neuronal circuit

When somebody says "the man determines the sex of the baby. you can't be trans because it doesn't exist. it's simple science you can't go against biology." this is what I tell them.

“You’re right, and you’re wrong. It’s actually not simple at all. On average, fertilization occurs about two weeks after your last menstrual period. When the sperm penetrates the egg, changes occur in the protein coating around it to prevent other sperm from entering. At the moment of fertilization, your baby’s genetic make-up is complete, including its sex.

If a Y sperm fertilizes the egg, your baby will be a boy; if an X sperm fertilizes the egg, your baby will be a girl. In that sense you are technically right, but gender is determined by so much more than that. We all know that a man’s brain is different to that of his female counterpart, right?” By which point the person who I’m talking to agrees. then I go on to say.

“In month 3 of Pregnancy

the baby has grown from embryo to fetus. by now the baby’s arms, hands, fingers, feet, and toes are fully formed. the baby can open and close its fists and mouth. Fingernails and toenails are beginning to develop and the external ears are formed. The beginnings of teeth are forming, and the baby’s reproductive organs are also developing, but the baby’s gender is difficult to distinguish on ultrasound, because the genitalia start out the same. Differentiation of the male and female reproductive systems does not occur until this crucial fetal period of development.

It is believed by scientists that during the intrauterine period the fetal brain develops in the male direction through a direct action of testosterone on the developing nerve cells, or in the female direction through the absence of this hormone surge. According to this concept, our gender identity (the conviction of belonging to the male or female gender) and sexual orientation should be programmed into our brain structures when we are still in the womb. However, since sexual differentiation of the genitals takes place in the beginning of the third trimester, (The third month of pregnancy) and sexual differentiation of the brain starts in the second half of pregnancy, these two processes can be influenced independently, which may result in trans-sexuality. This also means that in the event of ambiguous sex at birth, the degree of masculinization of the genitals may not reflect the degree of masculinization of the brain. There is no proof that social environment after birth has an effect on gender identity or sexual orientation. Data on genetic and hormone independent influence on gender identity are presently divergent and do not provide convincing information about the underlying etiology. To what extent fetal programming may determine sexual orientation is also a matter of discussion. A number of studies show patterns of sex atypical cerebral dimorphism in homosexual subjects. Although the crucial question, namely how such complex functions as sexual orientation and identity are processed in the brain remains unanswered, emerging data point at a key role of specific neuronal circuits involving the hypothalamus. So yes you are right, it is biology I’m not fighting anything other than ignorance.”


lexie grey appreciation week: Day 7 → au: where lexie didn’t die // team neuro

Neuroscience (or neurobiology) is the scientific study of the nervous system. It is a multidisciplinary branch of biology, that deals with the anatomy, biochemistry, molecular biology, and physiology of neurons and neural circuits.

Neuroscientists rewire brain of one species to have connectivity of another

Scientists at Georgia State University have rewired the neural circuit of one species and given it the connections of another species to test a hypothesis about the evolution of neural circuits and behavior.

Neurons are connected to each other to form networks that underlie behaviors. Drs. Akira Sakurai and Paul Katz of Georgia State’s Neuroscience Institute study the brains of sea slugs, more specifically nudibranchs, which have large neurons that form simple circuits and produce simple behaviors. In this study, they examined how the brains of these sea creatures produce swimming behaviors. They found that even though the brains of two species – the giant nudibranch and the hooded nudibranch – had the same neurons, and even though the behaviors were the same, the wiring was different.

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Balancing Time and Space in the Brain: A New Model Holds Promise for Predicting Brain Dynamics

For as long as scientists have been listening in on the activity of the brain, they have been trying to understand the source of its noisy, apparently random, activity. In the past 20 years, “balanced network theory” has emerged to explain this apparent randomness through a balance of excitation and inhibition in recurrently coupled networks of neurons. A team of scientists has extended the balanced model to provide deep and testable predictions linking brain circuits to brain activity.

Lead investigators at the University of Pittsburgh say the new model accurately explains experimental findings about the highly variable responses of neurons in the brains of living animals. On Oct. 31, their paper, “The spatial structure of correlated neuronal variability,” was published online by the journal Nature Neuroscience.

The new model provides a much richer understanding of how activity is coordinated between neurons in neural circuits. The model could be used in the future to discover neural “signatures” that predict brain activity associated with learning or disease, say the investigators.

