Posts tagged learning
Articles and news from the latest research reports.
Neurological Researchers Find Fat May Be Linked to Memory Loss
Although problems with memory become increasingly common as people age, in some persons, memories last long time, even a life time. On the other hand, some people experience milder to substantial memory problems even at an earlier age.
Although there are several risk factors of dementia, abnormal fat metabolism has been known to pose a risk for memory and learning. People with high amounts of abdominal fat in their middle age are 3.6 times as likely to develop memory loss and dementia later in their life.
Neurological scientists at the Rush University Medical Center in collaboration with the National Institutes of Health have discovered that same protein that controls fat metabolism in the liver resides in the memory center of the brain (hippocampus) and controls memory and learning.
Results from the study funded by the Alzheimer’s Association and the National Institutes of Health were recently published in Cell Reports.
“We need to better understand how fat is connected to memory and learning so that we can develop effective approach to protect memory and learning,” said Kalipada Pahan, PhD, the Floyd A. Davis professor of neurology at Rush University Medical Center.
The liver is the body’s major fat metabolizing organ. Peroxisome proliferator-activated receptor alpha (PPARalpha) is known to control fat metabolism in the liver. Accordingly, PPARalpha is highly expressed in the liver.
“We are surprised to find high level of PPARalpha in the hippocampus of animal models,” said Pahan.
“While PPARalpha deficient mice are poor in learning and memory, injection of PPARα to the hippocampus of PPARalpha deficient mice improves learning and memory,” said Pahan.
Since PPARalpha directly controls fat metabolism, people with abdominal fat levels have depleted PPARalpha in the liver and abnormal lipid metabolism. At first, these individuals lose PPARalpha from the liver and then eventually from the whole body including the brain. Therefore, abdominal fat is an early indication of some kind of dementia later in life, according to Pahan.
By bone marrow chimera technique, researchers were able to create some mice having normal PPARalpha in the liver and depleted PPARalpha in the brain. These mice were poor in memory and learning. On the other hand, mice that have normal PPARalpha in the brain and depleted PPARalpha in the liver showed normal memory.
“Our study indicates that people may suffer from memory-related problems only when they lose PPARalpha in the hippocampus”, said Pahan.
CREB (cyclic AMP response element-binding protein) is called the master regulator of memory as it controls different memory-related proteins. “Our study shows that PPARalpha directly stimulates CREB and thereby increases memory-related proteins”, said Pahan.
“Further research must be conducted to see how we could potentially maintain normal PPARalpha in the brain in order to be resistant to memory loss”, said Pahan.
(Source: rush.edu)
Enigmatic Neurons Help Flies Get Oriented
Neurons deep in the fly’s brain tune in to some of the same basic visual features that neurons in bigger animals such as humans pick out in their surroundings. The new research is an important milestone toward understanding how the fly brain extracts relevant information about a visual scene to guide behavior.
As a tiny fruit fly navigates through its environment, it relies on visual landmarks to orient itself. Now, researchers at the Howard Hughes Medical Institute’s Janelia Farm Research Campus have identified neurons deep in the fly’s brain that tune in to some of the same basic visual features that neurons in bigger animals such as humans pick out in their surroundings. The new research is an important milestone toward understanding how the fly brain extracts relevant information about a visual scene to guide behavior.
In Vivek Jayaraman’s lab at Janelia, researchers are studying fly neural circuits with the goal of understanding fundamental principles of information processing. “Our hope is that over time we will get a clear picture of the neural transformations and algorithms involved in creating actions from sensory and motor information,” Vivek says. In a study published October 9, 2013, in the journal Nature, Vivek and postdoctoral researcher Johannes Seelig report on visual representations in a region of the fly brain thought to be important for visual learning.
Researchers have gathered compelling evidence that fruit flies recognize and remember visual features in their environment. Flies can use that information to seek out safe spaces or to avoid uncomfortable ones. Genetic studies have indicated that a region deep in the fly brain called the central complex is critical for these behaviors.
The central complex is found in the brains of insects and some crustaceans. “It’s not purely involved in visual learning, and is quite likely to be broadly important for sensory-motor integration in all these critters,” Vivek says, noting that in butterflies and locusts, the central complex may facilitate the use of polarized light for navigation during migration. Also, studies in cockroaches have found that it is important for turning in response to antennal touch. But in flies, no one had yet examined the activity of the neurons in the central complex to characterize their role. “It really was quite a mystery what was going on in this part of the fly brain,” Seelig says, adding that this study is only one step on a long road.
