Posts tagged dendrites

Posts tagged dendrites
Activity in dendrites is critical in memory formation
Why do we remember some things and not others? In a unique imaging study, two Northwestern University researchers have discovered how neurons in the brain might allow some experiences to be remembered while others are forgotten. It turns out, if you want to remember something about your environment, you better involve your dendrites.
Using a high-resolution, one-of-a-kind microscope, Daniel A. Dombeck and Mark E. J. Sheffield peered into the brain of a living animal and saw exactly what was happening in individual neurons called place cells as the animal navigated a virtual reality maze.
The scientists found that, contrary to current thought, the activity of a neuron’s cell body and its dendrites can be different. They observed that when cell bodies were activated but the dendrites were not activated during an animal’s experience, a lasting memory of that experience was not formed by the neurons. This suggests that the cell body seems to represent ongoing experience, while dendrites, the treelike branches of a neuron, help to store that experience as a memory.
"There are a lot of theories on memory but very little data as to how individual neurons actually store information in a behaving animal," said Dombeck, assistant professor of neurobiology in the Weinberg College of Arts and Sciences and the study’s senior author. "Now we have uncovered signals in dendrites that we think are very important for learning and memory. Our findings could explain why some experiences are remembered and others are forgotten."
In the brain’s hippocampus, there are hundreds of thousands of place cells — neurons essential to the brain’s GPS system. Dombeck and Sheffield are the first to image the activity of individual dendrites in place cells.
Their findings contribute to our understanding of how the brain represents the world around it and also point to dendrites as a new potential target for therapeutics to combat memory deficits and debilitating diseases, such as Alzheimer’s disease (AD). Disruption to the brain’s GPS system is one of the first symptoms of AD, with many patients unable to find their way home. Understanding how place cells and their dendrites store these types of memories could help us find new ways to treat the disease.
The Northwestern study will be published Oct. 26 by the journal Nature.
Neuroscientist John O’Keefe discovered place cells in 1971 (and received this year’s Nobel Prize in physiology and medicine), but it is only in the last few years that scientists, such as Dombeck and Sheffield, have been able to image these neurons that represent a map of where we are in our environment.
In their study, Dombeck and Sheffield found dendrite signals that could explain how an animal can experience something without storing the experience as a memory.
They saw that dendrites are not always activated when the cell body is activated in a neuron. Signals produced in the dendrites (used to store information) and signals within the neuron cell body (used to compute and transmit information) can be either highly synchronized or desynchronized depending on how well the neurons remember different features of the maze.
Scientists have long believed that the neuronal tasks of computing and storing information are connected — when neurons compute information, they are also storing it, and vice versa. The Northwestern study provides evidence against this classic view of neuronal function.
"We experience events all the time, which must be represented in the brain by the activity of neurons, but not all these events can be recalled later," said Mark E. J. Sheffield, a postdoctoral fellow in Dombeck’s lab and first author of the study.
"A daily commute to work, for example, requires the activity of millions of neurons, but you would be hard pressed to remember what was happening halfway through your commute last Tuesday," Sheffield said. "How is it then that the neurons could be activated during the commute without storing that information in the brain? Now we may have an explanation for how this occurs."
Dombeck and Sheffield built their own laser scanning microscope that can image neurons on multiple planes. They then studied individual animals navigating (on a trackball) a virtual reality maze constructed using the video game Quake II.
Each lit-up structure seen in the images they took indicate a neuron firing action potentials. The activity of these neurons represents an animal’s experience of where it is in the environment, the researchers said. Whether the neurons store this experience or not appears to depend on the activity of the neurons’ dendrites.

(Image caption: A neuron in which the axon originates at a dendrite. Signals arriving at this dendrites become more efficiently forwarded than signals input elsewhere. Credit: Alexei V. Egorov, 2014)
Certain nerve cells take a shortcut for the transmission of information: signals are not conducted via the cell`s center, but around it like on a bypass road. The previously unknown nerve cell shape is now presented in the journal “Neuron" by a research team from Heidelberg, Mannheim and Bonn.
Nerve cells communicate by using electrical signals. Via widely ramified cell structures—the dendrites—, they receive signals from other neurons and then transmit them over a thin cell extension—the axon—to other nerve cells. Axon and dendrites are usually interconnected by the neuron’s cell body. A team of scientists at the Bernstein Center Heidelberg-Mannheim, Heidelberg University, and the University of Bonn has now discovered neurons in which the axon arises directly from one of the dendrites. Similar to taking a bypass road, the signal transmission is thus facilitated within the cell.
