Posts tagged neurons
Articles and news from the latest research reports.
Scientists Pinpoint Cell Type and Brain Region Affected by Gene Mutations in Autism
A team led by UC San Francisco scientists has identified the disruption of a single type of cell – in a particular brain region and at a particular time in brain development – as a significant factor in the emergence of autism.
The finding, reported in the Nov. 21 issue of Cell, was made with techniques developed only within the last few years, and marks a turning point in autism spectrum disorders (ASDs) research.
Large-scale gene sequencing projects are revealing hundreds of autism-associated genes, and scientists have begun to leverage new methods to decipher how mutations in these disparate genes might converge to exert their effects in the developing brain.
The new research focused on just nine genes, those most strongly associated with autism in recent sequencing studies, and investigated their effects using precise maps of gene expression during human brain development.
Led by Jeremy Willsey, a graduate student in the laboratory of senior author Matthew W. State, MD, PhD, chair of the UCSF Department of Psychiatry, the group showed that this set of genes contributes to abnormalities in brain cells known as cortical projection neurons in the deepest layers of the developing prefrontal cortex during the middle period of fetal development.
Though a range of developmental scenarios in multiple brain regions are surely at work in ASDs, the ability to place these specific genetic mutations in one specific set of cells – among hundreds of cell types in the brain, and at a specific time point in human development – is a critical step in beginning to understand how autism comes about.
“Given the small subset of autism genes we studied, I had no expectation that we would see the degree of spatiotemporal convergence that we saw,” said State, an international authority on the genetics of neurodevelopmental disorders.
“This strongly suggests that though there are hundreds of autism risk genes, the number of underlying biological mechanisms will be far fewer. This is a very important clue to advance precision medicine for autism toward the development of personalized and targeted therapies.”
Complex Genetic Architecture of ASDs
ASDs, marked by deficits in social interaction and language development, as well as by repetitive behaviors and/or restricted interests, are known to have a strong genetic component.
But these disorders are exceedingly complex, with considerable variation in symptoms and severity, and there does not appear to be a small collection of mutations widely shared among all affected individuals that always lead to ASDs.
Instead, with the rise of new sequencing methods over the past several years, researchers have identified many rare, non-inherited, spontaneous mutations that appear to act in combination with other genetic and non-genetic factors to cause ASDs. According to some estimates, mutations in as many as 1,000 genes could play a role in the development of these disorders.
While researchers have been heartened that specific genes are now rapidly being tied to ASDs, State said the complex genetic architecture of ASDs is also proving to be challenging.
“If there are 1,000 genes in the population that can contribute to risk in varying degrees and each has multiple developmental functions, it is not immediately obvious how to move forward to determine what is specifically related to autism. And without this, it is very difficult to think about how to develop new and better medications,” he said.
Focusing on Nine Genes
To begin to grapple with those questions, the researchers involved in the new study first selected as “seeds” the nine genes that have been most strongly tied to ASDs in recent sequencing research from their labs and others.
Importantly, these nine genes were chosen solely because of the statistical evidence for a relationship to ASDs, not because their function was known to fit a theory of the cause of ASDs. “We asked where the leads take us, without any preconceived idea about where they should take us,” said State.
The team then took advantage of BrainSpan, a digital atlas assembled by a large research consortium, including co-author Nenad Šestan, MD, PhD, and colleagues at Yale School of Medicine. Based on donated brain specimens, BrainSpan documents how and where genes are expressed in the human brain over the lifespan.
The scientists, who also included Bernie Devlin, PhD, of The University of Pittsburgh School of Medicine; Kathryn Roeder, PhD, of Carnegie-Mellon University; and James Noonan, PhD, of Yale School of Medicine, used this tool to investigate when and where the nine seed genes join up with other genes in “co-expression networks” to wire up the brain or maintain its function.
