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Fluorescent rabies virus tracks how experience alters neural circuits

January 7, 2012 1 comment

A technique called monosynaptic tracing reveals how experience remodels olfactory bulb microcircuitry

Computer reconstructions showing microcircuits with synaptic contacts onto newborn granule cells (scale bar = 15 micrometres). Image: Arenkiel et al (2011)
 

Contrary to an age-old dogma, the brain is not fixed and immutable. After decades of research, we now know that the brains of mammals (including humans) can produce new cells after embryonic development is ended. We also know that experience alters the connections between nerve cells in a number of ways, and it is widely believed that this process, which is referred to as synaptic plasticity, is critical for learning and memory.

The adult mammalian brain contains two discrete niches of stem cells which retain the ability to generate new neurons. In rodents, it is well established that newborn cells integrate into the existing circuitry and contribute to information processing, but exactly how is unknown. Researchers from the Baylor College of Medicine and Duke University now reveal some of the details of these processes. Using genetically engineered rabies viruses, they show how new cells form connections with older ones and how their connections are modified by sensory experience.

Benjamin Arenkiel and his colleagues used a technique called monosynaptic tracing, developed by Ed Callaway of the Salk Institute, which exploits the natural properties of the rabies virus. Rabies specifically targets cells in the peripheral nerves. Following infection at the nerve endings in the skin, the viral particles are carried along the nerve fibres into the brain, by means of the neuronal machinery that transports cellular materials back and forth.

In a technically challenging and time-consuming series of experiments, the researchers created genetically engineered mice in which small numbers of neurons born post-natally (or after birth), and all the older surrounding cells to which they have become connected, are labelled with fluoroescent protein markers.

To do so, they first created three different recombinant DNA molecules. One was a ‘reporter’ construct, containing the gene encoding the red fluorescent protein tdTomato and a short DNA sequence called a start codon, which guides the protein synthesis machinery to the beginning of the gene. The gene and start codon were separated by another short DNA sequence containing four stop codons, which block synthesis of the dtTomato reporter protein, and these stop signals were flanked by short DNA sequences called loxP sites.

The second was a plasmid, or circular molecule, containing the gene encoding the rabies virus coat protein, which normally envelops the viral DNA and facilitates its entry into host cells, the gene for receptor that the virus binds to in order to gain entry into cells, and the Cre gene, encoding an enzyme which recognizes pairs of short DNA sequences called loxP sites, cuts out the intervening DNA sequences then splices the loxP sequences back together.

The third construct contained a modified rabies virus DNA sequence in which the coat protein gene was replaced with the gene encoding enhanced green fluorescent protein (EGFP).

Next, the researchers injected the reporter construct into stem cells derived from 14-day-old mouse embryos, selected the ones that had integrated the construct into their chromosomes, and implanted them into surrogate mothers’ wombs to generate a strain of mice expressing the inactive reporter gene.

As soon as the animals were born, they were anaesthetized and the plasmid was injected into the lateral ventricles, whose walls contain stem cells that produce immature neurons which migrate long distances into the olfactory bulb. An electrical field was then applied across the animals’ heads, just behind the eyes, making the nerve cell membranes more permeable. Thus, many of the neurons destined for the olfactory bulb took up the plasmid DNA containing the Cre gene, which activates the red fluorescent dtTomato reporter gene.

The animals were then returned to their cages and reared with their mothers. Half of them were housed in special cages fitted with an automated robotic system that dispensed dozens of different odours. One month later, the researchers injected the rabies virus-GFP construct into the olfactory bulb. After another week, they dissected out the bulbs, sliced and examined them under the microscope.

The fluorescent virus targets the neurons which took up the plasmid, only they express the cell surface receptor which it recognizes, but it only enters a very small number of them, making them fluoresce over the red background of the dtTomato reporter, so that they appear yellow. Infected cells express the coat protein from the plasmid, so they synthesize “live” viruses that are transported towards the synapses and then jump across them, making the cells on the other side glow bright green. But their coat protein gene is missing, so the viruses cannot jump across any more synapses.

This clever experimental design enabled the researchers to visualize some of the microcircuits within the olfactory bulbs, and to identify individual granule cells, as well as all the cells forming connections with them, in each circuit. Their analyses reveal hitherto unknown details about how the various cell types are arranged in the bulb, showing that granule cells receive numerous inhibitory connections from a poorly understood population of cells with short axons.

They also show how newborn neurons are integrated into the circuits, and how an enriched sensory environment modifies their connections. Comparison of the olfactory bulbs from animals reared with and without exposure to smells revealed that exposure to smells dramatically increased the number of synaptic inputs onto the newly-integrated granule cells (above left and right, respectively).

