New Information about Neurons Could Lead to Advancements in Understanding Brain and Neurological Disorders

Neurons are electrically charged cells, located in the nervous system, that interpret and transmit information using electrical and chemical signals. Now, researchers at the University of Missouri have determined that individual neurons can react differently to electrical signals at the molecular level and in different ways—even among neurons of the same type. This variability may be important in discovering underlying problems associated with brain disorders and neural diseases such as epilepsy.

“Genetic mutations found in neurological disorders create imbalances in the inward and outward flow of electrical current through cells,” said David Schulz, associate professor in the Division of Biological Sciences in the College of Arts and Science and a researcher in the Interdisciplinary Neuroscience Program at MU. “Often, neurons react to electrical signals, or voltage, and compensate by altering their own electrical outputs. The variability in these imbalances, even among multiple cells of the same kind within the brain, is one of the major problems scientists face when trying to design therapeutics for disorders like epilepsy. Seizures in individuals can be caused by different imbalances—therefore getting to the root of how neurons act individually makes our studies important.”

Schulz and his team previously proved that two identical neurons can reach the same electrical activity in different ways. In his new study, Schulz hypothesized that neurons might use the cell’s genetic code, or its messenger RNA (mRNA), to “fine tune” the production of proteins, helping individual cells react accordingly.

Using clusters of neurons obtained from Jonah crabs, Schulz and his team experimentally altered electrical input and output in the neurons and measured the messenger RNA (mRNA) levels found within the cells. Invertebrates like crabs are useful in neuroscience research because their neurons are simple enough to observe and study, but advanced enough that they can be “scaled up” to apply to higher organisms, Schulz said.

They found that when normal patterns of stimulation were maintained, cells engaged the correct ratios of mRNA to produce the proteins needed to help keep electrical impulses in order; however, when normal patterns of activity were not maintained, this fundamentally changed the cells at the molecular level.

“We were the first to show that the correct ratios of mRNAs are actively maintained by the actual activity or voltage of the cell, and not chemical feedback,” Schulz said. “These results represent a novel aspect of regulation that might be useful for developing therapeutics for neuronal disorders later.”

Schulz’ study, “Activity-dependent feedback regulates correlated ion channel mRNA levels in single identified motor neurons,” was published in the August 18^th edition of Current Biology.

(Fig. 1: Two-photon image of the three types of cells in the visual cortex of a rat. Neuronal activity is measured via changes in fluorescence intensity. Green cells are inhibitory neurons, white cells are excitatory neurons, and red cells are astrocytes.)

Waking up the visual system

The ways that neurons in the brain respond to a given stimulus depends on whether an organism is asleep, drowsy, awake, paying careful attention or ignoring the stimulus. However, while the properties of neural circuits in the visual cortex are well known, the mechanisms responsible for the different patterns of activity in the awake and drowsy states remain poorly understood. A team of researchers led by Tadaharu Tsumoto from the RIKEN Brain Science Institute has observed the changes in activity that occur in rodents on waking from anesthesia.

The research team used a technique called two-photon functional calcium imaging to observe the activity of cells in the visual cortex of rats while they are anesthetized and exposed to a visual stimulus of an image moving across a screen. Using rats with inhibitory neurons labeled with a green fluorescent protein, the researchers were able to measure the activity separately in populations of inhibitory and excitatory neurons (Fig. 1). The neuronal activity in response to visual stimulation under anesthesia was recorded, and then the rats were allowed to wake and the change in activity of the two populations of neurons was observed.

Tsumoto’s team found that inhibitory neurons responded more reliably and with stronger activity to visual stimuli in the awake state than in the anesthetized state. The response of the excitatory neurons had a shorter decay time in the awake state, which means that their activity was more tightly linked to the presentation of the visual stimulus than when the animal was under the influence of anesthesia.

These changes that occur during wakefulness allow neurons in the visual cortex to respond more reliably to visual stimuli in their environment. “If animals are awakened from the drowsy state by howls or footsteps of enemies, the sensitivity or resolution of moving visual stimuli will increase so that they can more effectively judge how fast and from which location the enemies are coming,” explains Tsumoto.

The team then found that the basal forebrain region of the brain, which is known to play a role in state-dependent changes in cortical activity through its acetylcholine neurons, is responsible for these shifts in responses of neurons in the visual cortex of mice during wakefulness. They found that stimulating the basal forebrain of anesthetized animals could make visual cortical neurons take on the firing properties of the awake state. These findings highlight the role of the basal forebrain in modulating the responses of visual cortical neurons during wakefulness.

