I have read that neurons have proportionately less MHC molecules than other cells of the body. What is the advantage of this?
Antigen presentation by MHC will induce a cytotoxic response by the immune system, which is usually a good thing in the body since most cells can just divide and replicate again. Neurons, however, are particularly ineffective at regenerating from such an attack, and are not easy to come by; they are also rather important! Better not to risk it, eh?
That being said, neuronal expression of MHC is actually a pretty complex case, and this open-access article is a good start down the rabbit hole (see also here, here, and here if you have access).
Number of MHCs in neurons - Biology
Neurons and glia coordinate actions and transmit signals in the CNS and PNS.
Recall the differences in structure and function between the central and peripheral nervous systems
- The central nervous system contains the brain and spinal cord the peripheral nervous system consists of nerves, motor neurons, the autonomic nervous system, and the enteric nervous system.
- The nervous system coordinates the voluntary and involuntary actions of the body by transmitting signals from the brain to the other body parts and listening for feedback.
- Nervous systems vary across different animals some invertebrates lack a true nervous system or true brain, while other invertebrates have a brain and a system of nerves.
- Unlike vertebrates, not all invertebrates have both a CNS and PNS their nerve cords are located ventrally rather than dorsally.
- The functions of the nervous system are performed by two types of cells: neurons, which transmit signals between them and from one part of the body to another, and glia, which regulate homeostasis, providing support and protection to the function of neurons.
- neuron: cell of the nervous system that conducts nerve impulses consisting of an axon and several dendrites
- nervous system: an organ system that coordinates the body’s voluntary and involuntary actions and transmits signals between different parts of the body
- glial cell: cell in the nervous system that supports and protects neurons
The Nervous System: Introduction
The nervous system coordinates the body’s voluntary and involuntary actions and transmits signals between different parts of the body. Nervous tissue first arose in wormlike organisms approximately 550 to 600 million years ago. In most types of vertebrate animals, it consists of two main parts: the central nervous system (CNS) and the peripheral nervous system (PNS). The CNS contains the brain and spinal cord. The PNS consists mainly of nerves, which are long fibers that connect the CNS to every other part of the body. The PNS includes motor neurons (mediating voluntary movement), the autonomic nervous system (comprising the sympathetic nervous system and the parasympathetic nervous system, which regulate involuntary functions), and the enteric nervous system (a semi-independent part of the nervous system whose function is to control the gastrointestinal system).
The nervous system performs several functions simultaneously. For example, as you are reading, the visual system is processing what is seen on the page the motor system controls the turn of the pages (or click of the mouse) the prefrontal cortex maintains attention. Even fundamental functions, like breathing and regulation of body temperature, are controlled by the nervous system. A nervous system is an organism’s control center: it processes sensory information from outside (and inside) the body and controls all behaviors, from eating to sleeping to finding a mate.
Nervous system at work: An athlete’s nervous system is hard at work during the planning and execution of a movement as precise as a high jump. Parts of the nervous system are involved in determining how hard to push off and when to turn, as well as controlling the muscles throughout the body that make this complicated movement possible without knocking the bar down all in just a few seconds.
Nervous systems throughout the animal kingdom vary in structure and complexity. Some organisms, such as sea sponges, lack a true nervous system. Others, such as jellyfish, lack a true brain. Instead, they have a system of separate-but-connected nerve cells (neurons) called a “nerve net.” Echinoderms, such as sea stars, have nerve cells that are bundled into fibers called nerves. Flatworms of the phylum Platyhelminthes have both a central nervous system, made up of a small “brain” and two nerve cords, and a peripheral nervous system containing a system of nerves that extend throughout the body. The insect nervous system is more complex, but also fairly decentralized. It contains a brain, ventral nerve cord, and ganglia (clusters of connected neurons). These ganglia can control movements and behaviors without input from the brain. Octopi may have the most complicated of invertebrate nervous systems. They have neurons that are organized in specialized lobes and eyes that are structurally similar to vertebrate species.
