brain imaging
Researchers Map Neural Connections Key to Wakefulness in the Human Brain
Posted on by Dr. Monica M. Bertagnolli
Human consciousness requires a person to be both awake and aware. While neuroscientists have learned a great deal from research about the underlying brain networks that sustain awareness, surprisingly little has been known about the networks that keep us awake.
Now, an NIH-supported team of researchers has mapped the connectivity of a neural network they suggest is essential for wakefulness, or arousal, in the human brain. According to the researchers, this advance, reported in Science Translational Medicine, is essential for understanding human consciousness. It may also lead to new ways of understanding what happens in the brain when people lose consciousness, with potentially important implications for treating those who have entered a coma or vegetative state.
The team—led by Brian Edlow, Massachusetts General Hospital and Harvard Medical School, Boston, and Hannah Kinney, Boston Children’s Hospital and Harvard Medical School—set out to map the brain network that sustains wakefulness in a manner similar to earlier research that identified the default mode network, which influences awareness. Default networks in the brain are most active when people are at rest rather than focused on a goal-oriented task.
To map what they call the default ascending arousal network, the researchers knew they needed to capture connections deep within human brain areas previously implicated in wakefulness in animal studies. They wanted to use high resolution to uncover fine structural details. Because it isn’t currently possible to capture this in the brain of a living person within a reasonable scan time, the researchers looked to the brains of three organ donors who died without any neurological problems.
The researchers stained different types of brain cells in key areas of the brainstem, hypothalamus, thalamus, and basal forebrain, and took images of the donor brains using a sophisticated form of magnetic resonance imaging (MRI). Their data allowed them to map underlying structures and individual neural connections deep in the brain.
To learn more about how this wakefulness network functions, they next looked to a wealth of functional MRI data from 84 healthy study participants in the NIH-supported Human Connectome Project. Those data revealed functional connections between the arousal network and the previously identified default mode network that is active when people are awake but not attending to their surroundings. Further study revealed a “connectivity hub” between these networks in an area of the midbrain known as the dopaminergic ventral tegmental area, which helps in understanding how arousal and awareness are integrated in human consciousness.
These findings suggest that stimulating this key arousal hub for human consciousness may hold promise for helping people recover from a coma. In fact, the researchers have already launched a clinical trial to see whether stimulating the hub in people in a coma after traumatic brain injury could restore consciousness.
This new guide to brain areas that are essential to wakefulness may ultimately aid understanding of many conditions in which people have altered consciousness, including coma, seizures, and sudden infant death syndrome (SIDS), according to the researchers. And, to enable others to continue studying and uncovering other aspects of human consciousness, the team has made its MRI data, methods, and atlas freely available.
Reference:
[1] Edlow BL, et al. Multimodal MRI reveals brainstem connections that sustain wakefulness in human consciousness. Science Translational Medicine. DOI: 10.1126/scitranslmed.adj4303 (2024).
NIH Support: National Institute of Neurological Disorders and Stroke, National Institute for Biomedical Imaging and Bioengineering, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute on Deafness and Other Communication Disorders, National Institute on Aging, National Institute of Mental Health, NIH BRAIN Initiative
Changes in Normal Brain Connections Linked to Eating Disorders
Posted on by Lawrence Tabak, D.D.S., Ph.D.
Anyone who has ever had a bad habit knows how vexingly difficult breaking it can be. The reason is the repeated action, initially linked to some type of real or perceived reward, over time changes the way our very brains are wired to work. The bad habit becomes automatic, even when the action does us harm or we no longer wish to do it.
Now an intriguing new study shows that the same bundled nerve fibers, or brain circuits, involved in habit formation also can go awry in people with eating disorders. The findings may help to explain why eating disorders are so often resistant to will power alone. They also may help to point the way to improved approaches to treating eating disorders, suggesting strategies that adjust the actual brain circuitry in helpful ways.
These latest findings, published in the journal Science Translational Medicine, come from the NIH-supported Casey Halpern, University of Pennsylvania’s Perelman School of Medicine, Philadelphia, and Cara Bohon, Stanford University School of Medicine, Stanford, CA [1].
Halpern, Bohon, and colleagues were interested in a growing body of evidence linking habitual behaviors to mental health conditions, most notably substance use disorders and addictions. But what especially intrigued them was recent evidence also suggesting a possible role for habitual behaviors in the emergence of eating disorders.
To look deeper into the complex circuitry underlying habit formation and any changes there that might be associated with eating disorders, they took advantage of a vast collection of data from the NIH-funded Human Connectome Project (HCP). It was completed several years ago and now serves as a valuable online resource for researchers.
