Sousa march is added just for fun, what you see in the video above is the result of some very serious neuroscience research that is scientifically, as well as visually, breath taking. Credit for this work goes to an NIH-supported team that includes Ricardo Azevedo and Sunil Gandhi, at the Center for the Neurobiology of Learning and Memory, University of California, Irvine, and their collaborator Damian Wheeler, Translucence Biosystems, Irvine, CA. Azevedo is also an NIH National Research Service Award fellow and a Medical Scientist Training Program trainee with Gandhi.

The team’s video starts off with 3D, colorized renderings of a mouse brain at cellular resolution. About 25 seconds in, the video flashes to a bundle of nerve fibers called the fornix. Thanks to the wonders of fluorescent labeling combined with “tissue-clearing” and other innovative technologies, you can clearly see the round cell bodies of individual neurons, along with the long, arm-like axons that they use to send out signals and connect with other neurons to form signaling circuits. The human brain has nearly 100 trillion of these circuits and, when activated, they process incoming sensory information and provide outputs that lead to our thoughts, words, feelings, and actions.

As shown in the video, the nerve fibers of the fornix provide a major output pathway from the hippocampus, a region of the brain involved in memory. Next, we travel to the brain’s neocortex, the outermost part of the brain that’s responsible for complex behaviors, and then move on to explore an intricate structure called the corticospinal tract, which carries motor commands to the spinal cord. The final stop is the olfactory tubercle —towards the base of the frontal lobe—a key player in odor processing and motivated behaviors.

Azevedo and his colleagues imaged the brain in this video in about 40 minutes using their imaging platform called the Translucence Biosystems’ Mesoscale Imaging System™. This process starts with a tissue-clearing method that eliminates light-scattering lipids, leaving the mouse brain transparent. From there, advanced light-sheet microscopy makes thin optical sections of the tissue, and 3D data processing algorithms reconstruct the image to high resolution.

Using this platform, researchers can take brain-wide snapshots of neuronal activity linked to a specific behavior. They can also use it to trace neural circuits that span various regions of the brain, allowing them to form new hypotheses about the brain’s connectivity and how such connectivity contributes to memory and behavior.

The video that you see here is a special, extended version of the team’s first-place video from the NIH-supported BRAIN Initiative’s 2020 “Show Us Your BRAINS!” imaging contest. Because of the great potential of this next-generation technology, Translucence Biosystems has received Small Business Innovation Research grants from NIH’s National Institute of Mental Health to disseminate its “brain-clearing” imaging technology to the neuroscience community.

As more researchers try out this innovative approach, one can only imagine how much more data will be generated to enhance our understanding of how the brain functions in health and disease. That is what will be truly spectacular for everyone working on new and better ways to help people suffering from Alzheimer’s disease, Parkinson’s disease, schizophrenia, autism, epilepsy, traumatic brain injury, depression, and so many other neurological and psychiatric disorders.

Wishing all of you a happy and healthy July Fourth!


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

NIH National Research Service Award

Medical Scientist Training Program (National Institute of General Medical Sciences/NIH)

Small Business Innovation Research and Small Business Technology Transfer (NIH)

Translucence Biosystems (Irvine, CA)

Sunil Gandhi (University of California, Irvine)

Ricardo Azevedo (University of California, Irvine)

Video: iDISCO-cleared whole brain from a Thy1-GFP mouse (Translucence Biosystems)

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

NIH Support: National Institute of Mental Health; National Eye Institute

From Electrical Brain Maps to Learning More About Migraines

Posted on by

Rainbo Hultman
Credit: University of Iowa Health Care

One of life’s greatest mysteries is the brain’s ability to encode something as complex as human behavior. In an effort to begin to unravel this mystery, neuroscientists often zoom in to record the activities of individual neurons. Sometimes they expand their view to look at a specific region of the brain. But if they zoom out farther, neuroscientists can observe many thousands of neurons across the entire brain firing at once to produce electrical oscillations that somehow translate into behaviors as distinct as a smile and a frown. The complexity is truly daunting.