“Normally, brain activity appears highly random and variable most of the time, which looks like a weird way to compute,” said Brent Doiron, associate professor of mathematics at Pitt, senior author on the paper, and a member of the University of Pittsburgh Brain Institute (UPBI). “To understand the mechanics of neural computation, you need to know how the dynamics of a neuronal network depends on the network’s architecture, and this latest research brings us significantly closer to achieving this goal.”

Earlier versions of the balanced network theory captured how the timing and frequency of inputs—excitatory and inhibitory—shaped the emergence of variability in neural behavior, but these models used shortcuts that were biologically unrealistic, according to Doiron.

“The original balanced model ignored the spatial dependence of wiring in the brain, but it has long been known that neuron pairs that are near one another have a higher likelihood of connecting than pairs that are separated by larger distances. Earlier models produced unrealistic behavior—either completely random activity that was unlike the brain or completely synchronized neural behavior, such as you would see in a deep seizure. You could produce nothing in between.”

In the context of this balance, neurons are in a constant state of tension. According to co-author Matthew Smith, assistant professor of ophthalmology at Pitt and a member of UPBI, “It’s like balancing on one foot on your toes. If there are small overcorrections, the result is big fluctuations in neural firing, or communication.”

The new model accounts for temporal and spatial characteristics of neural networks and the correlations in the activity between neurons—whether firing in one neuron is correlated with firing in another. The model is such a substantial improvement that the scientists could use it to predict the behavior of living neurons examined in the area of the brain that processes the visual world.

After developing the model, the scientists examined data from the living visual cortex and found that their model accurately predicted the behavior of neurons based on how far apart they were. The activity of nearby neuron pairs was strongly correlated. At an intermediate distance, pairs of neurons were anticorrelated (When one responded more, the other responded less.), and at greater distances still they were independent.

“This model will help us to better understand how the brain computes information because it’s a big step forward in describing how network structure determines network variability,” said Doiron. “Any serious theory of brain computation must take into account the noise in the code. A shift in neuronal variability accompanies important cognitive functions, such as attention and learning, as well as being a signature of devastating pathologies like Parkinson’s disease and epilepsy.”

While the scientists examined the visual cortex, they believe their model could be used to predict activity in other parts of the brain, such as areas that process auditory or olfactory cues, for example. And they believe that the model generalizes to the brains of all mammals. In fact, the team found that a neural signature predicted by their model appeared in the visual cortex of living mice studied by another team of investigators.

“A hallmark of the computational approach that Doiron and Smith are taking is that its goal is to infer general principles of brain function that can be broadly applied to many scenarios. Remarkably, we still don’t have things like the laws of gravity for understanding the brain, but this is an important step for providing good theories in neuroscience that will allow us to make sense of the explosion of new experimental data that can now be collected,” said Nathan Urban, associate director of UPBI.

Les larmes viennent arroser des fleurs qui se trouvent à l'intérieur de mon âme
J'ai brûlé mon circuit neuronal à une époque de ma vie peu loquace
Quand ils me demandaient si je me droguais, je leur parlais de la musique
Parce que j'adore m'abrutir avec elle, me l'enveler serait un supplice
Je ne veux pas gaspiller mon temps à devenir ce que je suis déjà
J'ai dans ma tête un idéal qui est moi, sans mes penchants négatifs
—  Lonepsi

My mind lately
a graveyard 
of things buried and untold,
only nobody is mourning anymore.
There are grape vines and sometimes
pigeons fly above and land only for a moment 
but they’re not mourning either. 
I wonder if anything can truly die if
it never once existed outside of neuronal circuits and
badly scribbled words on cafe napkins
hoping to be discovered.

My nails lately
a graveyard
of dust and the memory of orange trees
that i tried scratching away but in silence,
perhaps because i was never asked and i wonder 
how many answers were not once questioned into existence.
I’m waiting for a full moon to come,
a zombie apocalypse of a kind
where graves crack open and hollywood-like monsters
come crawling out and then
i’ll finally sit down and sketch
the faces of all my poems.      

Scientists use magnetic fields to remotely stimulate brain -- and control body movements

The minimally invasive technique could lead to advances in mapping the brain and treating neurological disease

Scientists have used magnetism to activate tiny groups of cells in the brain, inducing bodily movements that include running, rotating and losing control of the extremities – an achievement that could lead to advances in studying and treating neurological disease.