The HCP offers a detailed wiring map of a normal human brain. It describes all the structural and functional neural connections based on careful analyses of hundreds of high-resolution brain scans. These connections are then layered with genetic, behavioral, and other types of data. This incredible map now allows researchers to explore and sometimes uncover the roots of neurological and mental health conditions within the brain’s many trillions of connections.
In the new study, Halpern, Bohon, and colleagues did just that. First, they used sophisticated mapping methods in 178 brain scans from the HCP data to locate key portions of a brain region called the striatum, which is thought to be involved in habit formation. What they really wanted to know was whether circuits operating within the striatum were altered in some way in people with binge eating disorder or bulimia nervosa.
To find out, the researchers recruited 34 women who have an eating disorder and, with their consent, imaged their brains using a variety of techniques. Twenty-one participants were diagnosed with binge eating disorder, and 13 had bulimia nervosa. For comparison purposes, the researchers looked at the same brain circuits in 19 healthy volunteers.
The two groups were otherwise similar in terms of their ages, weights, and other features. But the researchers suspected they might find differences between the healthy group and those with an eating disorder in brain circuits known to have links to habitual behaviors. And, indeed, they did.
In comparison to a “typical” brain, those from people with an eating disorder showed striking changes in the connectivity of a portion of the striatum known as the putamen. That’s especially notable because the putamen is known for its role in learning and movement control, including reward, thinking, and addiction. What’s more, those observed changes in the brain’s connections and circuitry in this key brain area were more evident in people whose eating disorder symptoms and emotional eating were more frequent and severe.
Using other brain imaging methods in 10 of the volunteers (eight with binge eating disorder and two healthy controls), the researchers also connected those changes in the habit-forming brain circuits to high levels of a protein receptor that responds to dopamine. Dopamine is an important chemical messenger in the brain involved in pleasure, motivation, and learning. They also observed in those with eating disorders structural changes in the architecture of the densely folded, outer layer of the brain known as grey matter.
While there’s much more to learn, the researchers note the findings may lead to future treatments aimed to modify the brain circuitry in beneficial ways. Indeed, Halpern already has encouraging early results from a small NIH-funded clinical trial testing the ability of deep brain stimulation (DBS) in people with binge eating disorder to disrupt signals that drive food cravings in another portion of the brain associated with reward and motivation, known as the nucleus accumbens, [2]. In DBS, doctors implant a pacemaker-like device capable of delivering harmless therapeutic electrical impulses deep into the brain, aiming for the spot where they can reset the abnormal circuitry that’s driving eating disorders or other troubling symptoms or behaviors.
But the latest findings published in Science Translational Medicine now suggest other mapped brain circuits as potentially beneficial DBS targets for tackling binge eating, bulimia nervosa, or other life-altering, hard-to-treat eating disorders. They also may ultimately have implications for treating other conditions involving various other forms of compulsive behavior.
These findings should come as a source of hope for the family and friends of the millions of Americans—many of them young people—who struggle with eating disorders. The findings also serve as an important reminder for the rest of us that, despite common misconceptions that disordered eating is a lifestyle choice, these conditions are in fact complex and serious mental health problems driven by fundamental changes in the brain’s underlying circuitry.
Finding new and more effective ways to treat serious eating disorders and other compulsive behaviors is a must. It will require equally serious ongoing efforts to unravel their underlying causes and find ways to alter their course—and this new study is an encouraging step in that direction.
References:
[1] Human habit neural circuitry may be perturbed in eating disorders. Wang AR, Kuijper FM, Barbosa DAN, Hagan KE, Lee E, Tong E, Choi EY, McNab JA, Bohon C, Halpern CH. Sci Transl Med. 2023 Mar 29;15(689):eabo4919.
[2] Pilot study of responsive nucleus accumbens deep brain stimulation for loss-of-control eating. Shivacharan RS, Rolle CE, Barbosa DAN, Cunningham TN, Feng A, Johnson ND, Safer DL, Bohon C, Keller C, Buch VP, Parker JJ, Azagury DE, Tass PA, Bhati MT, Malenka RC, Lock JD, Halpern CH. Nat Med. 2022 Sep;28(9):1791-1796.
Links:
Eating Disorders (National Institute of Mental Health/NIH)
Casey Halpern (Penn Medicine, Philadelphia)
Cara Bohon (Stanford University, Stanford, CA)
NIH Support: National Institute of Mental Health; National Institute of Neurological Disorders and Stroke
Celebrating the Power of Connection This Holiday Season
Posted on by Lawrence Tabak, D.D.S., Ph.D.
Happy holidays to one and all! This short science video brings to mind all those twinkling lights now brightening the night, as we mark the beginning of winter and shortest day of the year. This video also helps to remind us about the power of connection this holiday season.