New learning mechanism for individual nerve cells

“This means a dramatic increase in the brain’s learning capacity. The cells we have studied control the blink reflex, but there are many cells of the same type that control entirely different processes. It is therefore likely that the timing mechanism we have discovered also exists in other parts of the brain”, said Professor of neurophysiology Germund Hesslow.

Professor Hesslow and colleagues Fredrik Johansson and Dan-Anders Jirenhed have used ‘conditioned reflexes’ for the research. The principle comes from the Russian researcher Ivan Pavlov, who, around the turn of the last century, taught dogs to associate a certain sound with food so that they began to drool on hearing the sound.

In the present experiment, the researchers studied animals that learnt to associate a sound with a puff of air in the eye that caused them to blink. If the time between the sound and the puff of air was quarter of a second, the animals blinked after quarter of a second even if the puff of air was removed. If the time was changed to half a second, the animals blinked after half a second, and so on.

The prevalent theories in brain research state that this learnt timing mechanism is a result of strengthening or weakening of the contacts – or synapses – throughout a network of nerve cells. However, using super-thin electrodes, the Lund group have now shown that no networks are needed: one single cell can learn when it is time to react.

The cells which the researchers have studied are called Purkinje cells and are located in the cerebellum. The cerebellum is the part of the brain responsible for posture, balance and movement, and the researchers focused on those cells that control blinking.

This work is basic research, but possible future applications could include rehabilitation following a stroke, which often affects a patient’s movements. The findings could also have a bearing on conditions such as autism, ADHD and language problems, in which the cerebellum is believed to play a part.

“Intelligible speech is dependent on correct timing, so that the pauses between the sounds are right”, explained Germund Hesslow.

The new findings have already attracted attention in the research community: the internationally renowned memory researcher Charles Gallistel came all the way from Rutgers University in the spring to study the group’s work. Work is now continuing to study what transmitter substance and what receptor on the surface of the cell are responsible for the newly discovered timing mechanism.

Using the brain to forecast decisions

You’re waiting at a bus stop, expecting the bus to arrive any time. You watch the road. Nothing yet. A little later you start to pace. More time passes. “Maybe there is some problem”, you think. Finally, you give up and raise your arm and hail a taxi. Just as you pull away, you glimpse the bus gliding up. Did you have a choice to wait a bit longer? Or was giving up too soon the inevitable and predictable result of a chain of neural events?

In research published on 09/28/2014 in the journal Nature Neuroscience, scientists show that neural recordings can be used to forecast when spontaneous decisions will take place. “Experiments like this have been used to argue that free will is an illusion,” says Zachary Mainen, a neuroscientist at the Champalimaud Centre for the Unknown, in Lisbon, Portugal, who led the study, “but we think that interpretation is mistaken.”

The scientists used recordings of neurons in an area of the brain involved in planning movements to try to predict when a rat would give up waiting for a delayed tone. “We know they were not just responding to a stimulus, but spontaneously deciding when to give up, because the timing of their choice varied unpredictably from trial to trial” said Mainen. The researchers discovered that neurons in the premotor cortex could predict the animals’ actions more than one second in advance. According to Mainen, “This is remarkable because in similar experiments, humans report deciding when to move only around two tenths of a second before the movement.”

However, the scientists claim that this kind of predictive activity does not mean that the brain has decided. “Our data can be explained very well by a theory of decision-making known as an ‘integration-to-bound’ model” says Mainen. According to this theory, individual brain cells cast votes for or against a particular action, such as raising an arm. Circuits within the brain keep a tally of the votes in favor of each action and when a threshold is reached it is triggered. Critically, like individual voters in an election, individual neurons influence a decision but do not determine the outcome. Mainen explained: “Elections can be forecast by polling, and the more data available, the better the prediction, but these forecasts are never 100% accurate and being able to partly predict an election does not mean that its results are predetermined. In the same way, being able to use neural activity to predict a decision does not mean that a decision has already taken place.”

The scientists also described a second population of neurons whose activity is theorized to reflect the running tally of votes for a particular action. This activity, described as “ramping”, had previously been reported only in humans and other primates. According to Masayoshi Murakami, co-author of the paper, “we believe these data provide strong evidence that the brain is performing integration to a threshold, but there are still many unknowns.” Said Mainen, “what is the origin of the variability is a huge question. Until we understand that, we cannot say we understand how a decision works”.

