Tag Archives: neurons

Pain impairs our ability to feel pleasure — and now we know why, and how

Researchers are homing in on the brain circuits that handle pain-induced anhedonia, the reduction in motivation associated with experiencing pain. The findings, currently only involving lab rats, might prove pivotal in our efforts to address depression and the rising issue of opioid addiction.

Pain is definitely not a sensation most of us are excited to experience. And although physical hurt is obviously unpleasant, it isn’t the only component of this sensation. Affective pain can be just as debilitating, and much more insidious. New research has identified the brain circuits that mediate this kind of pain, in a bid to counteract its long-term effects — which can contribute to the emergence of depression and make people vulnerable to addictions that take that pain away, such as opioid use disorder (OUD).

Show me where it hurts

Chronic pain is experienced on many levels beyond just the physical, and this research demonstrates the biological basis of affective pain. It is a powerful reminder that psychological phenomena such as affective pain are the result of biological processes,” said National Institute on Drug Abuse (NIDA) Director Nora D. Volkow, M.D, who was not affiliated with this study.

“It is exciting to see the beginnings of a path forward that may pave the way for treatment interventions that address the motivational and emotional effects of pain.”

Pain, the authors explain, has two components: a sensory one (the part you can feel) and an affective, or emotional, component. Anhedonia — an inability to feel pleasure and a loss of motivation to pursue pleasurable activities — is one of the central consequences of affective pain. Considering the strong links between anhedonia, depression, and substance abuse, the NIDA has a keen interest in understanding how our brains produce and handle affective pain.

Previous studies found that rats in pain were more likely to consume higher doses of heroin compared to their peers. In addition to this, they lost a sizable chunk of their motivation to seek out other sources of reward (pleasure), such as sugar tablets.

The current paper built on these findings, and aimed to see exactly how this process takes place in the brain. The team measured the activity of dopamine-responding neurons in a part of the brain’s “reward pathway” known as the ventral tegmental area. This activity was measured while the rats used a lever with their front paw to receive a sugar tablet. In order to see what effect pain would have on the activity of these neurons, rats in the experimental group received an injection that produced local inflammation in their hind paw. Rats in the control group were injected with saline solution.

After 48 hours, the researchers noted that rats in the experimental group pressed the lever less than their peers, indicative of a loss of motivation. They also saw lower activity levels in their dopamine neurons. Further investigations revealed that these neurons were less active because the sensation of pain was activating cells from another region of the brain known as the rostromedial tegmental nucleus (RMTg). Neurons in the RMTg are, among other tasks, responsible for producing the neurotransmitter GABA, which inhibits the functions of dopamine neurons.

Despite this, when the authors artificially restored functionality to the dopamine neurons, the effects of pain on the reward pathway was completely reversed and the rats regained the motivation to push the lever and obtain their sugar tablet even with the sensation of pain.

In another round of lab experimentation, the team were able to reach the same effects by blocking the activity of neurons which produce GABA in response to pain. The rats who were part of this round of testing were similarly motivated to pick a solution of water and sugar over plain water even when experiencing pain. This, the authors explain, shows that the rats were better able to feel pleasure despite also experiencing pain.

All in all, even though the findings are valuable in and of themselves, the team says that this is the first time a link has been established between pain, an increase of activity of GABA neurons, and an inhibitory pathway effect in the reward system which causes decreased activity of dopamine neurons.

“Pain has primarily been studied at peripheral sites and not in the brain, with a goal of reducing or eliminating the sensory component of pain. Meanwhile, the emotional component of pain and associated comorbidities such as depression, anxiety, and lack of ability to feel pleasure that accompany pain has been largely ignored,” said study author Jose Morón-Concepcion, Ph.D., of Washington University in St. Louis.

“It is fulfilling to be able to show pain patients that their mental health and behavioral changes are as real as the physical sensations, and we may be able to treat these changes someday,” added study author Meaghan Creed, Ph.D., of Washington University in St. Louis.

The paper “Pain induces adaptations in ventral tegmental area dopamine neurons to drive anhedonia-like behavior” has been published in the journal Nature Neuroscience.

Mice can develop neural signs of depression when forced to watch other mice experiencing stress

Depression is a global problem, affecting an ever-growing number of individuals. In a bid to better understand its physiological underpinnings, a team from the Tokyo University of Science has explored how neural deterioration in areas of the brain such as the hippocampus, as well as physical and psychological stress, is tied to depression.

Image credits Tibor Janosi Mozes.

There are several theories regarding why and how depression emerges, both from psychological and physiological factors. In regards to the latter, the “neurogenic hypothesis of depression” has garnered a lot of scientific interest. It states that depression can stem from physical degradation in areas of the brain such as the hippocampus, degradation which can be incurred by stress.

While the link between physical stress and depression has been investigated in the past, much less is known about the effects of psychological stress. A new study aims to give us a better understanding of this topic, using mice as a model organism.

A grinding toll

“The number of individuals suffering from depression has been on the rise the world over. However, the detailed pathophysiology of depression still remains to be elucidated. So, we decided to focus on the possible mechanism of psychological stress in adult hippocampal neurogenesis, to understand its role in depressive disorders,” says Prof. Akiyoshi Saitoh from Tokyo University of Science, co-lead author of the study.

“We have found out that chronic mental stress affects the neurogenesis of the hippocampal dentate gyrus. Also, we believe that this animal model will play an important role in elucidating the pathophysiology of depression, and in the development of corresponding novel drug.”

For the study, the team exposed mice to “repeated psychological stress” in order to test how this impacts hippocampus degeneration in their brains. The experiment consisted of making the mice experience chronic social defeat stress (cSDS) via their peers — a source of psychological stress for the animals, as they are a highly social species. Chronic social defeat stress is an experimental tool through which stress is induced in a subject (such as a mouse), the ‘naive mouse’ to ‘aggressor’ mice. As part of this research, the mice were made to witness the naive mice, who were participating in the stressful situation.

After this exposure, the team analyzed their brains to measure the level of degradation it produced in key brain areas, as well as noting changes in behavior.

First off, they report that the mice exposed to this repeated source of stress started exhibiting behavioral issues such as social withdrawal, indicative of depression. In their brains, more specifically the dentate gyrus area of the hippocampus, the team recorded a decreased survival rate of new-born neurons compared to those of controls. This area is heavily involved in memory and sensory perception.

Lower new-born neuron survival rates persisted for up to four weeks after the animals were exposed to the stress-inducing scenarios. Chronic treatment with antidepressant fluoxetine was efficient in restoring neuronal survival rates for these mice. Other characteristics, such as cell growth, differentiation, and maturation rates were not impacted by stress in the experimental mice (as compared to controls), the team adds.

The authors link neural degradation in the hippocampus to the emergence of depression through the fact that avoidance behaviors in the experimental mice was “significantly enhanced” 4 weeks after the last stress-inducing exercise, compared to the first day after it. This behavior, they explain, is likely produced by degradation mounting in neurons of the hippocampus following the experience.

Although these findings have not yet been validated in humans, the authors believe that they can form an important part of understanding how depression emerges in the brain even among us. Further work is needed to validate the results and see whether they translate well to humans, however.

The paper “Chronic vicarious social defeat stress attenuates new-born neuronal cell survival in mouse hippocampus” has been published in the journal Behavioural Brain Research.

Nosy study finds we probably produce new neurons all the time

New research suggests that humans may actually be able to create new neurons after childhood. The paper reports on a new “neuron nursery” located in a section of our noses.

Human olfactory neuroepithelium.
Image credits Duke University.

The study was published in the context of a much wider (and long-lasting) debate on whether humans are able to create new neurons after the age of 13. Neurons, the ultra-specialized cells that underpin our nervous systems, aren’t only useful for thinking or telling muscles to move. The current study focuses on neurons that act as receptors in the olfactory neuroepithelium of the nose. These neurons directly underpin our ability to smell.

Smells brand new

“We do not fully understand why people lose their sense of smell, which can occur for many reasons, and our data sets provide a wealth of information about the cell populations present in adult olfactory tissue,” said Brad Goldstein, M.D., Ph.D., an associate professor and vice chair for research in the Department of Head and Neck Surgery and Communication Sciences at Duke University and senior author of the study.