It shows a motor neuron in a mouse’s primary motor cortex. In this portion of the brain, which controls voluntary movement, heavily branched neural projections interconnect, sending and receiving signals to and from distant parts of the body. A single motor neuron can receive thousands of inputs at a time from other branching sensory cells, depicted in the video as an array of blinking lights. It’s only through these connections—through open communication and cooperation—that voluntary movements are possible to navigate and enjoy our world in all its wonder. One neuron, like one person, can’t do it all alone.
This power of connection, captured in this award-winning video from the 2022 Show Us Your Brains Photo and Video contest, comes from Forrest Collman, Allen Institute for Brain Science, Seattle. The contest is part of NIH’s Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative.
In the version above, we’ve taken some liberties with the original video to enhance the twinkling lights from the synaptic connections. But creating the original was quite a task. Collman sifted through reams of data from high-resolution electron microscopy imaging of the motor cortex to masterfully reconstruct this individual motor neuron and its connections.
Those data came from The Machine Intelligence from Cortical Networks (MICrONS) program, supported by the Intelligence Advanced Research Projects Activity (IARPA). It’s part of the Office of the Director of National Intelligence, one of NIH’s governmental collaborators in the BRAIN Initiative.
The MICrONS program aims to better understand the brain’s internal wiring. With this increased knowledge, researchers will develop more sophisticated machine learning algorithms for artificial intelligence applications, which will in turn advance fundamental basic science discoveries and the practice of life-saving medicine. For instance, these applications may help in the future to detect and evaluate a broad range of neural conditions, including those that affect the primary motor cortex.
Pretty cool stuff. So, as you spend this holiday season with friends and family, let this video and its twinkling lights remind you that there’s much more to the season than eating, drinking, and watching football games.
The holidays are very much about the power of connection for people of all faiths, beliefs, and traditions. It’s about taking time out from the everyday to join together to share memories of days gone by as we build new memories and stronger bonds of cooperation for the years to come. With this in mind, happy holidays to one and all.
Links:
“NIH BRAIN Initiative Unveils Detailed Atlas of the Mammalian Primary Motor Cortex,” NIH News Release, October 6, 2021
Forrest Collman (Allen Institute for Brain Science, Seattle)
Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)
Show Us Your Brains Photo and Video Contest (BRAIN Initiative)
The Amazing Brain: Seeing Two Memories at Once
Posted on by Lawrence Tabak, D.D.S., Ph.D.
The NIH’s Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative is revolutionizing our understanding of the human brain. As described in the initiative’s name, the development of innovative imaging technologies will enable researchers to see the brain in new and increasingly dynamic ways. Each year, the initiative celebrates some standout and especially creative examples of such advances in the “Show Us Your BRAINs! Photo & Video Contest. During most of August, I’ll share some of the most eye-catching developments in our blog series, The Amazing Brain.
In this fascinating image, you’re seeing two stored memories, which scientists call engrams, in the hippocampus region of a mouse’s brain. The engrams show the neural intersection of a good memory (green) and a bad memory (pink). You can also see the nuclei of many neurons (blue), including nearby neurons not involved in the memory formation.
This award-winning image was produced by Stephanie Grella in the lab of NIH-supported neuroscientist Steve Ramirez, Boston University, MA. It’s also not the first time that the blog has featured Grella’s technical artistry. Grella, who will soon launch her own lab at Loyola University, Chicago, previously captured what a single memory looks like.
To capture two memories at once, Grella relied on a technology known as optogenetics. This powerful method allows researchers to genetically engineer neurons and selectively activate them in laboratory mice using blue light. In this case, Grella used a harmless virus to label neurons involved in recording a positive experience with a light-sensitive molecule, known as an opsin. Another molecular label was used to make those same cells appear green when activated.
After any new memory is formed, there’s a period of up to about 24 hours during which the memory is malleable. Then, the memory tends to stabilize. But with each retrieval, the memory can be modified as it restabilizes, a process known as memory reconsolidation.
Grella and team decided to try to use memory reconsolidation to their advantage to neutralize an existing fear. To do this, they placed their mice in an environment that had previously startled them. When a mouse was retrieving a fearful memory (pink), the researchers activated with light associated with the positive memory (green), which for these particular mice consisted of positive interactions with other mice. The aim was to override or disrupt the fearful memory.
As shown by the green all throughout the image, the experiment worked. While the mice still showed some traces of the fearful memory (pink), Grella explained that the specific cells that were the focus of her study shifted to the positive memory (green).