“Input signals at this dendrite do not need not be propagated across the cell body,” explains Christian Thome of the Bernstein Center Heidelberg-Mannheim and Heidelberg University, one of the two first authors of the study. For their analyses, the scientists specifically colored the places of origin of axons of so-called pyramidal cells in the hippocampus. This brain region is involved in memory processes. The surprising result: “We found that in more than half of the cells, the axon does not emerge from the cell body, but arises from a lower dendrite,” Thome says.
The researchers then studied the effect of signals received at this special dendrite. For this purpose, they injected a certain form of the neural transmitter substance glutamate into the brain tissue of mice that can be activated by light pulses. A high-resolution microscope allowed the neuroscientists to direct the light beam directly to a specific dendrite. By the subsequent activation of the messenger substance, they simulated an exciting input signal.
“Our measurements indicate that dendrites that are directly connected to the axon, actively propagate even small input stimuli and activate the neuron,” says second first author Tony Kelly, a member of the Sonderforschungsbereich (SFB) 1089 at the University of Bonn. A computer simulation of the scientists predicts that this effect is particularly pronounced when the information flow from other dendrites to the axon is suppressed by inhibitory input signals at the cell body.
“That way, information transmitted by this special dendrite influences the behavior of the nerve cell more than input from any other dendrite,” Kelly says. In a future step, the researchers attempt to figure out which biological function is actually strengthened through the specific dendrite—and what therefore might be the reason for the unusual shape of these neurons.
How neurons are created and integrate with each other is one of biology’s greatest riddles. Researcher Dietmar Schmucker from VIB-KU Leuven unravels a part of the mystery in Science magazine. He describes a mechanism that explains novel aspects of how the wiring of highly branched neurons in the brain works. These new insights into how complex neural networks are formed are very important for understanding and treating neurological diseases.

Neurons, or nerve cells
It is estimated that a person has 100 billion neurons, or nerve cells. These neurons have thin, elongated, highly branched offshoots called dendrites and axons. They are the body’s information and signal processors. The dendrites receive electrical impulses from the other neurons and conduct these to the cell body. The cell body then decides whether stimuli will or will not be transferred to other cells via the axon.
The brain’s wiring is very complex. Although the molecular mechanisms that explain the linear connection between neurons have already been described numerous times, little is as yet known about how the branched wiring works in the brain.
The connections between nerve cells
Prior research by Dietmar Schmucker and his team lead to the identification of the Dscam1 protein in the fruit fly. The neuron can create many different protein variations, or isoforms, from this same protein. The specific set of isoforms that occurs on a neuron’s cell surface determines the neuron’s unique molecular identity and plays an important role in the establishment of accurate connections. In other words, it describes why certain neurons either come into contact with each other or reject each other.
Recent work by Haihuai He and Yoshiaki Kise from Dietmar’s team indicates that different sets of Dscam1 isoforms occur inside one axon, between the newly formed offshoots amongst each other. If this was not the case, then only linear connections could come about between neurons. These results indicate for the first time the significance of why different sets of the same protein variations can occur in one neuron and it could explain mechanistically how this contributes to the complex wiring in our brain.
Clinical impact
Although this research was done with fruit flies, it also provides new insights that help explain the wiring and complex interactions of the human brain and shine a new light on neurological development disorders such as autism. Thorough knowledge of nerve cell creation and their neural interactions is considered essential knowledge for the future possibility of using stem cell therapy as standard treatment for certain nervous system disorders.
Questions
Given that this research can raise many questions, we would like to refer your questions in your report or article to the email address that the VIB has made available for this purpose. All questions regarding this and other medical research can be directed to: patients@vib.be.
Relevant scientific publication
The above-mentioned research was published in the prominent magazine Science.
(Source: vib.be)
Sleep After Learning Strengthens Connections Between Brain Cells and Enhances Memory
In study published today in Science, researchers at NYU Langone Medical Center show for the first time that sleep after learning encourages the growth of dendritic spines, the tiny protrusions from brain cells that connect to other brain cells and facilitate the passage of information across synapses, the junctions at which brain cells meet. Moreover, the activity of brain cells during deep sleep, or slow-wave sleep, after learning is critical for such growth.
The findings, in mice, provide important physical evidence in support of the hypothesis that sleep helps consolidate and strengthen new memories, and show for the first time how learning and sleep cause physical changes in the motor cortex, a brain region responsible for voluntary movements.