“This is an important step in developing treatment strategies for conditions when this tissue may be damaged.”

This study is the first of its kind to use human tissue samples (previously only mice nasal tissue samples were used). Starting from them, the team found that immature neurons being produced by stem cells made up over half of the number of neurons in the samples, suggesting that they were actively being produced there. Which, obviously, means that neurons can be produced throughout our lifetime.

Hiroaki Matsunami, Ph.D., a professor in the Department of Molecular Genetics and Microbiology at Duke University and co-author on the paper, explains that the molecular make-up of these immature neurons point heavily to them being grown there during adulthood.

The team says that their findings could help guide treatment options for conditions that cause smell damage or loss, but could in time be applicable to the nervous system as a whole.

“It will be very useful to use this window to analyze samples from people with conditions in which the nervous system has degeneration, such as Alzheimer’s disease,” said Goldstein.

“Alzheimer’s is of particular interest, since these patients lose their sense of smell quite early in the disease process, and we have few treatments for Alzheimer’s disease. So, it may make sense to look carefully at regions of the olfactory system in these patients.”

The nose is a very exposed site, the team adds, meaning that in time we could learn how to collect neuronal stem cells from the area and use them to treat other disorders involving the nervous system.

“It is not outside of the realm of possibility,” said Matsunami.

The paper “Single-cell analysis of olfactory neurogenesis and differentiation in adult humans” has been published in the journal Nature Neuroscience.

Schizophrenia patients show fewer brain connections than healthy people

New research confirms that schizophrenia’s cognitive symptoms are correlated with lower synaptic density in certain parts of the brain.

Image credits Ellis Chika Onwordi / MRC London Institute of Medical Sciences.

Researchers have hypothesized that there is a link between schizophrenia and malfunctioning synapses since the early 1980s but lacked proper tools needed to investigate this in living brains. However, it was confirmed in post-mortem brain samples and animal cells in the lab.

But there’s no better proof of something than seeing it in action. New research at the Medical Research Council (MRC) London Institute of Medical Sciences did just that by using advanced brain-imaging techniques to peer into the synapses of living schizophrenia patients.

Instant synapses, just add protein

“Our current treatments for schizophrenia only target one aspect of the disease—the psychotic symptoms—but the debilitating cognitive symptoms, such as loss of abilities to plan and remember, often cause much more long-term disability and there’s no treatment for them at the moment. Synaptic loss is thought to underlie these symptoms,” says Professor Oliver Howes from the MRC London Institute of Medical Sciences, Imperial College London and King’s College London, the paper’s lead author.

For the study, the team enlisted the help of 18 adults with schizophrenia and 18 people without (these were the controls). The research was made possible by a tracer molecule that emits a signal that can be picked up by a PET (positron emission tomography) brain scan. This tracer is injected into the bloodstream of a subject and binds to SV2A, a specific protein found in brain synapses. Animal and post-mortem human studies have shown that SV2A is a reliable marker for synaptic density in the brain.

The team reports that patients with schizophrenia showed lower levels of SV2A in the frontal and anterior cingulate cortices of the brain, which are involved in planning and other high-level functions. In essence, the lower levels of SV2A proteins seen here suggest a lower number of synapses (and thus, brain functionality) in the area.

“Our lab at the MRC London Institute of Medical Sciences is one of the few places in the world with this new tracer, which means we’ve been able for the first time to show there are lower levels of a synaptic protein in people with schizophrenia,” Professor Howes adds.

“This suggests that loss of synapses could underlie the development of schizophrenia.”

The schizophrenia patients that participated in this study had all received antipsychotic medication, which could affect the results. To address this, the team gave haloperidol and olanzapine, two antipsychotic drugs, to lab rats for 28 days, then analyzed their brains using the same method. Such medication had no effect on SV2A protein levels, they found, which helped to validate their results. This step also indicated that the antipsychotic medication currently in use doesn’t lead to a loss of synaptic density or function, which is always nice to know.

Therapeutic options for schizophrenia remain few and far between. The condition is a highly debilitating one, and any effective avenue of treatment would dramatically improve the quality of life for patients. Studies such as this one serve as a launching pad for developing future treatments, according to Dr. Ellis Onwordi from the MRC London Institute of Medical Sciences, lead author of the paper. The findings can also help guide brain research into other similar conditions by showcasing “how the extraordinarily complex wiring of the human brain is altered by this disease.”

“Having scans that can characterise the distribution of the approximately 100 trillion synapses in the living brain, and find differences in their distribution between people with and without schizophrenia, represents a significant advance in our ability to study schizophrenia,” he adds.

“We need to develop new treatments for schizophrenia. This protein SV2A could be a target for new treatments to restore synaptic function.”

In the future, the team hopes to scan the brains of younger people during the early stages of schizophrenia, to better understand how it develops in the brain. Do all the changes seen in this study happen suddenly, or do they develop over time as the condition progresses? Such data could help us better treat the condition, and maybe even stop it altogether.

The paper “Synaptic density marker SV2A is reduced in schizophrenia patients and unaffected by antipsychotics in rats” has been published in the journal Nature Communications.

Rare genetic mutations and the fruit fly explain how Zika causes microcephaly

In the early part of 2016, the World Health Organization’s Emergency Committee (EC) under the International Health Regulations (2005) (IHR 2005) discussed the clusters of microcephaly and Guillain-Barré Syndrome (GBS) cases that have been temporally associated with Zika virus transmission.

Brazil, France, the United States of America, and El Salvador provided information on a potential association between microcephaly and other neurological disorders with Zika virus. The recent cluster of microcephaly cases was considered a Public Health Emergency of International Concern (PHEIC). Several months later, the WHO confirmed in a scientific consensus that the Zika virus is linked with microcephaly as well as Guillain-Barré syndrome.

Three years and several studies later, researchers at Baylor College of Medicine revealed one way how in utero Zika virus infection can lead to microcephaly in newborns. The team discovered that the Zika virus protein NS4A interrupts the growth of the brain by taking control of a pathway that regulates the generation of new neurons.

Rare genetic mutations helped explain how Zika causes microcephaly

Zika virus protein NS4A interacts with ANKLE2, a protein linked to hereditary microcephaly.

“The current study was initiated when a patient presented with a small brain size at birth and severe abnormalities in brain structures at the Baylor Hopkins Center for Mendelian Genomics (CMG),” said Dr. Hugo Bellen, professor at Baylor, investigator at the Howard Hughes Medical Institute and Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital.

This patient and others in a cohort at CMG had not been infected by Zika virus in utero. They had a genetic defect that caused microcephaly. CMG scientists determined that the ANKLE2 gene was associated with the condition.

Several years ago, Dr. Bellen and colleagues discovered in the fruit fly model that the ANKLE2 gene was associated with neurodevelopmental disorders. In a subsequent fruit fly study, the researchers demonstrated that overexpression of Zika protein NS4A causes microcephaly in the flies by inhibiting the function of ANKLE2, a cell cycle regulator that acts by suppressing the activity of VRK1 protein. Since very little is known about the role of ANKLE2 or VRK1 in brain development, Bellen and his colleagues applied a multidisciplinary approach to tease apart the exact mechanism underlying ANKLE2-associated microcephaly.

The fruit fly helps clarify the mystery

This image shows the two lobes of the brain of a fruit fly larva with hundreds of neurons, colored green, and stem cells, colored magenta. 

To figure out how Ankle2 mutations were influencing brain formation, the researchers went back to flies. Normally, Ankle2 works with a series of other genes to control the division of neuroblasts — stem cells that give rise to neurons. These cells are crucial for proper brain development.

Mutations in the Ankle2 gene, though, messed with neuroblast division. Larval flies with the mutation had fewer neuroblasts and smaller-than-expected brains. Further analyses revealed more details about how Ankle2 regulates asymmetric neuroblast division. They found that Ankle2 protein interacts with VRK1 kinases, and that Ankle2 mutants alter this interaction in ways that disrupt asymmetric cell division.

The Zika connection

In the future, a drug that protects this protein could stop Zika’s damaging developmental effects, says Dr. Hugo Bellen.