What’s perhaps even more telling is that the evidence suggests the mice didn’t just trade one memory for another. Rather, it appears that activating a positive memory actually suppressed or neutralized the animal’s fearful memory. The hope is that this approach might one day inspire methods to help people overcome negative and unwanted memories, such as those that play a role in post-traumatic stress disorder (PTSD) and other mental health issues.
Links:
Stephanie Grella (Boston University, MA)
Ramirez Group (Boston University)
Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)
Show Us Your BRAINs Photo & Video Contest (BRAIN Initiative)
NIH Support: BRAIN Initiative; Common Fund
Human Brain Compresses Working Memories into Low-Res ‘Summaries’
Posted on by Lawrence Tabak, D.D.S., Ph.D.
You have probably done it already a few times today. Paused to remember a password, a shopping list, a phone number, or maybe the score to last night’s ballgame. The ability to store and recall needed information, called working memory, is essential for most of the human brain’s higher cognitive processes.
Researchers are still just beginning to piece together how working memory functions. But recently, NIH-funded researchers added an intriguing new piece to this neurobiological puzzle: how visual working memories are “formatted” and stored in the brain.
The findings, published in the journal Neuron, show that the visual cortex—the brain’s primary region for receiving, integrating, and processing visual information from the eye’s retina—acts more like a blackboard than a camera. That is, the visual cortex doesn’t photograph all the complex details of a visual image, such as the color of paper on which your password is written or the precise series of lines that make up the letters. Instead, it recodes visual information into something more like simple chalkboard sketches.
The discovery suggests that those pared down, low-res representations serve as a kind of abstract summary, capturing the relevant information while discarding features that aren’t relevant to the task at hand. It also shows that different visual inputs, such as spatial orientation and motion, may be stored in virtually identical, shared memory formats.
The new study, from Clayton Curtis and Yuna Kwak, New York University, New York, builds upon a known fundamental aspect of working memory. Many years ago, it was determined that the human brain tends to recode visual information. For instance, if passed a 10-digit phone number on a card, the visual information gets recoded and stored in the brain as the sounds of the numbers being read aloud.
Curtis and Kwak wanted to learn more about how the brain formats representations of working memory in patterns of brain activity. To find out, they measured brain activity with functional magnetic resonance imaging (fMRI) while participants used their visual working memory.
In each test, study participants were asked to remember a visual stimulus presented to them for 12 seconds and then make a memory-based judgment on what they’d just seen. In some trials, as shown in the image above, participants were shown a tilted grating, a series of black and white lines oriented at a particular angle. In others, they observed a cloud of dots, all moving in a direction to represent those same angles. After a short break, participants were asked to recall and precisely indicate the angle of the grating’s tilt or the dot cloud’s motion as accurately as possible.
It turned out that either visual stimulus—the grating or moving dots—resulted in the same patterns of neural activity in the visual cortex and parietal cortex. The parietal cortex is a part of the brain used in memory processing and storage.
These two distinct visual memories carrying the same relevant information seemed to have been recoded into a shared abstract memory format. As a result, the pattern of brain activity trained to recall motion direction was indistinguishable from that trained to recall the grating orientation.
This result indicated that only the task-relevant features of the visual stimuli had been extracted and recoded into a shared memory format. But Curtis and Kwak wondered whether there might be more to this finding.
To take a closer look, they used a sophisticated model that allowed them to project the three-dimensional patterns of brain activity into a more-informative, two-dimensional representation of visual space. And, indeed, their analysis of the data revealed a line-like pattern, similar to a chalkboard sketch that’s oriented at the relevant angles.
The findings suggest that participants weren’t actually remembering the grating or a complex cloud of moving dots at all. Instead, they’d compressed the images into a line representing the angle that they’d been asked to remember.
Many questions remain about how remembering a simple angle, a relatively straightforward memory formation, will translate to the more-complex sets of information stored in our working memory. On a technical level, though, the findings show that working memory can now be accessed and captured in ways that hadn’t been possible before. This will help to delineate the commonalities in working memory formation and the possible differences, whether it’s remembering a password, a shopping list, or the score of your team’s big victory last night.
Reference:
[1] Unveiling the abstract format of mnemonic representations. Kwak Y, Curtis CE. Neuron. 2022, April 7; 110(1-7).
Links:
Working Memory (National Institute of Mental Health/NIH)
The Curtis Lab (New York University, New York)
NIH Support: National Eye Institute
Tapping Into The Brain’s Primary Motor Cortex
Posted on by Dr. Francis Collins
If you’re like me, you might catch yourself during the day in front of a computer screen mindlessly tapping your fingers. (I always check first to be sure my mute button is on!) But all that tapping isn’t as mindless as you might think.