Various nervous systems: (a) In cnidarians, nerve cells form a decentralized nerve net. (b) In echinoderms, nerve cells are bundled into fibers called nerves. (c) In animals exhibiting bilateral symmetry, such as planarians, neurons cluster into an anterior brain that processes information. (d) In addition to a brain, arthropods have clusters of nerve cell bodies, called peripheral ganglia, located along the ventral nerve cord. Mollusks, such as squid and (e) octopi, which must hunt to survive, have complex brains containing millions of neurons. In (f) vertebrates, the brain and spinal cord comprise the central nervous system, while neurons extending into the rest of the body comprise the peripheral nervous system.
Compared to invertebrates, vertebrate nervous systems are more complex, centralized, and specialized. While there is great diversity among different vertebrate nervous systems, they all share a basic structure: a CNS and a PNS. One interesting difference between the nervous systems of invertebrates and vertebrates is that the nerve cords of many invertebrates are located ventrally (near the abdomen), whereas the vertebrate spinal cords are located dorsally (near the back). There is debate among evolutionary biologists as to whether these different nervous system plans evolved separately or whether the invertebrate body plan arrangement somehow “flipped” during the evolution of vertebrates.
The nervous system is made up of neurons, specialized cells that can receive and transmit chemical or electrical signals, and glia, cells that provide support functions for the neurons by playing an information processing role that is complementary to neurons. A neuron can be compared to an electrical wire: it transmits a signal from one place to another. Glia can be compared to the workers at the electric company who make sure wires go to the right places, maintain the wires, and take down wires that are broken. Although glial cells support neurons, recent evidence suggests they also assume some of the signaling functions of neurons.
Molecular Cell Biology. 4th edition.
In this introductory section, we describe the structural features that are unique to neurons and the types of electric signals that they use to process and transmit information. We then introduce synapses, the specialized sites where neurons send and receive information from other cells, and some of the circuits that allow groups of neurons to coordinate complex processes. Each of these topics will be covered in more detail in later sections of the chapter.
35.1 Neurons and Glial Cells
By the end of this section, you will be able to do the following:
- List and describe the functions of the structural components of a neuron
- List and describe the four main types of neurons
- Compare the functions of different types of glial cells
Nervous systems throughout the animal kingdom vary in structure and complexity, as illustrated by the variety of animals shown in Figure 35.2. Some organisms, like sea sponges, lack a true nervous system. Others, like jellyfish, lack a true brain and instead have a system of separate but connected nerve cells (neurons) called a “nerve net.” Echinoderms such as sea stars have nerve cells that are bundled into fibers called nerves. Flatworms of the phylum Platyhelminthes have both a central nervous system (CNS), made up of a small “brain” and two nerve cords, and a peripheral nervous system (PNS) containing a system of nerves that extend throughout the body. The insect nervous system is more complex but also fairly decentralized. It contains a brain, ventral nerve cord, and ganglia (clusters of connected neurons). These ganglia can control movements and behaviors without input from the brain. Octopi may have the most complicated of invertebrate nervous systems—they have neurons that are organized in specialized lobes and eyes that are structurally similar to vertebrate species.
Compared to invertebrates, vertebrate nervous systems are more complex, centralized, and specialized. While there is great diversity among different vertebrate nervous systems, they all share a basic structure: a CNS that contains a brain and spinal cord and a PNS made up of peripheral sensory and motor nerves. One interesting difference between the nervous systems of invertebrates and vertebrates is that the nerve cords of many invertebrates are located ventrally whereas the vertebrate spinal cords are located dorsally. There is debate among evolutionary biologists as to whether these different nervous system plans evolved separately or whether the invertebrate body plan arrangement somehow “flipped” during the evolution of vertebrates.
Link to Learning
Watch this video of biologist Mark Kirschner discussing the “flipping” phenomenon of vertebrate evolution.
The nervous system is made up of neurons , specialized cells that can receive and transmit chemical or electrical signals, and glia , cells that provide support functions for the neurons by playing an information processing role that is complementary to neurons. A neuron can be compared to an electrical wire—it transmits a signal from one place to another. Glia can be compared to the workers at the electric company who make sure wires go to the right places, maintain the wires, and take down wires that are broken. Although glia have been compared to workers, recent evidence suggests that they also usurp some of the signaling functions of neurons.