(Image caption: Archer1 fluorescence in a cultured rat hippocampal neuron. By monitoring changes in this fluorescence at up to a thousand frames per second, researchers can track the electrical activity of the cell. Credit: Nicholas Flytzanis, Claire Bedbrook and Viviana Gradinaru/Caltech)

Sensing Neuronal Activity With Light

For years, neuroscientists have been trying to develop tools that would allow them to clearly view the brain’s circuitry in action—from the first moment a neuron fires to the resulting behavior in a whole organism. To get this complete picture, neuroscientists are working to develop a range of new tools to study the brain. Researchers at Caltech have developed one such tool that provides a new way of mapping neural networks in a living organism.

The work—a collaboration between Viviana Gradinaru (BS ‘05), assistant professor of biology and biological engineering, and Frances Arnold, the Dick and Barbara Dickinson Professor of Chemical Engineering, Bioengineering and Biochemistry—was described in two separate papers published this month.

When a neuron is at rest, channels and pumps in the cell membrane maintain a cell-specific balance of positively and negatively charged ions within and outside of the cell resulting in a steady membrane voltage called the cell’s resting potential. However, if a stimulus is detected—for example, a scent or a sound—ions flood through newly open channels causing a change in membrane voltage. This voltage change is often manifested as an action potential—the neuronal impulse that sets circuit activity into motion.

The tool developed by Gradinaru and Arnold detects and serves as a marker of these voltage changes.

"Our overarching goal for this tool was to achieve sensing of neuronal activity with light rather than traditional electrophysiology, but this goal had a few prerequisites," Gradinaru says. "The sensor had to be fast, since action potentials happen in just milliseconds. Also, the sensor had to be very bright so that the signal could be detected with existing microscopy setups. And you need to be able to simultaneously study the multiple neurons that make up a neural network."

The researchers began by optimizing Archaerhodopsin (Arch), a light-sensitive protein from bacteria. In nature, opsins like Arch detect sunlight and initiate the microbes’ movement toward the light so that they can begin photosynthesis. However, researchers can also exploit the light-responsive qualities of opsins for a neuroscience method called optogenetics—in which an organism’s neurons are genetically modified to express these microbial opsins. Then, by simply shining a light on the modified neurons, the researchers can control the activity of the cells as well as their associated behaviors in the organism.

Gradinaru had previously engineered Arch for better tolerance and performance in mammalian cells as a traditional optogenetic tool used to control an organism’s behavior with light. When the modified neurons are exposed to green light, Arch acts as an inhibitor, controlling neuronal activity—and thus the associated behaviors—by preventing the neurons from firing.

However, Gradinaru and Arnold were most interested in another property of Arch: when exposed to red light, the protein acts as a voltage sensor, responding to changes in membrane voltages by producing a flash of light in the presence of an action potential. Although this property could in principle allow Arch to detect the activity of networks of neurons, the light signal marking this neuronal activity was often too dim to see.

To fix this problem, Arnold and her colleagues made the Arch protein brighter using a method called directed evolution—a technique Arnold originally pioneered in the early 1990s. The researchers introduced mutations into the Arch gene, thus encoding millions of variants of the protein. They transferred the mutated genes into E. coli cells, which produced the mutant proteins encoded by the genes. They then screened thousands of the resulting E. coli colonies for the intensities of their fluorescence. The genes for the brightest versions were isolated and subjected to further rounds of mutagenesis and screening until the bacteria produced proteins that were 20 times brighter than the original Arch protein.

A paper describing the process and the bright new protein variants that were created was published in the September 9 issue of the Proceedings of the National Academy of Science.

"This experiment demonstrates how rapidly these remarkable bacterial proteins can evolve in response to new demands. But even more exciting is what they can do in neurons, as Viviana discovered," says Arnold.

In a separate study led by Gradinaru’s graduate students Nicholas Flytzanis and Claire Bedbrook, who is also advised by Arnold, the researchers genetically incorporated the new, brighter Arch variants into rodent neurons in culture to see which of these versions was most sensitive to voltage changes—and therefore would be the best at detecting action potentials. One variant, Archer1, was not only bright and sensitive enough to mark action potentials in mammalian neurons in real time, it could also be used to identify which neurons were synaptically connected—and communicating with one another—in a circuit.