While a research participant performs a simple motor task, tapping her fingers together, this video shows blood flow within the folds of her brain’s primary motor cortex (gray and white), which controls voluntary movement. Areas of high brain activity (yellow and red) emerge in the omega-shaped “hand-knob” region, the part of the brain controlling hand movement (right of center) and then further back within the primary somatic cortex (which borders the motor cortex toward the back of the head).
About 38 seconds in, the right half of the video screen illustrates that the finger tapping activates both superficial and deep layers of the primary motor cortex. In contrast, the sensation of a hand being brushed (a sensory task) mostly activates superficial layers, where the primary sensory cortex is located. This fits with what we know about the superficial and deep layers of the hand-knob region, since they are responsible for receiving sensory input and generating motor output to control finger movements, respectively [1].
The video showcases a new technology called zoomed 7T perfusion functional MRI (fMRI). It was an entry in the recent Show Us Your BRAINs! Photo and Video Contest, supported by NIH’s Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative.
The technology is under development by an NIH-funded team led by Danny J.J. Wang, University of Southern California Mark and Mary Stevens Neuroimaging and Informatics Institute, Los Angeles. Zoomed 7T perfusion fMRI was developed by Xingfeng Shao and brought to life by the group’s medical animator Jim Stanis.
Measuring brain activity using fMRI to track perfusion is not new. The brain needs a lot of oxygen, carried to it by arteries running throughout the head, to carry out its many complex functions. Given the importance of oxygen to the brain, you can think of perfusion levels, measured by fMRI, as a stand-in measure for neural activity.
There are two things that are new about zoomed 7T perfusion fMRI. For one, it uses the first ultrahigh magnetic field imaging scanner approved by the Food and Drug Administration. The technology also has high sensitivity for detecting blood flow changes in tiny arteries and capillaries throughout the many layers of the cortex [2].
Compared to previous MRI methods with weaker magnets, the new technique can measure blood flow on a fine-grained scale, enabling scientists to remove unwanted signals (“noise”) such as those from surface-level arteries and veins. Getting an accurate read-out of activity from region to region across cortical layers can help scientists understand human brain function in greater detail in health and disease.
Having shown that the technology works as expected during relatively mundane hand movements, Wang and his team are now developing the approach for fine-grained 3D mapping of brain activity throughout the many layers of the brain. This type of analysis, known as mesoscale mapping, is key to understanding dynamic activities of neural circuits that connect brain cells across cortical layers and among brain regions.
Decoding circuits, and ultimately rewiring them, is a major goal of NIH’s BRAIN Initiative. Zoomed 7T perfusion fMRI gives us a window into 4D biology, which is the ability to watch 3D objects over time scales in which life happens, whether it’s playing an elaborate drum roll or just tapping your fingers.
References:
[1] Neuroanatomical localization of the ‘precentral knob’ with computed tomography imaging. Park MC, Goldman MA, Park MJ, Friehs GM. Stereotact Funct Neurosurg. 2007;85(4):158-61.
[2]. Laminar perfusion imaging with zoomed arterial spin labeling at 7 Tesla. Shao X, Guo F, Shou Q, Wang K, Jann K, Yan L, Toga AW, Zhang P, Wang D.J.J bioRxiv 2021.04.13.439689.
Links:
Brain Basics: Know Your Brain (National Institute of Neurological Disorders and Stroke)
Laboratory of Functional MRI Technology (University of Southern California Mark and Mary Stevens Neuroimaging and Informatics Institute)
The Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)
Show Us Your BRAINs! Photo and Video Contest (BRAIN Initiative)
NIH Support: National Institute of Neurological Disorders and Stroke; National Institute of Biomedical Imaging and Bioengineering; Office of the Director
The Amazing Brain: Motor Neurons of the Cervical Spine
Posted on by Dr. Francis Collins
Today, you may have opened a jar, done an upper body workout, played a guitar or a piano, texted a friend, or maybe even jotted down a grocery list longhand. All of these “skilled” arm, wrist, and hand movements are made possible by the bundled nerves, or circuits, running through a part of the central nervous system in the neck area called the cervical spine.
This video, which combines sophisticated imaging and computation with animation, shows the density of three types of nerve cells in the mouse cervical spine. There are the V1 interneurons (red), which sit between sensory and motor neurons; motor neurons associated with controlling the movement of the bicep (blue); and motor neurons associated with controlling the tricep (green).
At 4 seconds, the 3D animation morphs to show all the colors and cells intermixed as they are naturally in the cervical spine. At 8 seconds, the animation highlights the density of these three cells types. Notice in the bottom left corner, a light icon appears indicating the different imaging perspectives. What’s unique here is the frontal, or rostral, view of the cervical spine. The cervical spine is typically imaged from a lateral, or side, perspective.