“We’ve known for a long time that sleep plays an important role in learning and memory. If you don’t sleep well you won’t learn well,” says senior investigator Wen-Biao Gan, PhD, professor of neuroscience and physiology and a member of the Skirball Institute of Biomolecular Medicine at NYU Langone Medical Center. “But what’s the underlying physical mechanism responsible for this phenomenon? Here we’ve shown how sleep helps neurons form very specific connections on dendritic branches that may facilitate long-term memory. We also show how different types of learning form synapses on different branches of the same neurons, suggesting that learning causes very specific structural changes in the brain.”
On the cellular level, sleep is anything but restful: Brain cells that spark as we digest new information during waking hours replay during deep sleep, also known as slow-wave sleep, when brain waves slow down and rapid-eye movement, as well as dreaming, stops. Scientists have long believed that this nocturnal replay helps us form and recall new memories, yet the structural changes underpinning this process have remained poorly understood.
To shed light on this process, Dr. Gan and colleagues employed mice genetically engineered to express a fluorescent protein in neurons. Using a special laser-scanning microscope that illuminates the glowing fluorescent proteins in the motor cortex, the scientists were then able to track and image the growth of dendritic spines along individual branches of dendrites before and after mice learned to balance on a spin rod. Over time mice learned how to balance on the rod as it gradually spun faster. “It’s like learning to ride a bike,” says Dr. Gan. “Once you learn it, you never forget.”
After documenting that mice, in fact, sprout new spines along dendritic branches, within six hours after training on the spinning rod, the researchers set out to understand how sleep would impact this physical growth. They trained two sets of mice: one trained on the spinning rod for an hour and then slept for 7 hours; the second trained for the same period of time on the rod but stayed awake for 7 hours. The scientists found that the sleep-deprived mice experienced significantly less dendritic spine growth than the well-rested mice. Furthermore, they found that the type of task learned determined which dendritic branches spines would grow.
Running forward on the spinning rod, for instance, produced spine growth on different dendritic branches than running backward on the rod, suggesting that learning specific tasks causes specific structural changes in the brain.
“Now we know that when we learn something new, a neuron will grow new connections on a specific branch,” says Dr. Gan. “Imagine a tree that grows leaves (spines) on one branch but not another branch. When we learn something new, it’s like we’re sprouting leaves on a specific branch.”
Finally, the scientists showed that brain cells in the motor cortex that activate when mice learn a task reactivate during slow-wave deep sleep. Disrupting this process, they found, prevents dendritic spine growth. Their findings offer an important insight into the functional role of neuronal replay—the process by which the sleeping brain rehearses tasks learned during the day—observed in the motor cortex.
“Our data suggest that neuronal reactivation during sleep is quite important for growing specific connections within the motor cortex,” Dr. Gan adds.
(Image: Shutterstock)
The control of dendritic branching by mitochondria
A fundamental difference between neurons in real brains and those in artificial neural networks is the way the neurons in each are connected. In artificial nets, the synapses between neurons often have adjustable strengths, but the structure and scale of the input dendritic field generally counts for little. For real neurons, where a “connection” between cells is not just a synapse but rather a whole net unto itself, structure and scale are everything. The architect of this dendritic structure is neither a DNA code nor a spontaneous developmental physics that condenses order from a protein-lipid chaos. This structure is in fact the byproduct of competitive, yet cooperative mitochondria that administer that code to themselves and to their host to control its interaction with other similarly controlled hosts.
Reseachers from Osaku University have found that if mitochondria are depleted from developing dendrites in pyramidal cells, there is increased branching in the proximal region of the dendrites. In their paper last week in the Journal of Neuroscience, they also show that these dendrites grow longer. Since mitochondria distribute not just energy but also metabolites, proteins, and mRNAs throughout the cell, these results may be somewhat surprising. However depending on what manipulations have been done to alter the mitochondria, many things might be expected to happen to dendrites and the cell in general.

Existence of new neuron repair pathway discovered
Most of your neurons can’t be replaced.
Other parts of your body – such as skin and bone – can be replaced by the body growing new cells, but when you injure your neurons, you can’t just grow new ones; instead, the existing cells have to repair themselves.
In the case of axon injury, the neuron is able to repair or sometimes even fully regenerate its axon. But neurons have two sides – the axon (which sends signals to other cells) and the dendrite (which receives signals from other cells).