The work is described in a study published on September 15 in the journal Nature Communications.

"What was interesting is that we would see two cells over here light up, but not this one over there—because the first two are synaptically connected," Gradinaru says. "This tool gave us a way to observe a network where the perturbation of one cell affects another."

However, sensing activity in a living organism and correlating this activity with behavior remained the biggest challenge. To accomplish this goal Gradinaru’s team worked with Paul Sternberg, the Thomas Hunt Morgan Professor of Biology, to test Archer1 as a sensor in a living organism—the tiny nematode worm C. elegans. “There are a few reasons why we used the worms here: they are powerful organisms for quick genetic engineering and their tissues are nearly transparent, making it easy to see the fluorescent protein in a living animal,” she says.

After incorporating Archer1 into neurons that were a part of the worm’s olfactory system—a primary source of sensory information for C. elegans—the researchers exposed the worm to an odorant. When the odorant was present, a baseline fluorescent signal was seen, and when the odorant was removed, the researchers could see the circuit of neurons light up, meaning that these particular neurons are repressed in the presence of the stimulus and active in the absence of the stimulus. The experiment was the first time that an Arch variant had been used to observe an active circuit in a living organism.

Gradinaru next hopes to use tools like Archer1 to better understand the complex neuronal networks of mammals, using microbial opsins as sensing and actuating tools in optogenetically modified rodents.

"For the future work it’s useful that this tool is bifunctional. Although Archer1 acts as a voltage sensor under red light, with green light, it’s an inhibitor," she says. "And so now a long-term goal for our optogenetics experiments is to combine the tools with behavior-controlling properties and the tools with voltage-sensing properties. This would allow us to obtain all-optical access to neuronal circuits. But I think there is still a lot of work ahead."

One goal for the future, Gradinaru says, is to make Archer1 even brighter. Although the protein’s fluorescence can be seen through the nearly transparent tissues of the nematode worm, opaque organs such as the mammalian brain are still a challenge. More work, she says, will need to be done before Archer1 could be used to detect voltage changes in the neurons of living, behaving mammals.

And that will require further collaborations with protein engineers and biochemists like Arnold.

"As neuroscientists we often encounter experimental barriers, which open the potential for new methods. We then collaborate to generate tools through chemistry or instrumentation, then we validate them and suggest optimizations, and it just keeps going," she says. "There are a few things that we’d like to be better, and through these many iterations and hard work it can happen."

New research offers help for spinal cord patients

In a study on rats, researchers at the University of Copenhagen have discovered the cause of the involuntary muscle contractions which patients with severe spinal cord injuries frequently suffer. The findings have just been published in the Journal of Neuroscience and, in the long run, can pave the way for new treatment methods.

Three thousand Danish patients suffer from severe spinal cord injuries after being involved in traffic accidents or accidents at work. An injury to the spinal cord is a catastrophe for the individual, and often results in complete or partial paralysis of the person’s arms and legs. Despite the paralysis, several patients experience problems with involuntary muscle contractions or spasms which impair the patient’s quality of life.

The movements are due to the neurotransmitter serotonin, which normally plays a crucial role in relation to our voluntary control of movements by reinforcing the level of activity in the motor neurones when they have to activate the muscles to an extraordinary degree. Research shows that a group of cells in the spinal cord start supplying serotonin in an uncontrolled way following an injury, and this knocks the motor system out of control.

“We now have a qualified idea of why the serotonin level goes out of control, and we have documented that a special serotonin-producing enzyme plays a key role. By targeting the specific enzyme, in the long term we will be able to devise new methods of treatment when we are trying to impact functions in the nervous system,” says associate professor and neurophysiologist Jacob Wienecke.

The prospects of the study are interesting for both spinal cord patients and patients suffering from Parkinson’s disease.

Emergency response kicks in

The enzyme aromatic L-amino acid decarboxylase (AADC) plays an important role in the production of the neurotransmitter serotonin:

“In the first few days after an injury to the spinal cord, we can see there is a very rapid regulation of AADC which results in the uncontrolled production of serotonin. It is our guess that this is the spinal cord’s emergency response trying to boost the enzyme’s capacity,” says Jacob Wienecke.

According to the researchers, it may be the same emergency response which causes the involuntary movements – dyskinesia – that are also experienced by patients with Parkinson’s disease. However, for Parkinson’s patients, it is the dopamine system which is affected, but the enzyme which activates the emergency response is the same.