Starting at 16 seconds, the animation highlights the location and density of each of the individual neurons. For the grand finale, viewers zoom off on a brief fly-through of the cervical spine and a flurry of reds, blues, and greens.
The video comes from Jamie Anne Mortel, a research assistant in the lab of Samuel Pfaff, Salk Institute, La Jolla, CA. Mortel is part of a team supported by the NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative that’s developing a comprehensive atlas of the circuitry within the cervical spine that controls how mice control their forelimb movements, such as reaching and grasping.
This basic research will provide a better understanding of how the mammalian brain and spinal cord work together to produce movement. More than that, this research may provide valuable clues into better treating paralysis to arms, wrists, and/or hands caused by neurological diseases and spinal cord injuries.
As a part of this project, the Pfaff lab has been busy developing a software tool to take their imaging data from different parts of the cervical spine and present it in 3D. Mortel, who likes to make cute cartoon animations in her spare time, noticed that the software lacked animation capability. So she took the initiative and spent the next three weeks working after hours to produce this video—her first attempt at scientific animation. No doubt she must have been using a lot of wrist and hand movements!
With a positive response from her Salk labmates, Mortel decided to enter her scientific animation debut in the 2021 Show Us BRAINs! Photo and Video Contest. To her great surprise and delight, Mortel won third place in the video competition. Congratulations, and continued success for you and the team in producing this much-needed atlas to define the circuitry underlying skilled arm, wrist, and hand movements.
Links:
Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)
Spinal Cord Injury Information Page (National Institute of Neurological Disorders and Stroke/NIH)
Samuel Pfaff (Salk Institute, La Jolla, CA)
Show Us Your BRAINs! Photo and Video Contest (Brain Initiative/NIH)
NIH Support: National Institute of Neurological Disorders and Stroke
The Amazing Brain: Tracking Molecular Events with Calling Cards
Posted on by Dr. Francis Collins
In days mostly gone by, it was fashionable in some circles for people to hand out calling cards to mark their arrival at special social events. This genteel human tradition is now being adapted to the lab to allow certain benign viruses to issue their own high-tech calling cards and mark their arrival at precise locations in the genome. These special locations show where there’s activity involving transcription factors, specialized proteins that switch genes on and off and help determine cell fate.
The idea is that myriad, well-placed calling cards can track brain development over time in mice and detect changes in transcription factor activity associated with certain neuropsychiatric disorders. This colorful image, which won first place in this year’s Show Us Your BRAINs! Photo and Video contest, provides a striking display of these calling cards in action in living brain tissue.
The image comes from Allen Yen, a PhD candidate in the lab of Joseph Dougherty, collaborating with the nearby lab of Rob Mitra. Both labs are located in the Washington University School of Medicine, St. Louis.
Yen and colleagues zoomed in on this section of mouse brain tissue under a microscope to capture dozens of detailed images that they then stitched together to create this high-resolution overview. The image shows neural cells (red) and cell nuclei (blue). But focus in on the neural cells (green) concentrated in the brain’s outer cortex (top) and hippocampus (two lobes in the upper center). They’ve been labelled with calling cards that were dropped off by adeno-associated virus [1].
Once dropped off, a calling card doesn’t bear a pretentious name or title. Rather, the calling card, is a small mobile snippet of DNA called a transposon. It gets dropped off with the other essential component of the technology: a specialized enzyme called a transposase, which the researchers fuse to one of many specific transcription factors of interest.
Each time one of these transcription factors of interest binds DNA to help turn a gene on or off, the attached transposase “grabs” a transposon calling card and inserts it into the genome. As a result, it leaves behind a permanent record of the interaction.
What’s also nice is the calling cards are programmed to give away their general locations. That’s because they encode a fluorescent marker (in this image, it’s a green fluorescent protein). In fact, Yen and colleagues could look under a microscope and tell from all the green that their calling card technology was in place and working as intended.
The final step, though, was to find out precisely where in the genome those calling cards had been left. For this, the researchers used next-generation sequencing to produce a cumulative history and map of each and every calling card dropped off in the genome.
These comprehensive maps allow them to identify important DNA-protein binding events well after the fact. This innovative technology also enables scientists to attribute past molecular interactions with observable developmental outcomes in a way that isn’t otherwise possible.
While the Mitra and Dougherty labs continue to improve upon this technology, it’s already readily adaptable to answer many important questions about the brain and brain disorders. In fact, Yen is now applying the technology to study neurodevelopment in mouse models of neuropsychiatric disorders, specifically autism spectrum disorder (ASD) [2]. This calling card technology also is available for any lab to deploy for studying a transcription factor of interest.