Melissa Rolls, an associate professor of biochemistry and molecular biology at Penn State and director of the Huck Institutes’ Center for Cellular Dynamics, has done extensive comparisons of axons and dendrites – culminating recently in a paper published in Cell Reports.
“We know that the axon side can repair itself,” says Rolls, “and we know a bunch of the molecular players. But we really didn’t know whether neurons have the same capacity to regenerate their dendrites, and so that’s what we set out to find in this study.”
“Our lab uses a Drosophila model system, where the dendrites are very accessible to manipulation,” she says, “so we decided that we would start by removing all the dendrites from the neurons to see if they could regenerate. We didn’t start with anything subtle, like taking off just a few dendrites. We said ‘Let’s just push the system to its maximum and see if this is even possible.’ And we were surprised because we found that not only is it possible, it’s actually much faster than axon regeneration: at least in the cells that we’re using, axon regeneration takes a day or two to initiate, while dendrite regeneration typically initiates within four to six hours and it works really well. All the cells where we removed the dendrites grew new dendrites – none of them died; so it’s clear that these cells have a way to both detect dendrite injury and initiate regrowth of the injured part.”
New technique classifies retinal neurons into 15 categories, including some previously unknown types.

As we scan a scene, many types of neurons in our retinas interact to analyze different aspects of what we see and form a cohesive image. Each type is specialized to respond to a particular variety of visual input — for example, light or darkness, the edges of an object, or movement in a certain direction.
Neuroscientists believe there are 20 to 30 types of these specialized neurons, known as retinal ganglion cells, but they have yet to come up with a definitive classification system.
A new study from MIT neuroscientists has made some headway on this daunting task. Using a computer algorithm that traces the shapes of neurons and groups them based on structural similarity, the researchers sorted more than 350 mouse retinal neurons into 15 types, including six that were previously unidentified.
This technique, described in the March 24 online edition of Nature Communications, could also be deployed to help identify the huge array of neurons found in the brain’s cortex, says Uygar Sumbul, an MIT postdoc and one of the lead authors of the paper. “This delineates a program that we should be doing for the rest of the retina, and elsewhere in the brain, to robustly and precisely know the cell types,” he says.
The paper’s other lead author is former MIT postdoc Sen Song. Sebastian Seung, a former MIT professor of brain and cognitive sciences and physics who is now at Princeton University, is the paper’s senior author.
(Source: web.mit.edu)
Scientists identify clue to regrowing nerve cells
Researchers at Washington University School of Medicine in St. Louis have identified a chain reaction that triggers the regrowth of some damaged nerve cell branches, a discovery that one day may help improve treatments for nerve injuries that can cause loss of sensation or paralysis.
The scientists also showed that nerve cells in the brain and spinal cord are missing a link in this chain reaction. The link, a protein called HDAC5, may help explain why these cells are unlikely to regrow lost branches on their own. The new research suggests that activating HDAC5 in the central nervous system may turn on regeneration of nerve cell branches in this region, where injuries often cause lasting paralysis.
“We knew several genes that contribute to the regrowth of these nerve cell branches, which are called axons, but until now we didn’t know what activated the expression of these genes and, hence, the repair process,” said senior author Valeria Cavalli, PhD, assistant professor of neurobiology. “This puts us a step closer to one day being able to develop treatments that enhance axon regrowth.”
The research appears Nov. 7 in the journal Cell.
Axons are the branches of nerve cells that send messages. They typically are much longer and more vulnerable to injury than dendrites, the branches that receive messages.
In the peripheral nervous system — the network of nerve cells outside the brain and spinal column — cells sometimes naturally regenerate damaged axons. But in the central nervous system, comprised of the brain and spinal cord, injured nerve cells typically do not replace lost axons.
Working with peripheral nervous system cells grown in the laboratory, Yongcheol Cho, PhD, a postdoctoral research associate in Cavalli’s laboratory, severed the cells’ axons. He and his colleagues learned that this causes a surge of calcium to travel backward along the axon to the body of the cell. The surge is the first step in a series of reactions that activate axon repair mechanisms.
In peripheral nerve cells, one of the most important steps in this chain reaction is the release of a protein, HDAC5, from the cell nucleus, the central compartment where DNA is kept. The researchers learned that after leaving the nucleus, HDAC5 turns on a number of genes involved in the regrowth process. HDAC5 also travels to the site of the injury to assist in the creation of microtubules, rigid tubes that act as support structures for the cell and help establish the structure of the replacement axon.
