Posts tagged neurons
Articles and news from the latest research reports.
Experience leads to the growth of new brain cells
A new study examines how individuality develops
The DFG-Center for Regenerative Therapies Dresden - Cluster of Excellence at the TU Dresden (CRTD), the Dresden site of the German Center for Neurodegenerative Diseases (DZNE), and the Max Planck Institute for Human Development in Berlin played a pivotal role in the study.
The adult brain continues to grow with the challenges that it faces; its changes are linked to the development of personality and behavior. But what is the link between individual experience and brain structure? Why do identical twins not resemble each other perfectly even when they grew up together? To shed light on these questions, the scientists observed forty genetically identical mice that were kept in an enclosure offering a large variety of activity and exploration options.
"The animals were not only genetically identical, they were also living in the same environment," explains principal investigator Gerd Kempermann, Professor for Genomics of Regeneration, CRTD, and Site Speaker of the DZNE in Dresden. "However, this environment was so rich that each mouse gathered its own individual experiences in it. Over time, the animals therefore increasingly differed in their realm of experience and behavior."
New neurons for individualized brains
Each of the mice was equipped with a special micro-chip emitting electromagnetic signals. This allowed the scientists to construct the mice’s movement profiles and to quantify their exploratory behavior. The result: Despite a common environment and identical genes the mice showed highly individualized behavioral patterns. They reacted to their environment differently. In the course of the three-month experiment these differences increased in size.
"Though the animals shared the same life space, they increasingly differed in their activity levels. These differences were associated with differences in the generation of new neurons in the hippocampus, a region of the brain that supports learning and memory," says Kempermann. "Animals that explored the environment to a greater degree also grew more new neurons than animals that were more passive."
Adult neurogenesis, that is, the generation of new neurons in the hippocampus, allows the brain to react to new information flexibly. With this study, the authors show for the first time that personal experiences and ensuing behavior contribute to the „individualization of the brain.” The individualization they observed cannot be reduced to differences in environment or genetic makeup.
"Adult neurogenesis also occurs in the hippocampus of humans," says Kempermann. "Hence we assume that we have tracked down a neurobiological foundation for individuality that also applies to humans."
Impulses for discussion across disciplines
"The finding that behavior and experience contribute to differences between individuals has implications for debates in psychology, education science, biology, and medicine," states Prof. Ulman Lindenberger, Director of the Center for Lifespan Psychology at the Max Planck Institute for Human Development (MPIB) in Berlin. "Our findings show that development itself contributes to differences in adult behavior. This is what many have assumed, but now there is direct neurobiological evidence in support of this claim. Our results suggest that experience influences the aging of the human mind."
In the study, a control group of animals housed in a relatively unattractive enclosure was also examined; on average, neurogenesis in these animals was lower than in the experimental mice. „When viewed from educational and psychological perspectives, the results of our experiment suggest that an enriched environment fosters the development of individuality,” comments Lindenberger.
Interdisciplinary teamwork
The study is also an example of multidisciplinary cooperation — it was made possible because neuroscientists, ethologists, computer scientists, and developmental psychologists collaborated closely in designing the experimental set-up and applying new data analysis methods. Biologist Julia Freund from the CRTD Dresden and computer scientist Dr. Andreas Brandmaier from the MPIB in Berlin share first authorship on the article. In addition to the DZNE, CRTD, and the MPIB, the German Research Center for Artificial Intelligence in Saarbrücken and the Institute for Geoinformatics and the Department of Behavioural Biology at the University of Münster were also involved in this project.
Original publication
"Emergence of Individuality in Genetically Identical Mice", Julia Freund, Andreas M. Brandmaier, Lars Lewejohann, Imke Kirste, Mareike Kritzler, Antonio Krüger, Norbert Sachser, Ulman Lindenberger, Gerd Kempermann, Science
(Image: Dr Jonathan Clarke, Wellcome Images)
Neuroscientists put heads together at national brainstorming session
This week over 150 neuroscientists were invited to meet in Arlington, Virginia to discuss the finer points of President Obama’s recently announced BRAIN Initative. Rather than discuss funding particulars, each participant was given the chance to broadly declare what they thought needed to be done in neuroscience. At least 75 of the participants initially responded to a request for a short white paper outlining the major obstacles currently impeding neuroscience research. A live webcast of some of the key talks was available, although many of the smaller workshops were held in private. Fortunately, updates regarding the content discussed at these workshops was posted live to twitter under the handle @openconnectome. This precipitated lively discussion, primarily under the hashtags #nsfBRAINmtg or #braini, and provided a way for a larger audience to be involved.
The working title of this inaugural NSF meeting was Physical and Mathematical Principles of Brain Structure and Function. In actuality, there was little discussion of all that, and for good reason—no such principles have been shown to exist. Even more concerning, only a few principles have ever even been proposed. Simplistic scaling laws dealing with connectivity, particularly within sensory systems or the cortex, have been suggested in the past. Generally they seek to account for only one or two structural parameters at a time, like for example, axon diameter and branching order. Typically, the chosen parameters are only considered in the context of optimizing a single physical variable, like for example, electrotonic function. While these efforts are a start, they usually do not garner much attention from the larger neuroscience community.