The resulting co-expression networks were then tested using a variety of pre-determined criteria to see if they showed additional evidence of being related to ASDs. Once this link was established, the authors were then able to home in on where in the brain and when in development these networks were localizing, which proved to be in cortical projection neurons found in layers 5 and 6 of the prefrontal cortex, and during a time period spanning 10 to 24 weeks after conception. Notably, a study using different methods and published in the same issue of Cell also implicates cortical projection neurons in ASDs.
“To see these gene networks as highly connected as they are, as convergent as they are, is quite amazing,” said Willsey “An important outcome of this study is that for the first time it gives us the ability to design targeted experiments based on a strong idea about when and where in the brain we should be looking at specific genes with specific mutations.”
In addition to its importance in ASD research, State sees the new work as a reflection of the tremendous value of “big science” efforts, such as large-scale collaborative genomic studies and the creation of foundational resources such as the BrainSpan atlas.
“We couldn’t have done this even two years ago,” State said, “because we didn’t have the key ingredients: a set of unbiased autism genes that we have confidence in, and a map of the landscape of the developing human brain. This work combines large-scale ‘-omics’ data sets to pivot into a deeper understanding of the relationship between complex genetics and biology.”
Study finds altered brain connections in epilepsy patients
Patients with the most common form of focal epilepsy have widespread, abnormal connections in their brains that could provide clues toward diagnosis and treatment, according to a new study published online in the journal Radiology.
(Image: MP-RAGE volumes are segmented into 83 ROIs, which are further parcellated into 1000 cortical and 15 subcortical ROIs. Whole-brain white matter tractography is performed after voxelwise tensor calculation, and the density of fibers that connect each pair of cortical ROIs is used to calculate structural connectivity. T1w = T1-weighted. Credit: Courtesy of Radiology and RSNA)
Temporal lobe epilepsy is characterized by seizures emanating from the temporal lobes, which sit on each side of the brain just above the ear. Previously, experts believed that the condition was related to isolated injuries of structures within the temporal lobe, like the hippocampus. But recent research has implicated the default mode network (DMN), the set of brain regions activated during task-free introspection and deactivated during goal-directed behavior. The DMN consists of several hubs that are more active during the resting state.
To learn more, researchers performed diffusion tensor imaging, a type of MRI that tracks the movement, or diffusion, of water in the brain’s white matter, the nerve fibers that transmit signals throughout the brain. The study group consisted of 24 patients with left temporal lobe epilepsy who were slated for surgery to remove the site from where their seizures emanated. The researchers compared them with 24 healthy controls using an MRI protocol dedicated to finding white matter tracts with diffusion imaging at high resolution. The data was analyzed with a new technique that identifies and quantifies structural connections in the brain.
Patients with left temporal lobe epilepsy exhibited a decrease in long-range connectivity of 22 percent to 45 percent among areas of the DMN when compared with the healthy controls.
"Using diffusion MRI, we found alterations in the structural connectivity beyond the medial temporal lobe, especially in the default mode network," said Steven M. Stufflebeam, M.D., from the Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital in Boston.
In addition to reduced long-range connectivity, the epileptic patients had an 85 percent to 270 percent increase in local connectivity within and beyond the DMN. The researchers believe this may be an adaptation to the loss of the long-range connections.
"The increase in local connections could represent a maladaptive mechanism by which overall neural connectivity is maintained despite the loss of connections through important hub areas," Dr. Stufflebeam said.
The results are supported by prior functional MRI studies that have shown decreased functional connectivity in DMN areas in temporal lobe epilepsy. Researchers are not certain if the structural changes cause the functional changes, or vice versa.
"It’s probably a breakdown of myelin, which is the insulation of neurons, causing a slowdown in the propagation of information, but we don’t know for sure," Dr. Stufflebeam said.
Dr. Stufflebeam and colleagues plan to continue their research, using structural and functional MRI with electroencephalography and magnetoencephalography to track diffusion changes and look at real-time brain activity.
"Our long-term goal is to see if we can we predict from diffusion studies who will respond to surgery and who will not," he said.
