neural mechanisms

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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Fieldwork, from plant fossils to robotics

“Thousands of US groundwater aquifers have been inadvertently contaminated with chlorinated solvents, such as perchloroethene (PCE) and trichloroethene (TCE). Chlorinated solvents are both toxic and persistent and classified as possible carcinogens by the U.S. Environmental Protection Agency. I am investigating the reaction of these chemicals with iron minerals commonly found in the soil. I synthesize iron and sulfur bearing minerals and monitor reactions in experiments with PCE or TCE. We hypothesize that these minerals are one natural pathway that transforms these contaminants to benign products.”

– Johnathan D. Culpepper, graduate research assistant, The University of Iowa


“The definitions of race and crime change. Criminology is a multidisciplinary field that combines my interest in human behavior and the diverse ways societies define deviance and race. I am generally interested in social institutions, racial ideology, inequality and social disorganization theory. For example, one of my current projects examines the link between African American-owned businesses and urban crime. Additionally, I am exploring how pre-hire psychological screenings impact adverse correctional employee behavior. As a former correctional officer, I am proud of scientifically addressing issues that may have implications on policy and practice by establishing research relationships with institutions.”

– TaLisa J. Carter, Ph.D. student, Department of Sociology and Criminal Justice, University of Delaware


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12:43// Here we go again, psychology essay plans on neural mechanisms of eating behaviour. Made slightly more interesting by cute unicorn post it notes 😋

Working hard will pay off in the long run my loves ☄

nature.com
Neural correlates of maintaining one’s political beliefs in the face of counterevidence
Jonas T. Kaplan, Sarah I. Gimbel & Sam Harris

People often discount evidence that contradicts their firmly held beliefs. However, little is known about the neural mechanisms that govern this behavior. We used neuroimaging to investigate the neural systems involved in maintaining belief in the face of counterevidence, presenting 40 liberals with arguments that contradicted their strongly held political and non-political views. Challenges to political beliefs produced increased activity in the default mode network—a set of interconnected structures associated with self-representation and disengagement from the external world. Trials with greater belief resistance showed increased response in the dorsomedial prefrontal cortex and decreased activity in the orbitofrontal cortex. We also found that participants who changed their minds more showed less BOLD signal in the insula and the amygdala when evaluating counterevidence. These results highlight the role of emotion in belief-change resistance and offer insight into the neural systems involved in belief maintenance, motivated reasoning, and related phenomena.

Will computers ever truly understand what we're saying?

From Apple’s Siri to Honda’s robot Asimo, machines seem to be getting better and better at communicating with humans.

But some neuroscientists caution that today’s computers will never truly understand what we’re saying because they do not take into account the context of a conversation the way people do.

Specifically, say University of California, Berkeley, postdoctoral fellow Arjen Stolk and his Dutch colleagues, machines don’t develop a shared understanding of the people, place and situation – often including a long social history – that is key to human communication. Without such common ground, a computer cannot help but be confused.

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2 super simple scientifically tested tips to motivate your study

“Don’t wait for motivation to study” is one of the common sayings on studyblr. I was keen subscriber to this idea until I read a journal on the annual reviews of psychology. You do in fact need motivation to study. This is because motivation is defined as set of processes that help you stay on task and focus on the target. Therefore, if we do not have motivation we would not be able to anything at all.

Thus, I have provided 2 simple and scientifically accurate tips  to find your motivation. 

  1. Find your reward.Give yourself an appropriate reward for doing your task. This reward must be proportional to your task, otherwise it will have an opposite effect. It doesn’t have to be physical, for instance self-praising for a getting a good grade is a good reward.
  2. Give yourself a break after a task that require lots of motivation. Moving on immediately after a difficult task is bad for your motivation. You will become more susceptible to giving into procrastination. So set some free time after a hard session of study.  

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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.

Motivation to Bully Is Regulated by Brain Reward Circuits

Individual differences in the motivation to engage in or to avoid aggressive social interaction (bullying) are mediated by the basal forebrain, lateral habenula circuit in the brain, according to a study conducted at the Icahn School of Medicine at Mount Sinai and published June 29 in the journal Nature.

The Mount Sinai study focuses on identifying the mechanisms by which specific brain reward regions interact to modulate the motivational or rewarding component of aggressive behavior using a mouse model.

Maladaptive aggressive behavior is associated with a number of psychiatric disorders and is thought to partly result from inappropriate activation of brain reward systems in response to aggressive or violent social stimuli. While previous research has implicated the basal forebrain as a potentially important brain reward region for aggression-related behaviors, there had been limited functional evidence that the basal forebrain, or its projections to other brain regions, directly controls the rewarding aspects of aggression.