There is great diversity in the types of neurons and glia that are present in different parts of the nervous system. There are four major types of neurons, and they share several important cellular components.
The nervous system of the common laboratory fly, Drosophila melanogaster, contains around 100,000 neurons, the same number as a lobster. This number compares to 75 million in the mouse and 300 million in the octopus. A human brain contains around 86 billion neurons. Despite these very different numbers, the nervous systems of these animals control many of the same behaviors—from basic reflexes to more complicated behaviors like finding food and courting mates. The ability of neurons to communicate with each other as well as with other types of cells underlies all of these behaviors.
Most neurons share the same cellular components. But neurons are also highly specialized—different types of neurons have different sizes and shapes that relate to their functional roles.
Parts of a Neuron
Like other cells, each neuron has a cell body (or soma) that contains a nucleus, smooth and rough endoplasmic reticulum, Golgi apparatus, mitochondria, and other cellular components. Neurons also contain unique structures, illustrated in Figure 35.3 for receiving and sending the electrical signals that make neuronal communication possible. Dendrites are tree-like structures that extend away from the cell body to receive messages from other neurons at specialized junctions called synapses . Although some neurons do not have any dendrites, some types of neurons have multiple dendrites. Dendrites can have small protrusions called dendritic spines, which further increase surface area for possible synaptic connections.
Once a signal is received by the dendrite, it then travels passively to the cell body. The cell body contains a specialized structure, the axon hillock that integrates signals from multiple synapses and serves as a junction between the cell body and an axon . An axon is a tube-like structure that propagates the integrated signal to specialized endings called axon terminals . These terminals in turn synapse on other neurons, muscle, or target organs. Chemicals released at axon terminals allow signals to be communicated to these other cells. Neurons usually have one or two axons, but some neurons, like amacrine cells in the retina, do not contain any axons. Some axons are covered with myelin , which acts as an insulator to minimize dissipation of the electrical signal as it travels down the axon, greatly increasing the speed of conduction. This insulation is important as the axon from a human motor neuron can be as long as a meter—from the base of the spine to the toes. The myelin sheath is not actually part of the neuron. Myelin is produced by glial cells. Along the axon there are periodic gaps in the myelin sheath. These gaps are called nodes of Ranvier and are sites where the signal is “recharged” as it travels along the axon.
It is important to note that a single neuron does not act alone—neuronal communication depends on the connections that neurons make with one another (as well as with other cells, like muscle cells). Dendrites from a single neuron may receive synaptic contact from many other neurons. For example, dendrites from a Purkinje cell in the cerebellum are thought to receive contact from as many as 200,000 other neurons.
Which of the following statements is false?
- The soma is the cell body of a nerve cell.
- Myelin sheath provides an insulating layer to the dendrites.
- Axons carry the signal from the soma to the target.
- Dendrites carry the signal to the soma.
Types of Neurons
There are different types of neurons, and the functional role of a given neuron is intimately dependent on its structure. There is an amazing diversity of neuron shapes and sizes found in different parts of the nervous system (and across species), as illustrated by the neurons shown in Figure 35.4.
While there are many defined neuron cell subtypes, neurons are broadly divided into four basic types: unipolar, bipolar, multipolar, and pseudounipolar. Figure 35.5 illustrates these four basic neuron types. Unipolar neurons have only one structure that extends away from the soma. These neurons are not found in vertebrates but are found in insects where they stimulate muscles or glands. A bipolar neuron has one axon and one dendrite extending from the soma. An example of a bipolar neuron is a retinal bipolar cell, which receives signals from photoreceptor cells that are sensitive to light and transmits these signals to ganglion cells that carry the signal to the brain. Multipolar neurons are the most common type of neuron. Each multipolar neuron contains one axon and multiple dendrites. Multipolar neurons can be found in the central nervous system (brain and spinal cord). An example of a multipolar neuron is a Purkinje cell in the cerebellum, which has many branching dendrites but only one axon. Pseudounipolar cells share characteristics with both unipolar and bipolar cells. A pseudounipolar cell has a single process that extends from the soma, like a unipolar cell, but this process later branches into two distinct structures, like a bipolar cell. Most sensory neurons are pseudounipolar and have an axon that branches into two extensions: one connected to dendrites that receive sensory information and another that transmits this information to the spinal cord.