Technical limitations had prevented researchers from measuring neuronal activity in the fly’s central complex, where neurons are far smaller than they are in larger insects. Available techniques required flies to be immobilized, so scientists were limited to studying parts of the nervous system that detected sensory information, rather than those that processed that information or converted it into motor activity. But in 2010, Seelig and colleagues in Vivek’s lab at Janelia developed a method that enabled them to peer into the interior of a fly’s brain with a two-photon microscope, while the insect maintained the freedom to walk and move its wings. The microscope can detect genetically encoded proteins that light up when a nerve cell fires, due to the surge of calcium ions that accompanies a nerve impulse. “Once we had these tools, we really wanted to apply them to this central brain area,” Seelig says.
Using genetically modified strains of flies, Vivek and Seelig focused their experiments on specific classes of neurons and collected more comprehensive data about the activity of those populations than had been done in other species. They chose to zero in on a class of neurons known as ring neurons, on which the dendrites—the branching structures that connect to neighboring cells—were densely concentrated in specific spots within a region neighboring the central complex.
To test the ring neurons’ response to visual stimuli, Seelig placed the flies into a small virtual reality arena in which the flies could be presented with simple patterns of light. By monitoring the calcium-indicating dyes in the cells, Seelig could visualize nerve activity as each fly was exposed to different stimuli.
The researchers found that each neuron responded to visual stimuli in specific regions of the fly’s field of view. “Each cell seemed to have its receptive field in a slightly different area of that space,” Vivek explains. Further, they found that the orientation of the patterns that they projected onto the walls of the arena influenced the ring cells’ response: for example, vertical bars elicited a stronger response than horizontal bars for most cells.
Flies have an innate tendency to walk or fly toward vertically-oriented stimuli, but Vivek and Seelig were nonetheless surprised by the ring neurons’ strong bias towards detecting such patterns. Further, Seelig says, this preference for specific orientations parallels what others have found in larger animals. Neurons in the primary visual cortex of mammalian brains known as simple cells function similarly—identifying basic visual patterns and being tuned to their orientation. “A wide range of visual animals seem to use the same basic feature set when they break down the visual scene,” Vivek says, explaining that in humans, such simple features are combined by later brain regions into increasingly complex ones to eventually produce representations for faces.
He says it is not clear whether fruit flies reassemble the features in their visual field in the same way, or whether basic representations are instead converted directly into guidance for actions. “It’s an open question how complex a shape a fly needs to recognize and respond to,” he says.
The scientists also found that the ring neurons responded similarly to the visual environment regardless of whether the flies were stationary or walking. Flying diminished the response somewhat, but overall, Seelig says, visual patterns influenced the neurons’ activity far more than the insects’ behavior. “These particular neurons seem to filter out visual features, then send that information to other parts of the central complex that may transform that information into a behavioral signal. So this may be one of the major entry points for visual information to the region,” says Seelig.
Determining what happens next to the information received by ring neurons is an important question for Vivek and Seelig, who say they will expand their studies by testing the activity of other neurons in the central complex. “By marching through these networks, we hope to begin to understand how sensory information is integrated to make motor decisions,” Vivek explains.
To predict, perchance to update: Neural responses to the unexpected
Among the brain’s many functions is the use of predictive models to processing expected stimuli or actions. In such a model, we experience surprise when presented with an unexpected stimulus – that is, one which the model evaluates as having a low probability of occurrence. Interestingly, there can be two distinct – but often experimentally correlated – responses to a surprising event: reallocating additional neural resources to reprogram actions, and updating the predictive model to account for the new environmental stimulus. Recently, scientists at Oxford University used brain imaging to identify separate brain systems involved in reprogramming and updating, and created a mathematical and neuroanatomical model of how brains adjust to environmental change, Moreover, the researchers conclude that their model may also inform models of neurological disorders, such as extinction, Balint syndrome and neglect, in which this adaptive response to surprise fails.