When the researchers genetically modified the HDAC5 gene to keep its protein trapped in the nuclei of peripheral nerve cells, axons did not regenerate in cell cultures. The scientists also showed they could encourage axon regrowth in cell cultures and in animals by dosing the cells with drugs that made it easier for HDAC5 to leave the nucleus.
When the scientists looked for the same chain reaction in central nervous system cells, they found that HDAC5 never left the nuclei of the cells and did not travel to the site of the injury. They believe that failure to get this essential player out of the nucleus may be one of the most important reasons why central nervous system cells do not regenerate axons.
“This gives us the hope that if we can find ways to manipulate this system in brain and spinal cord neurons, we can help the cells of the central nervous system regrow lost branches,” Cavalli said. “We’re working on that now.”
It doesn’t take a Watson to realize that even the world’s best supercomputers are staggeringly inefficient and energy-intensive machines.
Our brains have upwards of 86 billion neurons, connected by synapses that not only complete myriad logic circuits; they continuously adapt to stimuli, strengthening some connections while weakening others. We call that process learning, and it enables the kind of rapid, highly efficient computational processes that put Siri and Blue Gene to shame.
Materials scientists at the Harvard School of Engineering and Applied Sciences (SEAS) have now created a new type of transistor that mimics the behavior of a synapse. The novel device simultaneously modulates the flow of information in a circuit and physically adapts to changing signals.
Exploiting unusual properties in modern materials, the synaptic transistor could mark the beginning of a new kind of artificial intelligence: one embedded not in smart algorithms but in the very architecture of a computer. The findings appear in Nature Communications.
“There’s extraordinary interest in building energy-efficient electronics these days,” says principal investigator Shriram Ramanathan, associate professor of materials science at Harvard SEAS. “Historically, people have been focused on speed, but with speed comes the penalty of power dissipation. With electronics becoming more and more powerful and ubiquitous, you could have a huge impact by cutting down the amount of energy they consume.”
The human mind, for all its phenomenal computing power, runs on roughly 20 Watts of energy (less than a household light bulb), so it offers a natural model for engineers.
“The transistor we’ve demonstrated is really an analog to the synapse in our brains,” says co-lead author Jian Shi, a postdoctoral fellow at SEAS. “Each time a neuron initiates an action and another neuron reacts, the synapse between them increases the strength of its connection. And the faster the neurons spike each time, the stronger the synaptic connection. Essentially, it memorizes the action between the neurons.”

In principle, a system integrating millions of tiny synaptic transistors and neuron terminals could take parallel computing into a new era of ultra-efficient high performance.
While calcium ions and receptors effect a change in a biological synapse, the artificial version achieves the same plasticity with oxygen ions. When a voltage is applied, these ions slip in and out of the crystal lattice of a very thin (80-nanometer) film of samarium nickelate, which acts as the synapse channel between two platinum “axon” and “dendrite” terminals. The varying concentration of ions in the nickelate raises or lowers its conductance—that is, its ability to carry information on an electrical current—and, just as in a natural synapse, the strength of the connection depends on the time delay in the electrical signal.
Structurally, the device consists of the nickelate semiconductor sandwiched between two platinum electrodes and adjacent to a small pocket of ionic liquid. An external circuit multiplexer converts the time delay into a magnitude of voltage which it applies to the ionic liquid, creating an electric field that either drives ions into the nickelate or removes them. The entire device, just a few hundred microns long, is embedded in a silicon chip.
The synaptic transistor offers several immediate advantages over traditional silicon transistors. For a start, it is not restricted to the binary system of ones and zeros.
“This system changes its conductance in an analog way, continuously, as the composition of the material changes,” explains Shi. “It would be rather challenging to use CMOS, the traditional circuit technology, to imitate a synapse, because real biological synapses have a practically unlimited number of possible states—not just ‘on’ or ‘off.’”
The synaptic transistor offers another advantage: non-volatile memory, which means even when power is interrupted, the device remembers its state.
Additionally, the new transistor is inherently energy efficient. The nickelate belongs to an unusual class of materials, called correlated electron systems, that can undergo an insulator-metal transition. At a certain temperature—or, in this case, when exposed to an external field—the conductance of the material suddenly changes.
“We exploit the extreme sensitivity of this material,” says Ramanathan. “A very small excitation allows you to get a large signal, so the input energy required to drive this switching is potentially very small. That could translate into a large boost for energy efficiency.”