Rainbo Hultman, University of Iowa Carver College of Medicine, Iowa City, realized years ago that by zooming out and finding a way to map all those emergent signals, she could help to change the study of brain function fundamentally. She also realized doing so offered her an opportunity to chip away at cracking the complicated code of the electrical oscillations that translate into such complex behaviors. To pursue her work in this emerging area of “electrical connectomics,” Hultman recently received a 2020 NIH Director’s New Innovator Award to study the most common human neurological disorder: migraine headaches.

A few years ago, Hultman made some impressive progress in electrical connectomics as a post-doctoral researcher in the lab of Kafui Dzirasa at Duke University, Durham, NC. Hultman and her colleagues refined a way to use electrodes to collect electrical field potentials across an unprecedented seven separate mouse brain regions at once. Using machine learning to help make sense of all the data, they uncovered a dynamic, yet reproducible, electrical brain network encoding depression [1].

What’s more, they found that the specific features of this brain-wide network could predict which mice subjected to chronic stress would develop signs of major depressive disorder. As Hultman noted, when measured and mapped in this way, the broad patterns of electrical brain activity, or “Electome factors,” could indicate which mice were vulnerable to stress and which were more resilient.

Moving on to her latest area of research, Hultman is especially intrigued by the fact that people who endure regular migraine attacks often pass through a characteristic sequence of symptoms. These symptoms can include a painful headache on one side of the head; visual disturbances; sensitivity to light, odors, or sound; mood changes; nausea; trouble speaking; and sometimes even paralysis. By studying the broad electrical patterns and networks associated with migraine in mice—simultaneously capturing electrical recordings from 14 brain regions on a millisecond timescale—she wants to understand how brain circuits are linked and work together in ways that produce the complex sequences of migraine symptoms.

More broadly, Hultman wants to understand how migraine and many other disorders affecting the brain lead to a state of heightened sensory sensitivity and how that emerges from integrated neural circuits in the brain. In her studies of migraine, the researcher suspects she might observe some of the same patterns seen earlier in depression. In fact, her team is setting up its experiments to ensure it can identify any brain network features that are shared across important disease states.

By the way, I happen to be one of many people who suffer from migraines, although fortunately not very often in my case. The visual aura of flashing jagged images that starts in the center of my visual field and then gradually moves to the periphery over about 20 minutes is pretty dramatic—a free light show! I’ve wondered what the electrical component of that must be like. But, even with treatment, the headache that follows can be pretty intense.

Hultman also has seen in her own life and family how debilitating migraines can be. Her goal isn’t just to map these neural networks, but to use them to identify where to target future therapeutics. Ultimately, she hopes her work will pave the way for more precise approaches for treating migraine and other brain disorders that are based on the emergent electrical characteristics of each individual’s brain activity. It’s a fascinating proposition, and I certainly look forward to where this research leads and what it may reveal about the fundamentals of how our brains encode complex behaviors and emotions.


[1] Brain-wide electrical spatiotemporal dynamics encode depression vulnerability. Hultman R, Ulrich K, Sachs BD, Blount C, Carlson DE, Ndubuizu N, Bagot RC, Parise EM, Vu MT, Gallagher NM, Wang J, Silva AJ, Deisseroth K, Mague SD, Caron MG, Nestler EJ, Carin L, Dzirasa K. Cell. 2018 Mar 22;173(1):166-180.e14.


Migraine Information Page (National Institute of Neurological Disorders and Stroke/NIH)

Laboratory for Brain-Network Based Molecular Medicine (University of Iowa, Iowa City)

Hultman Project Information (NIH RePORTER)

NIH Director’s New Innovator Award (Common Fund)

NIH Support: Common Fund; National Institute of Mental Health

Understanding Neuronal Diversity in the Spinal Cord

Posted on by

Cross-section image of spinal cord showing glowing green and magenta neurons.
Credit: Salk Institute, La Jolla, CA

The spinal cord, as a key part of our body’s central nervous system, contains millions of neurons that actively convey sensory and motor (movement) information to and from the brain. Scientists have long sorted these spinal neurons into what they call “cardinal” classes, a classification system based primarily on the developmental origin of each nerve cell. Now, by taking advantage of the power of single-cell genetic analysis, they’re finding that spinal neurons are more diverse than once thought.