The technique researchers developed is called magneto-thermal stimulation. It gives neuroscientists a powerful new tool: a remote, minimally invasive way to trigger activity deep inside the brain, turning specific cells on and off to study how these changes affect physiology.

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Supporting the damaged brain

A new study shows that embryonic nerve cells can functionally integrate into local neural networks when transplanted into damaged areas of the visual cortex of adult mice.

(Image caption: Neuronal transplants (blue) connect with host neurons (yellow) in the adult mouse brain in a highly specific manner, rebuilding neural networks lost upon injury. Credit: Sofia Grade, LMU/Helmholtz Zentrum München)

When it comes to recovering from insult, the adult human brain has very little ability to compensate for nerve-cell loss. Biomedical researchers and clinicians are therefore exploring the possibility of using transplanted nerve cells to replace neurons that have been irreparably damaged as a result of trauma or disease. Previous studies have suggested there is potential to remedy at least some of the clinical symptoms resulting from acquired brain disease through the transplantation of fetal nerve cells into damaged neuronal networks. However, it is not clear whether transplanted intact neurons can be sufficiently integrated to result in restored function of the lesioned network. Now researchers based at LMU Munich, the Max Planck Institute for Neurobiology in Martinsried and the Helmholtz Zentrum München have demonstrated that, in mice, transplanted embryonic nerve cells can indeed be incorporated into an existing network in such a way that they correctly carry out the tasks performed by the damaged cells originally found in that position. Such work is of importance in the potential treatment of all acquired brain disease including neurodegenerative illnesses such as Alzheimer‘s or Parkinson’s disease, as well as strokes and trauma, given each disease state leads to the large-scale, irreversible loss of nerve cells and the acquisition of a what is usually a lifelong neurological deficit for the affected person.

In the study published in Nature, researchers of the Ludwig Maximilians University Munich, the Max Planck Institute of Neurobiology, and the Helmholtz Zentrum München have specifically asked whether transplanted embryonic nerve cells can functionally integrate into the visual cortex of adult mice. “This region of the brain is ideal for such experiments,” says Magdalena Götz, joint leader of the study together with Mark Hübener. Hübener is a specialist in the structure and function of the mouse visual cortex in Professor Tobias Bonhoeffer’s Department (Synapses – Circuits – Plasticity) at the MPI for Neurobiology. As Hübener explains, “we know so much about the functions of the nerve cells in this region and the connections between them that we can readily assess whether the implanted nerve cells actually perform the tasks normally carried out by the network.” In their experiments, the team transplanted embryonic nerve cells from the cerebral cortex into lesioned areas of the visual cortex of adult mice. Over the course of the following weeks and months, they monitored the behavior of the implanted, immature neurons by means of two-photon microscopy to ascertain whether they differentiated into so-called pyramidal cells, a cell type normally found in the area of interest. “The very fact that the cells survived and continued to develop was very encouraging,” Hübener remarks. “But things got really exciting when we took a closer look at the electrical activity of the transplanted cells.” In their joint study, PhD student Susanne Falkner and Postdoc Sofia Grade were able to show that the new cells formed the synaptic connections that neurons in their position in the network would normally make, and that they responded to visual stimuli.

The team then went on to characterize, for the first time, the broader pattern of connections made by the transplanted neurons. Astonishingly, they found that pyramidal cells derived from the transplanted immature neurons formed functional connections with the appropriate nerve cells all over the brain. In other words, they received precisely the same inputs as their predecessors in the network. In addition, they were able to process that information and pass it on to the downstream neurons which had also differentiated in the correct manner. “These findings demonstrate that the implanted nerve cells have integrated with high precision into a neuronal network into which, under normal conditions, new nerve cells would never have been incorporated,” explains Götz, whose work at the Helmholtz Zentrum and at LMU focuses on finding ways to replace lost neurons in the central nervous system. The new study reveals that immature neurons are capable of correctly responding to differentiation signals in the adult mammalian brain and can close functional gaps in an existing neural network.

The Genes and Neural Circuits Behind Autism’s Impaired Sociability

Researchers at Beth Israel Deaconess Medical Center (BIDMC) have gained new insight into the genetic and neuronal circuit mechanisms that may contribute to impaired sociability in some forms of Autism Spectrum Disorder. Led by Matthew P. Anderson, MD, PhD, Director of Neuropathology at BIDMC, the scientists determined how a gene linked to one common form of autism works in a specific population of brain cells to impair sociability. The research, published in the journal Nature, reveals the neurobiological control of sociability and could represent important first steps toward interventions for patients with autism.