Research Fellow Jill X. O’Reilly discussed the research she and her colleagues conducted with Medical Xpress. “Sometimes we think of the brain as an input-output device which takes sensory information, processes it, and produces actions appropriately – but in fact, brains don’t passively ‘sit around’ waiting for sensory input,” O’Reilly explains. “Rather, they actively predict what is going to happen next, because by being prepared, they can process stimuli more efficiently.”
O’Reilly cites an important example of predictive processing, which the researchers used in their study: the control of eye movements. “You can actually only process quite a small portion of visual space accurately at any one time, which is why people tend to actively look at interesting objects,” O’Reilly tells Medical Xpress. “Parts of the brain that control eye movements – for example, the parietal cortex – are actively involved in trying to predict where visual objects that are worth looking at will occur next, in order to respond to them quickly and effectively.” Since the scientists were interested in how the brain forms predictions – such as where eye movements should be directed – they designed an experiment in which people’s expectations about where they should make eye movements were built up over time and then suddenly changed. (They did this moving the stimuli participants’ were instructed to fixate on to a different part of the computer screen.)
"However," notes O’Reilly, "we know from previous work that activity in many brain areas is evoked when people are expecting to make an eye movement to one place, and actually they have to make an eye movement to another. A lot of this brain activity has to do with reprogramming the eye movement itself, rather than learning about the changed environment. That means we needed to design an experiment in which re-planning of eye movements was sometimes accompanied by learning, and sometimes not." The researchers accomplished this by color-coding stimuli: participants knew that colorful stimuli indicated a real change in the environment, while grey stimuli were to be ignored.
To quantify how much participants learned on each trial of the experiment, the team constructed a computer participant that learned about the environment in the same way the real, human participants did. Because they could determine exactly what the computer participant knew or believed about the environment – that is, where it would need to look – on each trial, we could get mathematical measures of how surprising it found each stimulus (defined as how far the stimulus location was from where the computer participant expected it to be) and how much it learned on each trial.
Therefore, the computer participant allowed the scientists to separately measure the degree to which human participants had to respond to surprise in terms of reprogramming eye movements, and how much they learned on each trial. “We then needed to work out whether some parts of the brain were specifically involved in each of these processes,” O’Reilly continues. “To do this we used fMRI and looked for areas that increased their activity in proportion to how much the computer participant, and thereby the real participants, would need to reprogram their eye movements for each surprising stimulus – as well as the extent to which they’d have to update their predictions about future stimulus locations – on each trial.”
O’Reilly stresses that the computer participant was critical to addressing the challenges they encountered. “We had access to a complete model of what participants could know or should believe about where stimuli were expected to appear on each trial. That meant we could make very specific predictions about how much they should be surprised by certain stimuli and how much they learned from each stimulus.” The team checked these predictions by looking at behavioral measures like reaction time (participants were slower to move their eyes to surprising stimuli) and gaze dwell time (participants looked at stimuli for longer when the stimuli carried information about the possible locations of future stimuli).
O’Reilly describes how their study may inform understanding of neurological disorders in which this adjustment process fails by observing that a second saccade-sensitive region in the inferior posterior parietal cortex was activated by surprise and modulated by updating. “Some stroke victims are unable to move their eyes in order to look at stimuli that show up in their visual periphery, which turns out to be similar to the process of reprogramming to surprising stimuli in our model. In contrast,” she continues, “people with brain lesions in a slightly different brain region are able to move their eyes to look at stimuli, but seem unable to learn that stimuli could occur in some parts of space – usually towards the left of the body – even if given lots of hints and training.” Because the brain regions damaged in these two patient groups map onto the regions of parietal cortex active in the experiment’s reprogramming and updating conditions, the researchers think these two processes could be differentially affected in the two patient groups.
Moving forward, the researchers would like to test their paradigm in patients who have had strokes that damaged the different brain regions activated in their study. “We’d expect to find a difference between patients with damage in different parts of parietal cortex, such that one group might be slower to reprogram eye movements to all surprising stimuli whether these stimuli are informative about future stimulus locations or not,” O’Reilly concludes, “whereas the other group might have trouble learning that the location where stimuli are going to appear has changed.”
Drowsy Drosophila shed light on sleep and hunger
Scientists discover key function in molecule that regulates sleep, metabolism and hunger
Why does hunger keep us awake and a full belly make us tired? Why do people with sleep disorders such as insomnia often binge eat late at night? What can sleep patterns tell us about obesity?