The classic experiments of David Hubel and Torsten Weisel showed that the visual system is critically dependent upon sensory stimulation for proper development, and this new study shows that the same is also true of neurons that are born after the developmental period.

Monosynaptic tracing is one of several advanced techniques that have been developed in recent years to investigate neuronal circuits and systems. Another is optogenetics, in which specified cell types are made to express algal proteins that render them sensitive to light, so that they can be switched on or off with great accuracy using laser light pulses delivered through fibre optic cables.

Such techniques have already enabled researchers to examine brain circuits in unprecedented detail. They will continue to do so in the years to come, allowing for the dissection of circuitry in ever greater detail as they become more advanced. This is the first time monosynaptic tracing has been used to investigate how new cells integrate into existing circuitry. A better understanding of the process could be useful for the development of neural stem cell-based transplantation therapies for neurological disorders.

References:

Arenkiel, B., et al. (2011). Activity-Induced Remodeling of Olfactory Bulb Microcircuits Revealed by Monosynaptic Tracing. PLoS ONE6(12) DOI: 10.1371/journal.pone.0029423

Wickersham, I. R., et al. (2007). Monosynaptic restriction of transsynaptic tracing from single, genetically targeted neurons. Neuron53: 639-647. DOI: 10.1016/j.neuron.2007.01.033

Human Thought Can Voluntarily Control Neurons in Brain


Neuroscience research involving epileptic patients with brain electrodes surgically implanted in their medial temporal lobes shows that patients learned to consciously control individual neurons deep in the brain with thoughts.

Subjects learned to control mouse cursors, play video games and alter focus of digital images with their thoughts. The patients were each using brain computer interfaces, deep brain electrodes and software designed for the research.

Controlling Individual Cortical Nerve Cells by Human Thought

Five years ago, neuroscientist Christof Koch of the California Institute of Technology (Caltech), neurosurgeon Itzhak Fried of UCLA, and their colleagues discovered that a single neuron in the human brain can function much like a sophisticated computer and recognize people, landmarks, and objects, suggesting that a consistent and explicit code may help transform complex visual representations into long-term and more abstract memories.

Now Koch and Fried, along with former Caltech graduate student and current postdoctoral fellow Moran Cerf, have found that individuals can exert conscious control over the firing of these single neurons—despite the neurons’ location in an area of the brain previously thought inaccessible to conscious control—and, in doing so, manipulate the behavior of an image on a computer screen.

The work, which appears in a paper in the October 28 issue of the journal Nature, shows that “individuals can rapidly, consciously, and voluntarily control neurons deep inside their head,” says Koch, the Lois and Victor Troendle Professor of Cognitive and Behavioral Biology and professor of computation and neural systems at Caltech.

The study was conducted on 12 epilepsy patients at the David Geffen School of Medicine at UCLA, where Fried directs the Epilepsy Surgery Program. All of the patients suffered from seizures that could not be controlled by medication. To help localize where their seizures were originating in preparation for possible later surgery, the patients were surgically implanted with electrodes deep within the centers of their brains. Cerf used these electrodes to record the activity, as indicated by spikes on a computer screen, of individual neurons in parts of the medial temporal lobe—a brain region that plays a major role in human memory and emotion.

Prior to recording the activity of the neurons, Cerf interviewed each of the patients to learn about their interests. “I wanted to see what they like—say, the band Guns N’ Roses, the TV show House, and the Red Sox,” he says. Using that information, he created for each patient a data set of around 100 images reflecting the things he or she cares about. The patients then viewed those images, one after another, as Cerf monitored their brain activity to look for the targeted firing of single neurons. “Of 100 pictures, maybe 10 will have a strong correlation to a neuron,” he says. “Those images might represent cached memories—things the patient has recently seen.”

The four most strongly responding neurons, representing four different images, were selected for further investigation. “The goal was to get patients to control things with their minds,” Cerf says. By thinking about the individual images—a picture of Marilyn Monroe, for example—the patients triggered the activity of their corresponding neurons, which was translated first into the movement of a cursor on a computer screen. In this way, patients trained themselves to move that cursor up and down, or even play a computer game.

But, says Cerf, “we wanted to take it one step further than just brain–machine interfaces and tap into the competition for attention between thoughts that race through our mind.”

To do that, the team arranged for a situation in which two concepts competed for dominance in the mind of the patient. “We had patients sit in front of a blank screen and asked them to think of one of the target images,” Cerf explains. As they thought of the image, and the related neuron fired, “we made the image appear on the screen,” he says. That image is the “target.” Then one of the other three images is introduced, to serve as the “distractor.”