(Source: eurekalert.org)
Glowing Worms Illuminate Roots of Behavior
A research team at Worcester Polytechnic Institute (WPI) and The Rockefeller University in New York has developed a novel system to image brain activity in multiple awake and unconstrained worms. The technology, which makes it possible to study the genetics and neural circuitry associated with animal behavior, can also be used as a high-throughput screening tool for drug development targeting autism, anxiety, depression, schizophrenia, and other brain disorders.
Image: Neurons in the worms (marked by arrows) glow as the animals sense attractive odors.
The team details their technology and early results in the paper “High-throughput imaging of neuronal activity in Caenorhabditis elegans,” published on-line in advance of print by the journal Proceedings of the National Academy of Sciences.
"One of our major objectives is to understand the neural signals that direct behavior—how sensory information is processed through a network of neurons leading to specific decisions and responses," said Dirk Albrecht, PhD, assistant professor of biomedical engineering at WPI and senior author of the paper. Albrecht led the research team both at WPI and at Rockefeller, where he served previously as a postdoctoral researcher in the lab of Cori Bargmann, PhD, a Howard Hughes Medical Institute Investigator and a co-author of the new paper.
To study neuronal activity, Albrecht’s lab uses the tiny worm Caenorhabditis elegans (C. elegans), a nematode found in many environments around the world. A typical adult C. elegans is just 1 millimeter long and has 969 cells, of which 302 are neurons. Despite its small size, the worm is a complex organism able to do all of the things animals must do to survive. It can move, eat, mate, and process environmental cues that help it forage for food or react to threats. As a bonus for researchers, C.elegans is transparent. By using various imaging technologies, including optical microscopes, one can literally see into the worm and watch physiological processes in real time.
Numerous studies have been done by “worm labs” around the world exploring various neurological processes in C. elegans. These have typically been done using one worm at a time, with the animal’s body fixed in place on a slide. In their new paper, Albrecht’s team details how they imaged, recorded, and analyzed specific neurons in multiple animals as they wormed their way around a custom-designed microfluidic array, called an arena, where they were exposed to favorable or hostile sensory cues.
Specifically, the team engineered a strain of worms with neurons near the head that would glow when they sensed food odors. In experiments involving up to 23 worms at a time, Albrecht’s team infused pulses of attractive or repulsive odors into the arena and watched how the worms reacted. In general, the worms moved towards the positive odors and away from the negative odors, but the behaviors did not always follow this pattern. “We were able to show that the sensory neurons responded to the odors similarly in all the animals, but their behavioral responses differed significantly,” Albrecht said. “These animals are genetically identical, and they were raised together in the same environment, so where do their different choices come from?”
In addition to watching the head neurons light up as they picked up odor cues, the new system can trace signaling through “interneurons.” These are pathways that connect external sensors to the rest of the network (the “worm brain”) and send signals to muscle cells that adjust the worm’s movement based on the cues. Numerous brain disorders in people are believed to arise when neural networks malfunction. In some cases the malfunction is dramatic overreaction to a routine stimulus, while in others it is a lack of appropriate reactions to important cues. Since C. elegans and humans share many of the same genes, discovering genetic causes for differing neuronal responses in worms could be applicable to human physiology. Experimental compounds designed to modulate the action of nerve cells and neuronal networks could be tested first on worms using Albrecht’s new system. The compounds would be infused in the worm arena, along with other stimuli, and the reaction of the worms’ nervous systems could be imaged and analyzed.
"The basis of our work is to combine biomedical engineering and neuroscience to answer some of these fundamental questions and hopefully gain insight that would be beneficial for understanding and eventually treating human disorders," Albrecht said.
(Source: wpi.edu)
Social symptoms in autistic children may be caused by hyper-connected neurons
The brains of children with autism show more connections than the brains of typically developing children do. What’s more, the brains of individuals with the most severe social symptoms are also the most hyper-connected. The findings reported in two independent studies published in the Cell Press journal Cell Reports (1, 2) on November 7th are challenge the prevailing notion in the field that autistic brains are lacking in neural connections.