Sleep, hunger and metabolism are closely related, but scientists are still struggling to understand how they interact. Now, Brandeis University researchers have discovered a function in a molecule in fruit flies that may provide insight into the complicated relationship between sleep and food.
In the October issue of the journal Neuron, Brandeis scientists report that sNPF, a neuropeptide long known to regulate food intake and metabolism, is also an important component in regulating and promoting sleep. When researchers activated sNPF in fruit flies, the insects fell asleep almost immediately, awaking only long enough to eat before nodding off again. The flies were so sleepy that once they found a food source, they slept right on top of it for days — like falling asleep on a giant hamburger bun and waking up long enough to take a few nibbles before falling back to sleep.
When researchers returned sNPF functions to normal, the flies resumed their normal level of activity, leaving behind their couch potato ways.
The researchers, led by professor of biology Leslie Griffith, concluded that sNPF has an important regulatory function in sleep in addition to its previously known function coordinating behaviors such as eating and metabolism.
"This paper provides a nice bridge between feeding behavior and sleep behavior with just a single molecule," says Nathan Donelson, a post doctoral fellow in Griffith’s lab and one of the study’s lead authors.
Neurons use neuropeptides to communicate a range of brain functions including learning, metabolism, memory and social behaviors. In humans, Neuropeptide Y functions similarly to sNPF and has been studied as a possible drug target for obesity treatment.
But scientists don’t fully understand how regulating neuropeptide function at specific times and in specific cells affects sleeping and eating. By studying sNPF in fruit flies, scientists can learn which cells, neurotransmitters and genes are involved in eating and sleeping; what processes turn on and inhibit the behaviors, and how sleep cells are relevant to hunger drive.
"Our paper makes a significant step into tying all these things together," says Donelson, "and that is extremely important down the road to our understanding of human health."
(Source: eurekalert.org)
The song of songbirds is a learned, complex behavior and subject to strong selective forces. However, it is difficult to tease apart the influence of the genetic background and the environment on the expression of individual variation in song. Scientists from the Max Planck Institute for Ornithology in Seewiesen in collaboration with international researchers now compared song and brain structure of parents and offspring in zebra finches that have been raised either with their genetic or foster parents. They also varied the amount of food during breeding. Remarkably, both song and the underlying brain structure had a low heritability and were strongly influenced by environmental factors.
A central topic in behavioral biology is the question, which aspects of a behavior are learned or expressed due to genetic predisposition. Today it is known that our personality and behavior are far less determined by the genetic background. Especially during development environmental factors can shape brain and behavior via so-called epigenetic effects. Thereby hormones play an important role. A shift in hormone concentrations in early life can have long lasting effects for an organism, whereas the same change in adults often may show only short-term changes. However, whether the influence of the environment has either strong or weak effects can largely depend on the individual genetic predisposition. However, it is relatively hard to discriminate the effects of the environment from that of the genes.
An attempt to tease apart these effects has been conducted by researchers from the Max Planck Institute for Ornithology in collaboration with an international team of scientists in zebra finch breeding pairs. Using partial cross-fostering the researchers exchanged half of the eggs within a nest making them to “cuckoo’s eggs”. Therefore half of the hatchlings were raised by their genetic parents, whereas the other half was raised by their foster parents. In addition they modified the availability of food by mixing the seeds with husks so that the parents had to spend more time searching for food. When the male offspring were adult at 100 days the researchers recorded their songs and analyzed the underlying neuroanatomy. This partial cross-fostering design enabled the researchers to tease apart the involvement of genotype, the rearing environment and nutritional effects to variation in song behavior and brain structure.
The results showed that heritability values were low for most song characteristics, except the number of song syllables and maximum frequency. On the other hand the common rearing environment including the song of the foster father mainly predicted the proportion of unique syllables in the songs of the sons, moreover this relationship was dependent on food availability. Even more striking results were found when the researchers investigated the brain anatomy. Heritability of brain variables was very low and strongly controlled by the environment. For example, an emergence of a clear relationship between brain mass and genotype is prevented by varying environmental quality.
This result was quite surprising as previous studies have found a high heritability of the song control system in the songbird brain, however these studies did not account for variation of the rearing environment. ”Being highly flexible in response to environmental conditions can maintain genetic variation and influences song learning and brain development” says Stefan Leitner, senior author of the study.