“It is an interesting perspective, which will hopefully focus efforts on targeting drugs specifically at the AADC cells. Perhaps in the future we can regulate the undesired neural activity in this way so that the unnecessary ‘disturbance on the line’ disappears for the affected patients,” says Jacob Wienecke.

Existing treatment puts a damper on learning

Existing forms of treatment for spinal cord patients currently involve, for example, using the drug baclofen, which suppresses neural activity, and thereby the motor neurones which cause the involuntary movements. The problem with baclofen though is that it impacts motor learning – and thus the patients’ rehabilitation. However, there is still a long way to go. Developing new drugs is a protracted process, and the way is paved with obstacles. Injuries to the spinal column are extremely complex, and primarily result in interruptions to the signalling between the brain and the body.

“Finding a solution to the problem is no easy task. However, a lot suggests that regulating serotonin production more precisely could mitigate undesirable spasms while also supporting the rehabilitation of controlled movements. So far, the study has been carried out on rats, but we have reason to believe that the same mechanisms apply in humans,” says Jacob Wienecke in conclusion.

Scientists Discover Why Learning Tasks Can Be Difficult

Learning a new skill is easier when it is related to an ability we already have. For example, a trained pianist can learn a new melody easier than learning how to hit a tennis serve.

Scientists from the Center for the Neural Basis of Cognition (CNBC) — a joint program between Carnegie Mellon University and the University of Pittsburgh — have discovered a fundamental constraint in the brain that may explain why this happens. Published as the cover story in the Aug. 28, 2014, issue of Nature, they found for the first time that there are limitations on how adaptable the brain is during learning and that these restrictions are a key determinant for whether a new skill will be easy or difficult to learn. Understanding the ways in which the brain’s activity can be “flexed” during learning could eventually be used to develop better treatments for stroke and other brain injuries.

Lead author Patrick T. Sadtler, a Ph.D. candidate in Pitt’s Department of Bioengineering, compared the study’s findings to cooking.

"Suppose you have flour, sugar, baking soda, eggs, salt and milk. You can combine them to make different items - bread, pancakes and cookies — but it would be difficult to make hamburger patties with the existing ingredients," Sadtler said. "We found that the brain works in a similar way during learning. We found that subjects were able to more readily recombine familiar activity patterns in new ways relative to creating entirely novel patterns."

For the study, the research team trained animals to use a brain-computer interface (BCI), similar to ones that have shown recent promise in clinical trials for assisting quadriplegics and amputees.

"This evolving technology is a powerful tool for brain research," said Daofen Chen, program director at the National Institute of Neurological Disorders and Stroke (NINDS), part of the National Institutes of Health (NIH), which supported this research. "It helps scientists study the dynamics of brain circuits that may explain the neural basis of learning."

The researchers recorded neural activity in the subject’s motor cortex and directed the recordings into a computer, which translated the activity into movement of a cursor on the computer screen. This technique allowed the team to specify the activity patterns that would move the cursor. The test subjects’ goal was to move the cursor to targets on the screen, which required them to generate the patterns of neural activity that the experimenters had requested. If the subjects could move the cursor well, that meant that they had learned to generate the neural activity pattern that the researchers had specified.

The results showed that the subjects learned to generate some neural activity patterns more easily than others, since they only sometimes achieved accurate cursor movements. The harder-to-learn patterns were different from any of the pre-existing patterns, whereas the easier-to-learn patterns were combinations of pre-existing brain patterns. Because the existing brain patterns likely reflect how the neurons are interconnected, the results suggest that the connectivity among neurons shapes learning.

"We wanted to study how the brain changes its activity when you learn, and also how its activity cannot change. Cognitive flexibility has a limit — and we wanted to find out what that limit looks like in terms of neurons," said Aaron P. Batista, assistant professor of bioengineering at Pitt.

Byron M. Yu, assistant professor of electrical and computer engineering and biomedical engineering at Carnegie Mellon, believes this work demonstrates the utility of BCI for basic scientific studies that will eventually impact people’s lives.

"These findings could be the basis for novel rehabilitation procedures for the many neural disorders that are characterized by improper neural activity," Yu said. "Restoring function might require a person to generate a new pattern of neural activity. We could use techniques similar to what were used in this study to coach patients to generate proper neural activity."

(Image: Fotolia)