The early days of neuroscience were marked with the assertion of many principles and laws. They served well to focus ideas, but over time, they lost much of their original perceived generality. For example, concepts like one transmitter type per neuron, and no new neurons in adult brains later proved to have significant exceptions. The early breakthrough days in neuroscience have now given way to a grant system that stifles imagination, and by its competitiveness, encourages fraud. Many of the speakers at the BRAIN Initiative meeting have called for new tools and theories, but in most cases, they have offered only little has been offered. Instead of expanding the range acceptable pursuits, their vision appears to have imploded inward with calls for increased rigor, statistical power, diversity of animal models, experimental falsifiability, and most of all, data, on an increasingly limited range of ideas.
A lot of talk was given to the resolution at which connectivity, and activity maps should be detailed. Similar points were made for the need to develop electrode arrays of higher density and durability to more accurately record function. The ample discussion of an ideal animal model was punctuated by the notable advances made this year in whole brain recordings from Zebrafish, and also from large scale connectivity mapping now possible in small mammals with the new CLARITY transparent brain techniques. The general lack of agreement and clear path forward as to which organisms among many are ideal here was noted by representatives from several funding bodies who spoke at the meeting. Highlighting points made earlier in a talk by George Whitesides, they stressed the need to come to forward with a concrete plan that is comprehensible not only to the funding organizations, but the larger public as well.
Many discussions focused on brain mechanisms, like for example, how many neurons might contribute to a particular function. One participate, David Kleinfeld, called for a study of how many neurons are involved in communication at different scales. He also stressed the importance of looking at basic systems involving feedback, such as the brain stem and spinal cord, and their dynamic interaction with muscle. Michael Stryker observed that the goal should not be recording from the most neurons, and storing the most data, but rather finding the right neurons.
While it was not explicitly stated, a lot of the talk begged the conclusion that the answers to the questions we have will not be answered with animal studies. Knowing what a neuron does is itself an ill-posed question. In worms and flies, where the inputs and outputs of single neurons can be mapped to static sensory and motor functions in the real world, we might know what that neuron does. However in larger, human brains, we can ask an even better question—what does the neuron feel like? In most cases that answer will likely be, nothing.
If however, in a given human brain, a single neuron critically poised within that brain’s structural hierarchy can be stimulated to observable effect, some measure of its function has been gained. That effect might be a simple itch or twitch. Less plausibly perhaps it could be seeing a picture of a face undergo a change, sensing fear, or even imagining your grandmother. If that turns out not to be possible for most single neurons, we already know that we can find some minimal group of neurons where stimulation has uniquely perceivable effects.
While understanding the brain on different scales is important, the most rewarding endeavors likely exist where functionality can be correlated across those scales. Behavior at the scale of the organism within a given environment is readily observable. At the next scale down, the behavior of neurons witnessed by its spikes and structural alterations, is only observable now in part. Below the scale of the neuron, the mitochondria and other organelles move with a purpose and relation to activity of the neuron that has only been imagined, but is experimentally addressable.
Several speakers also mentioned the idea of a neural code. Spikes are a convenient metric for assessing brain activity, and we should seek to correlate their occurrence with behaviors on various scales mentioned above. They are a universal and non-local currency, among others in the brain, that inflates rapidly with stimulation and arousal. Unfortunately, the most logical conclusion for us must be that there is no code for spikes. Anyone attempting to observe and record a code for one neuron would probably find that it has, in short order, become unrecognizable, particularly in the context of the next. There are however constraints on spikes, and on neurons, and while considerable mention of the word was made at the meeting none were detailed in depth.
To formulate constraints on a system, at a level we don’t understand, we might look at constraints on other systems that we have some knowledge about. Neurons are neither wholly like ants, nor tress, but share some aspects of both. Similarly brains are neither like ant colonies, or forests, but shares some features in common. The most obvious constraint that comes to mind, and applies to these systems at every level, is energy. A subtle refinement of that is the concept of entropy generation. One key idea is that entropy generation at different scales, while proceeding according to as yet determined laws, need not necessarily maximize entropy at each point in time, but rather along paths through time.
A voice heard throughout the conference was that of Bill Bialek who diffusely observed that attempts to apply the laws of statistical mechanics to aspects of brain functions are not very productive because the brain is not at an equilibrium state. That would have been a good sentence to begin the conference perhaps rather than end it. Hopefully, the next NSF meeting will be a little more transparent to the public than the first. A more thorough webcast, with uploading to a media channel would be desirable to many who like to participate, as would a path for two-way communication on the issues. Mention should also be made of the efforts of a few neuroscientists peripheral to the BRAIN Initiative that have been maintaining important blog discussions, and metablog publication lists to track the progress made over last few months. This morning, NIH announced a new website has just been set up to provide additional public feedback.
(Source: medicalxpress.com)
Environment moulds behaviour - and not just that of people in society, but also at the microscopic level. This is because, for their function, neurons are dependent on the cell environment, the so-termed extracellular matrix. Researchers at the Ruhr-Universität have found evidence that this complex network of molecules controls the formation and activity of the neuronal connections. The team led by Dr. Maren Geißler und Prof. Andreas Faissner from the Department of Cell Morphology and Molecular Neurobiology reports in the “Journal of Neuroscience” in collaboration with the team of Dr. Ainhara Aguado, Prof. Christian Wetzel and Prof. Hanns Hatt from the Department of Cell Physiology.