Did you have a good time? We know where you’ll store the memory of it!
Where do you go for a tasty bite and where the food is not so good? Where are you likely to meet an attractive partner and where you risk damage to your health? For every person – but also for animals – the information about pleasant and unpleasant experiences is of key importance. Researchers from the Nencki Institute in Warsaw discovered how and where nice memories are stored.
As shown by researchers from the Nencki Institute of Experimental Biology in Warsaw, Poland, nice memories are stored in an area of the brain known as the central nucleus of the amygdala. The results obtained by the group of Prof. Leszek Kaczmarek and Dr. Ewelina Knapska, which were published in the well-known Journal of Neuroscience show that just one protein plays the key role in the process of memorizing pleasant experiences. In the future these results may help design more effective treatment of addictions, depression and schizophrenia.
“We want our research to help us understand the relation between the mind and the brain by studying memory, which is of fundamental importance for the mind. Without memory there is no mind”, Prof. Kaczmarek explains context of the research.
Neurobiologists differentiate between many types of memory, the most basic types of which are characterized by clear duality. For example we have short and long term memories, declarative (referring to events/data) and procedural (memory of actions). Researchers from the Nencki Institute focused on another dichotomy of great importance to every animal. They focused on appetitive memory related to memories of pleasant experiences and aversive memory related to unpleasant experiences.
Experimental research on human memory often comes across a very basic problem: there are no volunteers for the experiments. No one of sound mind will agree to participate in experiments involving his or her own memory. Fortunately having a mind is not limited to humans. Many mental activities typical for humans take place also in the minds of animals. Therefore scientists from the Nencki Institute conducted their experiments on mice.
These novel experiments on memory have been conducted on mice placed in the so-called IntelliCages. In each corner of such cage two water bottles have been placed. In order to get water a mouse has to get to the corner and nose poke on a small gate of a given bottle. Depending on the type of experiment, the mouse will either get water or harmless but unpleasant puff of air on the nose. All mice in the cage have individual ID chips and therefore researchers are able to tell exactly what decisions are made by each mouse.
IntelliCages make it possible to conduct different experiments. If for example in one corner sweet water (that is an appetitive stimulus) bottles are placed, the effectiveness of spatial memory in mice can be investigated. More subtle experiments are also possible by placing only one sweet water bottle in a selected corner. Then the mouse needs to remember not only the corner where the sweet water bottle is, but also which of two bottles contains sweet water.
Twenty five years ago Nencki researchers have observed changes in the activity of a gene known as c-fos in the nervous cell nuclei during learning. One of the proteins, the production of which is regulated by a protein encoded by the c-fos gene, is the MMP-9 enzyme active outside of the cell. Researchers decided to investigate the role of MMP-9 in memorizing pleasant and unpleasant experiences. In order to do this a series of experiments was conducted on control mice and on mice either lacking this protein entirely or with its selective blocking only within the central amygdala.
The amygdala is a small structure within the cerebral hemisphere and it is located at the base of the brain, close to the hippocampus. It consists of two groups of nuclei responsible for innate and acquired emotional reactions, such as laughter or fear.
Researchers were surprised by the experiments. When placed in the IntelliCages, the control mice after three days of learning almost always chose the corner with sweet water. Mice lacking MMP-9 behaved distinctly different: they showed no preference for any of the corners. At the same time all mice equally well remembered the corner where they received the unpleasant puff on their noses. Furthermore, selective blocking of MMP-9 just in the central amygdala produced the same effect – the memory for the sweet water location could not be formed.
“The results are clear. Pleasant experiences are memorised due to changes in plasticity within the neurons of the central nucleus of the amygdala. At the same time we have shown that just one protein, the MMP-9, is responsible for learning about pleasant experiences themselves and memorizing them. At the same time this protein has no impact on the memory of unpleasant experiences. These are important discoveries and to tell the truth making them was… very pleasant”, says Prof. Kaczmarek.
These research results, which stem from experiments conducted at the Nencki Institute for the past 25 years, hold great scientific significance for they explain the processes of learning and appetitive memory by referring to two seemingly very distant domains of neurobiology: system – investigating entire neuronal structures (such as the central nucleus of the amygdala) – and molecular, investigating physical and chemical processes responsible for various functions of nervous cells (in which the MMP-9 protein takes part).