“Our study is the first to demonstrate that bullying behavior activates a primary brain reward circuit that makes it pleasurable to a subset of individuals,” says Scott Russo, PhD, Associate Professor of Neuroscience at the Icahn School of Medicine at Mount Sinai. “Furthermore, we show that manipulating activity in this circuit alters the activity of brain cells and ultimately, aggression behavior.”

To study individual differences in aggressive behavior, the current team established a mouse behavioral model that exposed adult males to a younger subordinate mouse for three minutes each day for three consecutive days, and found that 70 percent of mice exhibited aggressive behavior (AGGs) while 30 percent of mice show no aggression at all (NONs).

Using conditioned place preference, a technique commonly used in animal studies to evaluate preferences for environmental stimuli that have been associated with a positive or negative reward, study investigators research found that AGGs mice bullied/attacked the subordinate mouse and subsequently developed a conditioned place preference for the intruder-paired context, suggesting that the aggressive mice found the ability to subordinate another mouse rewarding. Conversely, NONs mice did not bully/attack the intruder mouse and subsequently developed a conditioned place aversion.

All sensations, movements, thoughts, memories and feelings are the result of signals that pass through nerve cells (neurons), the primary functional unit of the brain and central nervous system. When a signal passes from the cell body to the end of the cell axon that stretches away from the cell body, chemicals known as neurotransmitters are released into the synapse, the place where signals are exchanged between cells. The neurotransmitters then cross the synapse and attach to receptors on the neighboring cell, which can change the properties of the receiving cell. Found throughout the brain and produced by neurons, gamma aminobutyric acid (GABA) is an inhibitory neurotransmitter that binds to GABA receptors, making the neighboring neuron less excitable.  

The current study team investigated GABA projection neurons that can send long-range connections to inhibit neurons in other brain regions. Specifically, using electrophysiological and histological techniques, the research team found that when exposed to the opportunity to bully another individual, AGGs mice exhibit increased activity of the basal forebrain GABA projection neurons that reduce activity in the lateral habenula, an area of the brain that would normally encode an aversion to aggressive stimuli. Conversely, they found NONs exhibit reduced basal forebrain activation and a subsequent increase in lateral habenula neuronal firing, which makes the aggression stimuli aversive.  

While previous research has found the lateral habenula to play a role in negative moods states and aversion across a broad range of species, including mice and humans, little was previously known about the neural mechanisms that directly regulate the motivational component of aggressive behavior.  

Researchers then used optogenetic tools to directly manipulate the activity of GABA between the basal forebrain and the lateral habenula, demonstrating that stimulation or inhibition of BF-lHb projections is both sufficient and necessary to alter the inclination to engage in or avoid the opportunity to bully.

“When we artificially induced the rapid GABA neuron activation between the basal forebrain and lateral habenula, we watched in real time as the aggressive mice became docile and no longer showed bullying behavior,” says Dr. Russo. “Our study is unique in that we took information about the basal forebrain, lateral habenula projections  and then actually went back and manipulated these connections within animals to conclusively show that the circuits bi-directionally control aggression behavior.”

The study findings demonstrate a previously unidentified functional role for the lateral habenula and its inputs from the basal forebrain in mediating the rewarding component of aggression and suggest that targeting shared underlying deficits in motivational circuitry may provide useful information for the development of novel therapeutic drugs for treating aggression-related neuropsychiatric disorders.

How older people learn

As a person ages, perception declines, accompanied by augmented brain activity. Learning and training may ameliorate age-related degradation of perception, but age-related brain changes cannot be undone. Rather, brain activity is enhanced even further, but for other reasons and with different outcomes. Researchers at Ruhr-Universität Bochum (RUB) discovered these facts in a recent study, the results of which have now been published in Scientific Reports.

Enhanced brain activity at old age

The researchers asked test participants in different age cohorts to feel two needlepoints that were located closely to each other with the tips of their fingers. Older participants perceived two points as a single event even when they were located quite far apart, whereas younger people were still able to distinguish them as two distinct points, which is evidence for degraded tactile perception at higher age. This impaired perception experienced by older people goes hand in hand with a spatial enhancement of brain activity, which researchers generally interpret as a compensatory mechanism.

Learning and training improve perception

“Age-related degraded perception is not irreversible; rather, it can be improved through training and learning,” explains Dr Hubert Dinse from the RUB Neural Plasticity Lab. The question researchers then asked was: if age-related impaired perception can be restored, will the age-related expansion of brain activity be reduced as well? In other words: can training and learning lead to a “rejuvenation” of the brain?

Learning too enhances brain activity

Studies with young adults have shown that learning processes are typically associated with an enhanced and broadened brain activity. If age-related impaired perception can be restored through learning, learning should have a different effect on the brain in older people than in young adults: the age-related enhanced brain activity should be reduced. Yet, as the neuroscientists from Bochum observed, the opposite is the case: learning processes in old people result in a further enhancement of brain activity too, which is associated with improved perception.