Anderson and colleagues focused on the gene UBE3A, multiple copies of which causes a form of autism in humans (called isodicentric chromosome 15q). Conversely, the lack of this same gene in humans leads to a developmental disorder called Angelman’s syndrome, characterized by increased sociability. In previous work, Anderson’s team demonstrated that mice engineered with extra copies of the UBE3A gene show impaired sociability, as well as heightened repetitive self-grooming and reduced vocalizations with other mice.

“In this study, we wanted to determine where in the brain this social behavior deficit arises and where and how increases of the UBE3A gene repress it,” said Anderson, who is also an Associate Professor in the Program in Neuroscience at Harvard Medical School and Director of Autism BrainNET Boston Node. “We had tools in hand that we built ourselves. We not only introduced the gene into specific brain regions of the mouse, but we could also direct it to specific cell types to test which ones played a role in regulating sociability.”

When Anderson and colleagues compared the brains of the mice engineered to model autism to those of normal – or wild type (WT) – mice, they observed that the increased UBE3A gene copies interacted with nearly 600 other genes. After analyzing and comparing protein interactions between the UBE3A regulated gene and genes altered in human autism, the researchers noticed that increased doses of UBE3A repressed Cerebellin genes.

Cerebellin is a family of genes that physically interact with other autism genes to form glutamatergic synapses, the junctions where neurons communicate with each other via the neurotransmitter glutamate. The researchers chose to focus on one of them, Cerebellin 1 (CBLN1), as the potential mediator of UBE3A’s effects. When they deleted CBLN1 in glutamate neurons, they recreated the same impaired sociability produced by increased UBE3A.
“Selecting Cerebellin 1 out of hundreds of other potential targets was something of a leap of faith,” Anderson said. “When we deleted the gene and were able to reconstitute the social deficits, that was the moment we realized we’d hit the right target. Cerebellin 1 was the gene repressed by UBE3A that seemed to mediate its effects.”

In another series of experiments, Anderson and colleagues demonstrated an even more definitive link between UBE3A and CBLN1. Seizures are a common symptom among people with autism including this genetic form. Seizures themselves when sufficiently severe, also impaired sociability. Anderson’s team suspected this seizure-induced impairment of sociability was the result of repressing the Cerebellin genes. Indeed, the researchers found that deleting UBE3A, upstream from Cerebellin genes, prevented the seizure-induced social impairments and blocked seizures ability to repress CBLN1.

“If you take away UBE3A, seizures can’t repress sociability or Cerebellin,” said Anderson. “The flip side is, if you have just a little extra UBE3A – as a subset of people with autism do – and you combine that with less severe seizures - you can get a full-blown loss of social interactions.”

The researchers next conducted a variety of brain mapping experiments to locate where in the brain these crucial seizure-gene interactions take place.

“We mapped this seat of sociability to a surprising location,“ Anderson explained. Most scientists would have thought they take place in the cortex – the area of the brain where sensory processing and motor commands take place – but, in fact, these interactions take place in the brain stem, in the reward system.”

Then the researchers used their engineered mouse model to confirm the precise location, the ventral tegmental area (VTA), part of the midbrain that plays a role in the reward system and addiction. Anderson and colleagues used chemogenetics – an approach that makes use of modified receptors introduced into neurons that responds to drugs, but not to naturally-occurring neurotransmitters – to switch this specific group of neurons on or off. Turning these neurons on could magnify sociability and rescue seizure and UBE3A-induced sociability deficits.

“We were able to abolish sociability by inhibiting these neurons and we could magnify and prolong sociability by turning them on,” said Anderson. “So we have a toggle switch for sociability. It has a therapeutic flavor; someday, we might be able to translate this into a treatment that will helps patients.”

Scientists Outline How Brain Separates Relevant & Irrelevant Information

Imagine yourself sitting in a noisy café trying to read. To focus on the book at hand, you need to ignore the surrounding chatter and clattering of cups, with your brain filtering out the irrelevant stimuli coming through your ears and “gating” in the relevant ones in your vision—words on a page.

In a new paper in the journal Nature Communications, New York University researchers offer a new theory, based on a computational model, on how the brain separates relevant from irrelevant information in these and other circumstances.