“For decades, researchers have been unsuccessful in finding experimental evidence between defects in asymmetric cell divisions and microcephaly in vertebrate models. The current work makes a giant leap in that direction and provides strong evidence that links a single evolutionarily conserved Ankle2/VRK1 pathway as a regulator of asymmetric division of neuroblasts and microcephaly. Moreover, it shows that irrespective of the nature of the initial triggering event, whether it is a Zika virus infection or congenital mutations, the microcephaly converges on the disruption of Ankle2 and VRK1, making them promising drug targets.”

Fried CD.

New research sheds light into how our brains handle metaphors

Your brain can read the lines, and it can read between the lines, but it does both using the same neurons.

Fried CD.

Image credits Chepe Nicoli.

While we can consciously tell when a word is being used literally or metaphorically, our brains process it just the same. The findings come from a new study by University of Arizona researcher Vicky Lai, which builds on previous research by looking at when, exactly, different regions of the brain are activated in metaphor comprehension.

Twisting our words

“Understanding how the brain approaches the complexity of language allows us to begin to test how complex language impacts other aspects of cognition,” she said.

People use metaphors all the time. On average, we sneak one in once every 20 words, says Lai, an assistant professor of psychology and cognitive science at the UA. As director of the Cognitive Neuroscience of Language Laboratory in the UA Department of Psychology, she is interested in how the brain distinguishes metaphors from the broad family of language, and how it processes them.

Previous research has hinted that our ability to understand metaphors may be rooted in bodily experiences. Functional brain imaging studies (fMRI), for example, have indicated that hearing a metaphor such as “a rough day” activates regions of the brain associated with the sense of touch. Hearing that someone is “sweet”, meanwhile, activates taste areas, whereas “grasping a concept” lights up brain regions involved in motor perception and planning are activated.

In order to get to the bottom of things, Lai used EEG (electroencephalography) to record the electrical patterns in the brains of participants who were presented with metaphors that contained action words — like “grasp the idea” or “bend the rules.” The participants were shown three different sentences on a computer screen, presented one word at a time. One of these sentences described a concrete action — “The bodyguard bent the rod.” Another was a metaphor using the same verb — “The church bent the rules.” The third sentence replaced the verb with a more abstract word that kept the metaphor’s meaning — “The church altered the rules.”

Seeing the world “bent” elicited a similar response in participants’ brains whether it was used literally or metaphorically. Their sensory-motor region activated almost immediately — within 200 milliseconds — of the verb appearing on screen. A different response, however, was elicited when “bent” was replaced with “altered.”

Lai says her work supports previous findings from fMRI (functional magnetic resonance imaging) studies. However, while fMRI measures blood flow in the brain as a proxy for neural activity, the EEG measures electrical activity directly. Thus, it provides a clearer picture of the role sensory-motor regions of the brain play in metaphor comprehension, she explains.

“In an fMRI, it takes time for oxygenation and deoxygenation of blood to reflect change caused by the language that was just uttered,” Lai said. “But language comprehension is fast — at the rate of four words per second.”

“By using the brainwave measure, we tease apart the time course of what happens first,” Lai said.

While an fMRI won’t show you exactly which brain region is working to decipher an action-based metaphor (because it won’t show you which region activates immediately and which does so after we already understand the metaphor), the EEG provides a much more precise sense of timing. The near-immediate activation of sensory-motor areas after the verb was displayed suggests that these areas of the brain are key to metaphor comprehension.

Lai recently presented ongoing research looking into how metaphors can aid learning and retention of science concepts at the annual meeting of the Cognitive Neuroscience Society in San Francisco. She hopes the study we’ve discussed today will help her lab better understand how humans comprehend language and serve as a base for her ongoing and future research.

The paper “Concrete processing of action metaphors: Evidence from ERP” has been published in the journal Brain Research.

Old and young.

Time flies as we age because our brains get bigger and less efficient, a new paper proposes

New research from Duke University says time flies as we age because of our brains maturing — and degrading.

Old and young.

Image credits Gerd Altmann.

The shift in how we perceive time throughout our lives takes place because our brain’s ability to process images slows down, reports a study penned by Adrian Bejan, the J.A. Jones Professor of Mechanical Engineering at Duke. This is a consequence of the natural development of our brains, as well as wear and tear.

Hardware, oldware

“People are often amazed at how much they remember from days that seemed to last forever in their youth,” said Bejan. “It’s not that their experiences were much deeper or more meaningful, it’s just that they were being processed in rapid fire.”

Bejan says that, as the bundles of nerves and neurons that make up our brains develop both in size and complexity, the electrical signals that encode sensory data have to travel through longer paths. We also grow in size, making the nerves feeding information to the brain physically longer. Nerve fibers are good conductors of electricity — but they’re not perfect; all that extra white matter slows down the transfer of data in our biological computers.

Wear and tear also play a role, he adds. As neural paths age, they also degrade, which further chips away at their ability to transport information.

These two elements combine to slow down our brain’s ability to transport, and thus process, data. One tell-tale sign of processing speeds degrading with age is the fact that infants tend to move their eyes more often than adults, Bejan explains. It’s not that they’re more ‘filled with energy’ or simply have shorter attention spans. Younger brains are quicker to absorb, process, and integrate new information, meaning they need to focus for shorter spans of time on a single object or stimuli to take it all in.

So, how does this impact our perception of time? The study explains that older people basically view fewer new images in a given unit of time than younglings, due to the processes outlined above. This makes it feel like time is passing more quickly for the former.  Objective, “measurable ‘clock time’ is not the same as the time perceived by the human mind,” the paper reads, as our brains tend to keep track of time by how many new bits of information it receives.

“The human mind senses time changing when the perceived images change,” said Bejan. “The present is different from the past because the mental viewing has changed, not because somebody’s clock rings.”

“Days seemed to last longer in your youth because the young mind receives more images during one day than the same mind in old age.”

It’s not the most heartening of results — who likes to hear their brains are getting laggy, right? — but it does help explain why we get that nagging feeling of time moving faster as we age. And, now that we know what’s causing it, we can try to counteract the effects.

That being said, maybe having a slower brain isn’t always that bad of a thing. If you’re stuck out on a boring date, or grinding away inside a cubicle from 9 to 5, at least you feel like you’re getting out quicker. Glass half full and all that, I suppose.

The paper “Why the Days Seem Shorter as We Get Older” has been published in the journal European Review.

Bee experiment.

Bees use a small number of neurons to count, and they’re one of the best counters we know

Not only can bees count — but they can do so using laughably few brain cells.

Bee in approach.

Image credits Christian Birkholz / Pixabay.

One team of researchers from the Queen Mary University of London looked into how bees count. The insects, they report, draw on a brain-wiring trick to allow them this skill using very small numbers of neurons. In order to understand how bee brains handle numbers, the team simulated an extremely simple brain network on a computer.

Despite containing just four neurons (far fewer than a real bee can boast), this artificial brain could still handle the task. Lab results showed that it could easily count small quantities of items when inspecting one item closely and then inspecting the next item closely and so on, which is the same way bees count. This differs from humans who glance at all the items and count them together.

Counting bee

Previous research has shown that bees can count — usually up to four or five items. Interestingly enough (and perhaps, uniquely among non-humans), they can also grasp the concept of zero when trained to choose ‘less’.

However, new research reveals something really surprising: it’s possible that bees have no clue what numbers (or other numerical concepts) are. By using specific flight movements to closely inspect items, the bees draw on their visual input to simplify the task of counting so much, it requires minimal brainpower. This shows that the intelligence of bees (potentially other animals’ as well) can be based on a very small number of nerve cells, as long as these are wired together in the right way.

“Careful examination of the actual inspection strategies used by animals might reveal that they often employ active scanning behaviours as shortcuts to simplify complex visual pattern discrimination tasks,” says lead author Dr Vera Vasas, from Queen Mary University of London. “Hopefully, our work will inspire others to look more closely not just at what cognitive tasks animals can solve, but also at how they are solving them.”

She goes on to explain that although counting is generally considered to “require high intelligence and large brains,” the findings show it can be done with a small — but properly-structured — network.

“We suggest that using specific flight movements to scan targets, rather than numerical concepts, explains the bees’ ability to count. This scanning streamlines the visual input and means a task like counting requires little brainpower.