The findings could lead to new treatment strategies and new ways to detect autism early, the researchers say. Autism spectrum disorder is a neurodevelopmental condition affecting nearly 1 in 88 children.
"Our study addresses one of the hottest open questions in autism research," said Kaustubh Supekar of Stanford University School of Medicine of his and his colleague Vinod Menon’s study aimed at characterizing whole-brain connectivity in children. "Using one of the largest and most heterogeneous pediatric functional neuroimaging datasets to date, we demonstrate that the brains of children with autism are hyper-connected in ways that are related to the severity of social impairment exhibited by these children."
In the second Cell Reports study, Ralph-Axel Müller and colleagues at San Diego State University focused specifically on neighboring brain regions to find an atypical increase in connections in adolescents with a diagnosis of autism spectrum disorder. That over-connection, which his team observed particularly in the regions of the brain that control vision, was also linked to symptom severity.
"Our findings support the special status of the visual system in children with heavier symptom load," Müller said, noting that all of the participants in his study were considered "high-functioning" with IQs above 70. He says measures of local connectivity in the cortex might be used as an aid to diagnosis, which today is based purely on behavioral criteria.
For Supekar and Menon, these new views of the autistic brain raise the intriguing possibility that epilepsy drugs might be used to treat autism.
"Our findings suggest that the imbalance of excitation and inhibition in the local brain circuits could engender cognitive and behavioral deficits observed in autism," Menon said. That imbalance is a hallmark of epilepsy as well, which might explain why children with autism so often suffer with epilepsy too.
"Drawing from these observations, it might not be too far fetched to speculate that the existing drugs used to treat epilepsy may be potentially useful in treating autism," Supekar said.
(Source: eurekalert.org)
While eating lunch, you notice an insect buzzing around your plate. Its color and motion could both influence how you respond. If the insect was yellow and black you might decide it was a bee and move away. Conversely, you might simply be annoyed at the buzzing motion and shoo the insect away. You perceive both color and motion, and decide based on the circumstances. Our brains make such contextual decisions in a heartbeat. The mystery is how.
In an article published Nov. 7 in the journal Nature, a team of Stanford neuroscientists and engineers delve into this decision-making process and report some findings that confound the conventional wisdom.
Until now, neuroscientists have believed that decisions of this sort involved two steps: one group of neurons that performed a gating function to ascertain whether motion or color was most relevant to the situation and a second group of neurons that considered only the sensory input relevant to making a decision under the circumstances.
But in a study that combined brain recordings from trained monkeys and a sophisticated computer model based on that biological data, Stanford neuroscientist William Newsome and three co-authors discovered that the entire decision-making process may occur in a localized region of the prefrontal cortex.
In this region of the brain, located in the frontal lobes just behind the forehead, they found that color and motion signals converged in a specific circuit of neurons. Based on their experimental evidence and computer simulations, the scientists hypothesized that these neurons act together to make two snap judgments: whether color or motion is the most relevant sensory input in the current context and what action to take.
“We were quite surprised,” said Newsome, the Harman Family Provostial Professor at the Stanford School of Medicine and lead author.
He and first author Valerio Mante, a former Stanford neurobiologist now at the University of Zurich and the Swiss Federal Institute of Technology, had begun the experiment expecting to find that the irrelevant signal, whether color or motion, would be gated out of the circuit long before the decision-making neurons went into action.
“What we saw instead was this complicated mix of signals that we could measure but whose meaning and underlying mechanism we couldn’t understand,” Newsome said. “These signals held information about the color and motion of the stimulus, which stimulus dimension was most relevant and the decision that the monkeys made. But the signals were profoundly mixed up at the single neuron level. We decided there was a lot more we needed to learn about these neurons and that the key to unlocking the secret might lie in a population level analysis of the circuit activity.”
To solve this brain puzzle the neurobiologists began a cross-disciplinary collaboration with Krishna Shenoy, a professor of electrical engineering at Stanford, and David Sussillo, co-first author on the paper and a postdoctoral scholar in Shenoy’s lab.