Neurons and astrocytes in culture
In cooperation with Prof. Uwe Rauch from Lund University in Sweden, Bochum’s biologists examined cells from the brains of two mouse species: a species with a normal extracellular matrix and a species which lacked four components of the extracellular matrix due to genetic manipulation, namely the molecules tenascin-C, tenascin-R, neurocan and brevican. They took the cells from the hippocampus, a brain structure that is crucial for the long-term memory. The team not only examined neurons but also astrocytes, which are in close contact with the neurons, support their function and secrete molecules for the extracellular matrix.
Formation, stability and activity of the neuronal connections depend on the matrix
The researchers cultivated the neurons and astrocytes together for four weeks with a specially developed culture strategy. Among other things, they observed how many connections, known as synapses, the neurons formed with each other and how stable these were over time. If either the astrocytes or the neurons in the culture dish derived from animals with a reduced extracellular matrix, these synapses proved to be less stable in the medium term, and their number was significantly reduced. Together with the Department of Cell Physiology at the RUB and the University of Regensburg, the team also showed that the neurons with a mutated matrix showed lower spontaneous activity than normal cells. The extracellular matrix thus regulates the formation, stability and activity of the neuronal connections. The researchers also examined a special structure of the extracellular matrix, the so-called perineuronal nets, which the Nobel laureate Camillo Golgi first described more than a century ago. They were significantly reduced in the environment of genetically modified cells.
![A tangle of talents untangles neurons
Brown’s growing programs in brain science and engineering come together in the lab of Diane Hoffman-Kim. In a recent paper, her group employed techniques ranging from semiconductor-style circuit patterning to rat cell culture to optimize the growth of nerve cells for applications such as reconstructive surgery.
Two wrongs don’t make a right, they say, but here’s how one tangle can straighten out another.
Diane Hoffman-Kim, associate professor of medicine in the Department of Molecular Pharmacology, Physiology, and Biotechnology, is an affiliate of both Brown’s Center for Biomedical Engineering and the Brown Institute for Brain Science. Every thread of expertise woven through those multidisciplinary titles mattered in the Hoffman-Kim lab’s most recent paper, led by graduate student Cristina Lopez-Fagundo.
In research published online last month in Acta Biomaterialia, Hoffman-Kim and Lopez-Fagundo employed their neurophysiological knowledge and technological ingenuity to unravel a tangle of branching, tendrilous nerve cells, or neurons.
The scientist-engineers helped explain how neurons grow in new tissues in response to physical guideposts, called Schwann cells. Their paper also provided medical device makers with an overt demonstration of how to craft the best artificial Schwann cell implants in silicone to make neurons grow as straight as possible in a desired direction.
“If you’ve got an injury in your arm or your leg then you’d like to have proper reconnection so you can get function,” Hoffman-Kim said. “If it’s a small injury, your body does that fairly well in natural ways that largely depend on the Schwann cells. If the injury gets even just a little bit large then the Schwann cells can’t do it alone.”
Silicone Schwanns
Hoffman-Kim and Lopez-Fagundo did not invent the idea of creating an implant to direct neural growth through repaired or reattached tissues. Their clinical goal is to make that technology the best it can be by systematically studying neural growth on Schwann-like substrates. As a matter of basic science, they wanted to learn how neural growth proceeds.
Lopez-Fagundo, whom Hoffman-Kim recruited for her lab in 2008 when she applied to Brown after graduating from the University of Puerto Rico, started the research with rigorous measurements of Schwann cells in cell cultures of rat neural tissue — the cell size, their elliptical shape, and the average distance between any two, as well as the length and width of the “processes” or wispy extensions that connect them.
“We were able to deconstruct the topography of Schwann cells,” said Lopez-Fagundo. “We were then able to manipulate it into different designs to better understand the influence this topography has.”
They came up with six archetypal designs. One of them mimicked the somewhat messy real-world layout of Schwann cells but the other five were arranged in neat horizontal rows. In one the elliptical Schwann cell bodies were few and far between. In another they were densely packed and in another their spacing was the exact average of Lopez-Fagundo’s measurements. Another design had no “processes” to connect the ellipses and another had only processes but no ellipses.
Using Brown’s microfabrication facility, Lopez-Fagundo patterned their designs on silicon wafers (like those used to make computer chips) and then transferred them to silicone squares about a centimeter on a side so that the ellipses and processes were in raised relief on the silicone. Then they put each pattern in a cell culture of rat neurons and watched them as the neurons grew across each pattern of artificial Schwann cells. As a control for their experiment, they also cultured cells on unpatterned silicone squares.
All of the patterns encouraged some directed neuron growth compared to the random growth of neurons on the unpatterned squares, but clearly some patterns did better than others.
After 17 hours, the two best patterns were the ones with only processes and the one with average ellipse spacing. The natural replica pattern and the one with only ellipses fared the worst.
But by day five, new winners emerged: the patterns where the ellipses were farther than average and nearer than average. Hoffman-Kim said she was surprised that the nerve cells didn’t remain content to follow the straightforward pattern of plain horizontal tracks formed by the process-only pattern. Meanwhile, to some extent, the neurons grew the proper way even without a continuous track at all, for instance in the ellipse-only pattern.
Lopez-Fagundo puzzled over the question of why the ellipses, also called “soma,” matter even as the neurons clearly also grow along the processes.