Bees only have about one million nerve cells overall, meaning they have really, really low brainpower (no offense, bees). Your average human, for example, boasts upward of 86 billion nerve cells.

Still, this limitation forced evolution to get creative, and it did. The bees overcome their relative lackluster hardware with fancy computational algorithms, the team reports. To model how these tiny insect brains receive information, the team analyzed the point of view of a bee as it flies close to the countable objects and inspects them one-by-one.

Bee experiment.

A bumblebee choosing between two patterns containing different numbers of yellow circles.
Image credits Lars Chittka.

This data was later fed to the simulated brain. It made reliable estimates of the number of items on display based on this video feed, the team reports — in essence, it could count. As such, the findings could also have implications for artificial intelligence.

“These findings add to the growing body of work showing that seemingly intelligent behaviour does not require large brains, but can be underpinned with small neural circuits that can easily be accommodated into the microcomputer that is the insect brain,” says lead author Professor Lars Chittka, also from Queen Mary University of London.

The paper “Insect-inspired sequential inspection strategy enables an artificial network of four neurons to estimate numerosity” has been published in the journal iScience.

Danger sign.

Scared? Here’s how your brain decides whether you freeze, flee, or fight

New research sheds light on how our brains react when faced with danger.

Danger sign.

Image credits spcbrass / Flickr.

Hear that? If you listen really hard, you can actually make out the sound of nothing hunting you right now. Safely ensconced in our society, we tend to take this for granted. Make no mistake, however: it’s anything but.

That’s exactly why we (and basically every other animal) evolved from the ground up with self-preservation in mind. Despite our sheltered existence, the brain circuits that generate our responses to perceived threats are still very much alive to this day. In a bid to better understand how these networks operate, and why they work the way they do, researchers at the Champalimaud Centre for the Unknown (CCU) in Lisbon, Portugal, set about to terrify the pants off some very tiny flies.

Fly, fruit fly!

“Just like any other animal in nature, our reaction to a threat is invariably one of the following three: escape, fight or freeze in place with the hope of remaining unnoticed,” says Marta Moita, co-lead author of the study.

“These behaviours are fundamental, but we still don’t know what the rules of the game are,” adds the study’s first author Ricardo Zacarias. “In each situation, how does the brain decide which of the three strategies to implement and how does it ensure that the body carries it through?”

Fruit flies (Drosophila melanogaster) might not seem like the coolest or smartest organism out there — in all honesty, they’re not — but they do have a few saving graces: they’re easy and cheap to care for in large numbers and they’re low maintenance. They also procreate fast and with a fury, so there’s always plenty of them to experiment on.

Given their simpler natures (and wings), Moita admits, many people “believed that flies only escape”, but the research showed that’s not the case. They devised an experiment in which the flies didn’t have the option of flying away and then spooked them to see their reaction.

The flies were placed in covered dishes and were then shown an expanding dark circle, which ” is how a threat looks like to a fly,” Moita explains. With flying away out of the question, the flies froze, the team reports. In a perfect mirror of the same behavior in mammals, birds, and several other species, the flies remained completely motionless for minutes on end. There’s no doubt as to why the flies froze since they would maintain positions that were obviously awkward and uncomfortable for them, such as half crouches, or holding a leg or two “suspended in the air,” Moita explains.

Some flies, however, decided to make a dash for it.

“This was very exciting,” says Vasconcelos, “because it meant that similarly to humans, the flies were choosing between alternative strategies.”

The next step was to take a closer look at what triggered each response. For this goal, the team used machine vision software to produce highly-detailed accounts of each fly’s behavior. Analyzing this data revealed that the flies’ response was determined by their walking speed at the moment the threat appeared. If the fly was walking slowly, it would freeze. By contrast, if it was traveling at speed, it would attempt to run away instead.

“This result is very important: it is the first report showing how the behavioural state of the animal can influence its choice of defensive strategy,” Vasconcelos points out.

The team later identified a single pair of neurons that underpin these defensive behaviors. The pair — with one neuron on each side of the flies’ brain — decided whether the flies would freeze or not. When the team inactivated these neurons, the flies stopped attempting to freeze and just ran away from threats all the time.

When the team artificially forced the neurons to stay active all the time, even without a threat being present, the flies would freeze depending on their walking speed — the fly would freeze if it was walking slowly, but not if it was walking quickly.

“This result places these neurons directly at the gateway of the circuit of choice,” says Zacarias.

“This is exactly what we were looking for: how the brain decides between competing strategies,” Moita adds. “And moreover, these neurons are of the type that sends motor commands from the brain to the ‘spinal cord’ of the fly. This means that they may be involved not only in the choice, but also in the execution”.

The findings should help provide a starting point for identifying how the brains of other species handle defense, the team explains, as “defensive behaviors are common to all animals”.

The paper “Speed dependent descending control of freezing behavior in Drosophila melanogaster” has been published in the journal Nature.

UNIGE1.

Overeager immune system cells may be to blame for multiple sclerosis

New research from the University of Geneva in Switzerland is inching in on the causes of multiple sclerosis.

UNIGE1.

In a multiple sclerosis, a cluster of lymphocytes T CD8+ (red) express TOX (green) within the nucleus (blue).
Image credits UNIGE.

Multiple sclerosis (MS) is a debilitating disease that affects roughly 3 in 10.000 people worldwide, and about 0.1% of the population (1 in 1,000 people) in the US. The disease is still as mysterious as ever: we know it involves the breakdown of the myelin sheaths around the tails of neurons in the brain, but not why. Symptoms range from physical or mental to psychiatric — vision problems, impairment of locomotor functions or speech difficulties among others — and they can come about in isolated attacks (relapsing forms) or set in over time (progressive forms). We can help patients manage the symptoms to some extent, but we don’t yet know how to cure the disease.

TOX and MS

Researchers at the University of Geneva (UNIGE), Switzerland, and Geneva University Hospitals (HUG) are investigating into one of the potential culprits behind MS. They have identified one DNA-binding factor named TOX which might play a role in triggering multiple sclerosis — the team reports that TOX enables cells to cause autoimmune damage to brain cells. The team’s findings could help us develop better treatments to both MS and autoimmune diseases in general.

We don’t know why some people develop MS while others don’t. We have observed, however, that the disease is linked with both genetic and environmental risk factors (among the latter being infection and even smoking). To get a better understanding of the processes that underpin MS’s onset, the team decided to look at the role infection factors play in its formation.

“We decided to analyse the infectious factors by studying the auto-immune reactions provoked by different pathogens,” explains Doron Merkler, a Professor at the HUG Clinical Pathology Department. “This was to try to pinpoint an element that might influence the development of multiple sclerosis where there has been an infection”.

The team used with two different pathogens — one viral, the other bacterial — that are known to elicit a response from the immune system. The research was performed using healthy mouse models. According to co-author Nicolas Page, a researcher in UNIGE’s Pathology and Immunology Department, both pathogens elicited a “quantitative identical immune reaction” from one particular type of white blood cells: lymphocytes CD8+ T.

“However, only the mouse infected with the viral pathogen developed an inflammatory brain disease reminiscent to Multiple Sclerosis,” he adds.

The team’s next step was to look at how gene expression levels in CD8+ T varied when different pathogens were used to activate them — which led to the discovery of TOX. This DNA-binding factor expressed only in cells activated by the viral pathogen, they explain. Later, the team confirmed the link between TOX and MS, using mice models in which they eliminating the expression of TOX in CD+ 8 lymphocytes. In this case, the mice didn’t develop the disease despite being infected with the viral pathogen.

However, for all the damage it can do, the team reports that TOX actually means well. Our brains can’t regenerate that well, and relying on tissue regrowth doesn’t guarantee the integrity of function or stored memories — so our body tries to prevent damage to neurons rather than make sure it can easily repair. Our brains are so fragile, however, that they also have to keep out our own immune system cells, which could damage the organ in their relentless fight against pathogens. So, the brain is insulated with barriers that prevent T lymphocytes from entering.

TOX, however, alters the expression of certain key receptors on the surface of CD+ T lymphocytes — the same receptors that receive the “stay away” signals from the brain’s barriers. The defending cells can thus bypass the filters, gain access to the brain, and inadvertently cause the outbreak of the disease, notes the team. Another damning piece of evidence, the team reports, is that TOX was also expressed in T cells present in multiple sclerosis lesions.