This image helps to visualize the story. Each dot represents the nucleus of a spinal neuron in a mouse; humans have a very similar arrangement. Most of these neurons are involved in the regulation of motor control, but they also differ in important ways. Some are involved in local connections (green), such as those that signal outward to a limb and prompt us to pull away reflexively when we touch painful stimuli, such as a hot frying pan. Others are involved in long-range connections (magenta), relaying commands across spinal segments and even upward to the brain. These enable us, for example, to swing our arms while running to help maintain balance.

It turns out that these two types of spinal neurons also have distinctive genetic signatures. That’s why researchers could label them here in different colors and tell them apart. Being able to distinguish more precisely among spinal neurons will prove useful in identifying precisely which ones are affected by a spinal cord injury or neurodegenerative disease, key information in learning to engineer new tissue to heal the damage.

This image comes from a study, published recently in the journal Science, conducted by an NIH-supported team led by Samuel Pfaff, Salk Institute for Biological Studies, La Jolla, CA. Pfaff and his colleagues, including Peter Osseward and Marito Hayashi, realized that the various classes and subtypes of neurons in our spines arose over the course of evolutionary time. They reasoned that the most-primitive original neurons would have gradually evolved subtypes with more specialized and diverse capabilities. They thought they could infer this evolutionary history by looking for conserved and then distinct, specialized gene-expression signatures in the different neural subtypes.

The researchers turned to single-cell RNA sequencing technologies to look for important similarities and differences in the genes expressed in nearly 7,000 mouse spinal neurons. They then used this vast collection of genomic data to group the neurons into closely related clusters, in much the same way that scientists might group related organisms into an evolutionary family tree based on careful study of their DNA.

The first major gene expression pattern they saw divided the spinal neurons into two types: sensory-related and motor-related. This suggested to them that one of the first steps in spinal cord evolution may have been a division of labor of spinal neurons into those two fundamentally important roles.

Further analyses divided the sensory-related neurons into excitatory neurons, which make neurons more likely to fire; and inhibitory neurons, which dampen neural firing. Then, the researchers zoomed in on motor-related neurons and found something unexpected. They discovered the cells fell into two distinct molecular groups based on whether they had long-range or short-range connections in the body. Researches were even more surprised when further study showed that those distinct connectivity signatures were shared across cardinal classes.

All of this means that, while previously scientists had to use many different genetic tags to narrow in on a particular type of neuron, they can now do it with just two: a previously known tag for cardinal class and the newly discovered genetic tag for long-range vs. short-range connections.

Not only is this newfound ability a great boon to basic neuroscientists, it also could prove useful for translational and clinical researchers trying to determine which specific neurons are affected by a spinal injury or disease. Eventually, it may even point the way to strategies for regrowing just the right set of neurons to repair serious neurologic problems. It’s a vivid reminder that fundamental discoveries, such as this one, often can lead to unexpected and important breakthroughs with potential to make a real difference in people’s lives.


[1] Conserved genetic signatures parcellate cardinal spinal neuron classes into local and projection subsets. Osseward PJ 2nd, Amin ND, Moore JD, Temple BA, Barriga BK, Bachmann LC, Beltran F Jr, Gullo M, Clark RC, Driscoll SP, Pfaff SL, Hayashi M. Science. 2021 Apr 23;372(6540):385-393.


What Are the Parts of the Nervous System? (Eunice Kennedy Shriver National Institute of Child Health and Human Development/NIH)

Spinal Cord Injury (National Institute of Neurological Disorders and Stroke/NIH)

Samuel Pfaff (Salk Institute, La Jolla, CA)

NIH Support: National Institute of Mental Health; National Institute of Neurological Disorders and Stroke; Eunice Kennedy Shriver National Institute of Child Health and Human Development

The Synchronicity of Memory

Posted on by

Credit: Zhou Y, 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

Posted on by

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

Next Page