“The patient starts with a 50/50 image, a hybrid, representing the ‘marriage’ of the two images,” Cerf says, and then has to make the target image fade in—just using his or her mind—and the distractor fade out. During the tests, the patients came up with their own personal strategies for making the right images appear; some simply thought of the picture, while others repeated the name of the image out loud or focused their gaze on a particular aspect of the image. Regardless of their tactics, the subjects quickly got the hang of the task, and they were successful in around 70 percent of trials.

“The patients clearly found this task to be incredibly fun as they started to feel that they control things in the environment purely with their thought,” says Cerf. “They were highly enthusiastic to try new things and see the boundaries of ‘thoughts’ that still allow them to activate things in the environment.”

Notably, even in cases where the patients were on the verge of failure—with, say, the distractor image representing 90 percent of the composite picture, so that it was essentially all the patients saw—”they were able to pull it back,” Cerf says. Imagine, for example, that the target image is Bill Clinton and the distractor George Bush. When the patient is “failing” the task, the George Bush image will dominate. “The patient will see George Bush, but they’re supposed to be thinking about Bill Clinton. So they shut off Bush—somehow figuring out how to control the flow of that information in their brain—and make other information appear. The imagery in their brain,” he says, “is stronger than the hybrid image on the screen.”

According to Koch, what is most exciting “is the discovery that the part of the brain that stores the instruction ‘think of Clinton’ reaches into the medial temporal lobe and excites the set of neurons responding to Clinton, simultaneously suppressing the population of neurons representing Bush, while leaving the vast majority of cells representing other concepts or familiar person untouched.”

The work in the paper, “On-line voluntary control of human temporal lobe neurons,” is part of a decade-long collaboration between the Fried and Koch groups, funded by the National Institute of Neurological Disorders and Stroke, the National Institute of Mental Health, the G. Harold & Leila Y. Mathers Charitable Foundation, and Korea’s World Class University program.

Source: California Institute of Technology (Caltech)

Research suggests humans can learn to consciously control individual neurons in the brain. Image credit: Moran Cerf and Maria Moon/Caltech

Two Universes, Same Structure

February 21, 2011 Leave a comment

 

 

 

This image is not of a neuron.

This image is of the other universe; the one outside our heads.

 

 

 

 

 

It depicts the “evolution of the matter distribution in a cubic region of the Universe over 2 billion light-years”, as computed by the Millennium Simulation. (Click the image above for a better view.)

The next image, of a neuron, is included for comparison.

It is tempting to wax philosophical on this structure equivalence. How is it that both the external and internal universes can have such similar structure, and at such vastly different physical scales?

If we choose to go philosophical, we may as well ponder something even more fundamental: Why is it that all complex systems seem to have a similar underlying network-like structure?

For illustration of this point, just take a glance at the front page of VisualComplexity.com (partially reproduced below).

These neural-network-like visual images represent complex systems and relations for domains as diverse as academic citations, the blogosphere, scientific knowledge, genealogy, iTunes music collections, and Italian wine production.

Does this imply some deep equivalence exists between all complex systems? Is it the nature of complex systems to be network-like?

Alternatively, this is perhaps simply how we, as neural networks, are able to conceptualize the external universe. Could it be that the external universe is vastly different in form from our internal universe, but we simply perceive that which happens to be compatible with our neural network knowledge structure?

It seems there are some situations where we have trouble representing reality for this reason. However, evolutionary pressures for survival likely drove the human brain to represent the world as accurately as possible. (Otherwise, e.g. our ancestors may have believed lions disappeared when hiding behind bushes; an obviously maladaptive representation of reality.) This suggests that even though our brains don’t represent the world with complete accuracy, it is nonetheless quite accurate in most cases.

Ultimately I think the equivalence between complex systems is due to the underlying nature of such systems. They must all involve massive integrated differentiation. In other words, there must be many different things (nodes), with many different relations among them (links) for a system to be complex. Thus integrated differentiation, the very basis of complexity, is inherently network-like (i.e., has the equivalent of nodes and links).

It is compelling to consider if neural systems, with their numerous nodes (neurons) and links (synapses) providing integrated differentiation, might have evolved complexity in order to represent other complex systems. In other words, neural systems may have evolved in order to mirror the complexity presented by the external universe, which helped each organism adapt and survive in its environment.

Thus the similarity between the internal and external universes may not be due to coincidence, but design.