Sussillo created a software model to simulate how these neurons worked. The idea was to build a model sophisticated enough to mimic the decision-making process but easier to study than taking repeated electrical readings from a brain.
The general model architecture they used is called a recurrent neural network: a set of software modules designed to accept inputs and perform tasks similar to how biological neurons operate. The scientists designed this artificial neural network using computational techniques that enabled the software model to make itself more proficient at decision-making over time.
“We challenged the artificial system to solve a problem analogous to the one given to the monkeys,” Sussillo explained. “But we didn’t tell the neural network how to solve the problem.”
As a result, once the artificial network learned to solve the task, the scientists could study the model to develop inferences about how the biological neurons might be working.
The entire process was grounded in the biological experiments.
The neuroscientists trained two macaque monkeys to view a random-dot visual display that had two different features – motion and color. For any given presentation, the dots could move to the right or left, and the color could be red or green. The monkeys were taught to use sideways glances to answer two different questions depending on the currently instructed “rule” or context. Were there more red or green dots (ignore the motion)? Or were the dots moving to the left or right (ignore the color)?
Eye-tracking instruments recorded the glances, or saccades, that the monkeys used to register their responses. Their answers were correlated with recordings of neuronal activity taken directly from an area in the prefrontal cortex known to control saccadic eye movements.
The neuroscientists collected 1,402 such experimental measurements. Each time the monkeys were asked one or the other question. The idea was to obtain brain recordings at the moment when the monkeys saw a visual cue that established the context (either the red/green or left/right question) and what decision the animal made regarding color or direction of motion.
It was the puzzling mish-mash of signals in the brain recordings from these experiments that prompted the scientists to build the recurrent neural network as a way to rerun the experiment, in a simulated way, time and time again.
As the four researchers became confident that their software simulations accurately mirrored the actual biological behavior, they studied the model to learn exactly how it solved the task. This allowed them to form a hypothesis about what was occurring in that patch of neurons in the prefrontal cortex where perception and decision occurred.
“The idea is really very simple,” Sussillo explained.
Their hypothesis revolves around two mathematical concepts: a line attractor and a selection vector.
The entire group of neurons being studied received sensory data about both the color and the motion of the dots.
The line attractor is a mathematical representation for the amount of information that this group of neurons was getting about either of the relevant inputs, color or motion.
The selection vector represented how the model responded when the experimenters flashed one of the two questions: red or green, left or right?
What the model showed was that when the question pertained to color, the selection vector directed the artificial neurons to accept color information while ignoring the irrelevant motion information. Color data became the line attractor. After a split second these neurons registered a decision, choosing the red or green answer based on the data they were supplied.
If question was about motion, the selection vector directed motion information to the line attractor, and the artificial neurons chose left or right.
“The amazing part is that a single neuronal circuit is doing all of this,” Sussillo says. “If our model is correct, then almost all neurons in this biological circuit appear to be contributing to almost all parts of the information selection and decision-making mechanism.”
Newsome put it like this: “We think that all of these neurons are interested in everything that’s going on, but they’re interested to different degrees. They’re multitasking like crazy.”
Other researchers who are aware of the work but were not directly involved are commenting on the paper.
“This is a spectacular example of excellent experimentation combined with clever data analysis and creative theoretical modeling,” said Larry Abbott, Co-Director of the Center for Theoretical Neuroscience and the William Bloor Professor, Neuroscience, Physiology & Cellular Biophysics, Biological Sciences at Columbia University.
Christopher Harvey, a professor of neurobiology at Harvard Medical School, said the paper “provides major new hypotheses about the inner-workings of the prefrontal cortex, which is a brain area that has frequently been identified as significant for higher cognitive processes but whose mechanistic functioning has remained mysterious.”
The Stanford scientists are now designing a new biological experiment to ascertain whether the interplay between selection vector and line attractor, which they deduced from their software model, can be measured in actual brain signals.