“This is an encouraging result for understanding the causes of the disease but there is still lots of work to be done to ascertain what really causes multiple sclerosis in humans,” admits Page.

The researchers now plan to study if and how TOX is involved in other autoimmune diseases, as well as certain cancers.

The paper “Expression of the DNA-Binding Factor TOX Promotes the Encephalitogenic Potential of Microbe-Induced Autoreactive CD8+ T Cells” has been published in the journal Immunity.

Scientists discover how ketamine is so good against depression

Ketamine, a drug generally used for anesthesia, but also for recreational purposes, is now in the spotlight for its promising results in fighting depression. As shown in previous research, ketamine improves depression’s symptoms in a few hours, unlike the rest of anti-depressants, which may take weeks, even months to work. Scientists have now discovered exactly how ketamine so rapidly soothes depression.

Via Wikipedia

 “People have tried really hard to figure out why it’s working so fast, because understanding this could perhaps lead us to the core mechanism of depression,” says Hailan Hu, a neuroscientist at Zhejiang University School of Medicine in Hangzhou, China, and a senior author of the study.

The team believed that ketamine affected a small part of the brain, called the lateral habenula, also known as the “anti–reward center.”

If you are wondering where is the habenula – follow the yellow area in the center of the brain.
Via Wikipedia

Neurons from the lateral habenula are activated by stimuli associated with unpleasant events, like the absence of the reward or punishment, especially when these are unpredictable. To better understand how they work, here is an example: If a rat or a mouse solves a maze, it will expect some form of reward. If the rodent doesn’t get any reward, even though it had successfully completed a task, the neurons from the lateral habenula will fire, thus inhibiting the activity of the reward areas. Researchers believe that these ‘reward-negative’ neurons in the brain are overreactive in depression.

To see if their hypothesis was right, researchers designed an experiment in which they directly infused the drug into the lateral habenula of rats with depression-like symptoms. Scientists discovered that the pattern of neuronal activity, not the overall activity of the lateral habenula was a key factor in triggering depression: a percentage of the neurons in the lateral habenula fire several times in quick bursts, rather than firing once at regular intervals.

These bursts of activity in rats with symptoms of depression are absent in healthy rodents. An analysis of brain slices of healthy rats showed that they only had about 7% of these bursting type of neurons, in comparison to the depressed rodents that had almost 23% bursting neurons.

Scientists found similar results when recording the brain activity of mice: The animals who suffered stressful events had more bursting cells in the lateral habenula. After using optogenetics — a technique that allows cells to be ‘turned on or off’ with the help of light — the mice became more depressed, refusing to swim in a container of water even if forced.

But after the mice and rats were given ketamine, the number of bursting neurons became similar to the one found in healthy animals. Even when the scientists directed the neurons to fire in bursts, animals that had been administered ketamine no longer exhibited symptoms of depression.

“Anything that can block the bursting … should be a potential target based on our model,” Hu says.

In an accompanying study published at the same time in the journal Nature, the team found a protein synthesized by astrocytes (another type of brain cell that interacts closely with neurons) could be one of these targets. This molecule controls the flow of ions between a cell and its environment and it is involved in the process of resetting the nerve cell after an electrical signal, which requires regathering all the ions that flowed out of the cell during the signal.

The protein identified by the research team changes the amount of potassium available to the nerve cell, altering the cell’s ability to fire again soon. By increasing the amount of this protein, researchers were able to induce depression-like symptoms in mice.

The paper published in the journal Nature truly casts light upon the exceptional anti-depressant mechanism of ketamine, also providing us with important insight into further understanding the pathology of depression.

Brain sculpture.

Mitochondria in the brain changed by cocaine use — the findings could help us better fight addictions

Exposure to cocaine leads to significant changes in the mitochondria of certain brain cells, new research reports. They are now investigating whether these changes play a hand in shaping addiction, for both cocaine and other classes of drugs.

Brain sculpture.

Image via Pixabay.

We’ve known that mitochondria embedded in brain cells play a role in brain disorders ranging from depression, generalized anxiety, and exaggerated stress responses, all the way to bipolar disorders. New research by scientists at the University of Maryland School of Medicine (UMSOM) has found that cocaine use also brings about changes in the little cellular powerhouses, with currently-unknown effects.

The team discovered the changes while working with mice. After repeated exposure to cocaine, cells in the rats’ reward pathways (nucleus accumbens, NAc) showed an increase in dynamin-related protein-1 (Drp1), the molecule that underpins mitochondrial division (fission). Higher levels of Drp1 in the mice’s NAc area caused mitochondria to divide — and thus multiply — faster.

[Read More] If you want to freshen up on your brain anatomy and see exactly where the NAc is, take a minute to peruse 3D Brain.

Such changes could, in turn, explain the chemical fluctuations we’ve seen in the brains of addicts. They report having successfully blocked these changes using a chemical dubbed Mdivi-1. Furthermore, they also blocked responses to cocaine by genetically manipulating the fission molecule within the mitochondria of brain cells.

“We are actually showing a new role for mitochondria in cocaine-induced behavior, and it’s important for us to further investigate that role,” said Mary Kay Lobo, Associate Professor of Anatomy and Neurobiology and corresponding author on the paper.

The team later harvested post-mortem brain tissue samples from individuals with a documented cocaine addiction to confirm that the changes also take place in human brains. Dr. Lobo says these findings could help us better understand how addiction impacts the brain, both from cocaine and other addictive substances.

“We are interested to see if there are mitochondrial changes when animals are taking opiates. That is definitely a future direction for the lab,” she added.

The paper “Drp1 Mitochondrial Fission in D1 Neurons Mediates Behavioral and Cellular Plasticity during Early Cocaine Abstinence” has been published in the journal Neuron.

Brain Learning.

Researchers identify brain patterns associated with learning to improve teaching, fight Alzheimer’s

Researchers have identified two different brain-wave patterns that correspond to different types of learning. They hope this discovery will allow us to help people learn faster or counteract the effects of dementia.

Brain Learning.

Image via Pixabay.

Playing the guitar and studying for an exam require two very different types of learning — and now, for the first time, researchers have distinguished each type by looking at the patterns of brain-waves they produce. The findings will go a long way to help researchers understand how our brains learn motor skills and handle complex cognitive tasks.

Firing just right

When neurons activate, their electrical signals combine to form brain waves that oscillate at different frequencies. A team of researchers led by Earl K. Miller, the Picower Professor of Neuroscience, at the Picower Institute for Learning and Memory and the Department of Brain and Cognitive Sciences set out to study how learning impacts these waves and gain a better understanding of how our brains learn.

“Our ultimate goal is to help people with learning and memory deficits,” notes Miller. “We might find a way to stimulate the human brain or optimize training techniques to mitigate those deficits.”

Not so long ago, scientists assumed that all learning is managed equivalently within the brain. That turned out to be wrong, as the famous case of Henry Molaison revealed. In 1953, Molaison had part of his brain removed in an attempt to bring his epileptic seizures under control and developed amnesia. He couldn’t remember eating a few minutes after he finished a meal, but he was still fully capable of learning and retaining motor skills. He, and similar patient cases, would get better at skills such as drawing a five-pointed star in a mirror but could hold no memory of ever performing the task.

Cases like this one demonstrated that our brains rely on two different learning mechanisms, dubbed explicit and implicit. Explicit learning occurs when you’re aware of what you’re learning, you’re thinking about what you’re learning, and, most importantly, you can articulate what it is that you’re learning. Memorizing part of a text or learning the rules of a new game are examples of explicit learning.

Implicit learning is, in broad terms, what you might know as motor skill learning or muscle memory. You don’t have conscious access to what you’re learning, you get better at these skills by practicing, and you can’t really articulate what you’re learning. Learning to ride a skateboard or throwing darts fall under implicit learning processes.

Some other tasks, like learning to play a new piece of music, require both kinds of learning,

All in the brain

Brain sand sculpture.

Image via Pixabay.