At one time, scientists believed that people were born with all the neurons they would ever have. Research performed during the last few decades indicates that neurogenesis, the birth of new neurons, continues into adulthood. Neurogenesis was first discovered in songbirds that produce new neurons while learning songs. For mammals, new neurons also play an important role in learning: about 1000 new neurons develop in the hippocampus (a brain structure involved in learning and memory) each day. While most of the new neurons will die, researchers found that an increase in the number of surviving new neurons in the hippocampus correlated with how well rats learned a new task. Interestingly, both exercise and some antidepressant medications also promote neurogenesis in the hippocampus. Stress has the opposite effect. While neurogenesis is quite limited compared to regeneration in other tissues, research in this area may lead to new treatments for disorders such as Alzheimer’s, stroke, and epilepsy.
How do scientists identify new neurons? A researcher can inject a compound called bromodeoxyuridine (BrdU) into the brain of an animal. While all cells will be exposed to BrdU, BrdU will only be incorporated into the DNA of newly generated cells that are in S phase. A technique called immunohistochemistry can be used to attach a fluorescent label to the incorporated BrdU, and a researcher can use fluorescent microscopy to visualize the presence of BrdU, and thus new neurons, in brain tissue. Figure 35.6 is a micrograph which shows fluorescently labeled neurons in the hippocampus of a rat.
Link to Learning
This site contains more information about neurogenesis, including an interactive laboratory simulation and a video that explains how BrdU labels new cells.
While glia are often thought of as the supporting cast of the nervous system, the number of glial cells in the brain actually outnumbers the number of neurons by a factor of ten. Neurons would be unable to function without the vital roles that are fulfilled by these glial cells. Glia guide developing neurons to their destinations, buffer ions and chemicals that would otherwise harm neurons, and provide myelin sheaths around axons. Scientists have recently discovered that they also play a role in responding to nerve activity and modulating communication between nerve cells. When glia do not function properly, the result can be disastrous—most brain tumors are caused by mutations in glia.
Types of Glia
There are several different types of glia with different functions, two of which are shown in Figure 35.7. Astrocytes , shown in Figure 35.8a make contact with both capillaries and neurons in the CNS. They provide nutrients and other substances to neurons, regulate the concentrations of ions and chemicals in the extracellular fluid, and provide structural support for synapses. Astrocytes also form the blood-brain barrier—a structure that blocks entrance of toxic substances into the brain. Astrocytes, in particular, have been shown through calcium imaging experiments to become active in response to nerve activity, transmit calcium waves between astrocytes, and modulate the activity of surrounding synapses. Satellite glia provide nutrients and structural support for neurons in the PNS. Microglia scavenge and degrade dead cells and protect the brain from invading microorganisms. Oligodendrocytes , shown in Figure 35.8b form myelin sheaths around axons in the CNS. One axon can be myelinated by several oligodendrocytes, and one oligodendrocyte can provide myelin for multiple neurons. This is distinctive from the PNS where a single Schwann cell provides myelin for only one axon as the entire Schwann cell surrounds the axon. Radial glia serve as scaffolds for developing neurons as they migrate to their end destinations. Ependymal cells line fluid-filled ventricles of the brain and the central canal of the spinal cord. They are involved in the production of cerebrospinal fluid, which serves as a cushion for the brain, moves the fluid between the spinal cord and the brain, and is a component for the choroid plexus.
Elephants Have The Most Neurons. Why Aren't They The Smartest Animals?
Why aren't elephants the smartest animals since they have the most neurons? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.
Answer by Fabian van den Berg, Neuropsychologist, on Quora:
Why aren't elephants the smartest animals since they have the most neurons?
We often hear 'bigger is better' which might be true for pay-checks but not for other things. I’m of course talking about brains, what else? Nature has an astounding diversity of life, each with a unique brain. Some of those brains grow to be massive organs, like that of the African Elephant with a 5kg brain (11lbs) and 257 billion neurons. Some brains stay tiny, like that of roundworms which comes in at only a fraction of a gram with about 300 neurons in total. Humans rank in between, with a 1.4kg (3lbs) brain and give or take 86 billion neurons.