“The model predicts a very specific type of neural activity under very specific circumstances,” Sussillo said. “If we can stimulate the prefrontal cortex in the right way, and then measure this activity, we will have gone a long way to proving that the model mechanism is indeed what is happening in the biological circuit.”
Scientists identify clue to regrowing nerve cells
Researchers at Washington University School of Medicine in St. Louis have identified a chain reaction that triggers the regrowth of some damaged nerve cell branches, a discovery that one day may help improve treatments for nerve injuries that can cause loss of sensation or paralysis.
The scientists also showed that nerve cells in the brain and spinal cord are missing a link in this chain reaction. The link, a protein called HDAC5, may help explain why these cells are unlikely to regrow lost branches on their own. The new research suggests that activating HDAC5 in the central nervous system may turn on regeneration of nerve cell branches in this region, where injuries often cause lasting paralysis.
“We knew several genes that contribute to the regrowth of these nerve cell branches, which are called axons, but until now we didn’t know what activated the expression of these genes and, hence, the repair process,” said senior author Valeria Cavalli, PhD, assistant professor of neurobiology. “This puts us a step closer to one day being able to develop treatments that enhance axon regrowth.”
The research appears Nov. 7 in the journal Cell.
Axons are the branches of nerve cells that send messages. They typically are much longer and more vulnerable to injury than dendrites, the branches that receive messages.
In the peripheral nervous system — the network of nerve cells outside the brain and spinal column — cells sometimes naturally regenerate damaged axons. But in the central nervous system, comprised of the brain and spinal cord, injured nerve cells typically do not replace lost axons.
Working with peripheral nervous system cells grown in the laboratory, Yongcheol Cho, PhD, a postdoctoral research associate in Cavalli’s laboratory, severed the cells’ axons. He and his colleagues learned that this causes a surge of calcium to travel backward along the axon to the body of the cell. The surge is the first step in a series of reactions that activate axon repair mechanisms.
In peripheral nerve cells, one of the most important steps in this chain reaction is the release of a protein, HDAC5, from the cell nucleus, the central compartment where DNA is kept. The researchers learned that after leaving the nucleus, HDAC5 turns on a number of genes involved in the regrowth process. HDAC5 also travels to the site of the injury to assist in the creation of microtubules, rigid tubes that act as support structures for the cell and help establish the structure of the replacement axon.
When the researchers genetically modified the HDAC5 gene to keep its protein trapped in the nuclei of peripheral nerve cells, axons did not regenerate in cell cultures. The scientists also showed they could encourage axon regrowth in cell cultures and in animals by dosing the cells with drugs that made it easier for HDAC5 to leave the nucleus.
When the scientists looked for the same chain reaction in central nervous system cells, they found that HDAC5 never left the nuclei of the cells and did not travel to the site of the injury. They believe that failure to get this essential player out of the nucleus may be one of the most important reasons why central nervous system cells do not regenerate axons.
“This gives us the hope that if we can find ways to manipulate this system in brain and spinal cord neurons, we can help the cells of the central nervous system regrow lost branches,” Cavalli said. “We’re working on that now.”
Monkeys Use Minds to Move Two Virtual Arms
In a study led by Duke researchers, monkeys have learned to control the movement of both arms on an avatar using just their brain activity.
The findings, published Nov. 6, 2013, in the journal Science Translational Medicine, advance efforts to develop bilateral movement in brain-controlled prosthetic devices for severely paralyzed patients.
To enable the monkeys to control two virtual arms, researchers recorded nearly 500 neurons from multiple areas in both cerebral hemispheres of the animals’ brains, the largest number of neurons recorded and reported to date
Millions of people worldwide suffer from sensory and motor deficits caused by spinal cord injuries. Researchers are working to develop tools to help restore their mobility and sense of touch by connecting their brains with assistive devices. The brain-machine interface approach, pioneered at the Duke University Center for Neuroengineering in the early 2000s, holds promise for reaching this goal. However, until now brain-machine interfaces could only control a single prosthetic limb.