“I asked myself that question a lot and it wasn’t until I sat at the computer and looked at the [time lapse] videos over and over,” Lopez-Fagundo said. “They use the soma as anchor points. They jump from soma to soma and use the long axis of the soma to guide themselves.”
It’s as if the neurons navigated most effectively when they had both roads (processes) and rest stops (ellipses or soma) where they could get their bearings.
And thus the neurons made their way along the artificially optimized straight and narrow. To the researchers, who also included co-authors Jennifer Mitchel, Talisha Ramchal, and Yu-Ting Dingle, the experiments were a triumph of how the meticulous analytical control afforded by engineering can demystify a complex biological phenomenon.
“Sometimes when I give lectures I say, ‘Biomedical engineers are control freaks and we consider that a compliment,’” Hoffman-Kim said.](http://41.media.tumblr.com/36fc7efde99ed4daa6b938cb97a3b3ee/tumblr_mmfcr6lu8L1rog5d1o1_500.jpg)
A tangle of talents untangles neurons
Brown’s growing programs in brain science and engineering come together in the lab of Diane Hoffman-Kim. In a recent paper, her group employed techniques ranging from semiconductor-style circuit patterning to rat cell culture to optimize the growth of nerve cells for applications such as reconstructive surgery.
Two wrongs don’t make a right, they say, but here’s how one tangle can straighten out another.
Diane Hoffman-Kim, associate professor of medicine in the Department of Molecular Pharmacology, Physiology, and Biotechnology, is an affiliate of both Brown’s Center for Biomedical Engineering and the Brown Institute for Brain Science. Every thread of expertise woven through those multidisciplinary titles mattered in the Hoffman-Kim lab’s most recent paper, led by graduate student Cristina Lopez-Fagundo.
In research published online last month in Acta Biomaterialia, Hoffman-Kim and Lopez-Fagundo employed their neurophysiological knowledge and technological ingenuity to unravel a tangle of branching, tendrilous nerve cells, or neurons.
The scientist-engineers helped explain how neurons grow in new tissues in response to physical guideposts, called Schwann cells. Their paper also provided medical device makers with an overt demonstration of how to craft the best artificial Schwann cell implants in silicone to make neurons grow as straight as possible in a desired direction.
“If you’ve got an injury in your arm or your leg then you’d like to have proper reconnection so you can get function,” Hoffman-Kim said. “If it’s a small injury, your body does that fairly well in natural ways that largely depend on the Schwann cells. If the injury gets even just a little bit large then the Schwann cells can’t do it alone.”
Silicone Schwanns
Hoffman-Kim and Lopez-Fagundo did not invent the idea of creating an implant to direct neural growth through repaired or reattached tissues. Their clinical goal is to make that technology the best it can be by systematically studying neural growth on Schwann-like substrates. As a matter of basic science, they wanted to learn how neural growth proceeds.
Lopez-Fagundo, whom Hoffman-Kim recruited for her lab in 2008 when she applied to Brown after graduating from the University of Puerto Rico, started the research with rigorous measurements of Schwann cells in cell cultures of rat neural tissue — the cell size, their elliptical shape, and the average distance between any two, as well as the length and width of the “processes” or wispy extensions that connect them.
“We were able to deconstruct the topography of Schwann cells,” said Lopez-Fagundo. “We were then able to manipulate it into different designs to better understand the influence this topography has.”
They came up with six archetypal designs. One of them mimicked the somewhat messy real-world layout of Schwann cells but the other five were arranged in neat horizontal rows. In one the elliptical Schwann cell bodies were few and far between. In another they were densely packed and in another their spacing was the exact average of Lopez-Fagundo’s measurements. Another design had no “processes” to connect the ellipses and another had only processes but no ellipses.
Using Brown’s microfabrication facility, Lopez-Fagundo patterned their designs on silicon wafers (like those used to make computer chips) and then transferred them to silicone squares about a centimeter on a side so that the ellipses and processes were in raised relief on the silicone. Then they put each pattern in a cell culture of rat neurons and watched them as the neurons grew across each pattern of artificial Schwann cells. As a control for their experiment, they also cultured cells on unpatterned silicone squares.
All of the patterns encouraged some directed neuron growth compared to the random growth of neurons on the unpatterned squares, but clearly some patterns did better than others.
After 17 hours, the two best patterns were the ones with only processes and the one with average ellipse spacing. The natural replica pattern and the one with only ellipses fared the worst.
But by day five, new winners emerged: the patterns where the ellipses were farther than average and nearer than average. Hoffman-Kim said she was surprised that the nerve cells didn’t remain content to follow the straightforward pattern of plain horizontal tracks formed by the process-only pattern. Meanwhile, to some extent, the neurons grew the proper way even without a continuous track at all, for instance in the ellipse-only pattern.
Lopez-Fagundo puzzled over the question of why the ellipses, also called “soma,” matter even as the neurons clearly also grow along the processes.
“I asked myself that question a lot and it wasn’t until I sat at the computer and looked at the [time lapse] videos over and over,” Lopez-Fagundo said. “They use the soma as anchor points. They jump from soma to soma and use the long axis of the soma to guide themselves.”
It’s as if the neurons navigated most effectively when they had both roads (processes) and rest stops (ellipses or soma) where they could get their bearings.
And thus the neurons made their way along the artificially optimized straight and narrow. To the researchers, who also included co-authors Jennifer Mitchel, Talisha Ramchal, and Yu-Ting Dingle, the experiments were a triumph of how the meticulous analytical control afforded by engineering can demystify a complex biological phenomenon.