That begs the question, if humans are outranked by animals such as elephants, why are we the self-proclaimed smartest creature on earth? How is it that an elephant with almost 3 times the number of neurons isn’t laughing at our struggle with quantum mechanics?
Like a late night news-report, the reason might surprise you. To put it bluntly, humans aren’t all that special. Like mentioned above, we don’t have the biggest brain with the most neurons. Nor do we have the brain with the biggest surface area dolphins beat us there with their amazingly complex brain folds. We get a bit closer if we take body size into account, but we’d lose from a marmoset (a sort of small monkey which honestly isn’t all that bright). A new measure was developed called the ‘encephalisation quotient’ (EQ), which takes into account that the relationship between brain and body size isn’t linear. It’s a whole formula, but it gave us what we needed for our ego, we were on top! Based on our size we have a brain that is 7 times larger than it should be. Sounds great for us, but the measure failed a bit for other animals. The rhesus monkey should be smarter than a gorilla if we were to believe their EQ, which isn’t the case. That puts us back to square one.
Humans don’t stand out that much in general, except when it comes to intelligence. Absolute brain size isn’t what makes us smart, neither is surface area, EQ, or neuron density. Then why is it that an elephant, with a huge brain and more neurons, isn’t as smart or even smarter than a human? This is where neuroscience and biology get a bit tricky, an example might help.
Consider the fastest supercomputer in the world. At the time of writing, that is the Summit made by IBM. It has an impressive 9.216 CPUs, 27.648 GPUs and can make 200 quadrillion calculations per second. For comparison, it would take every person on earth working together, doing 1 calculation per second for almost a year to do what this machine can do in 1 second. It is set to model the universe, explore cancer, and figure out genetics on a scale we cannot imagine. But can it run Minecraft? No it cannot. Yet my old i7 quad-core laptop can run Minecraft just fine. Weird isn’t it, an immense computer with more memory and processing power than fits in my apartment can’t run a simple game that my rickety laptop can? So much for “super” computers.
The truth is, the thing isn’t designed to run Minecraft. It’s made to run those complex astronomical and biological models, while my laptop is designed to run games and various other tasks useful to me. I’m sure with some fiddling you can get any game running on those systems, but you’d definitely get in trouble for that. When comparing brains, the absolute neuron count isn’t the only thing we need to look at. Just like absolute processing power isn’t the only thing you look for when you need to play Minecraft. What’s in a machine, how it’s connected, how it interfaces, all change depending on a computer’s purpose.
Human brains and Elephant brain are different in more ways than one. Different parts have different concentrations of neurons for example. Despite having three times as many neurons, elephants only have a third as many neurons in their cerebral cortex. The cortex just so happens to be the part of the brain we associate with a lot of “higher cognitive functions” and intelligence. All those elephant brain cells are concentrated in other areas, like the cerebellum which is used for movements (that trunk does look very capable).
The way the brain is put together is another factor. We estimate that Neanderthals had bigger brains than us they had the capacity for a 1600cm3 brain. When researchers recently grew some Neanderthal brain-matter, we saw that they were very different from our own. Human mini-brains were nice, smooth spheres, whereas Neanderthal brains were more like popcorn. The consequences are still not clear, but it does bring us to this point: brains are complicated. Brains aren’t homogenous masses of neurons and support cells. Brains have structure to them, neurons form columns and layers, have specific pathways to send and receive specific information. The way neurons are structured and connected affects what and how they process information. Different animals have different needs, different senses, and different bodies. Brains are formed to deal with all of that. An elephant needs to control its trunk to get food, not solve math problems to get good grades.
As mentioned in the beginning, nature has an astounding diversity of life and brains. Those brains have been sculpted by evolution over millions of years, and evolution doesn’t care about intelligence as much as we do. Evolution is a process without goals instead it takes more of a “good enough” approach. An organism has to function within its environment. For our elephant, an elephant brain is absolutely perfect for doing elephant things, it’s the pinnacle of elephantness.