“Bimanual movements in our daily activities — from typing on a keyboard to opening a can — are critically important,” said senior author Miguel Nicolelis, M.D., Ph.D., professor of neurobiology at Duke University School of Medicine. “Future brain-machine interfaces aimed at restoring mobility in humans will have to incorporate multiple limbs to greatly benefit severely paralyzed patients.”
Nicolelis and his colleagues studied large-scale cortical recordings to see if they could provide sufficient signals to brain-machine interfaces to accurately control bimanual movements.
The monkeys were trained in a virtual environment within which they viewed realistic avatar arms on a screen and were encouraged to place their virtual hands on specific targets in a bimanual motor task. The monkeys first learned to control the avatar arms using a pair of joysticks, but were able to learn to use just their brain activity to move both avatar arms without moving their own arms.
As the animals’ performance in controlling both virtual arms improved over time, the researchers observed widespread plasticity in cortical areas of their brains. These results suggest that the monkeys’ brains may incorporate the avatar arms into their internal image of their bodies, a finding recently reported by the same researchers in the journal Proceedings of the National Academy of Sciences.
The researchers also found that cortical regions showed specific patterns of neuronal electrical activity during bimanual movements that differed from the neuronal activity produced for moving each arm separately.
The study suggests that very large neuronal ensembles — not single neurons — define the underlying physiological unit of normal motor functions. Small neuronal samples of the cortex may be insufficient to control complex motor behaviors using a brain-machine interface.
“When we looked at the properties of individual neurons, or of whole populations of cortical cells, we noticed that simply summing up the neuronal activity correlated to movements of the right and left arms did not allow us to predict what the same individual neurons or neuronal populations would do when both arms were engaged together in a bimanual task,” Nicolelis said. “This finding points to an emergent brain property — a non-linear summation — for when both hands are engaged at once.”
Nicolelis is incorporating the study’s findings into the Walk Again Project, an international collaboration working to build a brain-controlled neuroprosthetic device. The Walk Again Project plans to demonstrate its first brain-controlled exoskeleton, which is currently being developed, during the opening ceremony of the 2014 FIFA World Cup.
Visual representations improved by reducing noise
Neuroscientist Suresh Krishna from the German Primate Center (DPZ) in cooperation with Annegret Falkner and Michael Goldberg at Columbia University, New York has revealed how the activity of neurons in an important area of the rhesus macaque’s brain becomes less variable when they represent important visual information during an eye movement task. This reduction in variability can improve the perceptual strength of attended or relevant aspects in a visual scene, and is enhanced when the animals are more motivated to perform the task.
Humans may see the same object again and again, but their brain response will be different each time, a phenomenon called neuronal noise. The same is true for rhesus macaques, which have a visual system very similar to that of humans. This variability often limits our ability to see a dim object or hear a faint sound. On the other hand, we benefit from variable responses as they are considered an essential part of the exploration stage of learning and for generating unpredictability during competitive interactions.
Despite this importance, brain variability is poorly understood. Neuroscientists Suresh Krishna of the DPZ and his colleagues Annegret Falkner and Michael Goldberg at Columbia University in New York examined the responses of neurons in the monkey brain’s lateral intraparietal area (LIP) while the monkey planned eye movements to spots of light at different locations on a computer screen. LIP is an area in the brain that is crucial for visual attention and for actively exploring visual scenes. To measure the activity of single LIP neurons, the scientists inserted electrodes thinner than a human hair into the monkey’s brain and recorded the neurons’ electrical activity. Because the brain is not pain-sensitive, this insertion of electrodes is painless for the animal.
Suresh Krishna and his colleagues could show how the activity of LIP neurons becomes less variable when the macaque performs a task and plans an eye movement. The reduction in variability was particularly strong where the monkey was planning to look and when the monkey was highly motivated to perform the task. This creation of a valley of reduced variability centered on relevant and interesting aspects of a visual scene may help the brain to filter the most important aspects from the sensory information delivered by the eye. The scientists developed a simple mathematical model that captures the patterns in the data and may also be a useful framework for the analysis of other brain areas.