This research is supported by the Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative. One of the major goals of BRAIN Initiative is to accelerate the development and application of innovative technologies to gain new understanding of the brain. This award-winning image is certainly a prime example of striving to meet this goal. I’ll look forward to what these calling cards will tell us in the future about ASD and other important neurodevelopmental conditions affecting the brain.
References:
[1] A viral toolkit for recording transcription factor-DNA interactions in live mouse tissues. Cammack AJ, Moudgil A, Chen J, Vasek MJ, Shabsovich M, McCullough K, Yen A, Lagunas T, Maloney SE, He J, Chen X, Hooda M, Wilkinson MN, Miller TM, Mitra RD, Dougherty JD. Proc Natl Acad Sci U S A. 2020 May 5;117(18):10003-10014.
[2] A MYT1L Syndrome mouse model recapitulates patient phenotypes and reveals altered brain development due to disrupted neuronal maturation. Jiayang Chen, Mary E. Lambo, Xia Ge, Joshua T. Dearborn, Yating Liu, Katherine B. McCullough, Raylynn G. Swift, Dora R. Tabachnick, Lucy Tian, Kevin Noguchi, Joel R. Garbow, John N. Constantino. bioRxiv. May 27, 2021.
Links:
Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)
Autism Spectrum Disorder (National Institute of Mental Health/NIH)
Dougherty Lab (Washington University School of Medicine, St. Louis)
Mitra Lab (Washington University School of Medicine)
Show Us Your BRAINs! Photo and Video Contest (BRAIN Initiative/NIH)
NIH Support: National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Center for Advancing Translational Sciences; National Human Genome Research Institute; National Institute of General Medical Sciences
The Amazing Brain: A Sharper Image of the Pyramidal Tract
Posted on by Dr. Francis Collins
Flip the image above upside down, and the shape may remind you of something. If you think it resembles a pyramid, then you and a lot of great neuroscientists are thinking alike. What you are viewing is a colorized, 3D reconstruction of a pyramidal tract, which are bundles of nerve fibers that originate from the brain’s cerebral cortex and relay signals to the brainstem or the spinal cord. These signals control many important activities, including the voluntary movement of our arms, legs, head, and face.
For a while now, it’s been possible to combine a specialized form of magnetic resonance imaging (MRI) with computer modeling tools to produce 3D reconstructions of complicated networks of nerve fibers, such as the pyramidal tract. Still, for technical reasons, the quality of these reconstructions has remained poor in parts of the brain where nerve fibers cross at angles of 40 degrees or less.
The video above demonstrates how adding a sophisticated algorithm, called Orientation Distribution Function (ODF)-Fingerprinting, to such modeling can help overcome this problem when reconstructing a pyramidal tract. It has potential to enhance the reliability of these 3D reconstructions as neurosurgeons begin to use them to plan out their surgeries to help ensure they are carried out with the utmost safety and precision.
In the first second of the video, you see gray, fuzzy images from a diffusion MRI of the pyramidal tract. But, very quickly, a more colorful, detailed 3D reconstruction begins to appear, swiftly filling in from the top down. Colors are used to indicate the primary orientations of the nerve fibers: left to right (red), back to front (green), and top to bottom (blue). The orange, magenta, and other colors represent combinations of these primary directional orientations.
About three seconds into the video, a rough draft of the 3D reconstruction is complete. The top of the pyramidal tract looks pretty good. However, looking lower down, you can see distortions in color and relatively poor resolution of the nerve fibers in the middle of the tract—exactly where the fibers cross each other at angles of less than 40 degrees. So, researchers tapped into the power of their new ODF-Fingerprinting software to improve the image—and, starting about nine seconds into the video, you can see an impressive final result.
The researchers who produced this amazing video are Patryk Filipiak and colleagues in the NIH-supported lab of Steven Baete, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York. The work paired diffusion MRI data from the NIH Human Connectome Project with the ODF-Fingerprinting algorithm, which was created by Baete to incorporate additional MRI imaging data on the shape of nerve fibers to infer their directionality [1].
This innovative approach to imaging recently earned Baete’s team second place in the 2021 “Show Us Your BRAINs” Photo and Video contest, sponsored by the NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative. But researchers aren’t stopping there! They are continuing to refine ODF-Fingerprinting, with the aim of modeling the pyramidal tract in even higher resolution for use in devising new and better ways of helping people undergoing neurosurgery.
Reference:
[1] Fingerprinting Orientation Distribution Functions in diffusion MRI detects smaller crossing angles. Baete SH, Cloos MA, Lin YC, Placantonakis DG, Shepherd T, Boada FE. Neuroimage. 2019 Sep;198:231-241.
