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Finding Better Ways to Image the Retina

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Two light microscopy fields of the retina showing small blue dots (rods) surrounding larger yellow dots (cones)
Credit: Johnny Tam, National Eye Institute, NIH

Every day, all around the world, eye care professionals are busy performing dilated eye exams. By looking through a patient’s widened pupil, they can view the retina—the postage stamp-sized tissue lining the back of the inner eye—and look for irregularities that may signal the development of vision loss.

The great news is that, thanks to research, retinal imaging just keeps getting better and better. The images above, which show the same cells viewed with two different microscopic techniques, provide good examples of how tweaking existing approaches can significantly improve our ability to visualize the retina’s two types of light-sensitive neurons: rod and cone cells.

Specifically, these images show an area of the outer retina, which is the part of the tissue that’s observed during a dilated eye exam. Thanks to colorization and other techniques, a viewer can readily distinguish between the light-sensing, color-detecting cone cells (orange) and the much smaller, lowlight-sensing rod cells (blue).

These high-res images come from Johnny Tam, a researcher with NIH’s National Eye Institute. Working with Alfredo Dubra, Stanford University, Palo Alto, CA, Tam and his team figured out how to limit light distortion of the rod cells. The key was illuminating the eye using less light, provided as a halo instead of the usual solid, circular beam.

But the researchers’ solution hit a temporary snag when the halo reflected from the rods and cones created another undesirable ring of light. To block it out, Tam’s team introduced a tiny pinhole, called a sub-Airy disk. Along with use of adaptive optics technology [1] to correct for other distortions of light, the scientists were excited to see such a clear view of individual rods and cones. They published their findings recently in the journal Optica [2]

The resolution produced using these techniques is so much improved (33 percent better than with current methods) that it’s even possible to visualize the tiny inner segments of both rods and cones. In the cones, for example, these inner segments help direct light coming into the eye to other, photosensitive parts that absorb single photons of light. The light is then converted into electrical signals that stream to the brain’s visual centers in the occipital cortex, which makes it possible for us to experience vision.

Tam and team are currently working with physician-scientists in the NIH Clinical Center to image the retinas of people with a variety of retinal diseases, including age-related macular degeneration (AMD), a leading cause of vision loss in older adults. These research studies are ongoing, but offer hopeful possibilities for safe and non-intrusive monitoring of individual rods and cones over time, as well as across disease types. That’s obviously good news for patients. Plus it will help scientists understand how a rod or cone cell stops working, as well as more precisely test the effects of gene therapy and other experimental treatments aimed at restoring vision.


[1] Noninvasive imaging of the human rod photoreceptor mosaic using a confocal adaptive optics scanning ophthalmoscope. Dubra A, Sulai Y, Norris JL, Cooper RF, Dubis AM, Williams DR, Carroll J. Biomed Opt Express. 2011 Jul 1;2(7):1864-76.

[1] In-vivo sub-diffraction adaptive optics imaging of photoreceptors in the human eye with annular pupil illumination and sub-Airy detection. Rongwen L, Aguilera N, Liu T, Liu J, Giannini JP, Li J, Bower AJ, Dubra A, Tam J. Optica 2021 8, 333-343.


Get a Dilated Eye Exam (National Eye Institute/NIH)

How the Eyes Work (NEI)

Eye Health Data and Statistics (NEI)

Tam Lab (NEI)

Dubra Lab (Stanford University, Palo Alto, CA)

NIH Support: National Eye Institute

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

How Our Brains Replay Memories

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Retrieving a Memory
Caption: Encoding and replaying learned memory. Left panel shows the timed sequence of neurons firing in a part of a person’s brain involved in memory as it encodes the random pair of words, “crow” and “jeep.” Colors are assigned to different neurons to differentiate their firing within the sequence. Right panel shows a highly similar timed sequence of those same neurons firing just before a person given the word “jeep,” recalled and said the correct answer “crow.” Credit: Vaz AP, Science, 2020.

Note to my blog readers: the whole world is now facing a major threat from the COVID-19 pandemic. We at NIH are doing everything we can to apply the best and most powerful science to the development of diagnostics, therapeutics, and vaccines, while also implementing public health measures to protect our staff and the patients in our hospital. This crisis is expected to span many weeks, and I will occasionally report on COVID-19 in this blog format. Meanwhile, science continues to progress on many other fronts—and so I will continue to try to bring you stories across a wide range of topics. Perhaps everyone can use a little break now and then from the coronavirus news? Today’s blog takes you into the intricacies of memory.