Researchers Find Early Success in New Treatment for Stroke Recovery
Researchers at The University of Texas at Dallas have taken a step toward developing a new treatment to aid the recovery of limb function after strokes.
In a study published online in the journal Neurobiology of Disease, researchers report the full recovery of forelimb strength in animals receiving vagus nerve stimulation.
“Stroke is a leading cause of disability worldwide,” said Dr. Navid Khodaparast, a postdoctoral researcher in the School of Behavioral and Brain Sciences and lead author of the study. “Every 40 seconds, someone in the U.S. has a stroke. Our results mark a major step in the development of a possible treatment.”
Vagus nerve stimulation (VNS) is an FDA-approved method for treating various illnesses, such as depression and epilepsy. It involves sending a mild electric pulse through the vagus nerve, which relays information about the state of the body to the brain.
Khodaparast and his colleagues used vagus nerve stimulation precisely timed to coincide with rehabilitative movements in rats. Each of the animals had previously experienced a stroke that impaired their ability to pull a handle.
Stimulation of the vagus nerve causes the release of chemicals in the brain known to enhance learning and memory called neurotransmitters, specifically acetylcholine and norepinephrine. Pairing this stimulation with rehabilitative training allowed Khodaparast and colleagues to improve recovery.
Many rehabilitative interventions try to enhance neuroplasticity (the brain’s ability to change) in conjunction with physical rehabilitation to drive the recovery of lost functions, according to Khodaparast. Unfortunately, up to 70 percent of stroke patients still display long-term impairment in arm function after traditional rehabilitation.
“For years, the majority of stroke patients have received treatment with various drugs and/or physical rehabilitation,” Khodaparast said. “Medications can have widespread effects in the brain and the effects can last for long periods of time. In some cases the side effects outweigh the benefits. Through the use of VNS, we are able to use the brain’s natural way of changing its neural circuitry and provide specific and long lasting effects.”
Khodaparast acknowledged the study has some limitations. For example, the animals were young and lacked some of the other illnesses that accompany an aged human population, such as diabetes or hypertension. But Khodaparast and his colleagues said they are optimistic about vagus nerve stimulation as a future tool. They will continue testing in chronically impaired animals with the hopes of translating the technique for stroke patients. Working with MicroTransponder Inc., a partner company in the current study, researchers at the University of Glasgow in Scotland have begun a small-scale trial in humans.
“There is strong evidence that VNS can be used safely in stroke patients because of its extensive use in the treatment of other neurological conditions,” said Dr. Michael Kilgard, professor in neuroscience at UT Dallas and senior author of the study.
Kilgard is also conducting clinical trials using vagus nerve stimulation to treat tinnitus, the medical condition of unexplained ringing in the ears. Kilgard’s lab first demonstrated the ability of vagus nerve stimulation to enhance brain adaptability in a 2011 Nature paper.
(Source: utdallas.edu)
Hitting the perfect tennis serve requires hours and hours of practice, but for scientists who study complex motor behaviors, there always has been a large unanswered question — what is the brain learning from those hours spent on the court? Is it simply the timing required to hit the perfect serve, or is it the precise path along which to move the hand?
The answer, Harvard researchers say, is both — but in separate circuits.
Bence Ölveczky, the John L. Loeb Associate Professor of the Natural Sciences, has found that the brain uses two largely independent neural circuits to learn the temporal and spatial aspects of a motor skill. The study is described in a Sept. 26 paper in Neuron.
“What we’re studying is the structure of motor-skill learning,” Ölveczky said. “What we were able to show is that the brain divides something that’s complex into modules — in this case for timing and for motor implementation — as a way to take advantage of the hierarchical structure of the motor system, and it imprints learning at the different levels independently.”
To tease out how those independent circuits operate, Ölveczky and his colleagues turned to a creature well-known for its ability to learn — the zebra finch. The tiny birds are regularly used in studies of learning because each male learns to sing a unique song from its father.
In a series of experiments, Ölveczky’s team used traditional conditioning techniques to change the timing of a bird’s song by speeding up or slowing down certain “syllables” in the song. They could also change which vocal muscles were activated and have the bird sing at a higher or lower pitch.