The nickelate system is also well positioned for seamless integration into existing silicon-based systems.
“In this paper, we demonstrate high-temperature operation, but the beauty of this type of a device is that the ‘learning’ behavior is more or less temperature insensitive, and that’s a big advantage,” says Ramanathan. “We can operate this anywhere from about room temperature up to at least 160 degrees Celsius.”
For now, the limitations relate to the challenges of synthesizing a relatively unexplored material system, and to the size of the device, which affects its speed.
“In our proof-of-concept device, the time constant is really set by our experimental geometry,” says Ramanathan. “In other words, to really make a super-fast device, all you’d have to do is confine the liquid and position the gate electrode closer to it.”
In fact, Ramanathan and his research team are already planning, with microfluidics experts at SEAS, to investigate the possibilities and limits for this “ultimate fluidic transistor.”
He also has a seed grant from the National Academy of Sciences to explore the integration of synaptic transistors into bioinspired circuits, with L. Mahadevan, Lola England de Valpine Professor of Applied Mathematics, professor of organismic and evolutionary biology, and professor of physics.
“In the SEAS setting it’s very exciting; we’re able to collaborate easily with people from very diverse interests,” Ramanathan says.
For the materials scientist, as much curiosity derives from exploring the capabilities of correlated oxides (like the nickelate used in this study) as from the possible applications.
“You have to build new instrumentation to be able to synthesize these new materials, but once you’re able to do that, you really have a completely new material system whose properties are virtually unexplored,” Ramanathan says. “It’s very exciting to have such materials to work with, where very little is known about them and you have an opportunity to build knowledge from scratch.”
“This kind of proof-of-concept demonstration carries that work into the ‘applied’ world,” he adds, “where you can really translate these exotic electronic properties into compelling, state-of-the-art devices.”
(Source: seas.harvard.edu)
Many animals have highly developed senses, such as vision in carnivores, touch in mice, and hearing in bats. New research from the RIKEN Brain Science Institute has uncovered a brain molecule that can explain the existence of such finely-tuned sensory capabilities, revealing how brain cells responsible for specific senses are positioned to receive incoming sensory information.

The study, led by Dr. Tomomi Shimogori and published in the journal Science, sought to uncover the molecule that enables high acuity sensing by examining brain regions that receive information from the senses. They found that areas responsible for touch in mice and vision in ferrets contain a protein called BTBD3 that optimizes neuronal shape to receive sensory input more efficiently.
Neurons have a highly specialized shape, sending signals through one long projection called an axon, while receiving signals from many branch-like projections called dendrites. The final shape and connections to other neurons are typically completed after birth. Some neurons have dendrites distributed equally all around the cell body, like a starfish, while in others they extend only from one side, like a squid, steering towards axons that are actively bringing in information from the peripheral nerves. It was previously unknown what enables neurons to have highly oriented dendrites.
“We were fascinated by the dendrite patterning changes that occurred during the early postnatal stage that is controlled by neuronal input,” says Dr. Shimogori. “We found a fundamental process that is important to remove unnecessary dendrites to prevent mis-wiring and to make efficient neuronal circuits.”
The researchers searched for genes that are active exclusively in the mouse somatosensory cortex, the brain region responsible for their sense of touch, and found that the gene coding for the protein BTBD3 was active in the neurons of the barrel cortex, which receives input from their whiskers, the highly sensitive tactile sensors in mice, and that these neurons had unidirectional dendrites.
Using gene manipulations in embryonic mouse brain the authors found that eliminating BTBD3 made dendrites uniformly distribute around neurons in the mouse barrel cortex. In contrast, artificially introducing BTBD3 in the visual cortex of mice where BTBD3 is not normally found, reoriented the normally symmetrically positioned dendrites to one side. The same mechanism shaped neurons in the visual cortex of ferrets, which unlike the mouse contains BTBD3.
“High acuity sensory function may have been enabled by the evolution of BTBD3 and related proteins in brain development,” adds Dr. Shimogori. “Finding BTBD3 selectively in the visual and auditory cortex of the common marmoset, a species that relies heavily on high acuity vocal and visual communication for survival, and in mouse, where it is expressed in high-acuity tactile and olfactory areas, but not in low acuity visual cortex, supports this idea.” The authors plan to examine their theory by testing sensory function in mice without BTBD3 gene expression.
(Source: riken.jp)