When recalling the name of an acquaintance, you might replay an earlier introduction, trying to remember the correct combination of first and last names. (Was it Scott James? Or James Scott?) Now, neuroscientists have found that in the split second before you come up with the right answer, your brain’s neurons fire in the same order as when you first learned the information [1].

This new insight into memory retrieval comes from recording the electrical activity of thousands of neurons in the brains of six people during memory tests of random word pairs, such as “jeep” and “crow.” While similar firing patterns had been described before in mice, the new study is the first to confirm that the human brain stores memories in specific sequences of neural activity that can be replayed again and again.

The new study, published in the journal Science, is the latest insight from neurosurgeon and researcher Kareem Zaghloul at NIH’s National Institute of Neurological Disorders and Stroke (NINDS). Zaghloul’s team has for years been involved in an NIH Clinical Center study for patients with drug-resistant epilepsy whose seizures cannot be controlled with drugs.

As part of this work, his surgical team often temporarily places a 4 millimeter-by-4 millimeter array of tiny electrodes on the surface of the brains of the study’s participants. They do this in an effort to pinpoint brain tissues that may be the source of their seizures before performing surgery to remove them. With a patient’s informed consent to take part in additional research, the procedure also has led to a series of insights into what happens in the human brain when we make and later retrieve new memories.

Here’s how it works: The researchers record electrical currents as participants are asked to learn random word pairs presented to them on a computer screen, such as “cake” and “fox,” or “lime” and “camel.” After a period of rest, their brain activity is again recorded as they are given a word and asked to recall the matching word.

Last year, the researchers reported that the split second before a person got the right answer, tiny ripples of electrical activity appeared in two specific areas of the brain [2]. The team also had shown that, when a person correctly recalled a word pair, the brain showed patterns of activity that corresponded to those formed when he or she first learned to make a word association.

The new work takes this a step further. As study participants learned a word pair, the researchers noticed not only the initial rippling wave of electricity, but also that particular neurons in the brain’s cerebral cortex fired repeatedly in a sequential order. In fact, with each new word pair, the researchers observed unique firing patterns among the active neurons.

If the order of neuronal firing was essential for storing new memories, the researchers reasoned that the same would be true for correctly retrieving the information. And, indeed, that’s what they were able to show. For example, when individuals were shown “cake” for a second time, they replayed a very similar firing pattern to the one recorded initially for this word just milliseconds before correctly recalling the paired word “fox.”

The researchers then calculated the average sequence similarity between the firing patterns of learning and retrieval. They found that as a person recalled a word, those patterns gradually became more similar. Just before a correct answer was given, the recorded neurons locked onto the right firing sequence. That didn’t happen when a person gave an incorrect answer.

Further analysis confirmed that the exact order of neural firing was specific to each word pair. The findings show that our memories are encoded as unique sequences that must be replayed for accurate retrieval, though we still don’t understand the molecular mechanisms that undergird this.

Zaghloul reports that there’s still more to learn about how these processes are influenced by other factors such as our attention. It’s not yet known whether the brain replays sequences similarly when retrieving longer-term memories. Along with these intriguing insights into normal learning and memory, the researchers think this line of research will yield important clues as to what changes in people who suffer from memory disorders, with potentially important implications for developing the next generation of treatments.


[1] Replay of cortical spiking sequences during human memory retrieval. Vaz AP, Wittig JH Jr, Inati SK, Zaghloul KA. Science. 2020 Mar 6;367(6482):1131-1134.

[2] Coupled ripple oscillations between the medial temporal lobe and neocortex retrieve human memory. Vaz AP, Inati SK, Brunel N, Zaghloul KA. Science. 2019 Mar 1;363(6430):975-978.


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

Brain Basics (NINDS)

Zaghloul Lab (NINDS)

NIH Support: National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences

Largest-Ever Genetic Study of Autism Yields New Insights

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Baby and DNA Strands

Anyone who’s spent time with people affected by autism spectrum disorder (ASD) can tell you that it’s a very complex puzzle. The wide variability seen among individuals with this group of developmental brain disorders, which can disrupt communication, behavior control, and social skills, has also posed a huge challenge for researchers trying to identify underlying genetic and environmental factors. So, it’s no surprise that there’s been considerable interest in the recent findings of the largest-ever genetic study of ASD.

In a landmark study that analyzed the DNA of more than 35,000 people from around the world, the NIH-funded international Autism Sequencing Consortium (ASC) identified variants in 102 genes associated with increased risk of developing ASD, up from 65 identified previously. Of the 102 genes, 60 had not been previously linked to ASD and 53 appeared to be primarily connected to ASD as opposed to other types of intellectual disability or developmental delay. It is expected that this newfound genetic knowledge will serve to improve understanding of the complex biological mechanisms involved in ASD, ultimately paving the way for new approaches to diagnosis and treatment.