Humans had different survival tactics and evolutionary challenges. We didn’t have claws and weren’t very big and strong, instead we were smart and social. In evolutionary terms we bet everything on our brain, which is reflected by our cerebral cortex. Unlike other measurements, our cerebral cortex usually comes out on top compared to other animals. Even when compared to other primates, our cortex is astounding (more so in organization than size). It does require a lot of fuel, making it very reasonable to assume we beat other primates in the intelligence game because we started cooking. But that’s a story for another day.
Intelligence is an elusive concept we don’t really know for sure what makes one species smarter than another. It’ll be a while before we have definitive answers, but we do know it has to do with a lot of factors. Brain size, number of neurons, number of connections, different structures, densities, how they are connected, they all play a role. No single measure can explain why some animals are smarter than others, let alone why some humans are smarter than others.
An elephant is not as intelligent as a human, because an elephant brain is formed and wired to do elephant things. Just like a supercomputer isn’t made to play Minecraft, but rather focuses on simulating supernovae. Human brains do human things instead of elephant things in fact we make terrible elephants.
It’s not the size of the brain that matters it’s how you use it.
This question originally appeared on Quora - the place to gain and share knowledge, empowering people to learn from others and better understand the world. You can follow Quora on Twitter, Facebook, and Google+. More questions:
Neurons are the cells that transmit information in an animal's nervous system so that it can sense stimuli from its environment and behave accordingly. Not all animals have neurons Trichoplax and sponges lack nerve cells altogether.
Neurons may be packed to form structures such as the brain of vertebrates or the neural ganglions of insects.
The number of neurons and their relative abundance in different parts of the brain is a determinant of neural function and, consequently, of behavior.
All numbers for neurons (except Caenorhabditis and Ciona), and all numbers for synapses (except Ciona) are estimations.
The cerebral cortex is a structure of particular interest at the intersection between comparative neuroanatomy and comparative cognitive psychology. Historically, it had been assumed that since only mammals have a cerebral cortex, only they benefit from the information processing functions associated with it, notably awareness and thought.  It is now known that non-avian reptiles also have a cerebral cortex and that birds have a functional equivalent called the dorsal ventricular ridge (DVR), which in fact appears to be a modification subsequent to the reptilian cortex. A modern understanding of comparative neuroanatomy now suggests that for all vertebrates, the pallium roughly corresponds to this general sensory-associative structure.  It is also a widely accepted view that arthropods and closely related worms have an equivalent structure, the corpora pedunculata, more commonly known as mushroom bodies. In fact this structure in invertebrates and the pallium in vertebrates may have a common evolutionary origin from a common ancestor. 
Given the apparent function of the sensory-associative structure, it has been suggested that the total number of neurons in the pallium or its equivalents may be the best predictor of intelligence when comparing species, being more representative than total brain mass or volume, brain-to-body mass ratio, or encephalization quotient (EQ).  It may thus be reasonably assumed that the total number of neurons in an animal's corresponding sensory-associative structure strongly relates to its degree of awareness, breadth and variety of subjective experiences, and intelligence. 
The methods used to arrive at the numbers in this list include neuron count by isotropic fractionator, optical fractionator or estimation based on correlations observed between number of cortical neurons and brain mass within closely related taxa. Isotropic fractionation is often considered more straightforward and reliable than optical fractionation which may yield both overestimates and underestimates.  Estimation based on brain mass and taxon is to be considered the least reliable method.
Chasing down an immune protein in the brain could shed light on autism
One lab at Princeton University is finding that a protein famous for its role in the immune system is also active in the brain and might be a key to understanding some cases of autism.
Fifteen years ago, the proteins that Princeton neuroscientist Lisa Boulanger has staked her career on weren’t even thought to exist in the brain. Known as major histocompatibility complex class I, or MHCI proteins, they are essential for an adaptive immune response. The thought at the time was that the brain was an area of the body where the immune system wasn’t active. It simply wouldn’t need MHCs.
An immunological surpriseAs a postdoc at Harvard, Boulanger was studying how depth perception forms in the brain, and did an unbiased screen for the genes responsible. Unexpectedly, MHC genes popped up.