“Sometimes when I give lectures I say, ‘Biomedical engineers are control freaks and we consider that a compliment,’” Hoffman-Kim said.
Epilepsy Cured in Mice Using Brain Cells
Epilepsy that does not respond to drugs can be halted in adult mice by transplanting a specific type of cell into the brain, UC San Francisco researchers have discovered, raising hope that a similar treatment might work in severe forms of human epilepsy.
UCSF scientists controlled seizures in epileptic mice with a one-time transplantation of medial ganglionic eminence (MGE) cells, which inhibit signaling in overactive nerve circuits, into the hippocampus, a brain region associated with seizures, as well as with learning and memory. Other researchers had previously used different cell types in rodent cell transplantation experiments and failed to stop seizures.
Cell therapy has become an active focus of epilepsy research, in part because current medications, even when effective, only control symptoms and not underlying causes of the disease, according to Scott C. Baraban, PhD, who holds the William K. Bowes Jr. Endowed Chair in Neuroscience Research at UCSF and led the new study. In many types of epilepsy, he said, current drugs have no therapeutic value at all.
“Our results are an encouraging step toward using inhibitory neurons for cell transplantation in adults with severe forms of epilepsy,” Baraban said. “This procedure offers the possibility of controlling seizures and rescuing cognitive deficits in these patients.”
The findings, which are the first ever to report stopping seizures in mouse models of adult human epilepsy, will be published online May 5 in the journal Nature Neuroscience.
During epileptic seizures, extreme muscle contractions and, often, a loss of consciousness can cause seizure sufferers to lose control, fall and sometimes be seriously injured. The unseen malfunction behind these effects is the abnormal firing of many excitatory nerve cells in the brain at the same time.
In the UCSF study, the transplanted inhibitory cells quenched this synchronous, nerve-signaling firestorm, eliminating seizures in half of the treated mice and dramatically reducing the number of spontaneous seizures in the rest. Robert Hunt, PhD, a postdoctoral fellow in the Baraban lab, guided many of the key experiments.
In another encouraging step, UCSF researchers reported May 2 that they found a way to reliably generate human MGE-like cells in the laboratory, and that, when transplanted into healthy mice,the cells similarly spun off functional inhibitory nerve cells. That research can be found online in the journal Cell Stem Cell.
In many forms of epilepsy, loss or malfunction of inhibitory nerve cells within the hippocampus plays a critical role. MGE cells are progenitor cells that form early within the embryo and are capable of generating mature inhibitory nerve cells called interneurons. In the Baraban-led UCSF study, the transplanted MGE cells from mouse embryos migrated and generated interneurons, in effect replacing the cells that fail in epilepsy. The new cells integrated into existing neural circuits in the mice, the researchers found.
“These cells migrate widely and integrate into the adult brain as new inhibitory neurons,” Baraban said. “This is the first report in a mouse model of adult epilepsy in which mice that already were having seizures stopped having seizures after treatment.”
The mouse model of disease that Baraban’s lab team worked with is meant to resemble a severe and typically drug-resistant form of human epilepsy called mesial temporal lobe epilepsy, in which seizures are thought to arise in the hippocampus. In contrast to transplants into the hippocampus, transplants into the amygdala, a brain region involved in memory and emotion, failed to halt seizure activity in this same mouse model, the researcher found.
Temporal lobe epilepsy often develops in adolescence, in some cases long after a seizure episode triggered during early childhood by a high fever. A similar condition in mice can be induced with a chemical exposure, and in addition to seizures, this mouse model shares other pathological features with the human condition, such as loss of cells in the hippocampus, behavioral alterations and impaired problem solving.
In the Nature Neuroscience study, in addition to having fewer seizures, treated mice became less abnormally agitated, less hyperactive, and performed better in water-maze tests.
(Source: newswise.com)
Study shows that individual brain cells track where we are and how we move
Leaving the house in the morning may seem simple, but with every move we make, our brains are working feverishly to create maps of the outside world that allow us to navigate and to remember where we are.
Take one step out the front door, and an individual brain cell fires. Pass by your rose bush on the way to the car, another specific neuron fires. And so it goes. Ultimately, the brain constructs its own pinpoint geographical chart that is far more precise than anything you’d find on Google Maps.
But just how neurons make these maps of space has fascinated scientists for decades. It is known that several types of stimuli influence the creation of neuronal maps, including visual cues in the physical environment — that rose bush, for instance — the body’s innate knowledge of how fast it is moving, and other inputs, like smell. Yet the mechanisms by which groups of neurons combine these various stimuli to make precise maps are unknown.
To solve this puzzle, UCLA neurophysicists built a virtual-reality environment that allowed them to manipulate these cues while measuring the activity of map-making neurons in rats. Surprisingly, they found that when certain cues were removed, the neurons that typically fire each time a rat passes a fixed point or landmark in the real world instead began to compute the rat’s relative position, firing, for example, each time the rodent walked five paces forward, then five paces back, regardless of landmarks. And many other mapping cells shut down altogether, suggesting that different sensory cues strongly influence these neurons.
Finally, the researchers found that in this virtual world, the rhythmic firing of neurons that normally speeds up or slows down depending on the rate at which an animal moves, was profoundly altered. The rats’ brains maintained a single, steady rhythmic pattern.