For neurons to work as a team, it helps to have a beat

September 22, 2010 Leave a comment

This is an illustration of how brain rhythms organize distributed groups of neurons into functional cell assemblies. The colors represent different cell assemblies. Neurons in widely separated brain areas often need to work together without interfering with other, spatially overlapping groups. Each assembly is sensitive to different frequencies, producing independent patterns of coordinated neural activity, depicted as color traces to the right of each network. Credit: Ryan Canolty, UC Berkeley

When it comes to conducting complex tasks, it turns out that the brain needs rhythm, according to researchers at the University of California, Berkeley.

Specifically, cortical rhythms, or oscillations, can effectively rally groups of neurons in widely dispersed regions of the brain to engage in coordinated activity, much like a conductor will summon up various sections of an orchestra in a symphony.

Even the simple act of catching a ball necessitates an impressive coordination of multiple groups of neurons to perceive the object, judge its speed and trajectory, decide when it’s time to catch it and then direct the muscles in the body to grasp it before it whizzes by or drops to the ground.

Until now, neuroscientists had not fully understood how these neuron groups in widely dispersed regions of the brain first get linked together so they can work in concert for such complex tasks.

The UC Berkeley findings are to be published the week of Sept. 20 in the online early edition of the journal Proceedings of the National Academy of Sciences.

“One of the key problems in neuroscience right now is how you go from billions of diverse and independent neurons, on the one hand, to a unified brain able to act and survive in a complex world, on the other,” said principal investigator Jose Carmena, UC Berkeley assistant professor at the Department of Electrical Engineering and Computer Sciences, the Program in Cognitive Science, and the Helen Wills Neuroscience Institute. “Evidence from this study supports the idea that neuronal oscillations are a critical mechanism for organizing the activity of individual neurons into larger functional groups.”

The idea behind anatomically dispersed but functionally related groups of neurons is credited to neuroscientist Donald Hebb, who put forward the concept in his 1949 book “The Organization of Behavior.”

“Hebb basically said that single neurons weren’t the most important unit of brain operation, and that it’s really the cell assembly that matters,” said study lead author Ryan Canolty, a UC Berkeley postdoctoral fellow in the Carmena lab.

It took decades after Hebb’s book for scientists to start unraveling how groups of neurons dynamically assemble. Not only do neuron groups need to work together for the task of perception – such as following the course of a baseball as it makes its way through the air – but they then need to join forces with groups of neurons in other parts of the brain, such as in regions responsible for cognition and body control.

At UC Berkeley, neuroscientists examined existing data recorded over the past four years from four macaque monkeys. Half of the subjects were engaged in brain-machine interface tasks, and the other half were participating in working memory tasks. The researchers looked at how the timing of electrical spikes – or action potentials – emitted by nerve cells was related to rhythms occurring in multiple areas across the brain.

Among the squiggly lines, patterns emerged that give literal meaning to the phrase “tuned in.” The timing of when individual neurons spiked was synchronized with brain rhythms occurring in distinct frequency bands in other regions of the brain. For example, the high-beta band – 25 to 40 hertz (cycles per second) – was especially important for brain areas involved in motor control and planning.

“Many neurons are thought to respond to a receptive field, so that if I look at one motor neuron as I move my hand to the left, I’ll see it fire more often, but if I move my hand to the right, the neuron fires less often,” said Carmena. “What we’ve shown here is that, in addition to these traditional ‘external’ receptive fields, many neurons also respond to ‘internal’ receptive fields. Those internal fields focus on large-scale patterns of synchronization involving distinct cortical areas within a larger functional network.”

The researchers expressed surprise that this spike dependence was not restricted to the neuron’s local environment. It turns out that this local-to-global connection is vital for organizing spatially distributed neuronal groups.

“If neurons only cared about what was happening in their local environment, then it would be difficult to get neurons to work together if they happened to be in different cortical areas,” said Canolty. “But when multiple neurons spread all over the brain are tuned in to a specific pattern of electrical activity at a specific frequency, then whenever that global activity pattern occurs, those neurons can act as a coordinated assembly.”

The researchers pointed out that this mechanism of cell assembly formation via oscillatory phase coupling is selective. Two neurons that are sensitive to different frequencies or to different spatial coupling patterns will exhibit independent activity, no matter how close they are spatially, and will not be part of the same assembly. Conversely, two neurons that prefer a similar pattern of coupling will exhibit similar spiking activity over time, even if they are widely separated or in different brain areas.

“It is like the radio communication between emergency first responders at an earthquake,” Canolty said. “You have many people spread out over a large area, and the police need to be able to talk to each other on the radio to coordinate their action without interfering with the firefighters, and the firefighters need to be able to communicate without disrupting the EMTs. So each group tunes into and uses a different radio frequency, providing each group with an independent channel of communication despite the fact that they are spatially spread out and overlapping.”