"Our study represents one of the most detailed descriptions of neuronal variability in the brain. It offers important insights into fascinating brain functions as diverse as the focusing of visual attention and the control of eye movements during active viewing of visual scenes. The brain’s valley of variability that we discovered may help humans and animals to interact with their complex environment.", Suresh Krishna comments on the findings.
Antidepressant drug induces a juvenile-like state in neurons of the prefrontal cortex
For long, brain development and maturation has been thought to be a one-way process, in which plasticity diminishes with age. The possibility that the adult brain can revert to a younger state and regain plasticity has not been considered, often. In a paper appearing on November 4 in the online open-access journal Molecular Brain, Dr. Tsuyoshi Miyakawa and his colleagues from Fujita Health University show that chronic administration of one of the most widely used antidepressants fluoxetine (FLX, which is also known by trade names like Prozac, Sarafem, and Fontex and is a selective serotonin reuptake inhibitor) can induce a juvenile-like state in specific types of neurons in the prefrontal cortex of adult mice.
In their study, FLX-treated adult mice showed reduced expression of parvalbumin and perineuronal nets, which are molecular markers for maturation and are expressed in a certain group of mature neurons in adults, and increased expression of an immature marker, which typically appears in developing juvenile brains, in the prefrontal cortex. These findings suggest the possibility that certain types of adult neurons in the prefrontal cortex can partially regain a youth-like state; the authors termed this as induced-youth or iYouth. These researchers as well as other groups had previously reported similar effects of FLX in the hippocampal dentate gyrus, basolateral amygdala, and visual cortex, which were associated with increased neural plasticity in certain types of neurons. This study is the first to report on “iYouth” in the prefrontal cortex, which is the brain region critically involved in functions such as working memory, decision-making, personality expression, and social behavior, as well as in psychiatric disorders related to deficits in these functions.
Network dysfunction in the prefrontal cortex and limbic system, including the hippocampus and amygdala, is known to be involved in the pathophysiology of depressive disorders. Reversion to a youth-like state may mediate some of the therapeutic effects of FLX by restoring neural plasticity in these regions. On the other hand, some non-preferable aspects of FLX-induced pseudo-youth may play a role in certain behavioral effects associated with FLX treatment, such as aggression, violence, and psychosis, which have recently received attention as adverse effects of FLX. Interestingly, expression of the same molecular markers of maturation, as discussed in this study, has been reported to be decreased in the prefrontal cortex of postmortem brains of patients with schizophrenia. This raises the possibility that some of FLX’s adverse effects may be attributable to iYouth in the same type of neurons in this region. Currently, basic knowledge on this is lacking, and there are several unanswered questions like: What are the molecular and cellular mechanisms underlying iYouth? What are the differences between actual youth and iYouth? Is iYouth good or bad? Future studies to answer these questions could potentially revolutionize the prevention and/or treatment of various neuropsychiatric disorders and aid in improving the quality of life for an aging population.
(Source: eurekalert.org)
Learning and memory: How neurons activate PP1
A study in The Journal of Cell Biology describes how neurons activate the protein PP1, providing key insights into the biology of learning and memory.
PP1 is known to be a key regulator of synaptic plasticity, the phenomenon in which neurons remodel their synaptic connections in order to store and relay information—the foundation of learning and memory. But how PP1 is controlled has been unclear. Now, a team led by researchers from the LSU Health Science Center describes several mechanisms for PP1 regulation that close some major gaps in our understanding of its role in neuronal signaling.
Among the novel findings, the researchers describe how the neurotransmitter NMDA leads to activation of PP1. They show that, when NMDA activates neuronal synapses, it switches off an enzyme, Cdk5, that would otherwise inhibit PP1. This allows PP1 to activate itself and promote synaptic remodeling. In addition, the researchers suggest that, despite its name, a regulatory protein called inhibitor-2 helps promote PP1 activity in neurons. Together, these findings significantly extend our understanding of how PP1 is regulated in the context of synaptic plasticity.
(Source: eurekalert.org)