Links:
Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)
Human Connectome Project (University of Southern California, Los Angeles)
Steven Baete (Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York)
Show Us Your BRAINs! Photo and Video Contest (BRAIN Initiative/NIH)
NIH Support: National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Cancer Institute
The Amazing Brain: Visualizing Data to Understand Brain Networks
Posted on by Dr. Francis Collins
The NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative continues to teach us about the world’s most sophisticated computer: the human brain. This striking image offers a spectacular case in point, thanks to a new tool called Visual Neuronal Dynamics (VND).
VND is not a camera. It is a powerful software program that can display, animate, and analyze models of neurons and their connections, or networks, using 3D graphics. What you’re seeing in this colorful image is a strip of mouse primary visual cortex, the area in the brain where incoming sensory information gets processed into vision.
This strip contains more than 230,000 neurons of 17 different cell types. Long and spindly excitatory neurons that point upward (purple, blue, red, orange) are intermingled with short and stubby inhibitory neurons (green, cyan, magenta). Slicing through the neuronal landscape is a neuropixels probe (silver): a tiny flexible silicon detector that can record brain activity in awake animals [1].
Developed by Emad Tajkhorshid and his team at University of Illinois at Urbana-Champaign, along with Anton Arkhipov of the Allen Institute, Seattle, VND represents a scientific milestone for neuroscience: using an adept software tool to see and analyze massive neuronal datasets on a computer. What’s also nice is the computer doesn’t have to be a fancy one, and VND’s instructions, or code, are publicly available for anyone to use.
VND is the neuroscience-adapted cousin of Visual Molecular Dynamics (VMD), a popular molecular biology visualization tool to see life up close in 3D, also developed by Tajkhorshid’s group [2]. By modeling and visualizing neurons and their connections, VND helps neuroscientists understand at their desktops how neural networks are organized and what happens when they are manipulated. Those visualizations then lay the groundwork for follow-up lab studies to validate the data and build upon them.
Through the Allen Institute, the NIH BRAIN Initiative is compiling a comprehensive whole-brain atlas of cell types in the mouse, and Arkhipov’s work integrates these data into computer models. In May 2020, his group published comprehensive models of the mouse primary visual cortex [3].
Arkhipov and team are now working to understand how the primary visual cortex’s physical structure (the cell shapes and connections within its complicated circuits) determines its outputs. For example, how do specific connections determine network activity? Or, how fast do cells fire under different conditions?
Ultimately, such computational research may help us understand how brain injuries or disease affect the structure and function of these neural networks. VND should also propel understanding of many other areas of the brain, for which the data are accumulating rapidly, to answer similar questions that still remain mysterious to scientists.
In the meantime, VND is also creating some award-winning art. The image above was the second-place photo in the 2021 “Show us Your BRAINs!” Photo and Video Contest sponsored by the NIH BRAIN Initiative.
References:
[1] Fully integrated silicon probes for high-density recording of neural activity. Jun JJ, Steinmetz NA, Siegle JH, Denman DJ, Bauza M, Barbarits B, Lee AK, Anastassiou CA, Andrei A, Aydın Ç, Barbic M, Blanche TJ, Bonin V, Couto J, Dutta B, Gratiy SL, Gutnisky DA, Häusser M, Karsh B, Ledochowitsch P, Lopez CM, Mitelut C, Musa S, Okun M, Pachitariu M, Putzeys J, Rich PD, Rossant C, Sun WL, Svoboda K, Carandini M, Harris KD, Koch C, O’Keefe J, Harris TD. Nature. 2017 Nov 8;551(7679):232-236.
[2] VMD: visual molecular dynamics. Humphrey W, Dalke A, Schulten K. J Mol Graph. 1996 Feb;14(1):33-8, 27-8.
[3] Systematic integration of structural and functional data into multi-scale models of mouse primary visual cortex. Billeh YN, Cai B, Gratiy SL, Dai K, Iyer R, Gouwens NW, Abbasi-Asl R, Jia X, Siegle JH, Olsen SR, Koch C, Mihalas S, Arkhipov A. Neuron. 2020 May 6;106(3):388-403.e18
Links:
The Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)
Models of the Mouse Primary Visual Cortex (Allen Institute, Seattle)
Visual Neuronal Dynamics (NIH Center for Macromolecular Modeling and Bioinformatics, University of Illinois at Urbana-Champaign)
Tajkhorshid Lab (University of Illinois at Urbana-Champaign)
Arkhipov Lab (Allen Institute)
Show Us Your BRAINs! Photo & Video Contest (BRAIN Initiative/NIH)
NIH Support: National Institute of Neurological Disorders and Stroke
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