The authors noted that this local-to-global relationship in brain activity may prove useful for improving the performance of brain-machine interfaces, or lead to novel strategies for regulating dysfunctional brain networks through electrical stimulation. Treatment of movement disorders through deep brain stimulation, for example, usually targets a single area. This study suggests that gentler rhythmic stimulation in several areas at once may also prove effective, the authors said.

Provided by University of California – Berkeley

PhysOrg.com http://www.physorg.com/news204220208.html

Categories: Neuroscience Tags: ,

A Single Neuron Can Change the Activity of the Whole Brain

September 21, 2010 1 comment

The pulsing of a single neuron can switch a brain’s waves from the equivalent of a big ocean swell to ripples on a pond, according to new research from Howard Hughes Medical Institute investigator Yang Dan of the University of California, Berkeley.


The study reveals important new information about how the brain controls large-scale activity patterns and suggests that an individual cell has more influence than previously thought. The findings, published in the May 1, 2009, issue of the journal Science, could ultimately shed light on how chaotic brain patterns can lead to sleep disorders such as sleepwalking.

Brain cells use electrical pulses to talk with one another and guide functions ranging from heart rate and breathing to decision-making and navigation. Like the din of a crowd, the chatter of 100 billion neuronal cells in the human brain creates larger patterns of activity commonly called brain waves.

These patterns reveal the brain’s general state of arousal. For instance, large, slow brain waves that are synchronized throughout the brain are indicative of deep sleep. “Many neurons are doing the same thing at the same time,” says Dan. During so-called rapid eye movement (REM) sleep, on the other hand, different brain areas are less synchronized, firing in smaller and more frequent oscillations. And in an awake person, the brain broadcasts a rapid, uncoordinated pattern.

Dan and her colleagues wanted to understand how large-scale wave patterns influence the connection between two neurons. They knew that neuronal connections could strengthen or weaken over time, and these changes seem to underlie learning and memory. They wondered whether the overall pattern of brain activity altered nerve cells’ ability to change their connection strength.

Studying anesthetized rats, they used one electrode to spur a neuron to fire rapidly and used another electrode nearby to activate the local neuronal connections. A third electrode was used to pick up the larger pattern emitted by all the neurons in the area. They wanted the overall brain state to remain constant during the experiment, but instead found that tickling one neuron could cause the entire brain state to change.

“Initially, this was very inconvenient,” says Dan. But then the researchers realized that the phenomenon deserved more attention. Looking more closely, they verified that a neuron firing at high frequency could switch the brain from a “non-REM pattern” of activity to a “REM pattern,” and vice versa.

The result was counterintuitive. “Every neuron makes connections to roughly 1,000 other neurons, but most of those are quite weak,” says Dan. A target cell won’t respond unless many, many neurons that connect to it fire at the same time and therefore she says it’s surprising that a single neuron could change the activity of the whole brain. “Single neurons have more weight than we used to think,” she says.

Dan doesn’t yet know how one cell could exert such power. The researchers had to repeatedly and rapidly fire a cell to cause the pattern to switch, so they might be emulating the effect of many cells firing at once. A neuron doesn’t normally fire in that way, so it is an open question whether the activity of a single neuron could change overall brain pattern under normal circumstances.

The findings add a new twist to how brain patterns are established. Researchers know that certain brain structures, such as the hypothalamus and the brain stem, play a part in setting the pace of global brain activity. In this study, Dan and her team were tickling brain cells in a different area: the cortex, the thin sheet of neurons on the surface of the brain involved in such abilities as moving and seeing.

Dan isn’t certain how cells in the cortex might control brain state, but she posits that signaling there could link back to the thalamus and spur it to set up a new pattern. “We know that a lot of circuits are involved in controlling brain state,” says Dan. “We’re saying that cortex is also part of that loop.”

By providing new information about how brain states are controlled, the study might ultimately lead to new knowledge about what causes certain sleep disorders. “In sleepwalking, there is a mixed-up boundary between slow-wave sleep and the awake state,” says Dan. “Your muscles move, but you aren’t consciously aware of your surroundings.” Understanding the circuitry that establishes brain states could ultimately reveal how that mixed-up situation is established.

Next, Dan wants to study animals that are naturally awake or sleeping, rather than anesthetized, to see if under normal conditions, a single neuron or a few neurons really can turn the tide on the entire brain.

Provided by Howard Hughes Medical Institute (news : web)

PhysOrg.com http://www.physorg.com/news160407260.html

Categories: Neuroscience Tags: ,