 

Evan G. Antzoulatos, paper co-author and a former MIT postdoc currently located at University of California, Davis, studied the behavior of animals learning new skills and found evidence that they also rely on implicit and explicit processes. For example, in tasks that required comparing and matching two objects, the animals appeared to use both correct and incorrect answers to improve their next matches, indicating an explicit form of learning. In tasks where the animals had to move their gaze in one direction or another in response to visual patterns, their performance only improved after correct answers — which would suggest implicit learning.

More importantly, the researchers found that the different types of behavior follow different patterns of brain waves.

Explicit learning tasks caused an increase in alpha2-beta brain waves (a pattern of oscillations at 10 to 30 hertz) following a correct choice and an increase in delta-theta waves (which occur at 3 to 7 hertz) after an incorrect choice. Explicit tasks also resulted in a general increase in alpha2-beta waves, which decreased as learning progressed. Finally, the team noticed neural activity spikes in response to behavioral errors, a phenomenon known as event-related negativity, only occurred in tasks that required explicit learning. This suggests that there is a conscious learning process in which the animals’ brains can ‘tell’ when they made a wrong choice or assumption.

Miller explains that the increase in alpha2-beta waves during explicit learning “could reflect the building of a model of the task,” and that after the animals learn the task, “the alpha-beta rhythms then drop off because the model is already built.”

By contrast, in implicit learning tasks, the team observed increased delta-theta rhythms in response to correct answers and a subsequent decrease in these rhythms during learning. Miller says this pattern could be indicative of “rewiring” to help encode the motor skill during learning.

“This showed us that there are different mechanisms at play during explicit versus implicit learning,” he notes.

Roman F. Loonis, a graduate student in the Miller Lab and first author of the paper, says the findings could open up new avenues of teaching or training people to do specific tasks.

“If we can detect the kind of learning that’s going on, then we may be able to enhance or provide better feedback for that individual,” he says. “For instance, if they are using implicit learning more, that means they’re more likely relying on positive feedback, and we could modify their learning to take advantage of that.”

They could also help detect the onset of disorders such as Alzheimer’s disease at an early age. This disease destroys the brain’s ability to perform explicit learning processes, leaving only implicit learning intact. Finally, the paper shows “a lot of overlap” between implicit and explicit learning, although previous research has found that the two processes are housed in separate areas of the brain.

The paper, entitled “A Meta-Analysis Suggests Different Neural Correlates for Implicit and Explicit Learning”, has been published in the journal Neuron.

 

Left: digital copy of the neocortex. Right: shapes of different geometries, each attempting to represent structures ranging from 1 to 7 dimensions. The structure in the middle that resembles a black hole is a complex of multi-dimensional spaces or cavities. Credit: Frontiers in Computational Neuroscience.

Neurons in the human brain actually form 11-dimensional structures

Our eyes and brain are designed to interpret the world around us from a three-dimensional perspective. Understanding a higher-dimensional world is a stretch of the imagination for most people and no one can actually visualize more than three dimensions — just like a 2-D ‘flat-lander’ has no hope of visualizing 3-D. Neuroscientists, however, claim that our brain, which never ceases to amaze us it seems, is comprised of structures that are seven dimensions, some up to eleven dimensions.

“We found a world that we had never imagined,” says neuroscientist Henry Markram, director of Blue Brain Project and professor at the EPFL in Lausanne, Switzerland, “there are tens of millions of these objects even in a small speck of the brain, up through seven dimensions. In some networks, we even found structures with up to eleven dimensions.”

Left: digital copy of the neocortex. Right: shapes of different geometries, each attempting to represent structures ranging from 1 to 7 dimensions. The structure in the middle that resembles a black hole is a complex of multi-dimensional spaces or cavities. Credit: Frontiers in Computational Neuroscience.

Left: digital copy of the neocortex. Right: shapes of different geometries, each attempting to represent structures ranging from 1 to 7 dimensions. The structure in the middle that resembles a black hole is a complex of multi-dimensional spaces or cavities. Credit: Frontiers in Computational Neuroscience.

The human brain is the least understood of any human body part — not coincidentally, it’s also the most complex. According to Makram and colleagues working with the Blue Brain Project — an initiative that aims to create a digital reconstruction of the brain by reverse-engineering mammalian brain circuitry —  these mind-boggling higher-dimensional structures can partly explain why it’s so hard to understand the brain. But what does that mean, really?

“The progression of activity through the brain resembles a multi-dimensional sandcastle that materializes out of the sand and then disintegrates”

Kathryn Hess from EPFL and Ran Levi from Aberdeen University are skilled in an obscure but edifying branch of mathematics called algebraic topology, the study of the global properties of spaces by means of algebra. To get an idea of what algebraic topology is about, think about the fact that we live on the surface of a sphere but locally this is difficult to distinguish from living on a flat plane. Algebraic topology is concerned with the whole surface and points to the obvious fact that the surface of a sphere is a finite area with no boundary and the flat plane does not have this property.

What makes algebraic topology so powerful has always been its wide degree of applicability to other fields from physics, to number theory, to differential geometry. This is the firs time it has been used in neuroscience, though.

“Algebraic topology is like a telescope and microscope at the same time. It can zoom into networks to find hidden structures – the trees in the forest – and see the empty spaces – the clearings – all at the same time,” explains Hess.

Two years ago, the Blue Brain released the first digital copy of a partial neocortex. The neocortex is the portion of the human brain that is responsible for language and consciousness. It’s the most evolved part of the brain and makes up approximately 76% of the human brain, making it the largest when compared to similar structures in other animals. Now, with the help of algebraic topology, Blue Brain researchers showed that the multi-dimensional brain structures discovered could never be produced by chance, based on studies of the virtual brain. Later, experiments on real brain tissue confirmed the virtual findings suggesting that the brain constantly rewires during development to build a network with as many high-dimensional structures as possible.

Were it not for algebraic topology, the researchers couldn’t have been able to discern highly organized structures hidden in the seemingly chaotic firing patterns of neurons.

The topological diagram shows how groups of neurons form multi-dimensional 'cliques'. Credit: Blue Brain Project.

The topological diagram shows how groups of neurons form multi-dimensional ‘cliques’. Credit: Blue Brain Project.

When a stimulus was made onto the virtual brain tissue, cliques of progressively higher dimensions assembled momentarily to enclose high-dimensional holes or cavities as the researchers refer to them. The more neurons there are in a clique, the higher the ‘dimension’ of the object. Some speculate it’s in these cavities that memories may be stored in the brain.

“The appearance of high-dimensional cavities when the brain is processing information means that the neurons in the network react to stimuli in an extremely organized manner,” says Levi. “It is as if the brain reacts to a stimulus by building then razing a tower of multi-dimensional blocks, starting with rods (1D), then planks (2D), then cubes (3D), and then more complex geometries with 4D, 5D, etc. The progression of activity through the brain resembles a multi-dimensional sandcastle that materializes out of the sand and then disintegrates.”

The team is now trying to understand whether there’s any relation between these multi-dimensional ‘sandcastles’ and cognition.

Findings appeared in the journal Frontiers in Computational Neuroscience

 

Neurons.

Depressed? It might be because your neurons got their branches tangled up

A team of Columbia researchers has found the gene that dictates how serotonin-releasing neurons branch out in the brain. Tests on mice engineered to lack this gene showed that their neurons’ dendrites (branches) became entangled, negatively impacted serotonin distribution in their brains and leading to signs of depression.

Neurons.

Image credits Colin Behrens.

The findings come from the lab of Tom Maniatis, PhD, a principal investigator at Columbia’s Mortimer B. Zuckerman Mind Brain Behavior Institute, the Isidore S. Edelman Professor and Chair of the department of Biochemistry & Molecular Biophysics at Columbia University Medical Center. Initially, Maniatis set out together with his colleagues to find out how individual neurons in the brain keep track of their neighbors so that their thousands of branches wind through the brain without getting tangled up with others.

They focused on a group of genes called clustered protocadherins (Pcdhs), as previous research has shown that these genes stamp barcode-like compounds on the cell’s surface, so each neuron can distinguish themselves from their other neurons. In broad lines, they work like this: each neuron’s Pcdh code is unique. In the case of a contact, each branch compares its code to the one it touches. If it’s the same, they steer clear of each other to avoid entanglements, a process known as self-avoidance.