The findings, reported in the May 2 online edition of the journal Science, provide further clues to how the brain learns and makes memories.
The mystery of how cells determine place
"Place cells" are individual neurons located in the brain’s hippocampus that create maps by registering specific places in the outside environment. These cells are crucial for learning and memory. They are also known to play a role in such conditions as post-traumatic stress disorder and Alzheimer’s disease when damaged.
For some 40 years, the thinking had been that the maps made by place cells were based primarily on visual landmarks in the environment, known as distal cues — a tall tree, a building — as well on motion, or gait, cues. But, as UCLA neurophysicist and senior study author Mayank Mehta points out, other cues are present in the real world: the smell of the local pizzeria, the sound of a nearby subway tunnel, the tactile feel of one’s feet on a surface. These other cues, which Mehta likes to refer to as “stuff,” were believed to have only a small influence on place cells.
Could it be that these different sensory modalities led place cells to create individual maps, wondered Mehta, a professor with joint appointments in the departments of neurology, physics and astronomy. And if so, do these individual maps cooperate with each other, or do they compete? No one really knew for sure.
Virtual reality reveals new clues
To investigate, Mehta and his colleagues needed to separate the distal and gait cues from all the other “stuff.” They did this by crafting a virtual-reality maze for rats in which odors, sounds and all stimuli, except distal and gait cues, were removed. As video of a physical environment was projected around them, the rats, held by a harness, were placed on a ball that rotated as they moved. When they ran, the video would move along with them, giving the animals the illusion that they were navigating their way through an actual physical environment.
As a comparison, the researchers had the rats — six altogether — run a real-world maze that was visually identical to the virtual-reality version but that included the additional “stuff” cues. Using micro-electrodes 10 times thinner than a human hair, the team measured the activity of some 3,000 space-mapping neurons in the rats’ brains as they completed both mazes.
What they found intrigued them. The elimination of the “stuff” cues in the virtual-reality maze had a huge effect: Fully half of the neurons being recorded became inactive, despite the fact that the distal and gate cues were similar in the virtual and real worlds. The results, Mehta said, show that these other sensory cues, once thought to play only a minor role in activating the brain, actually have a major influence on place cells.
And while in the real world, place cells responded to fixed, absolute positions, spiking at those same positions each time rats passed them, regardless of the direction they were moving — a finding consistent with previous experiments — this was not the case in the virtual-reality maze.
"In the virtual world," Mehta said, "we found that the neurons almost never did that. Instead, the neurons spiked at the same relative distance in the two directions as the rat moved back and forth. In other words, going back to the front door-to-car analogy, in a virtual world, the cell that fires five steps away from the door when leaving your home would not fire five steps away from the door upon your return. Instead, it would fire five steps away from the car when leaving the car. Thus, these cells are keeping track of the relative distance traveled rather than absolute position. This gives us evidence for the individual place cell’s ability to represent relative distances."
Mehta thinks this is because neuronal maps are generated by three different categories of stimuli — distal cues, gait and “stuff” — and that all are competing for control of neural activity. This competition is what ultimately generates the “full” map of space.
"All the external stuff is fixed at the same absolute position and hence generates a representation of absolute space," he said. "But when all the stuff is removed, the profound contribution of gait is revealed, which enables neurons to compute relative distances traveled."
The researchers also made a new discovery about the brain’s theta rhythm. It is known that place cells use the rhythmic firing of neurons to keep track of “brain time,” the brain’s internal clock. Normally, Mehta said, the theta rhythm becomes faster as subjects run faster, and slower as running speed decreases. This speed-dependent change in brain rhythm was thought to be crucial for generating the ‘brain time’ for place cells. But the team found that in the virtual world, the theta rhythm was uninfluenced by running speed.
"That was a surprising and fascinating discovery, because the ‘brain time’ of place cells was as precise in the virtual world as in the real world, even though the speed-dependence of the theta rhythm was abolished," Mehta said. "This gives us a new insight about how the brain keeps track of space-time."
The researchers found that the firing of place cells was very precise, down to one-hundredth of a second, “so fast that we humans cannot perceive it but neurons can,” Mehta said. “We have found that this very precise spiking of neurons with respect to ‘brain-time’ is crucial for learning and making new memories.”
Mehta said the results, taken together, provide insight into how distinct sensory cues both cooperate and compete to influence the intricate network of neuronal activity. Understanding how these cells function is key to understanding how the brain makes and retains memories, which are vulnerable to such disorders as Alzheimer’s and PTSD.
"Ultimately, understanding how these intricate neuronal networks function is a key to developing therapies to prevent such disorders," he said.
Tiny worm sheds light on giant mystery about neurons
Scientists have identified a gene that keeps our nerve fibers from clogging up. Researchers in Ken Miller’s laboratory at the Oklahoma Medical Research Foundation (OMRF) found that the unc-16 gene of the roundworm Caenorhabditis elegans encodes a gatekeeper that restricts flow of cellular organelles from the cell body to the axon, a long, narrow extension that neurons use for signaling. Organelles clogging the axon could interfere with neuronal signaling or cause the axon to degenerate, leading to neurodegenerative disorders. This research, published in the May 2013 Genetics Society of America’s journal GENETICS, adds an unexpected twist to our understanding of trafficking within neurons.