“It is critical to our everyday life that our brain processes the most important information out of everything presented to us,” explains Xiao-Jing Wang, Global Professor of Neural Science at NYU and NYU Shanghai and the paper’s senior author. “Within an extremely complicated neural circuit in the brain, there must be a gating mechanism to route relevant information to the right place at the right time.”

The analysis focuses on inhibitory neurons—the brain’s traffic cops that help ensure proper neurological responses to incoming stimuli by suppressing other neurons and working to balance excitatory neurons, which aim to stimulate neuronal activity.

“Our model uses a fundamental element of the brain circuit, involving multiple types of inhibitory neurons, to achieve this goal,” Wang adds. “Our computational model shows that inhibitory neurons can enable a neural circuit to gate in specific pathways of information while filtering out the rest.”

In their analysis, led by Guangyu Robert Yang, a doctoral candidate in Wang’s lab, the researchers devised a model that maps out a more complicated role for inhibitory neurons than had previously been suggested.

Of particular interest to the team was a specific subtype of inhibitory neurons that targets the excitatory neurons’ dendrites—components of a neuron where inputs from other neurons are located. These dendrite-targeting inhibitory neurons are labeled by a biological marker called somatostatin and can be studied selectively by experimentalists. The researchers proposed that they not only control the overall inputs to a neuron, but also the inputs from individual pathways—for example, the visual or auditory pathways converging onto a neuron.

“This was thought to be difficult because the connections from inhibitory neurons to excitatory neurons appeared dense and unstructured,” observes Yang. “Thus a surprising finding from our study is that the precision required for pathway-specific gating can be realized by inhibitory neurons.”

The study’s authors used computational models to show that even with the seemingly random connections, these dendrite-targeting neurons can gate individual pathways by aligning with excitatory inputs through different pathways. They showed that this alignment can be realized through synaptic plasticity—a brain mechanism for learning through experience.

Can the brain feel it? The world’s smallest extracellular needle-electrodes

A research team in the Department of Electrical and Electronic Information Engineering and the Electronics-Inspired Interdisciplinary Research Institute (EIIRIS) at Toyohashi University of Technology developed 5-μm-diameter needle-electrodes on 1 mm × 1 mm block modules. This tiny needle may help solve the mysteries of the brain and facilitate the development of a brain-machine interface. The research results were reported in Scientific Reports
on Oct 25, 2016.

(Image caption: Extracellular needle-electrode with a diameter of 5 μm mounted on a connector)

The neuron networks in the human brain are extremely complex. Microfabricated silicon needle-electrode devices were expected to be an innovation that would be able to record and analyze the electrical activities of the microscale neuronal circuits in the brain.

However, smaller needle technologies (e.g., needle diameter < 10 μm) are necessary to reduce damage to brain tissue. In addition to the needle geometry, the device substrate should be minimized not only to reduce the total amount of damage to tissue but also to enhance the accessibility of the
electrode in the brain. Thus, these electrode technologies will realize new experimental neurophysiological concepts.

A research team in the Department of Electrical and Electronic Information Engineering and the EIIRIS at Toyohashi University of Technology developed 5-
μm-diameter needle-electrodes on 1 mm × 1 mm block modules.

The individual microneedles are fabricated on the block modules, which are small enough to use in the narrow spaces present in brain tissue; as demonstrated in the recording using mouse cerebrum cortices. In addition, the block module remarkably improves the design variability in the packaging, offering numerous in vivo recording applications.

“We demonstrated the high design variability in the packaging of our electrode device, and in vivo neuronal recordings were performed by simply placing the device on a mouse’s brain. We were very surprised that high quality signals of a single unit were stably recorded over a long period using the 5-μm-diameter needle,” explained the first author, Assistant Professor Hirohito Sawahata, and co-author, researcher Shota Yamagiwa.

The leader of the research team, Associate Professor Takeshi Kawano said: “Our silicon needle technology offers low invasive neuronal recordings and provides novel methodologies for electrophysiology; therefore, it has the potential to enhance experimental neuroscience.” He added, “We expect the development of applications to solve the mysteries of the brain and the development of brain–machine interfaces.”

Scientists Develop Computer Model Explaining How Brain Learns to Categorize

New York University researchers have devised a computer model to explain how a neural circuit learns to classify sensory stimuli into discrete categories, such as “car vs. motorcycle.” Their findings, which appear in the journal Nature Communication, shed new light on the brain processes underpinning judgments we make on a daily basis.