The study reported in the journal Cell was led by Joseph Buxbaum, Icahn School of Medicine at Mount Sinai, New York; Stephan Sanders, University of California, San Francisco; Kathryn Roeder, Carnegie Mellon University, Pittsburgh, PA; and Mark Daly, Massachusetts General Hospital, Boston, MA and the Broad Institute of MIT and Harvard, Cambridge, MA. These researchers and their teams faced what might seem like a rather daunting task.

While common genetic variants collectively are known to contribute substantially to ASD, rare variants have been recognized individually as more major contributors to a person’s risk of developing ASD. The challenge was how to find such rare variants—whether inherited or newly arising.

To do so, the researchers needed to analyze a enormous amount of DNA data. Fortunately, they and their ASC colleagues already had assembled a vast trove of data. Over the last decade, the ASC had collected DNA samples with full consent from thousands of people with and without ASD, including unaffected siblings and parents. All were aggregated with other studies, and, at the time of this investigation, they had gathered 35,584 unique samples. Those included more than 21,000 family-based samples and almost 12,000 samples from people diagnosed with ASD.

In search of rare genetic alterations, they sequenced whole exomes, the approximately 1.5 percent of the genome that codes for proteins. Their search produced a list of 102 ASD-associated genes, including 30 that had never been implicated in any developmental brain disorder previously.

But that was just the beginning. Next, the ASC team dug deeper into this list. The researchers knew from previous work that up to half of people with ASD also have an intellectual disability or developmental delay. Many of the associated genes overlap, meaning they play roles in both outcomes. So, in one set of analyses, the team compared the list to the results of another genetic study of people diagnosed with developmental delays, including problems with learning or gross motor skills such as delayed walking.

The detailed comparison allowed them to discern genes that are more associated with features of ASD, as opposed to those that are more specific to these developmental delays. It turns out that 49 of the 102 autism-associated genes were altered more often in people with developmental delay than in those diagnosed with ASD. The other 53 were altered more often in ASD, suggesting that they may be more closely linked to this condition’s unique features.

Further study also showed that people who carried alterations in genes found predominantly in ASD also had better intellectual function. They also were more likely to have learned to walk without a developmental delay.

The 102 new genes fell primarily into one of two categories. Many play a role in the brain’s neural connections. The rest are involved primarily in switching other genes on and off in brain development. Interestingly, they are expressed both in excitatory neurons, which are active in sending signals in the brain, and in inhibitory neurons that squelch such activity. Many of these genes are also commonly expressed in the brain’s cerebral cortex, the outermost part of the brain that is responsible for many complex behaviors.

Overall, these findings underscore that ASD truly does exist on a spectrum. Indeed, there are many molecular paths to this disorder. The ASC researchers continue to collect samples, so we can expect this list of 102 genes will continue to expand in the future.

With these gene discoveries in hand, the researchers will now also turn their attention to unravelling additional details about how these genes function in the brain. The hope is that this growing list of genes will converge on a smaller number of important molecular pathways, pointing the way to new and more precise ways of treating ASD in all its complexity.


[1] Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism. Satterstrom FK, Kosmicki JA, Wang J, Breen MS, De Rubeis S, An JY, Peng M, Collins R, Grove J, Klei L, Stevens C, Reichert J, Mulhern MS, Artomov M, Gerges S, Sheppard B, Xu X, Bhaduri A, Norman U, Brand H, Schwartz G, Nguyen R, Guerrero EE, Dias C; Autism Sequencing Consortium; iPSYCH-Broad Consortium, Betancur C, Cook EH, Gallagher L, Gill M, Sutcliffe JS, Thurm A, Zwick ME, Børglum AD, State MW, Cicek AE, Talkowski ME, Cutler DJ, Devlin B, Sanders SJ, Roeder K, Daly MJ, Buxbaum JD.Cell. 2020 Jan 23. {Epub ahead of print]


Autism Spectrum Disorder (NIH/National Institute of Mental Health)

Joseph Buxbaum (Icahn School of Medicine at Mount Sinai, New York)

Sanders Lab (University of California, San Francisco)

Kathryn Roeder (Carnegie Mellon University, Pittsburgh, PA)

Mark Daly (Broad Institute of MIT and Harvard, Cambridge, MA)

Autism Sequencing Consortium (Emory University, Atlanta)

NIH Support: National Institute Mental Health; National Human Genome Research Institute

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