Proteins equivalent to UNC-16 are present in the neurons of all animals, including humans And are known to interact with proteins associated with neurodegenerative disorders in humans (Hereditary Spastic Paraplegia) and mice (Legs at Odd Angles). However, the underlying cause of these disorders is not well understood.
"Our UNC-16 study provides the first insights into a previously unrecognized trafficking system that protects axons from invasion by organelles from the cell soma," Dr. Miller said. "A breakdown in this gatekeeper may be the underlying cause of this group of disorders," he added.
The use of the model organism C. elegans, a tiny, translucent roundworm with only 300 neurons, enabled the discovery because the researchers were able to apply complex genetic techniques and imaging methods in living organisms, which would be impossible in larger animals. Dr. Miller’s team tagged organelles with fluorescent proteins and then used time-lapse imaging to follow the movements of the organelles. In normal axons, organelles exited the cell body and entered the initial segment of the axon, but did not move beyond that. In axons of unc-16 mutants, the organelles hitched a ride on tiny motors that carried them deep into the axon, where they accumulated.
Dr. Miller acknowledges there are still a lot of unanswered questions. His lab is currently investigating how UNC-16 performs its crucial gatekeeper function by looking for other mutant worms with similar phenotypes. A Commentary on the article, also published in this issue of GENETICS, calls the work “provocative”, and highlights several important questions prompted by this pioneering study.
"This research once again shows how studies of simple model organisms can bring insight into complex neurodegenerative diseases in humans," said Mark Johnston, Editor-in-Chief of the journal GENETICS. “This kind of basic research is necessary if we are to understand diseases that can’t easily be studied in more complex animals.”
(Source: eurekalert.org)
Sniffing Out Schizophrenia
Neurons in the nose could be the key to early, fast, and accurate diagnosis, says a TAU researcher
A debilitating mental illness, schizophrenia can be difficult to diagnose. Because physiological evidence confirming the disease can only be gathered from the brain during an autopsy, mental health professionals have had to rely on a battery of psychological evaluations to diagnose their patients.
Now, Dr. Noam Shomron and Prof. Ruth Navon of Tel Aviv University’s Sackler Faculty of Medicine, together with PhD student Eyal Mor from Dr. Shomron’s lab and Prof. Akira Sawa of Johns Hopkins Hospital in Baltimore, Maryland, have discovered a method for physical diagnosis — by collecting tissue from the nose through a simple biopsy. Surprisingly, collecting and sequencing neurons from the nose may lead to “more sure-fire” diagnostic capabilities than ever before, Dr. Shomron says.
This finding, which was reported in the journal Neurobiology of Disease, could not only lead to a more accurate diagnosis, it may also permit the crucial, early detection of the disease, giving rise to vastly improved treatment overall.
From the nose to diagnosis
Until now, biomarkers for schizophrenia had only been found in the neuron cells of the brain, which can’t be collected before death. By that point it’s obviously too late to do the patient any good, says Dr. Shomron. Instead, psychiatrists depend on psychological evaluations for diagnosis, including interviews with the patient and reports by family and friends.
For a solution to this diagnostic dilemma, the researchers turned to the olfactory system, which includes neurons located on the upper part of the inner nose. Researchers at Johns Hopkins University collected samples of olfactory neurons from patients diagnosed with schizophrenia and a control group of non-affected individuals, then sent them to Dr. Shomron’s TAU lab.
Dr. Shomron and his fellow researchers applied a high-throughput technology to these samples, studying the microRNA of the olfactory neurons. Within these molecules, which help to regulate our genetic code, they were able to identify a microRNA which is highly elevated in those with schizophrenia, compared to individuals who do not have the disease.
"We were able to narrow down the microRNA to a differentially expressed set, and from there down to a specific microRNA which is elevated in individuals with the disease compared to healthy individuals," explains Dr. Shomron. Further research revealed that this particular microRNA controls genes associated with the generation of neurons.
In practice, material for biopsy could be collected through a quick and easy outpatient procedure, using a local anesthetic, says Dr. Shomron. And with microRNA profiling results ready in a matter of hours, this method could evolve into a relatively simple and accurate test to diagnose a very complicated illness.
Early detection, early intervention
Though there is much more to investigate, Dr. Shomron has high hopes for this diagnostic method. It’s important to determine whether this alteration in microRNA expression begins before schizophrenic symptoms begin to exhibit themselves, or only after the disease fully develops, he says. If this change comes near the beginning of the timeline, it could be invaluable for early diagnostics. This would mean early intervention, better treatment, and possibly even the postponement of symptoms.
If, for example, a person has a family history of schizophrenia, this test could reveal whether they too suffer from the disease. And while such advanced warning doesn’t mean a cure is on the horizon, it will help both patient and doctor identify and prepare for the challenges ahead.
(Source: aftau.org)
Study identifies key shift in the brain that creates drive to overeat
A team of American and Italian neuroscientists has identified a cellular change in the brain that accompanies obesity. The findings could explain the body’s tendency to maintain undesirable weight levels, rather than an ideal weight, and identify possible targets for pharmacological efforts to address obesity.
The findings, published in the Proceedings of the National Academy of Sciences Early Edition this week, identify a switch that occurs in neurons within the hypothalamus. The switch involves receptors that trigger or inhibit the release of the orexin A peptide, which stimulates the appetite, among other behaviors. In normal-weight mice, activation of this receptor decreases orexin A release. In obese mice, activation of this receptor stimulates orexin A release.