“Categorization is vital for survival, such as distinguishing food from inedible things, as well as for formation of concepts, for instance ‘dog vs. cat,’ and relationship between concepts, such as hierarchical classification of animals,” says author Xiao-Jing Wang, Global Professor of Neural Science, Physics, and Mathematics at NYU and NYU Shanghai. “Our proposed model can only explain category learning of simple visual stimuli. Future research is needed to explore if the general principles extracted from this model are applicable to more complex categorizations.”

Wang conducted the study with Tatiana Engel, a postdoctoral associate at the time of the study, and Jah Chaisangmongkon, a doctoral candidate in his group, in collaboration with experimentalist David Freedman, a neurobiologist at the University of Chicago. Freedman had previously developed a behavioral paradigm for investigating electrical activity of single-neurons that are correlated with category memberships of visual stimuli.

In this neural-circuit model, which incorporates what we know about the organization and neurophysiology of the cortex, lower-level neural circuits send information about visual stimuli to a higher-level neural circuit where an analog stimulus feature (like the direction of a random pattern of moving dots) is classified into binary categories (A or B). The researchers’ results showed that the model captured a wide range of experimental observations and yielded specific predictions that were confirmed by an analysis of single-neuron electrical activity recorded in a category-learning experiment.

Interestingly, the researchers found that learning a correct category boundary (dividing the continuous feature into A and B) requires top-down feedback projection from category-selective neurons to feature-coding neurons.

Since the pioneering work by NYU’s J. Anthony Movshon, Stanford’s William Newsome, and others, it has been well known that feature-coding sensory neurons reflect an animal’s choice about categorical membership (A or B) of a stimulus in a probabilistic way (quantified as “choice probability”). The common belief was that this is because a category choice is influenced by stochastic, or random, activity of sensory neurons through bottom-up, sensory-to-category pathways.

The new model, reported in the Nature Communications article, suggests a novel interpretation, namely that such “choice probability” results from category-to-sensory, top-down signaling.

This finding offers new insights into feedback projections in the brain whose functional significance had previously been a long-standing puzzle, the researchers note.

How Traumatic Memories Hide In The Brain, And How To Retrieve Them

Some stressful experiences – such as chronic childhood abuse – are so overwhelming and traumatic, the memories hide like a shadow in the brain.

At first, hidden memories that can’t be consciously accessed may protect the individual from the emotional pain of recalling the event. But eventually those suppressed memories can cause debilitating psychological problems, such as anxiety, depression, post-traumatic stress disorder or dissociative disorders.

A process known as state-dependent learning is believed to contribute to the formation of memories that are inaccessible to normal consciousness. Thus, memories formed in a particular mood, arousal or drug-induced state can best be retrieved when the brain is back in that state.

In a new study with mice, Northwestern Medicine scientists have discovered for the first time the mechanism by which state-dependent learning renders stressful fear-related memories consciously inaccessible.

“The findings show there are multiple pathways to storage of fear-inducing memories, and we identified an important one for fear-related memories,” said principal investigator Dr. Jelena Radulovic, the Dunbar Professor in Bipolar Disease at Northwestern University Feinberg School of Medicine. “This could eventually lead to new treatments for patients with psychiatric disorders for whom conscious access to their traumatic memories is needed if they are to recover.”

It’s difficult for therapists to help these patients, Radulovic said, because the patients themselves can’t remember their traumatic experiences that are the root cause of their symptoms.

The best way to access the memories in this system is to return the brain to the same state of consciousness as when the memory was encoded, the study showed.

The study was published August 17 in Nature Neuroscience.

Changing the Brain’s Radio Frequencies

Two amino acids, glutamate and GABA, are the yin and yang of the brain, directing its emotional tides and controlling whether nerve cells are excited or inhibited (calm). Under normal conditions the system is balanced. But when we are hyper-aroused and vigilant, glutamate surges. Glutamate is also the primary chemical that helps store memories in our neuronal networks in a way that they are easy to remember.

GABA, on the other hand, calms us and helps us sleep, blocking the action of the excitable glutamate. The most commonly used tranquilizing drug, benzodiazepine, activates GABA receptors in our brains.