In two new papers published in the journal Science, Maniatis and his team detail how in the case of olfactory sensory neurons (OSNs), a diverse range of Phcds work together to make up sufficient ‘codes’ to give each neuron its unique identity. But if there isn’t enough Phcd diversity for each neuron to receive a unique code, OSNs fail to wire properly in the brain and the mice can’t distinguish between different smells. The findings show how important neuronal wiring is to overall brain health and its ability to function properly.

Faulty wiring

Through a series of experiments in mice, Dr. Maniatis’ team identified a single gene within the Pcdh cluster, Pcdh-alpha-c2, that was responsible for the ability of serotonergic neurons to assemble into a tiled pattern throughout the brain and evenly distribute serotonin.

“The main job of these neurons is to distribute serotonin uniformly throughout the brain, which is responsible for maintaining mood balance. To do this, the neurons lay their branches out in a precise, evenly-spaced pattern — a process called axonal tiling. However, the exact mechanism that allows them to do this remained elusive,” said Dr. Maniatis, who is also director of Columbia’s Precision Medicine Initiative.

“We were surprised to find that, unlike other neurons that displays distinct barcodes of diverse Pcdhs, all serotonergic neurons display a single functional recognition protein. Thus, serotonergic axonal branches can recognize and repel one another, leading to their even spacing.”

But by deleting the Pcdh-alpha-c2 gene in these neurons, the team was able to make them tangle and clump together. When the cells released serotonin, it wasn’t evenly distributed through the brain, leading to striking changes in behavior. Pcdh-alpha-c2-deficient mice showed a reduced desire to escape (behavioral despair) and enhanced fear memory (increased freezing when frightened) — both classic signs of depression.

Serotonin imbalances have been linked to a range of psychiatric disorders such as depression, bipolar disorder, and schizophrenia. But most research focuses on problems with the production or uptake of serotonin and ignore the problem of neural wiring, Dr. Manitis adds. The results suggest that psychiatric disorders associated with serotonin imbalances — such as depression, bipolar disorder, schizophrenia, and autism — could be caused by errors in this wiring.

The first paper “Multicluster Pcdh diversity is required for mouse olfactory neural circuit assembly” has been published in the journal Science.

The second paper, “Pcdhαc2 is required for axonal tiling and assembly of serotonergic circuitries in mice” has been published in the journal Science.

 

Fungus-derived molecule enables axon regrowth — potentially treating brain and spinal chord injuries

One family of proteins that plants use to combat fungal infections could have an unexpected use: repairing axons — the long thread-like parts of a nerve cell.

Fluorescent bundles of axons.
Image credits Minyoung Choi / Wikipedia.

Axons are the large projections that neurons use to ferry signals to other parts of the body. They’re the main component of white matter, and without them, the nervous communication in the body would grind to a halt. Axonal damage can also lead to a host of disabilities associated with conditions such as spinal cord injury or stroke.

Andrew Kaplan, a PhD candidate at the Montreal Neurological Institute and Hospital of McGill University, was trying to find a substance that could help undo the damage for people suffering these conditions as part of Dr. Alyson Fournier’s team, professor of neurology and neurosurgery and senior author on the study. During his research, he found one family of proteins with neuroprotective functions known as 14-3-3 which could hold the key to creating axon-repairing drugs.

This family of proteins takes on a surprising role in plants which are fighting off a certain fungal strain. The fungus releases a marker molecule called fusicoccin-A. When exposed to this molecule, the plants’ leaves will wilt but their roots grow longer. This happens because fusicoccin-A affects 14-3-3’s normal interaction with other proteins, promoting growth.

“While 14-3-3 is the common denominator in this phenomenon, the identity of the other proteins involved and the resulting biological activities differ between plants and animals,” says Kaplan.

Kaplan’s theory was that fusicoccin-A could be used to harness 14-3-3 for use in repairing axons. He and his team placed mechanically damaged neurons in a culture with the substance and waited to see what happened.

“When I looked under the microscope the following day the axons were growing like weeds, an exciting result that led us to determine that fusicoccin-A can stimulate axon repair in the injured nervous system,” says Kaplan.

Beyond brain or spinal chord injuries, axonal damage also plays a central role in other disorders and diseases, such as multiple sclerosis or neurodegenerative conditions. Fusicoccin-A and similar molecules could become the starting point for a new class of drugs to treat and repair this damage. Kaplan says future research should aim to better understand the underlying mechanism by which fusicoccin-a improves axonal repair, which can be used to develop even more powerful medication.

One protein called GCN1 holds particular promise. The team found that GCN1 and 14-3-3 bonding can be an important factor in the fusicoccin-A-induced growth.

“We have identified a novel strategy to promote axon regeneration with a family of small molecules that may be excellent candidates for future drug development,” says Fournier.

“This is an exciting advance because the field has struggled to find treatments and identify targets for drugs that stimulate axon repair.”

The full paper “Small-Molecule Stabilization of 14-3-3 Protein-Protein Interactions Stimulates Axon Regeneration” has been published in the journal Neuron.

 

 

Man in REM sleep. Credit: Giphy.

During REM sleep, memory is consolidated by weeding out unwanted neural connections

Man in REM sleep. Credit: Giphy.

Man in REM sleep. Credit: Giphy.

Rapid eye movement sleep (REM) is a unique mammalian sleep phase during which the eyes move quickly in different directions. There’s much more going on when you slumber during this phase than just retina gymnastics, though. The brain is more active than in the non-REM phase which is evidenced by intense dreaming that may occur. REM sleep is also known to consolidate learning and memories. It was never clear until recently, however, how this mechanism that transforms temporary memories into permanent looks like in the brain.

Now, a paper published in Nature Neuroscience may have made REM sleep a lot less mysterious. According to experiments carried out by New York University School of Medicine researchers, some neural structures which help form connections get pruned during REM while others are strengthened. In other words, the brain selects which of these structures are allowed to support stronger connections in a timely manner, ultimately causing long-lasting memories to form.

These neural structures in questions are called dendritic spines. They’re small outgrowths found on a neuron’s dendrite — the branched extension of the neuron where impulses received from other cells at synapses are transmitted to the cell body.

The spines aren’t permanent structures. Instead, these will grow, shorten or entirely disappear in time as the importance of different connections changes. This shift in priorities is critical — otherwise, we would never be able to make sense of all the information we absorb on a daily basis. Previous research found up to 10 percent of all new synapses are formed daily but only a smaller number will be stably maintained over time.

A depiction of spine formation and elimination. Credit: Wikimedia Commons.

A depiction of spine formation and elimination. Credit: Wikimedia Commons.

To investigate the functions and underlying mechanisms of REM sleep, the researchers subjected lab mice to motor learning tasks then examined postsynaptic dendritic spines of neurons in the mouse primary motor cortex. Some of the mice were either allowed to enjoy a full night’s rest or deprived of the REM phase.

Mice that had the chance to go through REM sleep cycles showed significantly higher pruning of new dendritic spines compared to the REM-deprived mice. This difference was observed only in the case of new dendritic spines. Previously existing spines were pruned or strengthened at the same rate, signaling that REM was a decisive factor.

The researchers also analyzed how dendritic pruning changes as the mouse ages. They found that neural pruning happens the most frequently during a mouse’s juvenile stage. Pruning occurred during REM sleep later in life too, at adulthood, but less frequently. Without REM sleep, the size of spines that are retained doesn’t grow.

These findings seem to agree with previous work on humans. REM sleep deprivation during development can have a detrimental effect on cognitive development which is why doctors will often tell teens sleep is very important. In adulthood, REM sleep deprivation can cause behavior changes and mood swings.

Calcium channels seem to play a role in the decision-making that leads to the pruning or strengthening of the dendritic spines. Observations suggest sudden changes in the amount of calcium seen during REM sleep can kick start the selection process. When calcium channels were blocked, no selection occurred.

“More study is needed to investigate whether REM sleep has similar or different roles in regulating synapse development and plasticity of other types of neurons in different cortical layers and brain regions, ” the researchers wrote in their paper.

Scientists discover ‘hunting circuits’ that can turn fuzzy rats into fuzzy murderous rats

Two sets of neurons have been identified in the amygdala that, when activated, can turn mice into highly effective killers, a new study reports. The findings could help determine how hunting behavior evolved, hundred of millions of years ago.