"The striking finding is that you have a massive shift of receptors from one set of nerve endings impinging on these neurons to another set," said Ken Mackie, professor in the Department of Psychological and Brain Sciences in the College of Arts and Sciences at IU Bloomington. "Before, activating this receptor inhibited the secretion of orexin; now it promotes it. This identifies potential targets where an intervention could influence obesity."
The work is part of a longstanding collaboration between Mackie’s team at the Gill Center for Biomolecular Science at IU Bloomington and Vincenzo Di Marzo’s team at the Institute of Biomolecular Chemistry in Pozzuoli, Italy. Both teams study the endocannabinoid system, which is composed of receptors and signaling chemicals that occur naturally in the brain and have similarities to the active ingredients in cannabis, or marijuana. This neurochemical system is involved in a variety of physiological processes, including appetite, pain, mood, stress responses and memory.
Food consumption is controlled in part by the hypothalamus, a portion of the brain that regulates many essential behaviors. Like other important body systems, food consumption is regulated by multiple neurochemical systems, including the endocannabinoid system, representing what Mackie describes as a “balance of a very fine web of regulatory networks.”
An emerging idea, Mackie said, is that this network is reset during obesity so that food consumption matches maintenance of current weight, not a person’s ideal weight. Thus, an obese individual who loses weight finds it difficult to keep the weight off, as the brain signals the body to eat more in an attempt to return to the heavier weight.
Using mice, this study found that in obesity, CB1 cannabinoid receptors become enriched on the nerve terminals that normally inhibit orexin neuron activity, and the orexin neurons produce more of the endocannabinoids to activate these receptors. Activating these CB1 receptors decreases inhibition of the orexin neurons, increasing orexin A release and food consumption.
"This study identifies a mechanism for the body’s ongoing tendency to return to the heavier weight," Mackie said.
The researchers conducted several experiments with mice to understand how this change takes place. They uncovered a role of leptin, a key hormone made by fat cells that influences metabolism, hunger and food consumption. Obesity causes leptin levels to be chronically high, making brain cells less sensitive to its actions, which contributes to the molecular switch that leads to the overproduction of orexin.
(Source: eurekalert.org)
Νeuroscientists use statistical model to draft fantasy teams of neurons
This past weekend teams from the National Football League used statistics like height, weight and speed to draft the best college players, and in a few weeks, armchair enthusiasts will use similar measures to select players for their own fantasy football teams. Neuroscientists at Carnegie Mellon University are taking a similar approach to compile “dream teams” of neurons using a statistics-based method that can evaluate the fitness of individual neurons.
After assembling the teams, a computer simulation pitted the groups of neurons against one another in a playoff-style format to find out which population was the best. Researchers analyzed the winning teams to see what types of neurons made the most successful squads.
The results were published in the early online edition of the Proceedings of the National Academy of Sciences the week of April 29.
"We wanted to know what team of neurons would be most likely to perform best in response to a variety of stimuli," said Nathan Urban, the Dr. Frederick A. Schwertz Distinguished Professor of Life Sciences and head of the Department of Biological Sciences at Carnegie Mellon.
The human brain contains more than 100 billion neurons that work together in smaller groups to complete certain tasks like processing an odor, or seeing a color. Previous work by Urban’s lab found that no two neurons are exactly alike and that diverse teams of neurons were better able to determine a stimulus than teams of similar neurons.
"The next step in our work was to figure out how to assemble the best possible population of neurons in order to complete a task," said Urban, who is also a member of the joint Carnegie Mellon/University of Pittsburgh Center for the Neural Basis of Cognition (CNBC).
However, using existing methods, scouting for the best team of neurons was a seemingly daunting task. It would be impossible for scientists to determine how each of the billions of neurons in the brain would individually respond to a multitude of stimuli. Urban and Shreejoy Tripathy, the article’s lead author and graduate student in the CNBC’s Program in Neural Computation, solved this problem using a statistical modeling approach, known as generalized linear models (GLMs), to analyze the cell-to-cell variability. Urban and Tripathy found that by applying this approach they were able to accurately reproduce the behavior of individual neurons in a computer, allowing them to gather statistics on each single cell.
Then, much like in fantasy football, the computer model used the statistics to put together thousands of teams of neurons. The teams competed against one another in a computer simulation to see which were able to most accurately recreate a stimulus delivered to the team of neurons. In the end researchers identified a small set of teams that they could study to see what characteristics made those populations successful.
They found that the winning teams of neurons were diverse but not as diverse as they would be if they were selected at random from the general population of neurons. The most successful sets contained a heterogeneous group of neurons that were flexible and able to respond well to a variety of stimuli.
"You can’t have a football team made up of only linebackers. You need linebackers and tight ends, a quarterback and a kicker. But, the players can’t just be random people off of the street; they all need to be good athletes. And you need to draft for positions, not just the best player available. If your best player is a quarterback — you don’t take another quarterback with your first pick," Urban said. "It’s the same with neurons. To make the most effective grouping of neurons, you need a diverse bunch that also happens to be more robust and flexible than your average neuron."
Urban believes that GLMs can be used to further understand the importance of neuronal diversity. He plans to use the models to predict how alterations in the variability of neurons’ responses, which can be caused by learning or disease, impact function.
(Image courtesy: University of Iowa)