“But when you change the pitch of a syllable, the duration doesn’t change, and when you change the duration the pitch doesn’t change,” Ölveczky said. “It appears the neural circuits for the two features are separate.”
Additional evidence that the circuits for learning motor implementation and timing are distinct came when researchers lesioned the basal ganglia of the birds — the region of the brain long thought to play a critical role in song learning.
“The thinking had been that there was one circuit for song-learning in general,” Ölveczky said. “We found that if we lesioned the basal ganglia and repeated the pitch-shift experiment, the bird could no longer use the information it got from our feedback to change its behavior — in other words, it couldn’t learn.”
Experiments aimed at changing the birds’ timing, however, were just as effective, suggesting two separate learning circuits — with only one involving the basal ganglia.
Such independence and modularity is critical, Ölveczky said, because it allows different features of a behavior to be modified independently if circumstances change. Parallel learning of different features can also speed up the learning process and enable the flexibility we see in birdsong and many human motor skills.
“If you learn something — it could be your tennis serve, or it could be any behavior — and you need to slow it down or speed it up to fit some new contingency, you don’t have to completely re-learn the whole thing, you can just change the timing, and everything else will remain exactly the same.
“In fact, ‘slow practice,’ a technique used by many piano and dance teachers, makes good use of this modularity,” Ölveczky said. “Students are first taught to perform the movements of a piece slowly. Once they have learned it, all they need to do is get the timing right. The technique works because the two processes — motor implementation and timing — do not interfere with each other.”
The hope among researchers, Ölveczky said, is that a better understanding of how birds learn complex motor tasks such as singing unique songs will help shed new light on the neural underpinnings of learning in humans.
“For us, this is inspiration to look at similar types of questions in mammals,” he said. “The flexibility with which we can alter the spatial and temporal structure of our motor output is similar to songbirds, but our understanding of how the mammalian brain implements the underlying learning process is not anywhere near as advanced as for songbirds. The intriguing parallels in both circuitry and behavior, however, suggest a general principle of how the brain parses the motor skill learning process.”
Made to Order at the Synapse: Dynamics of Protein Synthesis at Neuron Tip is Basis for Memory and Learning
Understanding RNA biology in dendrites may inform neurological and psychiatric illness therapeutics
Protein synthesis in the extensions of nerve cells, called dendrites, underlies long-term memory formation in the brain, among other functions. “Thousands of messenger RNAs reside in dendrites, yet the dynamics of how multiple dendrite messenger RNAs translate into their final proteins remain elusive,” says James Eberwine, PhD, professor of Pharmacology, Perelman School of Medicine at the University of Pennsylvania, and co-director of the Penn Genome Frontiers Institute.
Dendrites, which branch from the cell body of the neuron, play a key role in the communication between cells of the nervous system, allowing for many neurons to connect with each other. Dendrites detect the electrical and chemical signals transmitted to the neuron by the axons of other neurons. The synapse is the neuronal structure where this chemical connection is formed, and investigators surmise that it is here where learning and memory occur.
These structural and chemical changes – called synaptic plasticity — require rapid, new synthesis of proteins. Cells may use different rates of translation in different types of mRNA to produce the right amounts and ratios of required proteins.
Knowing how proteins are made to order – as it were - at the synapse can help researchers better understand how memories are made. Nevertheless, the role of this “local” environment in regulating which messenger RNAs are translated into proteins in a neuron’s periphery is still a mystery.
Eberwine, first author Tae Kyung Kim, PhD, a postdoc in the Eberwine lab, and colleagues including Jai Yoon Sul, PhD, assistant professor in Pharmacology, showed that protein translation of two dendrite mRNAs is complex in space and time, as reported online in Cell Reports this week.
“We needed to look at more than one RNA at the same time to get a better handle on real- world processes, and this is the first study to do that in a live neuron,” Eberwine explains.
At Home in the Hippocampus
“It’s not always one particular RNA that dominates at a translation hotspot versus another type of RNA,” says Eberwine. “Since there are 1,000 to 3,000 different mRNA types present in the dendrite overall, but not 1,000 to 3,000 different translational hot spots, do the mRNAs ‘take turns’ being translated in space and time at the ribosomes at the hotspots?”