Learning to understand ageing and learning processes with the computer

“We asked ourselves: how can the different effects of enhanced brain activity on perception in older people be explained?” recounts Dr Burkhard Pleger from the RUB Neurology Clinic in Bergmannsheil Hospital. For the purpose of the study, the researchers used computer simulations to model both brain activity and associated perception. To this end, they simulated a number of alternatives of how those results might have been generated. These simulations showed that the observed pattern of age-related changes at the level of brain activity and perception could only be explained by the weakening of a mechanism that limits spread of activation, thus keeping activity focussed. In contrast, the observed learning effects could only be explained by reduced inhibition, which leads to higher brain activity. This mechanism is operating in both young and older people. Thus, the older brain learns according to the same principles as the younger brain. Considering the magnitude of learning-induced improved perceptual ability in younger and older participants, the study shows that older people improve even more than younger people. This result too can be explained by the computer simulations through reduced suppressive neural mechanisms in the elderly participants.

Training pays off at every age – but it does not rejuvenate the brain

“The computer simulations explain how changed brain activity can have opposite effects on the level of perception. In addition, they explain the observation that the ‘treatment’ of ageing processes does not reverse age-related brain changes, but rather remodels them,” says Hubert Dinse. “They demonstrate that training and learning pay off at every age, in order to remain fit.”

Nerves move to avoid damage

New data presented by Marinko Rade in his doctoral thesis can help explain the insurgence of widespread syndromes such as Carpal Tunnel Syndrome or Sciatica. He showed that neural movements can be measured using non-invasive techniques, also applicable in diagnostics and rehabilitation planning.

For the results published as part of his thesis, he has been awarded the “Young Scientist Award 2013” by the Finnish Spine Society, and the “2014 Young Investigator Award” by the world top-rated scientific journal Spine.

Work or hobbies can put a strain on nerves

Daily motions can be extremely various in terms of movements of peripheral nerves. Office workers can be writing for hours on computer keyboards, repeatedly compressing the median nerve in its pathway into the carpal tunnel, but not all of them will develop carpal tunnel syndrome. Water polo and handball players are vulnerable for stretching of the median nerve around the glenohumeral joint and in front of the elbow during the preparation for a shoot, but not all of them will become symptomatic and develop peripheral neuritis. Auto mechanics are prone for compression of the median nerve in the carpal tunnel in a similar way as keyboard workers do but not all of them will eventually need medical help. Marinko Rade’s doctoral thesis helps us better understand the reasons behind all this.

Nerves move, this is why

It has been widely showed on cadavers that nerves move. But why should nerves move within the body in the first place? It is believed they move in order to avoid potentially harmful mechanical forces such as tension and compression. So nerves slide longitudinally to avoid tensile forces and transversally within our body to avoid compression. However, it has not been known whether the direction and magnitude of such movements can be measured and predicted in patients. Marinko Rade showed in his dissertation that neural movements can indeed be quantified and also predicted, and moreover, using non-invasive techniques.

His research offered new data on the subject, particularly in aspects that have not been studied before, namely spinal cord movement and muscular protective effects during limb movements that produce excursion of nerve tissues. Research on living patients now being possible, cadavers may be a thing of the past.

More individual rehabilitation planning

In the first part of his doctoral thesis Marinko Rade explored the use of magnetic resonance imaging to investigate the neural movements into the thoraco-lumbar vertebral canal of in-vivo and structurally intact asymptomatic human subjects. He showed that those movements can be predicted and used in clinical practice to perform diagnosis and plan a very specific rehabilitation process.

In the second part of his doctoral thesis he focused on electrophysiological methods to quantify the muscular reactions in response to neural stress following the hypothesis that the muscles may be reflexively activated in order to protect the peripheral nerves in the most logical way; by shortening their pathway and opposing the harmful body movement. From the results it seems that it is indeed like that.

“In order to explore the normal neural adaptation mechanisms, the principle of no-harm has to be respected, that is, the investigation methodologies have to be non-invasive,” Marinko Rade says.

He adds that the aim of his dissertation is not only to present plain data, but to try to shift the clinician’s concept of nerves passively enclosed in tunnels delimited by bones, ligaments and muscles,  to the concept of nerves sliding and moving freely in those tunnels in order to avoid potentially harmful mechanical forces as tension and compression arising from interfacing structures, and increase the awareness of the fact that those movements can be measured, understood, predicted and also possibly used at our advantage in our everyday clinical practice.

“It is theorized that the preservation of a free sliding of the neural structures in the anatomical tunnels might be the conditio sine qua non for maintaining an asymptomatic situation. If this will be achieved, then this thesis will have served its purpose.”