There are two kinds of GABA receptors. One kind, synaptic GABA receptors, works in tandem with glutamate receptors to balance the excitation of the brain in response to external events such as stress.

The other population, extra-synaptic GABA receptors, are independent agents. They ignore the peppy glutamate. Instead, their job is internally focused, adjusting brain waves and mental states according to the levels of internal chemicals, such as GABA, sex hormones and micro RNAs. Extra-synaptic GABA receptors change the brain’s state to make us aroused, sleepy, alert, sedated, inebriated or even psychotic. However, Northwestern scientists discovered another critical role; these receptors also help encode memories of a fear-inducing event and then store them away, hidden from consciousness.

“The brain functions in different states, much like a radio operates at AM and FM frequency bands,” Radulovic said. “It’s as if the brain is normally tuned to FM stations to access memories, but needs to be tuned to AM stations to access subconscious memories. If a traumatic event occurs when these extra-synaptic GABA receptors are activated, the memory of this event cannot be accessed unless these receptors are activated once again, essentially tuning the brain into the AM stations.”

Retrieving Stressful Memories in Mice

In the experiment, scientists infused the hippocampus of mice with gaboxadol, a drug that stimulates extra-synaptic GABA receptors. “It’s like we got them a little inebriated, just enough to change their brain state,” Radulovic said.

Then the mice were put in a box and given a brief, mild electric shock. When the mice were returned to the same box the next day, they moved about freely and weren’t afraid, indicating they didn’t recall the earlier shock in the space. However, when scientists put the mice back on the drug and returned them to the box, they froze, fearfully anticipating another shock.

“This establishes when the mice were returned to the same brain state created by the drug, they remembered the stressful experience of the shock,” Radulovic said.

The experiment showed when the extra-synaptic GABA receptors were activated with the drug, they changed the way the stressful event was encoded. In the drug-induced state, the brain used completely different molecular pathways and neuronal circuits to store the memory.

“It’s an entirely different system even at the genetic and molecular level than the one that encodes normal memories,” said lead study author Vladimir Jovasevic, who worked on the study when he was a postdoctoral fellow in Radulovic’s lab.

This different system is regulated by a small microRNA, miR-33, and may be the brain’s protective mechanism when an experience is overwhelmingly stressful.

The findings imply that in response to traumatic stress, some individuals, instead of activating the glutamate system to store memories, activate the extra-synaptic GABA system and form inaccessible traumatic memories.

Traumatic Memories Rerouted and Hidden Away

Memories are usually stored in distributed brain networks including the cortex, and can thus be readily accessed to consciously remember an event. But when the mice were in a different brain state induced by gaboxadol, the stressful event primarily activated subcortical memory regions of the brain. The drug rerouted the processing of stress-related memories within the brain circuits so that they couldn’t be consciously accessed.

Leptin also influences brain cells that control appetite

Twenty years after the hormone leptin was found to regulate metabolism, appetite, and weight through brain cells called neurons, Yale School of Medicine researchers have found that the hormone also acts on other types of cells to control appetite.

Published in the June 1 issue of Nature Neuroscience, the findings could lead to development of treatments for metabolic disorders such as obesity and diabetes.

“Up until now, the scientific community thought that leptin acts exclusively in neurons to modulate behavior and body weight,” said senior author Tamas Horvath, the Jean and David W. Wallace Professor of Biomedical Research and chair of comparative medicine at Yale School of Medicine. “This work is now changing that paradigm.”

Leptin, a naturally occurring hormone, is known for its hunger-blocking effect on the hypothalamus, a region in the brain. Food intake is influenced by signals that travel from the body to the brain. Leptin is one of the molecules that signal the brain to modulate food intake. It is produced in fat cells and informs the brain of the metabolic state. If animals are missing leptin, or the leptin receptor, they eat too much and become severely obese.

Leptin’s effect on metabolism has been found to control the brain’s neuronal circuits, but no previous studies have definitively found that leptin could control the behavior of cells other than neurons.

To test the theory, Horvath and his team selectively knocked out leptin receptors in the adult non-neuronal glial cells of mice. The team then recorded the water and food intake, as well as physical activity every five days. They found that animals responded less to feeding reducing effects of leptin but had heightened feeding responses to the hunger hormone ghrelin.

“Glial cells provide the main barrier between the periphery and the brain,” said Horvath. “Thus glial cells could be targeted for drugs that treat metabolic disorders, including obesity and diabetes.”