The researchers engineered the glutamate receptor RNAs to contain different fluorescent proteins that are independently detectable, as well as a photo-switchable protein to determine when new proteins were being made. In the case of the photo-switchable protein studies, when an mRNA for the glutamate receptor protein is marked green, it means it has already been translated.
When a laser is passed over the green protein, it changes to red as a way of tagging when it has been been translated, and new proteins synthesized at that hotspot would be green, which is visible by the appearance of yellow fluorescence (green + red, as measured by light on the visible spectrum). These tricks of the light allow the team to keep track of newly made proteins over time and space.
“This is the first time this method of protein labeling has been used to measure the act of translation of multiple proteins over space and time in a quantitative way,” says Eberwine. “We call it quantitative functional genomics of live cell translation.”
“Our results suggest that the location of the translational hotspot is a regulator of the simultaneous translation of multiple messenger RNAs in nerve cell dendrites and therefore synaptic plasticity,” says Sul.
Laying the Groundwork
Almost 10 years ago, the Eberwine lab discovered that nerve-cell dendrites have the capacity to splice messenger RNA, a process once believed to take place only in the nucleus of cells. Here, a gene is copied into mRNA, which possesses both exons (mature mRNA regions that code for proteins) and introns (non-coding regions). mRNA splicing works by cutting out introns and merging the remaining exon pieces, resulting in an mRNA capable of being translated into a specific protein.
The vast array of proteins within the human body arises in part from the many ways that mRNAs can be spliced and reconnected. Specifically, splicing removes pieces of intron and exon regions from the RNA. The resulting spliced RNA is made into protein.
If the RNA has different exons spliced in and out of it, then different proteins can be made from this RNA. The Eberwine lab was successful in showing that splicing can occur in dendrites because they used sensitive technologies developed in their lab, which permits them to detect and quantify RNA splicing, as well as the translated protein in single isolated dendrites.
Understanding the dynamics of RNA biology and protein translation in dendrites promises to provide insight into regulatory mechanisms that may be modulated for therapeutic purposes in neurological and psychiatric illnesses. The directed development of therapeutics requires this detailed knowledge, says Eberwine.
Size matters: brain processes ‘big’ words faster than ‘small’ words
Bigger may not always be better, but when it comes to brain processing speed, it appears that size does matter.
A new study has revealed that words which refer to big things are processed more quickly by the brain than words for small things.
Researchers at the University of Glasgow had previously found that big concrete words – ‘ocean’, ‘dinosaur’, ‘cathedral’ – were read more quickly than small ones such as ‘apple’, ‘parasite’ and ‘cigarette’.
Now they have discovered that abstract words which are thought of as big – ‘greed’, ‘genius’, ‘paradise’ – are also processed faster than concepts considered to be small such as ‘haste’, ‘polite’ and ‘intimate’.
Dr Sara Sereno, a Reader in the Institute of Neuroscience and Psychology who led the study said: “It seems that size matters, even when it’s abstract and you can’t see it.”
The study, published in the online journal PLoS ONE, also involved researchers from Kent, Manchester and Oregon. Participants were presented with a series of real words referring to objects and concepts both big and small, as well as nonsense, made-up words, totalling nearly 500 items. The different word types were matched for length and frequency of use.
The 60 participants were asked to press one of two buttons to indicate whether each item was a real word or not. This decision took just over 500 milliseconds or around a half second per item. Results showed that words referring to larger objects or concepts were processed around 20 milliseconds faster than words referring to smaller objects or concepts.
“This might seem like a very short period of time,” said Dr Sereno, “but it’s significant and the effect size is typical for this task.”
Lead author Dr Bo Yao said: “It turned out that our big concrete and abstract words, like ‘shark’ and ‘panic’, tended to be more emotionally arousing than our small concrete and abstract words, like ‘acorn’ and ‘tight’. Our analysis showed that these emotional links played a greater role in the identification of abstract compared to concrete words.”
“Even though abstract words don’t refer to physical objects in the real world, we found that it’s actually quite easy to think of certain concepts in terms of their size,” said co-author Prof Paddy O’Donnell. “Everyone thinks that ‘devotion’ is something big and that ‘mischief’ is something small.”
Bigger things it seems, whether real or imagined, grab our attention more easily and our brains process them faster – even when they are represented by written words.