Image credits Alexas_Fotos / Pixabay.

Here’s one the conspiracy theorists will love.

A team from Yale university have managed to hack the brains of mice into highly efficient killing machines. They ramped up the animals’ aggression by activating two sets of neurons in their amygdala, the paper states.

“The animals become very efficient in hunting,” says Ivan de Araujo, associate professor of psychiatry at Yale University and an associate fellow at The John B. Pierce Laboratory in New Haven.

“They pursue the prey [a live cricket] faster and they are more capable of capturing and killing it.”

Tampering with these neurons caused the mice to attack even inanimate objects — sticks, bottle caps, and an insect-like toy. Dr De Araujo says that the animals bit the toy “intensively” and even used “their forepaws in an attempt to kill it.”

Bloodlust, but with manners

The mice saved their aggressiveness only for prey, as De Araujo reports that the furry rodents didn’t attack one another even with both sets of neurons activated. These results offer a glimpse into how the brain changed hundreds of millions of years ago when jaws first developed. It was the first time any brain had an efficient tool with which to kill prey, a change that “must have influenced the way the brain is wired up in a major way,” De Araujo says.

Just like the military has a chain of command to make sure everything is where it’s supposed to be in battle, brains needed to re-wire to allow for specialized hunting circuits. These serve to govern and coordinate the movements of predators’ jaws and neck muscles, turning a clumsy beast into a deadly predator.

“This is a very complex and demanding task,” De Araujo says.

The team used mice since we know these animals are predatory — they hunt and eat whatever they can, really, mostly insects and worms. One species, in particular, is known as the killer mouse for its habit of feeding on live prey, even other mice at times.

By watching brain scans of hunting mice, they discovered one set of neurons that activated when chasing prey and another that would flare up when biting or killing something. Both of these bundles of neurons are located in the amygdala, which is involved in regulating emotion and motivation.

The next step was to use optogenetics to create mice in which these sets of neurons could be activated using a laser.

“When we stimulate [both sets of] neurons […] they assume the body posture and actions usually associated with real hunting

“It is as if there is a prey in front of the animal,” De Araujo says.

The team found evidence of similar “hunting circuits” in other species that relied on hunting to survive — including humans.

Knowing how the brain processes hunting and killing gives us a glimpse of how — and when — these behaviors evolved. It might also help us understand how aggression, in general, is handled by the brain.

The paper “Integrated Control of Predatory Hunting by the Central Nucleus of the Amygdala” has been published in the journal Cell.

Opposing

Memories for opposing behaviors are stored in the same parts of the brain, study finds

The same brain region can both motivate us to undertake a learned behavior or suppress it altogether, a new study found. The results will help us better understand how our brain stores memories and how they’re called upon when needed.

Opposing

Image credits Gerd Altmann / Pixabay.

While there is a general consensus that different memories are stored in different areas of the brain, there has been a lot of debate if each area can hold contradicting memories — those that control opposing behavior. For example, are the behaviors for a red or green traffic light encoded in the same area of the brain?

Pushing both ways

Questions like this one may seem a bit like nit-picking, but they’re actually really important in understanding us and our minds. Memories make us who we are. They’re also what the brain relies on to decide when and whether to take an action. So scientists are obviously keen on understanding how they work.

A new study from The Scripps Research Institute comes to answer this question. It is the first to offer proof that the same brain region can both motivate and suppress the same learned behavior.

“We behave the way we do in a specific situation because we have learned an association — a memory — tying an environmental cue to a behavior,” said Nobuyoshi Suto, TSRI Assistant Professor of Molecular and Cellular Neuroscience and co-author of the study.

“This study provides causal evidence that one brain region can store different memories.”

Suto’s work focuses on the brain structures that control motivation. For the study, he and the team trained rats to press a lever to get a reward of sugar water. After they got this down (the rats caught on pretty fast) the researchers further trained the animals to recognize two colored lights: green if the reward was available when pressing the lever, red if they would receive none. The rats quickly started adjusting their behavior after training in response to the colors. They pressed the lever more often when the green light was on, and didn’t bother with it when the red one was shining.

Based on previous electrophysiology studies, the team suspected that the mice’s brains stored both sessions of training they received in a region of the brain called the infralimbic cortex.

“We’ve seen correlational evidence, where we see brain activity together with a behavior, and we connect the dots to say it must be this brain activity causing this behavior,” said Suto.

“But such correlational evidence alone cannot establish the causality — proof that the specific brain activity is directly controlling the specific behavior.”

A weapon against addiction

The scientists then started systematically switching off specific groups of brain cells, or ‘neural ensembles’. These ensembles react to ques signaling if the reward is available or not. With the neurons inactivated, the rats didn’t perform any of the behavior encoded in the memories of those ensembles.

This proves that distinct neural ensembles in the same region of the brain directly control reward-seeking behavior or its suppression. Suto called the findings a step towards understanding how different memories are stored in the brain. He says the findings could help battle addiction by discovering which neurons are activated to motivate or prevent drug relapse.

In the future, he’d like to look at what other brain regions these infralimbic cortex neurons may be communicating with. In addition, he also would like to determine the brain chemicals mediating the promotion or suppression of reward seeking.

The full paper “Distinct memory engrams in the infralimbic cortex of rats control opposing environmental actions on a learned behavior” has been published in the journal eLife.

Scientists may have witnessed how memories form in real time — a first

A new study of mice brains might give us our first glimpse into how memories are formed in the brain.

Memory in the making.
Image credits Susanne Reichinnek / Institut de neurobiologie de la mediterranee.

Our brains assign certain neurons to keep track of where we are, the path we took and how far we’ve traveled to get here. Researchers have long been curious to see exactly how they handle this process, but we’ve never been able to actually see the magic happening.

A team from the Institut de Neurobiologie de la Méditerranée in Marseille, France, has found a way to do just that. The team worked with rats — whose brains also have “placekeeping” neurons — to study how memories are formed. These cells are known to fire in sequence when a rat is resting, said Rosa Cossart, as if the animal’s brain was retracing its steps. She believes that this process underlies the formation of memories — but, without any way to accurately map the activity of a large enough number of these neurons, its actual purpose has so far remained unclear.

For decades now, researchers have suspected that these cells fire together in small groups, but nobody could really look at them, she adds.

To study their behavior, Cossart and her team added a fluorescent protein to the neurons of four mice. This protein shines brightest when calcium ions flood into the neuron — the chemical process of a neuron “firing”. Using this fluorescence, they mapped neural activity on a much larger scale and with greater precision than previous techniques, which relied on implanted electrodes.

They analyzed the activity of more than a thousand neurons per mouse while the animal was walking on a treadmill or standing still. While the animals were running, the neurons responsible for tracing distance fired in a sequential pattern, keeping track of the movements. The same neurons also activated when the mice were resting but the pattern was different, Cossart found. They fired in the same sequence as they had when the animals were running, only much faster. And rather than firing in turn, they fired together in sequential blocks, each one reflecting a chunk of the original episode that the mouse experienced.

“We’ve been able to image the individual building-blocks of memory,” Cossart says.

The neurons handling each piece of the memory aren’t all bunched together in the brain — they’re strewn all over the hippocampus. But each one of their activations showed a clear and strong association with other neurons that helped record the memory.

But Cossart’s findings haven’t been universally accepted. George Dragoi at Yale University isn’t sure if what she’s recorded are actually memories being formed — for all we know, the mice may not even have any recollection of the time they ran on the treadmills, he said for New Scientist. The neuron groups that fired while the animals were resting may have just been default brain activity. Kamran Diba of Wisconsin University, Milwaukee, finds it surprising that the mice’s brains would first process the experience as continuous and in separate segments later on.

“The cells essentially fire in order throughout the run,” says Diba. “So why would it break down into discrete assemblies?”

It would be interesting to see some more research done to confirm whether the study’s findings are accurate. Do the brains of other animals, including ourselves, behave the same way? And if so, could this memory fragmentation process be what allows us to dream?

The full paper “Awake hippocampal reactivations project onto orthogonal neuronal assemblies” has been published in the journal Science.