“We assumed it was a mistake,” she said. “Because if you open any immunology textbook, the MHC chapter starts by saying it’s found in most nucleated cells in the body except neurons.”
But it wasn’t a mistake. In the years that followed, it became clear that MHCs weren’t just doing things in the brain with regard to vision, either. In the hippocampus, the brain’s learning and memory center, MHCs alter the strength of communication among neurons. And MHCs help limit the number of synapses.
“If you have 10 synapses where you should have two, you’ll have a big problem, potentially,” Boulanger says. “Even though bigger brain, more synapses sounds like a great idea, it’s actually not.”
Boulanger wanted to figure out how MHCs were performing this critical job, and knew that yet another unusual suspect also controlled synapse density: the insulin receptor. In the rest of the body, those receptors help regulate the amount of sugar in the bloodstream. But in neurons, signaling through them increases the number of synapses.
Boulanger remembered decades-old studies that suggested that MHCs might affect insulin receptor signaling in liver cells and fat cells. It seemed like a long shot, but she wondered if MHCs were insulin receptors might connect to what MHC was doing in the brain.
A graduate student, Tracy Dixon-Salazar, first looked to see whether insulin signaling was normal in mice without MHC. Consistent with a connection, signaling in the mice was abnormally high.
A visual testTo find out for sure, postdoctoral fellow Carolyn Tyler used a drug to block insulin signaling in brain samples from either normal mice, or those without MHC. Then it was time to count synapses.
The most direct way, Boulanger says, is to physically count them. Princeton undergraduate Joseph Park spent dozens of hours snapping pictures of brain slices on an electron microscope. Zooming in 4,000 times closer than the naked eye can see, synapses come into focus and become countable.
“This is something that you see in textbooks when you’re doing your training,” says Tyler. “To see it in your own tissue on the scope, up close, it’s really amazing.”
Even most neuroscientists, she says, don’t ever get a chance to personally see a synapse. To an untrained eye, the black and white images are difficult to decipher.
“If you’re not used to it, you would look at this picture and say this is a really bad satellite image of a very crowded city,” says Boulanger.
After mastering the skill of identification, Park saw that mice without MHC had about 20 percent more synapses than regular mice do. But in those same mice, the brain samples that had been treated with the drug were normal.
“When we fixed their insulin signaling using a drug, we fixed their synapse density,” says Boulanger. “That tells us this is actually the way that MHC is changing the number of synapses in the developing brain.”
The team published their results in the Journal of Neuroscience.
Manifold connection to diseaseThe findings might explain why inflammation — which increases MHC levels — might lead to insulin resistance and type 2 diabetes elsewhere in the body.
More troubling is the fact that MHC, even if in the brain, still can perform its immune duties, which include siting on the surface of cells and offering samples of what’s inside to T cells searching for infection.
“You have one molecular machine that’s moonlighting in these two places,” says Boulanger. “You could have some wanted or unwanted interactions between those two functions of this one group of proteins.”
Boulanger’s results are also consistent with an emerging understanding of some types of autism as a failure of the brain to trim its many connections, says Manny DiCicco-Bloom, a neuroscientist and child neurologist at Rutgers Robert Wood Johnson Medical School.
DiCicco-Bloom says the same drug that Boulanger found so effective in fixing the brain connections in the mice without MHC is also used to treat a disorder called tuberous sclerosis. Caused by a mutation in one of two genes, it’s often accompanied by autism. The drug, rapamycin, is used in short bursts to stave off tuberous growths in the heart, but it might also be doing more.
“We really probably can’t sanction giving children with autism rapamycin,” says DiCicco-Bloom. “But we can consider, and we have done a clinical trial with children who have tuberous sclerosis, to see whether it improves their social function.”
Insight into our pastThe clinical applications are intriguing, but Boulanger cautions that for now they are only speculative. On the other end, she’s also thinking about what MHC’s presence in the brain might mean in terms of evolution.
“Very primitive organisms have neurons and synapses, and the adaptive immune system is a relatively new thing,” says Boulanger. “So what if [MHC] came from the brain and the immune system borrowed it?”
For Boulanger, that prospect offers an exciting possibility: that the secrets she’s uncovered about immune proteins in the brain would return the favor, and help immunologists find the origins of our immune system.
Figure 6 Variation in the tilt and roll of the TCR on top of the MHC. The left and right views are related by a 90° rotation about a horizontal axis. The MHC peptide backbones and the MHC helices are shown as gray tubes. The orientation axes are colored individually for each TCR. For 15 individual TCRs, the pseudo-twofold axes that relate the Vα and Vβ domains of the TCRs to each other are shown, giving a good estimate of the inclination (roll, tilt) of the TCR on top of the MHC. The TCR twofold axes tend to cluster around P4-P6 at the center of the interface. Labels are placed at the top of each axis. The figure also indicates any shifts of the TCR along the peptide where the Ob.1A12 and LC13 TCRs mark the extremes, centered around P1 and P6, respectively. 3A6 and SB27 also are outliers at present where they are centered on one half of the peptide.
Nerve Cell: Dendrites receive messages from other neurons. The message then moves through the axon to the other end of the neuron, then to the tips of the axon and then into the space between neurons. From there the message can move to the next neuron.
Neurons pass messages to each other using a special type of electrical signal. Some of these signals bring information to the brain from outside of your body, such as the things you see, hear, and smell. Other signals are instructions for your organs, glands and muscles.
Neurons receive these signals from neighbor neurons through their dendrites. From there, the signal travels to the main cell body, known as the soma. Next, the signal leaves the soma and travels down the axon to the synapse.
Myelin sheaths cover the axon and work like insulation to help keep the electrical signal inside the cell, which makes it move more quickly. As a final step, the signal leaves through the synapse to be passed along to the next nerve cell.
Let's look a bit closer at how this all works.
The human brain is the most ridiculously complex computer that’s ever existed, and mapping this dense tangle of neurons, synapses and other cells is nigh on impossible. But engineers at Google and Harvard have given it the best shot yet, producing a browsable, searchable 3D map of a small section of human cerebral cortex.
With about 86 billion neurons connecting via 100 trillion synapses, it’s a Herculean task to figure out exactly what each of them does and how those connections form the basis of thought, emotion, memory, behavior and consciousness. Daunting as it may be, though, teams of scientists around the world are rolling up their sleeves and trying to build a wiring diagram for the human brain – a so-called “connectome.”
Last year, researchers at Google and the Howard Hughes Medical Institute paved the way with a fruit fly brain connectome that encompassed about half of the insect’s full brain. Now, Google and the Lichtman Lab at Harvard have released a similar model of a tiny section of human brain.
The researchers started with a sample taken from the temporal lobe of a human cerebral cortex, measuring just 1 mm 3 . This was stained for visual clarity, coated in resin to preserve it, and then cut into about 5,300 slices each about 30 nanometers (nm) thick. These were then imaged using a scanning electron microscope, with a resolution down to 4 nm. That created 225 million two-dimensional images, which were then stitched back together into one 3D volume.
Machine learning algorithms scanned the sample to identify the different cells and structures within. After a few passes by different automated systems, human eyes “proofread” some of the cells to ensure the algorithms were correctly identifying them.
The end result, which Google calls the H01 dataset, is one of the most comprehensive maps of the human brain ever compiled. It contains 50,000 cells and 130 million synapses, as well as smaller segments of the cells such axons, dendrites, myelin and cilia. But perhaps the most stunning statistic is that the whole thing takes up 1.4 petabytes of data – that’s more than a million gigabytes.
Left: a small section of the dataset. Right: A subgraph of neurons, highlighting excitatory neurons in green and inhibitory neurons in red.
And that’s just a tiny fragment of the whole thing – Google says the sample is just one millionth of the volume of the full human brain. Clearly it’s going to take a huge amount of work to scale that up, as will finding a way to store the immense data load and develop a way to organize and access it in a useful way.
While the team begins tackling those problems, the H01 dataset is now available online for researchers and curious onlookers to explore. A companion pre-print paper describing the work is also available on bioRxiv.
A zooming tour through the different layers can be seen in the video below.